Substrate Processing System

Abstract

A substrate processing system comprising: a frame forming a substrate transport space within the substrate processing system; a substrate transport apparatus operably coupled to the frame, the substrate transport apparatus comprising a movable arm and a drive section configured to move the movable arm to transport a substrate held on an end effector of the arm through the transport space from a first position in the substrate processing system to a second position in the substrate processing system that is different from the first position; and a controller operably coupled to the movable arm and the drive section to cause movement of the movable arm to the different system positions, the controller being communicatively coupled to at least one arm motion sensor and at least one system metrology sensor, the at least one system metrology sensor sensing a predetermined characteristic of the system metrology that is different from the predetermined characteristic of the arm motion.

Description

[Technical Field]

[0001] This application is a non-provisional application of and claims the benefit of U.S. Provisional Patent Application No. 63 / 479,431, filed January 11, 2023, the entire disclosure of which is incorporated herein by reference.

[0002] [Technical field] FIELD The exemplary embodiments relate generally to automated processing systems, and more particularly to diagnostics for automated processing systems. [Background technology]

[0003] A brief description of related developments An automated processing system, such as a semiconductor processing system, includes multiple components that support the implementation of processes that result in a predetermined level of quality and repeatability in semiconductor chip manufacturing. Examples of the multiple components include wafer handlers (e.g., robotic manipulators), wafer handler motion controllers, wafer presence sensors, slot valves, load locks, process modules, transfer modules, tool safety controllers, and tool host controllers. Typically, these multiple components are utilized as separate modules in the automated processing system and operate in their respective domains, where the tool host controller (and possibly a wafer handler controller) communicates with one or more other components of the multiple components to send commands for wafer transport and processing. Summary of the Invention

[0004] The foregoing aspects and other features of the disclosed embodiments are explained in the following description taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0005] [Figure 1A] 1 is a schematic perspective view of an exemplary substrate processing system incorporating aspects of the disclosed embodiments; [Figure 1B] 1B is a schematic plan view of the substrate processing system of FIG. 1A in accordance with aspects of the disclosed embodiment; [Figure 1C] 1 is a schematic plan view of an exemplary substrate processing system incorporating aspects of the disclosed embodiments; [Figure 1D] 1 is a schematic elevational view of an exemplary substrate processing system incorporating aspects of the disclosed embodiment; [Figure 2A] 1 is a schematic plan view of an exemplary substrate processing system incorporating aspects of the disclosed embodiments; [Figure 2B] 1 is a schematic plan view of an exemplary substrate processing system incorporating aspects of the disclosed embodiments; [Figure 2C] 1 is a schematic plan view of an exemplary substrate processing system incorporating aspects of the disclosed embodiments; [Figure 2D] 1 is a schematic plan view of an exemplary substrate processing system incorporating aspects of the disclosed embodiments; [Figure 2E] 1 is a schematic perspective view of an exemplary substrate transport apparatus incorporating aspects of the disclosed embodiments; [Figure 2F] 1 is a schematic perspective view of an exemplary substrate transport apparatus incorporating aspects of the disclosed embodiments; [Figure 2G] 1 is a schematic perspective view of an exemplary substrate transport apparatus incorporating aspects of the disclosed embodiments; [Figure 2H] 1 is a schematic perspective view of an exemplary substrate transport apparatus incorporating aspects of the disclosed embodiments; [Figure 2I] 1 is a schematic perspective view of an exemplary substrate transport apparatus incorporating aspects of the disclosed embodiments; [Figure 3] 1 is a schematic illustration of a portion of a modular metrology station in accordance with aspects of the disclosed embodiment; [Figure 4] 1 is a schematic illustration of a portion of a modular metrology station in accordance with aspects of the disclosed embodiment; [Figure 5] 1A-2I is a schematic diagram of an exemplary substrate processing system incorporating aspects of the disclosed embodiment and general to the substrate processing systems and components thereof shown in FIGS. [Figure 6] 6 is a schematic plan view of a portion of the substrate processing system of FIG. 5 in accordance with aspects of the disclosed embodiment; [Figure 7] 6 is a schematic plan view of a portion of the substrate processing system of FIG. 5 in accordance with aspects of the disclosed embodiment; [Figure 8] 6 is a schematic illustration of a portion of the substrate processing system of FIG. 5 in accordance with aspects of the disclosed embodiment; [Figure 9] 6 is a schematic illustration of a portion of the substrate processing system of FIG. 5 in accordance with aspects of the disclosed embodiment; [Figure 10] 6 is an exemplary flow diagram illustrating an adaptive control law for maximizing system level performance of the substrate processing apparatus of FIG. 5 based on control variables of the substrate processing apparatus, in accordance with aspects of the disclosed embodiment. [Figure 11] 6 is an exemplary flow diagram of an adaptive control law for minimizing system level characteristics of the substrate processing apparatus of FIG. 5 based on control variables of the substrate processing apparatus, in accordance with aspects of the disclosed embodiment. [Figure 12] 6 is an exemplary graph illustrating the adaptation of predetermined performance characteristic indicators and their respective variables to result in maximization of one or more of the predetermined performance characteristic indicators of the substrate processing apparatus of FIG. 5 in accordance with aspects of the disclosed embodiment. [Figure 13] FIG. 10 is an exemplary flow diagram of a method according to aspects of the disclosed embodiment; [Figure 14] FIG. 10 is an exemplary flow diagram of a method according to aspects of the disclosed embodiment; DETAILED DESCRIPTION OF THE INVENTION

[0006] 1-2D illustrate exemplary substrate processing systems 410, 11090, 2099, 3000, 3000A, 3000B, and 3000C in accordance with aspects of the disclosed embodiment. While aspects of the disclosed embodiment will be described with reference to the drawings, it should be understood that aspects of the disclosed embodiment can be embodied in many forms. Furthermore, any suitable size, shape, or type of elements or materials may be used.

[0007] Each of the substrate processing systems 410, 11090, 2099, 3000, 3000A, 3000B, 3000C has a frame 410F, 1190F, 2099F, 3000F, 3000AF, 3000BF, 3000CF that forms a substrate transport space within the respective substrate processing system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C. A substrate transport apparatus or wafer or substrate handler 11013, 11014, 2080, 26B, 26i, 3023, 3033, 550 is operably coupled to the frame 410F, 1190F, 2099F, 3000F, 3000AF, 3000BF, 3000CF. The substrate transport apparatus 11013, 11014, 2080, 26B, 26i, 3023, 3033, 550 includes a movable articulated arm 214-218 (referred to herein as an arm) and a substrate handling system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C. The substrate handling system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C may be configured to move the arm 214-218 from a first position (e.g., any of the substrate holding positions described herein) of the substrate handling system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C to a position different from the first position. and a drive section 299 configured to transport a wafer or substrate S (the terms wafer and substrate are used interchangeably herein, although it is noted that a substrate may be any suitable workpiece) held on the end effector EE of the arm 214-218 through a transport space to a second position among the positions 0, 2099, 3000, 3000A, 3000B, and 3000C (e.g., any of the substrate holding positions described herein). The arm drive section may be a rotary drive section (see Figures 2E-2I) having one or more drive shafts driven by suitable motors or a linear drive section 777 (Figure 7) having distributed electromagnetic drive elements 776 that magnetically levitate the arm 550A and drive its motion. Suitable examples of linear drive sections and transport systems in which aspects of the disclosed embodiments may be utilized are described in U.S. Patent Application No. 17 / 180,298, filed February 19, 2021, entitled "Substrate Process Apparatus," the entire disclosure of which is incorporated herein by reference.

[0008] The substrate processing systems 410, 11090, 2099, 3000, 3000A, 3000B, 3000C are configured with respective sensing systems that provide an intelligent, symbiotic, and adaptive relationship between at least the wafer handler controller and the various other components of the substrate processing systems 410, 11090, 2099, 3000, 3000A, 3000B, 3000C. Unlike the conventional automated processing systems described above, aspects of the disclosed embodiments provide for the sharing of information between respective domains of the various components 800 (as described herein (see FIG. 8)) of the substrate processing systems 410, 11090, 2099, 3000, 3000A, 3000B, 3000C. For example, a substrate transport apparatus 11013, 11014, 2080, 26B, 26i, 3023, 3033, 550 operating in a substrate processing system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C is controlled based on sensor feedback embodying at least the operating characteristics (e.g., vibration, temperature, airflow, etc. as described herein) of other components (e.g., slot valves, other substrate transport apparatuses, process modules, aligners, front end units, etc. as described herein) of the substrate processing system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C. The controlled motion of the substrate transport apparatus can be modified / adapted depending on the operating characteristics of the other components. An intelligent symbiotic and adaptive relationship between at least the wafer handler controller and various other components of the substrate processing system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C may result in increased value and reduced cost of ownership of the substrate processing system 410, 11090, 2099, 3000, 3000A, 3000B, 3000C by improving productivity metrics such as wafers per hour (WPH), increased tool uptime (e.g., the amount of time the processing system is running), reduced service time, reduced preventative maintenance occurrences, and reduced setup time.

[0009] As described herein, aspects of the disclosed embodiments define substrate processing tool variables and associated performance metrics that are utilized to support an adaptive control and diagnostic framework that modifies system-level performance attributes to maximize productivity metrics such as wafers per hour (WPH), increased tool uptime (e.g., the amount of time the processing system is operational), reduced service time, reduced preventative maintenance occurrences, and reduced setup time.

[0010] 1A and 1B, a processing apparatus, such as, for example, a semiconductor processing system 11090, is shown in accordance with aspects of the disclosed embodiments. While a semiconductor processing system 11090 is shown in the drawings, aspects of the disclosed embodiments described herein may be applied to any tool station or application utilizing a robotic manipulator. In this example, the semiconductor processing system 11090 is shown as a cluster tool, but aspects of the disclosed embodiments may be applied to any suitable tool station, such as, for example, a linear tool station, such as those shown in FIGS. 1C and 1D and described in U.S. Pat. No. 8,398,355, entitled "Linearly Distributed Semiconductor Workpiece Processing Tool," issued March 19, 2013, and U.S. Patent Application No. 17 / 180,298, entitled "Substrate Processing Apparatus," filed February 19, 2021, the entire disclosures of which are incorporated herein by reference. The semiconductor tool station or processing system 11090 generally includes an atmospheric front end 11000, a vacuum load lock 11010, and a vacuum back end 11020. In other embodiments, the tool station may have any suitable configuration. Each component of the front end 11000, the vacuum load lock 11010, and the vacuum back end 11020 may be connected to a controller 11091, which may be part of any suitable control architecture, such as, for example, a clustered architecture control.

[0011] The controller may be a closed-loop controller having a master controller, cluster controllers, and autonomous remote controllers, such as those disclosed in U.S. Patent No. 7,904,182, issued March 8, 2011, entitled "Scalable Motion Control System," the entire disclosure of which is incorporated herein by reference. In other embodiments, any suitable controller and / or control system may be utilized. As described herein, the controller 11091 is communicatively connected to a drive section (e.g., drive section 299 (see FIGS. 2E-2F)) of a substrate transport robot (such as those described herein and also referred to as a substrate transport device or handler) to move a transport arm (such as transport arms 214-218 of FIGS. 2E-2I or any other transport arm described herein). The controller 11091 is also communicatively connected to at least one sensor processing unit 300 (see FIG. 3), as described herein, to provide an intelligent, symbiotic and adaptive relationship between the components of the semiconductor processing system 11090.

[0012] In one embodiment, the front end 11000 generally includes a load port module (also referred to herein as a workpiece load station) 11005 and a minienvironment 11060, such as, for example, an equipment front end module (EFEM) (which in some embodiments includes wafer sorting functionality). In other embodiments, the processing stations include wafer buffers, wafer inverters, and wafer shuffle stations (which may be located in the vacuum back end 11020, the front end 11000, and / or connecting the front end 11000 to the vacuum back end 11020 (e.g., in a load lock, etc.)). The front end 11000 and the vacuum back end 11020 each include a frame that, when coupled together, forms the frame 11090F of the semiconductor processing system 11090. The load port module 11005 may be a Box Opener / Loader-Tool Standard (BOLTS) interface conforming to SEMI Standards E15.1, E47.1, E62, E19.5, or E1.9 for 300 mm load ports, front-opening or bottom-opening boxes / pods, and cassettes. In other embodiments, the load port module may be configured as a 200 mm or 450 mm wafer interface, or any other suitable wafer interface, such as for larger or smaller wafers or flat panels for flat panel displays. While two load port modules 11005 are shown in FIG. 1A , in other embodiments, any suitable number of load port modules may be incorporated into the vacuum front end 11000. The load port module 11005 may be configured to receive wafer / substrate carriers or cassettes 11050 from an overhead transport system, an automated guided vehicle, a manned guided vehicle, a rail-guided automated guided vehicle, or any other suitable transport method. The load port module 11005 may interface with the minienvironment 11060 via the load port 11040 .The substrate cassettes 11050 are received on the respective load port modules 11005 at a predetermined load station home position 11005L that kinematically positions the substrate cassette 11050 on the load port module 11005. In one aspect, the load port 11040 allows for the passage of wafers between the substrate cassette 11050 and the minienvironment 11060.

[0013] In one embodiment, the mini-environment 11060 generally includes any suitable transfer robot 11013. In one embodiment, the transfer robot 11013 may be a track-mounted robot such as those described in U.S. Pat. Nos. 6,002,840 and 7,066,707, the entire disclosures of which are incorporated herein by reference, or in other embodiments, any other suitable transfer robot having any suitable configuration. The mini-environment 11060 may provide a controlled, clean area for wafer transfer between multiple load port modules.

[0014] The vacuum load lock 11010 may be located between and connected to the mini-environment 11060 and the vacuum back end 11020. The term vacuum as used herein refers to the temperature at which wafers are processed. -5 It is noted that vacuum refers to high vacuum, such as Torr or below. The vacuum load lock 11010 generally includes atmospheric pressure and a vacuum slot valve. The slot valve may provide environmental isolation utilized to evacuate the load lock after loading wafers from the atmospheric front end and to maintain a vacuum within the transfer chamber when venting the load lock with an inert gas such as nitrogen. In one embodiment, the vacuum load lock 11010 includes an aligner 11011 for aligning a reference wafer to a desired position for processing, while in other embodiments, wafer alignment is provided by a transfer robot as described herein. In other embodiments, the vacuum load lock may be located in any suitable location in the processing equipment and may have any suitable configuration and / or metrology equipment.

[0015] The vacuum backend 11020 generally includes a transfer chamber 11025, one or more processing stations or modules 11030, and any suitable transfer robot 11014. The transfer robot 11014, described below, may be disposed within the transfer chamber 11025 to transfer wafers between the vacuum load lock 11010 and the various processing modules 11030. The processing modules 11030 may operate on the wafers through various deposition, etching, or other types of processes to form electrical circuits or other desired structures on the wafers. Typical processes include, but are not limited to, thin film processes using vacuum, such as plasma etching or other etching processes, chemical vapor deposition (CVD), plasma deposition (PVD), implantation, such as ion implantation, metrology, rapid thermal processing (RTP), dry strip atomic layer deposition (ALD), oxidation / diffusion, nitride formation, vacuum lithography, epitaxy (EPI), wire bonder and evaporation, or other thin film processes using vacuum pressure. The processing modules 11030 are connected to the transfer chamber 11025 to allow wafers to pass from the transfer chamber 11025 to the processing modules 11030 and vice versa. In one embodiment, the load port modules 11005 and load ports 11040 are substantially directly coupled to the vacuum back end 11020 such that a substrate cassette 11050 attached to the load port substantially directly interfaces with the vacuum environment of the transfer chamber 11025 and / or the processing vacuum of the process module 11030 (e.g., the processing vacuum and / or vacuum environment extends between and is common between the process module 11030 and the substrate cassette 11050) (e.g., in one embodiment, at least the mini-environment 11060 is omitted, while in other embodiments, the vacuum load lock 11010 is also omitted and the substrate cassette 11050 is pumped down to vacuum in a manner similar to the vacuum load lock 11010).

[0016] 1C , a schematic plan view of a linear processing system 2099 is shown in which the tool interface section 2012 is mounted to the transfer chamber module 3018 so as to generally face toward (e.g., inwardly) but offset from the longitudinal axis X of the transfer chamber module 3018. The transfer chamber module 3018 can be extended in any suitable direction by attaching other transfer chamber modules 3018A, 3018I, 3018J to interfaces 2050, 2060, 2070, as described in U.S. Pat. No. 8,398,355, previously incorporated by reference. Each transfer chamber module 3018, 3018A, 3018I, 3018J includes any suitable substrate transport apparatus 2080 that can operate in accordance with aspects of the disclosed embodiments described herein for transporting wafers throughout the linear processing system 2099, for example, to and from processing modules PM. As can be appreciated, each chamber module may be capable of holding an isolated or controlled atmosphere (eg, N2, clean air, vacuum).

[0017] Referring to FIG. 1D , a schematic elevation view of an exemplary processing tool 410 as may be taken along the longitudinal axis X of the linear transport chamber 416 is shown. In the disclosed embodiment shown in FIG. 1D , the tool interface section 12 may typically be connected to the transport chamber 416. In this embodiment, the interface section 12 may define one end of the tool transport chamber 416. As seen in FIG. 1D , the transport chamber 416 may have another workpiece entry / exit station 412, for example, at the end opposite the interface station 12. In other embodiments, other entry / exit stations for inserting / removing workpieces from the transport chamber may be provided. In one embodiment, the interface section 12 and the entry / exit station 412 may enable loading and unloading of workpieces from the tool. In other embodiments, workpieces may be loaded into the tool from one end and removed from the other end. In one embodiment, the transport chamber 416 may have one or more transfer chamber modules 18B, 18i. Each chamber module may be capable of holding an isolated or controlled atmosphere (e.g., N2, clean air, vacuum). As previously mentioned, the configuration / arrangement of the transfer chamber modules 18B, 18i, load lock modules 56A, 56B, and workpiece stations forming the transfer chamber 416 shown in FIG. 1D is merely exemplary; in other embodiments, the transfer chamber may have more or fewer modules arranged in any desired modular arrangement. In the embodiment shown, station 412 may be a load lock. In other embodiments, a load lock module may be located between end entry / exit stations (similar to station 412), or an adjacent transfer chamber module (similar to module 18i) may be configured to operate as a load lock.

[0018] As previously mentioned, each transport chamber module 18B, 18i has one or more corresponding transport apparatuses 26B, 26i disposed therein, which may include one or more aspects of the disclosed embodiments described herein. The transport apparatuses 26B, 26i of each transport chamber module 18B, 18i may cooperate to provide a linearly distributed workpiece transport system within the transport chamber. In this embodiment, the transport apparatus 26B may have a typical SCARA arm configuration (see also FIG. 2I), although in other embodiments, the transport arm may have any other desired configuration, such as, for example, an arrangement generally similar to the transfer robots 11013, 11014 of the cluster tool illustrated in FIGS. 1A and 1B, a linear sliding arm 214 as shown in FIG. 2F, or other suitable arms having any suitable arm linkage mechanism. Suitable examples of arm link linkage mechanisms are described, for example, in U.S. Pat. No. 7,578,649 issued on August 25, 2009, U.S. Pat. No. 5,794,487 issued on August 18, 1998, U.S. Pat. No. 7,946,800 issued on May 24, 2011, U.S. Pat. No. 6,485,250 issued on November 26, 2002, U.S. Pat. No. 7,891,935 issued on February 22, 2011, U.S. Pat. No. 8,419,341 issued on April 16, 2013, U.S. Patent Application No. 13 / 293,717 entitled "Dual Arm Robot" filed on November 10, 2011, and U.S. Patent Application No. 13 / 293,717 entitled "Linear Vacuum Robot with ZMotion and Articulated Arm" filed on September 5, 2013. No. 13 / 861,693, entitled "Arm," the entire disclosures of which are incorporated herein by reference.In aspects of the disclosed embodiment, at least one transfer arm may be derived from a conventional SCARA (selectively compliant articulated robotic arm) type design, including an upper arm, a band-driven forearm, and a band-constrained end effector, or from any other suitable arm design, such as a telescoping arm, or a Cartesian linear sliding arm, where any such design configuration also includes a slide body 420, alignment system 499, and end effector(s) 420A, 420B... 420n as further described herein. For example, in one aspect, slide body 420 is attached to an arm link of any suitable articulated transport arm. Suitable examples of transport arms can be found, for example, in U.S. Patent Application No. 12 / 117,415, entitled "Substrate Transport Apparatus with Multiple Movable Arms Utilizing a Mechanical Switch Mechanism," filed May 8, 2008, and U.S. Patent No. 7,648,327, issued January 19, 2010, the entire disclosures of which are incorporated herein by reference. Operation of the transport arms can be independent of one another (e.g., extension and retraction of each arm is independent of the other arms), via lost motion switches, or operably linked in any suitable manner so that the arms share at least one common drive axis. In still other embodiments, the transport arms can have any other desired configuration, such as a frog-leg arm 216 (FIG. 2E), leap-frog arm 217 (FIG. 2H), or bidirectional symmetric arm 218 (FIG. 2G) configuration.Suitable examples of transfer arms are described in U.S. Patent No. 6,231,297 issued May 15, 2001, U.S. Patent No. 5,180,276 issued January 19, 1993, U.S. Patent No. 6,464,448 issued October 15, 2002, U.S. Patent No. 6,224,319 issued May 1, 2001, and U.S. Patent No. 5,447,409 issued September 5, 1995. No. 7,578,649 issued on August 25, 2009; U.S. Pat. No. 5,794,487 issued on August 18, 1998; U.S. Pat. No. 7,946,800 issued on May 24, 2011; U.S. Pat. No. 6,485,250 issued on November 26, 2002; U.S. Pat. No. 7,891,935 issued on February 22, 2011; U.S. patent application Ser. No. 13 / 293,717 entitled "Dual Arm Robot," filed on November 10, 2011; and U.S. patent application Ser. No. 13 / 270,844 entitled "Coaxial Drive Vacuum Robot," filed on October 11, 2011, the entire disclosures of which are all incorporated herein by reference.

[0019] In the disclosed embodiment shown in FIG. 1D , the arms and / or end effectors of the transport apparatus 26B can be arranged to provide what is known as a fast-exchange configuration, which allows the transport apparatus to quickly exchange wafers from a pick / place position. The transport arm 26B can have any suitable drive section (e.g., coaxially arranged drive shafts, side-by-side drive shafts, horizontally adjacent motors, vertically stacked motors, etc.) to provide each arm with any suitable number of degrees of freedom (e.g., independent rotation about shoulder and elbow joints with Z-axis motion). As seen in FIG. 1D , in this embodiment, modules 56A, 56B, 30i can be positioned in the gaps between the transfer chamber modules 18B, 18i to define appropriate processing modules, load lock(s), buffer station(s), metrology station(s), or any other desired station(s). For example, intervening modules such as load locks 56A, 56B and workpiece station 30i each have stationary workpiece supports / shelves 56S, 56S1, 56S2, 30S1, 30S2 that cooperate with a transport arm to provide transport of the workpieces along the length of the transport chamber along the linear axis X of the transport chamber. By way of example, workpiece(s) may be loaded into transport chamber 416 by interface section 12. The workpiece(s) may be positioned on support(s) of load lock module 56A by transport arm 15 of the interface section. Workpiece(s) in load lock module 56A may be moved between load lock module 56A and load lock module 56 by transport arm 26B in module 18B, and in a similar and sequential manner may be moved between load lock 56 and workpiece station 30i by arm 26i (in module 18i) and between station 30i and station 412 by arm 26i in module 18i. This process may be reversed in whole or in part to move the workpiece(s) in the opposite direction.Thus, in one embodiment, workpieces can be moved in any direction along axis X to any position along the transport chamber and loaded onto or removed from any desired module (processing module or other module) in communication with the transport chamber. In other embodiments, intervening transport chamber modules with static workpiece supports or shelves may not be provided between the transport chamber modules 18B, 18i. In such embodiments, the transport arms of adjacent transport chamber modules may move workpieces through the transport chamber, either directly to their end effectors or by passing them from one transport arm to the end effector of another. Processing station modules may operate on wafers via various deposition, etching, or other types of processes to form electrical circuits or other desired structures on the wafers. The processing station modules are connected to the transport chamber modules to enable wafers to pass from the transfer chamber to a processing station or vice versa. Suitable examples of processing tools having general features similar to the processing device shown in FIG. 1D are described in U.S. Pat. No. 8,398,355, previously incorporated by reference in its entirety.

[0020] 2A-2D, the processing tools are illustrated as linear processing tools 3000, 3000A, 3000B, 3000C having one or more cluster workpieces 3010-3013, each having one or more transfer chambers 3001-3003 and multiple processing modules 11030 (e.g., a combination linear cluster tool). In one aspect, the linear processing tools 3000, 3000A, 3000B, 3000C are generally similar to those described in U.S. patent application Ser. No. 14 / 377,987, filed Aug. 11, 2014, entitled "Substrate Processing Apparatus," the entire disclosure of which is incorporated herein by reference. In one aspect, the cluster workstations 3010-3013 are generally similar to the vacuum backend 11020 described above. The cluster workstations 3010-3013 are connected to one another by one or more transfer chambers 3020, 3021 and one or more linear transfer tunnels (also referred to herein as vacuum tunnels) 3030, each having a transfer robot 3033. As can be appreciated, each of the transfer chambers 3020, 3021 includes a transfer robot 3023.

[0021] 3, 4, 5, and 8, at least one substrate processing station (processing module, aligner, etc.) and at least one substrate input or output station (e.g., load port, load lock, etc.) of a substrate processing apparatus described herein form a substrate processing echelon of the respective substrate processing system. At least one substrate transport apparatus of a substrate processing system described herein transports substrates or wafers S along the substrate processing echelon between the input or output station and the substrate processing station, and the at least one substrate transport apparatus forms a transport echelon of the respective substrate processing system. The substrate transport apparatus 550 (similar to those described herein) and substrate processing components (e.g., processing stations and input / output stations) of the substrate processing apparatus 555 (which may be generally similar to the cluster and / or linear processing apparatus described herein) are communicatively coupled to any suitable controller, such as controller 11091 or master controller 570 (see FIG. 5, which may be part of controller 11091 as described above). A group of sensors, including a transfer echelon sensor (also referred to as an arm motion sensor 566) and a process echelon metrology sensor (also referred to herein as system metrology sensors 500A-500z), are communicatively coupled to the controller 11091 in any suitable manner (such as those described herein). The (at least one) arm motion sensor 566 is communicatively coupled to the substrate transport apparatus 550 and is positioned to sense a predetermined characteristic of the transfer echelon (as described herein). The process echelon metrology sensor is coupled to one or more of the substrate processing components (e.g., transfer chamber, process module, front end unit, substrate transport apparatus, etc.) and is positioned to sense a predetermined characteristic of the process echelon metrology (as described herein) that is different from the predetermined characteristic of the transfer echelon.

[0022] Movement of the substrate transport apparatus is effected by a controller 11091 to move the arm 550A (similar to those described herein) to various substrate-holding positions of a substrate processing system 555 (similar to those described herein). The controller 11091 is communicatively coupled to at least one arm motion sensor 566 and at least one system metrology sensor 500A-500z (where "z" is an integer and indicates an upper limit on the number of system metrology sensors (see FIGS. 2E-2I, 5, and 8)). As described herein, the at least one arm motion sensor 566 and the at least one system metrology sensor 500A-500z are modular metrology sensors or stations 400 having a common, selectively configurable modular platform 496 (FIG. 4). The at least one arm motion sensor 566 is configured to sense a predetermined characteristic or metric of kinematic and / or dynamic arm motion, including, but not limited to, acceleration, position, and velocity. The at least one system metrology sensor 500A-500z is configured to sense a predetermined characteristic or metric of the system metrology, including, but not limited to, component vibration, temperature, position, acceleration, and airflow. The predetermined characteristic of the system metrology is different from the predetermined characteristic of the kinematic and / or dynamic arm motion. The controller 11091 is configured to record data DAT, DAT2 from the at least one arm motion sensor 566 and at least one of the at least one system metrology sensor 500A-500z.

[0023] The controller 11091 is configured to effect movement of the arm 550A (via commands to the drive section 299) based on feedback from at least one system metrology sensor 500A-500z. The feedback embodies predetermined characteristics of system metrology of one or more system components 800 of the substrate processing system 555 (e.g., wafer handlers (e.g., robotic manipulators), slot valves, load locks, aligners, process modules, transfer modules, front end units, load ports, substrate elevators, etc., as described herein) that may affect the operation of the substrate transport apparatus 550. The controller 11091 can adapt the operation of the substrate transport apparatus 550 in response to the predetermined characteristics of the system metrology of the system components 800. This sensor feedback is obtained from at least one system metrology sensor 500A-500z as raw sensing variables that are utilized (as described herein) to adaptively operate the substrate transport apparatus 550 (similar to the substrate transport apparatus described herein). In some aspects, the predetermined characteristics of the system metrology of the substrate transport apparatus 550 are utilized by the controller along with predetermined characteristics of the system metrology of other, different system components 800 to effect adaptive operation of the substrate transport apparatus 550. Additionally, although aspects of the disclosed embodiments are described herein as adaptively operating the substrate transport apparatus 550, operation of other components 800 (e.g., slot valves, aligners, elevators, etc.) as other, different components 800 of the substrate processing apparatus 555 may be adapted based on the predetermined characteristics of the system metrology of the substrate transport apparatus 550.

[0024] The at least one system metrology sensor 500A-500z may be one or more of: camera(s) (two-dimensional and / or three-dimensional line scan), charge-coupled device (CCD) array(s), vibration / seismic sensor(s) (e.g., accelerometer(s)), temperature sensor(s) (e.g., infrared or other), ranging sensor(s) (e.g., distance sensors such as sonar, LIDAR, time-of-flight cameras), proximity sensor(s), current sensor(s), flow sensor(s), magnetic sensor(s) (e.g., Hall effect, giant magnetoresistance, etc.), and any other suitable sensor(s) for measuring operational characteristics of one or more components 800 of the substrate processing system 555 (which may be generally similar to these substrate processing systems 410, 11090, 2099, 3000, 3000A, 3000B, 3000C described herein). At least one system metrology sensor 500A-500z may be integrated into or coupled in any suitable manner to a respective component of the substrate processing system 555. For illustrative purposes only, Figure 5 illustrates the substrate processing apparatus 550 along with a valve 551 (such as a slot valve) and a processing chamber lid 552, although it is noted that the substrate processing system 555 may have any suitable components 800 as described herein, and each of these components 800 may include one or more metrology sensors 500A-500z.

[0025] The substrate processing system 555 includes at least one modular metrology station 400, 400A-400D. Each modular metrology station 400, 400A-400D includes one or more of the at least one system metrology sensor(s) 500A-500z and / or one or more of the at least one arm motion sensor(s) 566. Each modular metrology station 400 (note that the modular metrology stations 400A-400D are generally similar) also includes a sensor processing unit 300 that is communicatively coupled (wired or wirelessly) to one or more of the at least one system metrology sensor(s) 500A-500z. The sensor processing unit 300 can be added to or removed from the substrate processing system 555 as a modular unit. For example, in one embodiment, the sensor processing unit 300 has one or more of the respective system metrology sensors 500A-500z mounted on a common base 496 (FIG. 4) where remote sensor probes are integrated and coupled to components 800 (such as valves 551 and processing chamber lids 552 (see FIG. 5)), while in other embodiments, the system metrology sensors 500A-500z are located remotely from the sensor processing unit 300 (see FIG. 5 where the sensors are integrated or coupled to the substrate transport apparatus 550) and are communicatively coupled to the sensor processing unit in any suitable manner (such as via a wired or wireless connection).

[0026] The sensor processing unit 300 includes one or more central processing units CPU1 to CPUn (where n is an integer indicating an upper limit on the number of central processing units), one or more graphics processing units GPU1 to GPUm (where m is an integer indicating an upper limit on the number of graphics processing units), field programmable gate arrays FPGA1 to FPGAk (where k is an integer indicating an upper limit on the number of field programmable gate arrays), sensor interfaces SINT1 to SINTr (where r is an integer indicating an upper limit on the number of sensor interfaces), network interfaces NINT1 to NINTs (where s is an integer indicating an upper limit on the number of network interfaces), and memory (including one or more of non-volatile memory NVM and volatile memory VM).

[0027] The sensor processing unit is configured to establish (e.g., using appropriate non-transitory computer program code executed by one or more of the central processing units CPU1-CPUn, the graphics processing units GPU1-GPUm, and the field programmable gate array) a hardware interface (e.g., a plug-and-play sensor interface in some embodiments) compatible with each one (or more) of the system measurement sensors 500A-500z, extract raw data from each of the system measurement sensors 500A-500z, timestamp the extracted raw data, process the raw data from each system measurement sensor to convert the raw data into variables of interest (e.g., for control and diagnostic purposes), and broadcast the processed data over the network. For example, sensor processing unit 300, including its own operating system, communicates (using the associated network protocol) with any suitable controller (e.g., robot controller, processing system master controller 570 (which may be part of controller 11091 or integrated with controller 11091 (see FIG. 1A)), tool safety controller 580 (which may be part of controller 11091 or integrated with controller 11091 (see FIG. 1A))), and other sensor processing units 300 over deterministic and / or non-deterministic networks, including, but not limited to, EtherCat, EtherNet, Firewire, etc. Sensor processing unit 300 includes one or more communication ports N1 through Nu (where u is an integer indicating an upper limit on the number of communication ports), each of which is configured with a corresponding communication protocol to communicate over the corresponding network (EtherCat, EtherNet, Firewire, etc.).

[0028] According to the disclosed embodiments, there may be different modular metrology stations 400, 400A-400D, each having different operating characteristics that differ from another modular metrology station 400, 400A-400D, such that the configuration of the different modular metrology stations 400, 400A-400D is based on the type and configuration of the component 800 being monitored and the sensors utilized to monitor the component 800. As a non-limiting example, a different operating characteristic may be the type of network in which the modular metrology station 400, 400A-400D operates. In some embodiments, the modular metering stations 400, 400A-400D are configured to operate on a common network, while in other embodiments, some of the modular metering stations 400, 400A-400D are configured to operate on one network (e.g., EtherCat®, EtherNet®, Firewire®, etc.) and the remainder of the modular metering stations 400, 400A-400D are configured to operate on another, different network (e.g., a different one of EtherCat®, EtherNet®, Firewire®, etc.), e.g., providing support for different types of hardware interfaces and different network protocols.

[0029] The modular metrology stations 400, 400A-400D are in communication with the controller 11091 to provide data DAT2 from at least one system metrology sensor 500A-500z deterministically and in real time, although in other embodiments, the data DAT2 is provided asynchronously (on-demand). Here, the modular metrology stations 400, 400A-400D are configured to take data measurements (e.g., acquire data DAT2) in connection with operation of the substrate transport apparatus 550, and wherein the sensor processing units 300 of the modular metrology stations 400, 400A-400D are configured to acquire data from the at least one system metrology sensor 500A-500z at predetermined times. For example, data acquisition of the modular metrology stations 400, 400A-400D may be triggered by or synchronized with operation of the arm 550A by the controller 11091 in any suitable manner. For example, the controller 11091 is configured to cause broadcast of position data of the substrate transport apparatus 550 to the modular metrology stations 400, 400A-400D, where the data is captured at a predetermined position of the substrate transport apparatus 550 within the substrate transport space of the substrate processing system 555.

[0030] As an example, if the modular metrology stations 400, 400A-400D include a visual sensor (e.g., a camera) positioned to capture data regarding the edge of the substrate S carried by the end effector EE of the substrate processing apparatus 550, the broadcast position of the substrate transport apparatus 550 informs the modular metrology stations 400, 400A-400D of the time to capture data from the camera such that the edge of the substrate S is within the field of view of the camera coupled to the modular metrology station 400, 400A-400D. Another example is if the modular metrology stations 400, 400A-400D include a temperature sensor positioned to measure the temperature(s) of the substrate S before and / or after substrate processing in a process module, where data is collected from the temperature sensor based on the broadcast position of the substrate transport apparatus 550 such that the substrate S is in a predetermined position relative to the temperature sensor to provide the temperature measurement(s) of the substrate S. As a further example, the modular metrology stations 400, 400A-400D are configured to capture data regarding a time interval of vertical acceleration of the substrate S while the substrate transport apparatus is extended at a process module to pick / place the substrate S based on the broadcast position of the substrate transport apparatus 550. In other embodiments, the data capture of the modular metrology stations 400, 400A-400D may be based on buffered and / or time-stamped position data of the substrate transport apparatus 550 being communicated to the modular metrology stations 400, 400A-400D by the controller 11091 such that the data captured by the modular metrology stations 400, 400A-400D is within a predetermined target range of the position of the substrate transport apparatus 550.

[0031] As described above, the modular metrology station(s) 400, 400A-400D include one or more processing units (e.g., central processing units CPU1-CPUn, graphics processing units GPU1-GPUm, and / or field programmable gate arrays FPGA1-FPGAk) and memory (e.g., non-volatile memory NVM and / or volatile memory VM). Also as described herein, the modular metrology station(s) 400, 400A-400D are coupled to a controller 11091, wherein the one or more processing units and memory of the modular metrology station(s) 400, 400A-400D may offload or transfer memory and computational load from the controller 11091 to the modular metrology station(s) 400, 400A-400D. Here, the modular metrology stations 400, 400A-400D may result in a simplified configuration / architecture of the controller 11091 (software and / or hardware) (e.g., via offloading of memory and computational load) and may provide additional sensing / feedback near the process modules or other components 800 (such as substantially direct position feedback of the substrate in the substrate processing system 555), increasing system data collection capacity for system diagnostics and machine learning. According to disclosed embodiments, utilization of the modular metrology stations 400, 400A-400D may provide a framework for creating encapsulated objects or defined classes (as in object-oriented programming), where each modular metrology station 400, 400A-400D is represented as an object within the software of the controller 11091. In some aspects, the modular metrology stations 400, 400A-400D may be defined as part of a semiconductor device profile within the protocol context of EtherCat®.

[0032] 5 , as described above, the controller 11091 is communicatively coupled to the transfer echelon sensors (e.g., arm motion sensor(s) 566) and the metrology echelon sensors (e.g., system metrology sensors 500A-500z) and is configured to generate a set of predetermined functional characteristic indicators (as described herein) from the sensor data DAT, DAT2 embodying both the predetermined characteristics of the transfer echelon (as described herein) and the predetermined characteristics of the processing echelon metrology (as described herein), each indicator corresponding to a different respective predetermined functional characteristic of the substrate transport apparatus 550 transporting the substrate S or of the substrate processing echelon, and indicating a relationship between each predetermined functional characteristic and the operational quality of the substrate S transported by the substrate transport apparatus 550. As described in further detail herein, the controller 11091 is configured to determine an integrated overall measurement indicator (e.g., wafer operational quality indicator WMQIdx) of the overall operational quality of the substrate S transported by the substrate transport apparatus 550 from the set of predetermined functional characteristic indicators.

[0033] The controller 11091 is configured to record data DAT, DAT2 from at least one of the at least one arm motion sensor 566 and at least one system metrology sensor 500A-500z. The controller 11091 is configured to determine, from the recorded data, a performance value for each different respective predetermined functional characteristic and factor the performance value against a corresponding reference value for each different predetermined functional characteristic. For example, the controller 11091 determines, from the recorded data DAT, DAT2, a set of predetermined functional characteristic indicators or values ​​(as described herein), each indicator corresponding to a different respective predetermined functional characteristic of the arm motion or of the system transporting the substrate and indicating a relationship between each predetermined functional characteristic and the motion quality of the substrate S transported by the movable arm 550A. Each different predetermined functional characteristic depends on at least one specific control parameter of the arm 550A or the system 555 controlled by commands of the controller 11091.

[0034] As described herein, the controller 11091 is configured to determine an integrated or combined overall metric or value (e.g., wafer motion quality metric WMQIdx) of the overall motion quality of the substrate S being transported by the movable arm 550A from a set of predetermined functional characteristic metrics. Here, aspects of the disclosed embodiments provide metrics or characteristics for wafer motion quality and utilization of such metrics to adapt motion control of the substrate transport apparatus 550 based on the metrics to maximize tool throughput and tool uptime (e.g., tool operation).

[0035] As described herein, each predetermined functional characteristic includes at least one of substrates per hour (WPH), position loop servo gain margin (GM), position loop servo phase margin (PM), wafer handling error (WHE), wafer slippage (WS), settling time (ST), wafer handoff vibration (WHV), wafer motion swing (WWE), and wafer motion vibration (WMV). Also, as described herein, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic including at least one of substrates per hour (WPH), position loop servo gain margin (GM), position loop servo phase margin (PM), wafer handling error (WHE), wafer slippage (WS), settling time (ST), wafer handoff vibration (WHV), wafer motion swing (WWE), and wafer motion vibration (WMV). At least one of the predetermined characteristics of the system measurements is derived from (eg, depends on) the arm motion (or predetermined characteristics of the arm motion).

[0036] The wafer operation quality index WMQIdx represents a performance index or cost function of the operation of the substrate processing system 555 in terms of substrate handling performance variables, such that the value of the wafer operation quality index WMQIdx indicates the substrate health (or substrate health index) of the substrate processing system 555. Maximizing the wafer operation quality index WMQIdx maximizes the operating efficiency / performance of the substrate processing system 555. The wafer operation quality index WMQIdx is defined by operational automation variables that can be dynamically changed or adapted, such as via adaptive components or control laws (and associated parameters / gains) provided by the controller 11091, to maximize the wafer operation quality index WMQIdx. The wafer quality index WMQIdx is defined by performance variables of the substrate processing tool 555 that substantially directly impact the quality of the handling operation of the substrate S within the substrate processing tool 555, as in equation [1].

[0037]

number

[0038] where WPHIdx is the number of wafers processed per hour index, GMIdx is the position loop servo gain margin index, PMIdx is the position loop servo phase margin index, WHEIdx is the wafer handling error index, WSIdx is the wafer slippage index, STIdx is the settling time index, WHVIdx is the wafer handoff vibration index, WWEIdx is the wafer motion swing index, and WMVIdx is the wafer motion vibration index. The aforementioned indices are normalized versions of the associated evaluation index / characteristics, and an index greater than 1 indicates that the associated variable is performing above its nominal (e.g., baseline) value. The aforementioned indices are defined as follows:

[0039]

number

[0040]

number

[0041]

number

[0042]

number

[0043]

number

[0044]

number

[0045]

number

[0046]

number

[0047]

number

[0048] Where WPH is the current number of wafers processed per hour, WPH ref is the nominal (reference) number of wafers processed per hour, GM is the stability gain margin of the motion servo, and GM min is the minimum acceptable stability gain margin of the motion servo, PM is the phase margin of the motion servo, and PM min is the minimum allowable motion servo stability phase margin, WHE is the wafer handoff error, WHE maxis the maximum tolerable wafer handoff error, WS is the wafer slippage at the end effector EE of the substrate transport apparatus 550 (see, e.g., FIGS. 2E-2I), and WS max is the maximum allowable wafer slippage at the end effector EE of the substrate transport apparatus 550, ST is the motion settling time of the substrate transport apparatus 550, and ST max is the maximum allowable settling time of the substrate transport device, WHV is the wafer handoff vibration, and WHV max is the maximum allowable wafer hand-off vibration, WWE is the wafer motion sway (e.g., of the arm with the arm extended in the substrate holding station), and WWE max is the maximum allowable wafer motion swing (e.g., of the arm when the arm is extended in the substrate holding station), WMV is the wafer motion vibration, and WMV max is the maximum allowable wafer operating vibration, and k var are the weights between 0 and 1 associated with each of the variables mentioned above (e.g., k wph is the weight associated with the current number of wafers processed per hour, and k GM is the weight associated with the stability gain margin of the motion servo, etc.

[0049] The wafers per hour WPH may be determined in any suitable manner, such as by the average time between two processed wafers exiting the substrate processing apparatus 555. The wafers per hour WPH represent the flow of wafers or substrates S from the substrate processing apparatus 555 to a load lock or from a load lock to the substrate processing apparatus 555 (see, for example, FIG. 1A and load lock 11010 and other load locks described herein).

[0050] The wafer handoff error WHE is defined by the difference in wafer offset (reported from any suitable position feedback system of the substrate processing apparatus, including but not limited to, a modular metrology station 400B including an on-the-fly substrate centering sensor (see FIG. 6)) between subsequent pick (or place) operations from the same substrate holding station. FIG. 6 illustrates a modular metrology station 400B having at least one two-dimensional and / or three-dimensional position sensor 600, 601 (e.g., camera, CCD array, etc.) and configured to determine the pick-place offset of the substrate S relative to the end effector EE of the arm 550A of the substrate transport apparatus 550. Other suitable examples of on-the-fly substrate sensors that may be utilized in accordance with aspects of the disclosed embodiments are described, for example, in U.S. Patent No. 6,556,887, issued April 29, 2003, U.S. Patent No. 6,990,430, issued January 24, 2006, and U.S. Patent No. 10,134,623, issued November 20, 2018, the entire disclosures of which are incorporated herein by reference. An increasing trend between pick (and / or place) wafer offsets reported from the same substrate holding station may be an indication of a wafer handoff error.

[0051] Wafer slippage WS at the end effector EE (see, e.g., FIGS. 2E-2I) is defined as the amount of measurable slippage of the substrate or wafer S between the wafer S and the end effector EE of the arm 550A as a result of acceleration or vibration of the arm 550A. Wafer slippage WS may be measured in any suitable manner, such as by comparing the reported wafer offsets (as described above) between pick and place operations between an origin (i.e., pick from) substrate holding station and a destination (i.e., place to) substrate holding station. An increasing trend in the difference between the respective reported wafer offsets (e.g., pick and place wafer offsets) may be an indication of wafer slippage on the end effector EE.

[0052] The motion settling time ST of the substrate transport apparatus 550 (such as arm 550A) is defined as the time from the end of a commanded arm motion to the time when the motion servo loop error settles within a predetermined tolerance. If the motion servo loop error is within its respective tolerance by the end of the commanded motion, the motion settling time ST will be zero; however, the predetermined tolerance is generally defined as the allowable settling error limit for the position error and velocity error of each of the motion axes. The motion of arm 550A is complete (e.g., settled) when the position error and velocity error of each of the motion axes are within the predetermined tolerance at approximately the same time. An increasing trend in the motion settling time ST may indicate a change to the mechanical behavior of the substrate transport apparatus 550, such as increased friction or vibration.

[0053] The motion servo stability gain margin G and motion servo stability phase margin P may be determined in any suitable manner, such as by Bode plot. According to aspects of the disclosed embodiment, the servo loop for each motion axis of the substrate transport apparatus 550 is tuned to maximize the stability gain margin and stability phase margin, taking into account variations in the operation of the substrate transport apparatus 550 affected by mechanical and / or environmental operating conditions, including, but not limited to, temperature gradients, thermal stress, bearing wear, and changes in transmission band tension. A decrease in the motion servo stability gain margin G and motion servo stability phase margin P below a predetermined minimum threshold may indicate operational quality symptoms (e.g., motion vibrations and wafer slippage) during operation of the substrate transport apparatus 550 and / or indicate a maintenance alert to the operator.

[0054] The wafer or substrate hand-off vibration WHV is defined as the peak-to-peak tracking error of the end effector EE motion during wafer hand-off at the respective substrate holding station (e.g., vertical lift or lowering of the wafer relative to the substrate holding station along the vertical Z-axis (see FIG. 9 )). The substrate hand-off vibration may be determined in any suitable manner, such as by substantially direct measurement of points on the substrate S or end effector EE (using any contact or non-contact sensor, e.g., optical sensor, accelerometer, etc.) during the raising or lowering of the arm 55OA of the substrate transport apparatus 550. Referring also to FIG. 9 , the modular metrology station 400B is illustrated as having at least one distance measuring sensor 888 (e.g., optical laser sensor, etc.). The modular metrology station 400B with at least one distance measuring sensor 888 is configured to sense changes in distance of the substrate S and / or end effector EE (e.g., relative to movement of the substrate S or end effector along the Z-axis of movement), indicative of vibration of the substrate / end effector. Here, the modular metrology station 400B utilizes a power spectral density (or its integral over a frequency range) analysis of the output of at least one distance measuring sensor 888 obtained by movement of the substrate S and / or end effector EE along the Z-axis of movement to determine the wafer hand-off vibration WHV, although it is noted that in other aspects, any suitable sensor / sensor analysis may be utilized to determine the wafer hand-off vibration WHV by the modular metrology station 400B. The wafer motion wobble WWE is defined as the maximum deviation error between the commanded trajectory of the wafer S and the actual trajectory of the wafer S at a given wafer S entry point of the substrate processing module 11030. Referring again to FIG. 6 , the modular metrology station 400B, including position sensors 600, 601, may also be utilized to provide a measurement of the wafer motion wobble WWE.Here, the modular metrology station may utilize wafer position measurements and end effector perimeter position measurements to provide real-time feedback of the position of the wafer S in space relative to the reported position of the arm 550A (such as by the encoder 299E of any suitable drive section 299). The modular metrology station 400B may communicate with the controller 11091 via any suitable deterministic network (such as those described herein) to provide real-time feedback of the path of the wafer S and calculation of the wafer wobble WWE error.

[0055] The wafer motion vibration WMV is a measurement of the vibration of the wafer S during movement of the wafer S between substrate holding stations (e.g., between one or more load ports, process modules, load locks, aligners, etc.). The wafer motion vibration WMV may be measured in any suitable manner, but for example, the wafer motion vibration WMV may be defined as the peak value of the compound acceleration error during wafer transfers resulting in one wafer processing cycle. In other aspects, the wafer motion vibration WMV may be determined by the root mean square of the compound acceleration error during wafer transfers resulting in one wafer processing cycle. In yet other aspects, the wafer motion vibration WMV is defined as the sum of the magnitudes of the power spectral density of the motion acceleration or torque values ​​over a specified frequency range for the wafer transfers resulting in one wafer processing cycle.

[0056] Table 1 below shows the correlation between the above-mentioned predetermined arm motion characteristics / evaluation indexes (motion automation variables) and each control parameter that can be used in association with the predetermined arm motion characteristics / evaluation indexes.

[0057] [Table 1]

[0058] As described above, the wafer operational quality index WMQIdx is defined by operational automation variables that can be dynamically changed or adapted, such as through adaptive components or control laws (and associated parameters / gains) implemented by the controller 11091, to maximize the wafer quality index WMQIdx. Here, the controller 11091 is programmed with adaptive control laws and / or machine learning-based laws that direct changes in control parameters to generate a maximum wafer quality index WMQIdx (e.g., a maximum overall measurement index) or minimize the progression of adverse changes (as described herein) in the wafer quality index WMQIdx. The adaptive control laws and / or machine learning-based laws adjust the above-mentioned control parameters shown in Table 1, for example, to maximize the wafer operational quality index WMQIdx of the substrate processing apparatus 550. It is noted that the adaptive control laws and / or machine learning based laws (described herein and in the examples provided below) may be provided at least in part by the controller 11091, however, as discussed above, calculations and / or memory may be offloaded from the controller 11091 to the modular metering stations 400, 400A-400D described herein, such that the modular metering stations 400, 400A-400D may perform some of the calculations and / or provide memory to provide the adaptive control laws and / or machine learning based laws.

[0059] For non-limiting illustrative purposes only, the wafers per hour (WPH) can be adjusted by the controller 11091 by modifying the motion trajectory constraints, as shown (for illustrative purposes) in Table 1. The type of constraint (or limit) that is changed depends on the type of trajectory shape selected to effect the motion of the arm 550A, such as that described in U.S. Patent No. 6,216,058, issued April 10, 2001, the entire disclosure of which is incorporated herein by reference. The adaptive control law and / or machine learning-based law is configured to determine which of the various types of motions that the arm 550A may perform to transfer wafers (S) has the greatest impact on the wafers per hour (WPH) metric. FIG. 10 is an exemplary flow diagram illustrating the adaptation of the wafers per hour (WPH) of the substrate processing apparatus 550, for example, based on each control variable described herein. For purposes of illustration in FIG. 10 , the radial extension movement of arm 550A to the station for the place operation (with wafer S on end effector EE) is determined to have the greatest substantial impact (e.g., be the dominant movement) on the number of wafers per hour (WPH) at each substrate holding station of substrate processing apparatus 550 ( FIG. 10 , block 900). Also, for illustrative purposes only, the trajectory shape of the radial extension movement at each substrate holding station is determined as the acceleration-limited trajectory shape ( FIG. 10 , block 910). In this example, to achieve an approximately 10% improvement in wafers per hour (WPH), the adaptive control law may increase the acceleration limit by a similar percentage of approximately 10%, and the response of the other performance indicators (discussed above) to the increased acceleration limit may be measured (using modular metrology stations 400, 400A-400D) ( FIG. 10 , block 920), and the new number of wafers per hour may be calculated ( FIG. 10 , block 930). Blocks 900-930 of FIG. 10 may continue in a loop (eg, systematically increasing the acceleration limit) until an inflection point is reached where the wafer motion quality indicator WMQIdx begins to decrease.For example, if the acceleration limit becomes too high, the wafer slippage WS may reach an unacceptable point, increasing the wafer slippage index WSIdx and, as a result, leading to a decrease in the overall wafer performance quality index WMQIdx, despite the improvement in the number of wafers processed per hour index WPHIdx.

[0060]

[0013] Referring also to Figure 11, an exemplary flow diagram of an adaptive control law for minimizing wafer handling error WHE is illustrated. An approach similar to that illustrated in Figure 11 may be utilized to minimize other system-level characteristic / metrics (and related metrics), such as wafer slippage W, settling time ST, wafer handoff vibration WHV, wafer motion swing WWE, etc. In the example illustrated in Figure 11, the wafer handling error WHE is calculated / determined (e.g., as described above with respect to the modular metrology station 400B illustrated in Figure 6) (Figure 11, block 1000), and it is determined (e.g., by the modular metrology station 400B or the controller 11091) whether the wafer handling error WHE exceeds a predetermined maximum allowable threshold (Figure 11, block 1010). If the wafer handling error WHE exceeds a predetermined maximum acceptable threshold and the wafer handling error WHE is not within the acceptable range (e.g., the tolerance limit exceeds the predetermined maximum acceptable threshold), the controller 11091 causes issuance of a service request to an operator of the substrate processing apparatus 550 (FIG. 11, block 1020). If the wafer handling error WHE exceeds a predetermined maximum acceptable threshold and the wafer handling error WHE is within the acceptable limits, constraints on the Z-axis movement of the wafer S are identified (FIG. 11, blocks 1030-1032). For example, if the movement of the wafer S along the Z-axis is jerk-limited, the jerk limit can be lowered to reduce the amount of wafer handling error WHE (FIG. 11, block 1040). If the movement of the wafer S along the Z-axis is acceleration-limited, the acceleration limit can be lowered to reduce the amount of wafer handling error WHE (FIG. 11, block 1041). If the movement of the wafer S along the Z axis is rate limited, the rate limit may be reduced to reduce the amount of wafer handling error WHE (FIG. 11, block 1042).The controller 11091 or the modular metrology stations 400, 400A-400D may determine whether the productivity of the substrate processing apparatus is within acceptable limits in any suitable manner (e.g., when one or more of the jerk limit, acceleration limit, and velocity limit are reduced), and if not, the controller 11091 may issue a service request error to the operator of the substrate processing apparatus 550 (Figure 11, block 1050).

[0061] 12, an exemplary graph illustrating the adaptation of predetermined performance characteristic indicators and their respective variables to result in maximization of the wafer processing rate indicator WPHIdx is illustrated, however, it should be understood that the exemplary graph represents the maximization / minimization of any one or more of the predetermined performance characteristic indicators (and their respective variables) described herein, as well as the maximization of the wafer movement quality indicator WMQIdx. It is noted that the exemplary graph of FIG. 12 also represents the maximization / minimization of any one or more of the predetermined performance characteristic indicators (and their respective variables) described herein, as well as the maximization of the wafer movement quality indicator WMQIdx between any suitable processing / holding position of the substrate processing apparatus 555 and any of the substrate processing apparatuses illustrated in FIGS. 1A-2D. For example, with reference to FIG. 1A, the adaptation of predetermined performance characteristic indicators and their respective variables described herein may be utilized throughout the substrate processing apparatus 11090 (e.g., from the load port 11040, through the substrate processing apparatus (according to a predetermined substrate processing recipe) and back to the load port 11040). The adaptation of the predetermined functional characteristic indicators and their respective variables described herein may also be utilized between any two points in a process performed by the substrate processing apparatus 11090, such as between the load port 11040 and the load lock 11010 via the mini-environment (front end unit) 11060, or between the load lock 11010 and the process module 11030. As can be understood from Figure 12 and its description, each of the predetermined functional characteristic indicators is modifiable such that one or more modifications of the predetermined functional characteristic indicators are collectively implemented to maximize the wafer operational quality indicator WMQIdx.

[0062] In the graph illustrated in FIG. 12 , the effect of maximizing the number of wafers processed per hour index WPHIdx on the wafer slippage index WSIdx and the wafer motion quality index WMQIdx is illustrated for illustrative purposes only, although it should be noted that any one or more of the predetermined functional characteristic indexes may be varied in a manner generally similar to that described herein. The illustrated graph is divided into five intervals, which, as described above, may be intervals within the movement of a substrate or wafer S between any two or more points (referred to as substrate processing points A and B in FIG. 12 ) in one or more processes performed by the substrate processing apparatus 11090. In other embodiments, the intervals may be time intervals or intervals of any suitable number of robot cycles. In interval 1, the substrate transport apparatus 550 is controlled to increase the acceleration of arm 550A to increase the number of wafers processed per hour index WPHIdx. In interval 1, the wafer slippage index WSIdx and the wafer motion quality index are substantially unaffected by an increase in the number of wafers per hour. During interval 2, wafer slippage occurs (i.e., wafer slippage index WSIdx increases), causing the wafer operation quality index WMQIdx to decrease, but the wafer slippage remains within an acceptable level. During interval 3, when the respective wafer slippage index WSIdx exceeds a predetermined maximum threshold WSIdxmax, the rate of the wafer number per hour index WPHIdx is zeroed while the wafer slippage reaches an unacceptable level. During interval 4, the controller 11091 slows the operation of arm 550A of the substrate transport apparatus 550 to bring the wafer slippage within an acceptable level, where the wafer operation quality index WMQIdx decreases due to the slow operation of arm 550A. During interval 5, the wafer slippage index WSIdx and the wafer number per hour index WPHIdx are stabilized to optimal levels for the conditions of the substrate processing apparatus 555 during time interval 5, resulting in an optimal wafer operation quality index WMQIdx.This adaptive process to maximize the wafer operational quality index WMQIdx may continue (e.g., in a virtual loop by the controller 11091 using one or more modular metrology stations 400, 400A-400D) until it becomes impossible to manage wafer slippage while maintaining an acceptable wafer per hour WPH evaluation metric, and the controller 11091 issues a service call to an operator of the substrate processing apparatus 555 for servicing the substrate transport apparatus 550.

[0063] As noted above, and still referring to FIG. 5 , the substrate processing apparatus 555 may include one or more modular metrology stations 400, 400A-400D. The modular metrology stations 400, 400A-400D may collect processing information from the substrate transport apparatus 550, the isolation valves 551, the processing chambers (such as those with sensors located on the processing chamber lids 552), and any other substrate processing equipment (e.g., aligners, slot valves, substrate elevators, load locks, load ports, front-end units / fan filter units, vacuum gauges, etc.). This data from the various substrate processing equipment described above may provide the controller 11091 with respective system-level variables that may be utilized to effect maximization of the wafer operational quality index WMQIdx. Table 2 below provides an exemplary summary of additional system-level variables or predetermined functional characteristics for each individual automated component of the substrate processing apparatus 550.

[0064] [Table 2]

[0065] Each of the system-level variables listed in Table 2 may have an associated performance indicator in a manner similar to that described in equations [2]-

[10] above. As a result, the system component performance indicators SCPIdx may also be incorporated into the definition of equation [1], such as by being added to the numerator of a fraction. According to aspects of the disclosed embodiment, the controller 11091 monitors an overall measurement indicator (e.g., a wafer operational quality indicator WMQIdx), identifies trends therein, and, in response to the identified trends, adaptively generates commands that effect changes to control parameters that alter dependent predetermined functional characteristics and their corresponding indicators. For example, a load lock (such as load lock 11010 in FIG. 1A) may be an entry and exit point for wafers S in the substrate processing apparatus 555, where the load lock's environment alternates between vacuum and atmospheric pressure. Pump and vent times (e.g., determined from the pressure gauge 588 of the modular metrology system 400A) are productivity performance parameters of the substrate processing apparatus 555 that can be measured and tracked over time to detect increasing trends in the loadlock 11010 processing times. Deviations or trends in pump and vent times can be utilized by the controller 11091 to control the loadlock to modify the opening and closing times of the isolation valves to compensate for the increase in loadlock processing time. Another possible adaptation of the loadlock 11010 can be a modification / adaptation (e.g., by the controller 11091 utilizing adaptive control laws and / or machine learning based laws) of the operation timing of the vertical lift mechanism of the wafer support in the loadlock that controls the vertical / lift movement of the wafer in the loadlock.

[0066] As another example of an adaptive control law and / or a machine learning-based law, the controller 11091 monitors a change in an overall measurement index (e.g., a wafer operational quality index WMQIdx) from a transient state of at least one index of each predetermined functional characteristic in response to a controller command that alters a control parameter that determines the respective predetermined functional characteristic. For example, the opening and closing time interval of the slot valve 551 can be utilized as a performance indicator of wafer processing time for the substrate processing apparatus 555. As can be appreciated, the opening and closing time interval of the slot valve 551 can also be indicative of wear of a slot valve seal. For example, a change in the opening and closing time interval of the slot valve 551 can indicate required maintenance of an O-ring (or other suitable) seal that is part of an isolation device. If a positive trend is observed in the time it takes to open and close the slot valve 551, the opening and closing time interval of the slot valve 551 can degrade tool performance. Here, this slot valve opening and closing time interval and its trend (obtained, for example, by modular metrology station 400A and its appropriate sensors 500A-500C) can be utilized by controller 11091 to dynamically change the trajectory profile of door 551D of slot valve 551 to compensate for the change in slot valve opening and closing time interval and offset any adverse changes in the wafer's operational quality index WMQIdx.

[0067] The controller 11091 monitors a change in at least one indicator of the wafer's operation quality index WMQIdx from a transient state, and in response to a predetermined adverse change in the wafer's operation quality index WMQIdx, commands a change in a control parameter that determines another respective predetermined functional characteristic that at least partially offsets the predetermined adverse change in the wafer's operation quality index WMQIdx. For example, in the slot valve example above, the controller 11091 may also (or instead of changing the trajectory profile of the door 551D of the slot valve 551 to compensate for a change in the slot valve's opening and closing time interval) modify (e.g., accelerate) the operation of the substrate transport apparatus 550 to compensate for delays caused by a degradation in the performance of the slot valve 551 and offset the adverse change in the wafer's operation quality index WMQIdx.

[0068] The controller 11091 calculates a change in the wafer motion quality index WMQIdx from a transient state of at least one predetermined functional characteristic index (e.g., from one of the wafer processing rate index WPHIdx, the position loop servo gain margin index GMIdx, the position loop servo phase margin index PMIdx, the wafer handling error index WHEIdx, the wafer slippage index WSIdx, the settling time index STIdx, the wafer handoff vibration index WHVIdx, the wafer motion swing index WWEIdx, and the wafer motion vibration index WMVIdx) by calculating the change in the wafer motion quality index WMQIdx from a transient state of at least one predetermined functional characteristic index (e.g., from one of the wafer processing rate index WPHIdx, the position loop servo gain margin index GMIdx, the position loop servo phase margin index PMIdx, the wafer handling error index WHEIdx, the wafer slippage index WSIdx, the settling time index STIdx, the wafer handoff vibration index WHVIdx, the wafer motion swing index WWEIdx, and the wafer motion vibration index WMVIdx). and comparing relative changes in the wafer operation quality index WMQIdx from other different transient states of at least another different predetermined functional characteristic index (such as from a different one of the wafer phase margin index PMIdx, the wafer handling error index WHEIdx, the wafer slippage index WSIdx, the settling time index STIdx, the wafer handoff vibration index WHVIdx, the wafer operation sway index WWEIdx, and the wafer operation vibration index WMVIdx), and scaling the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the wafer operation quality index WMQIdx due to the transient state and the other different transient state. For example, referring to equations [2]-

[10] , the controller 11091 may be configured to scale the weights k of the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other such that the wafer operation quality index WMQIdx and each of the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other are optimized. var can be adjusted.

[0069] According to aspects of the disclosed embodiments, the modular metrology stations 400, 400A-400D and adaptive control laws and / or machine learning-based laws described herein provide the substrate processing apparatus 555 (and its components) with monitoring of the occurrence and timing of self-induced or external vibration sources. For example, with respect to the effect of vibration on the substrate transport apparatus 550, it is noted that the opening and closing of slot valves creates vibration impulses that can affect the quality of wafer operation in the substrate processing apparatus 555. A modular metrology station, such as modular metrology station 400A, may capture vibration information in conjunction with the timing of actuation of the slot valve 551 (e.g., using appropriate sensors 500A-500C) and / or may time-stamp the capture of vibration information. A robotics controller, such as controller 11091, may control the substrate transport apparatus 550 such that high-precision wafer placement by the substrate transport apparatus does not occur during actuation of the slot valve 551, where the slot valve 551 is part of the substrate processing station that is not associated with high-precision wafer placement. Here, high-precision wafer placement can be achieved during “quiet” times, i.e., times when there is no vibration from actuation of the slot valves 551 from elsewhere within the substrate processing apparatus 555. In other embodiments, other vibrations from sources external to the substrate transport apparatus 550, such as from the vacuum pump VP (e.g., from the load lock 11010 and / or process module 11030), can be detected by a position sensor (e.g., encoder 299E of drive section 299 (see FIGS. 2E-2I)) and processed within the controller 11091 (or modular metrology station 400B) to quantify the effect of the external vibrations on the position servo loop performance of the substrate transport apparatus 550. Here, the controller 11091 can use adaptive control laws and / or machine learning-based laws to make changes to the filter parameters of the servo loop (e.g., a Bi-Quad filter, etc.) to dampen the servo loop response to external vibrations emanating from the vacuum pump.

[0070] According to aspects of the disclosed embodiment, the modular metrology stations 400, 400A-400D and adaptive control laws and / or machine learning-based laws described herein provide a substrate processing apparatus 555 with monitoring of wafer alignment time performance of the aligner 553. In a manner similar to that described above with respect to the slot valve 551, wafer alignment time may be affected by degradation of components of the aligner 553, such as wafer support (backside or edge contact) pads. Here, if an upward trend in wafer alignment time is observed, the wafer alignment time may decrease productivity of the substrate processing apparatus 555. The wafer alignment time measured by the appropriate sensor 500J of the modular metrology station 400D is utilized by the controller 11091 to dynamically adapt / alter the operating performance of the substrate transport apparatus 550 (e.g., increase acceleration and / or velocity) to significantly avoid or otherwise mitigate wafer productivity losses.

[0071] In some embodiments, the modular metrology station 400D provides for recording and establishing trends regarding the wafer offset and wafer reference position of the wafer liner 553. For example, as can be appreciated, given the repeatability of operations in the substrate processing equipment 555, the aligner 553 may determine a typical offset and reference position of a wafer S aligned thereby and communicate that information to the controller 11091 and / or the modular metrology station 400D. The typical offset and reference position information may be utilized by the controller 11091 and / or the modular metrology station 400D (such as when computing power is offloaded from the controller 11091 to the modular metrology station 400D) to predict wafer offset prior to placing the wafer on the aligner 553. Here, the aligner 553 may be utilized to scan the wafer offset within a narrower range (smaller scale) to improve the accuracy of the aligner 553.

[0072] As described herein, the modular metrology station 400C includes sensors 500G-500I disposed on the process chamber lid 552. The sensors 500G-500I may include temperature sensors disposed to monitor the temperature of the wafer S (and / or the temperature of the arm link, as described herein) before and after the wafer S is processed in the respective substrate processing module 11030. As can be appreciated, the temperature of the wafer S may affect the acceleration limit of the end effector EE of the substrate transport apparatus 550 before wafer slippage occurs. Here, the operation of the substrate transport apparatus 550 may be optimized by the controller 11091 (or by the modular metrology station 400B, if such optimization is communicated to the controller 11091) to effect the transfer of the wafer S at maximum acceleration based on the temperature of the wafer S reported at the start of the wafer S transfer operation.

[0073] Monitoring the temperatures of the modular metrology station 400C and the wafer S may result in adaptive operation of the substrate transport apparatus 550 to extend the life of the substrate transport apparatus. For example, if data obtained by the modular metrology station 400C indicates an increasing trend in the temperature of the wafer S from a substrate processing module 11030 picking operation, such wafer S temperature information may be communicated from the modular metrology station 400C to the controller 11091, which may then adaptively change the operation of the substrate transport apparatus 550 such that motion (e.g., acceleration and / or speed) is reduced and / or robot idle time is increased to allow cooling of bearings (and other components of the substrate transport apparatus 550) affected by the increased wafer / processing module temperature.

[0074] 5, in one or more embodiments, the lid of a transfer chamber (e.g., transfer chamber 11025) in which the substrate transport apparatus 550 is disposed includes a sensor 500K associated with a modular metrology station in a manner generally similar to the process chamber lid 552 described herein. Here, the modular metrology station sensor 500K includes a suitable temperature sensor (e.g., an infrared sensor or other suitable sensor) positioned to sense the temperature of a flange 550F (e.g., a mechanical interface between the drive 299 and the chamber in which the substrate transport apparatus is disposed) and / or an arm link (see FIGS. 2E-2I) of the substrate transport apparatus 550. Depending on the temperature of the flange 550F and the arm link, the controller 11091 effects the positioning of the wafer S, taking into account thermal effects on the substrate transport apparatus 550. For example, the controller 11091 may adapt servo loop control parameters of the substrate transport apparatus to prevent instabilities caused by temperature changes. The lid of the transfer chamber 11025 may also include optical / visual sensors (e.g., cameras) such that its modular metrology station is configured to optically track the position (and / or thermal growth / contraction) of the substrate transport apparatus 550. Here, the controller 11091 can utilize feedback of the temperature and / or position of different links to estimate the thermal expansion of the arm links and modify the motion model of the substrate transport apparatus to take into account the thermal effects on the arm links and thereby improve placement accuracy by placing the wafer at the target location.

[0075] 1A and 5, airflow from the fan filter unit FFU of the mini-environment (or front end unit) 11060 may be monitored by the flow meter / sensor 500L of the modular metrology station 400E. Airflow may be a variable of the substrate processing apparatus 11090, 555 that may affect the operation of the substrate transport apparatus 11013 within the mini-environment 11060 (e.g., where the substrate transport apparatus 11013 may be generally similar to the substrate transport apparatus 550). For example, airflow (e.g., amount, velocity, etc.) may affect the repeatability of wafer placement of the substrate transport apparatus 11013 (e.g., affecting settling time, inducing vibrations in the arm 550A, etc.), where the controller 11061 may dynamically adapt / adjust the operation of the substrate transport apparatus 11013 to minimize the effect of the airflow of the fan filter unit FFU.

[0076] With reference to Table 3 below, additional substrate transport apparatus variables or predetermined functional characteristics may be utilized as predetermined characteristics or metrics for the wafer motion quality index WMQIdx. The additional variables listed in Table 3 are described, for example, in relation to substrate transport apparatus performance within a template transport. Suitable examples of template transport can be found, for example, in U.S. Patent Application No. 15 / 971,827, filed May 4, 2018, and entitled "Method and Apparatus for Health Assessment of Transport Apparatus," the entire disclosure of which is incorporated herein by reference.

[0077] [Table 3]

[0078] The transport device performance index RPIdx may be defined based on the variables set forth in Table 3, where the transport device performance index RPIdx is defined as follows:

[0079]

number

[0080] where PMTIdx is the peak motor temperature index, PMCIdx is the peak motor current index, PMVIdx is the peak motor voltage index, MMWIdx is the peak motor mechanical work index, PTEIdx is the peak tracking error index, PAOIdx is the peak acceleration overshoot index, RMSIdx is the root mean square acceleration index, and PDMEIdx is the peak dynamic model error index. In a manner similar to that described above with respect to the definitions presented in equations [2]-

[10] , each index in equation

[11] may be defined as the ratio of the most recent value of the respective variable in Table 3 to its tolerance threshold. The system substrate transport equipment performance index RPIdx may be added to the numerator of equation [1] such that the wafer motion quality index WMQIdx is further defined as:

[0081]

number

[0082] Referring again to FIG. 5 , aspects of the disclosed embodiment provide a scalable platform for robotic control and diagnostics as described herein. The modular metrology station 400 may be added to process equipment (such as process modules 598, substrate transport apparatus 599, and any other suitable process equipment (such as those described herein)) added to an existing substrate processing apparatus 555. For example, FIGS. 1C, 1D, and 2A-2D illustrate scalable linear and cluster tool configurations in which the modular metrology station 400 may be utilized to provide system-level component diagnostics (as described herein) in addition to adaptive operation of tool components 800 ( FIG. 8 ). As described herein, additional modular metrology stations 400 may be coupled to the controller 11091 in any suitable manner (such as plug-and-play) to provide for modular addition of modular metrology stations 400 and associated substrate processing equipment.

[0083] 5 and 13, an exemplary method will be described according to aspects of the disclosed embodiment. The method includes providing a substrate processing system 555 (such as those described herein) (FIG. 13, block 1300). At least one arm motion sensor (also referred to as a transfer echelon sensor) 566 coupled to a controller 11091 senses a predetermined characteristic of the arm motion (or transfer echelon) (FIG. 13, block 1310). At least one system metrology sensor (also referred to as a process echelon metrology sensor) 500A-500z coupled to the controller 11091 senses a predetermined characteristic of the system metrology (or process echelon) that is different from the predetermined characteristic of the arm motion (FIG. 13, block 1320). The controller 11091 records data DAT, DAT2 from the at least one arm motion sensor 566 and at least one of the at least one system metrology sensors 500A-500z, and determines a set of predetermined functional characteristic indicators (as described herein) from the recorded data DAT, DAT2 ( FIG. 13 , block 1330). Each predetermined functional indicator corresponds to a different respective predetermined functional characteristic of the arm motion transporting the substrate S or of the substrate processing system 555, and indicates a relationship between each predetermined functional characteristic and the motion quality of the substrate S transported by the movable arm 550A. An integrated overall measurement indicator of the overall motion quality of the substrate S transported by the movable arm 550A (e.g., wafer motion quality indicator WMQIdx) is determined by the controller 11091 from the set of predetermined functional characteristic indicators ( FIG. 13 , block 1340).

[0084] 5 and 14, an exemplary method is described according to aspects of the disclosed embodiment. The method includes providing a substrate processing system 555 (such as those described herein) (FIG. 14, block 1400). Using a controller 11091, a set of predetermined functional characteristic indicators is generated from sensor data DAT, DAT2 embodying both predetermined characteristics of the transfer echelon (e.g., arm motion) and predetermined characteristics of processing echelon (or system) metrology (FIG. 14, block 1410). As described above, each predetermined functional characteristic indicator corresponds to a different respective predetermined functional characteristic of the substrate transport apparatus 550 transporting the substrate S or of the substrate processing echelon, and indicates a relationship between each predetermined functional characteristic and the operational quality of the substrate S transported by the substrate transport apparatus 550. An integrated overall metric of the overall operational quality of the substrate S transported by the substrate transport apparatus 550 (e.g., wafer operational quality indicator WMQIdx) is determined from the set of predetermined functional characteristic indicators using the controller (FIG. 14, block 1420).

[0085] In accordance with one or more aspects of the disclosed embodiment the substrate processing system comprises: a frame that forms a substrate transfer space within the substrate processing system; a substrate transport apparatus operably coupled to the frame, the substrate transport apparatus comprising a movable arm and a drive section configured to move the movable arm to transport a substrate held on an end effector of the arm through a transport space from a first location of the substrate processing system to a second location of the substrate processing system that is different from the first location; a controller operatively coupled to the movable arm and the drive section to effect movement of the movable arm to different system positions, the controller communicatively coupled to at least one arm motion sensor and at least one system metrology sensor, the at least one arm motion sensor sensing a predetermined characteristic of the arm motion, and the at least one system metrology sensor sensing a predetermined characteristic of the system metrology that is different from the predetermined characteristic of the arm motion; Equipped with the controller is configured to record data from at least one of the at least one arm motion sensor and the at least one system metrology sensor, and determine from the recorded data a set of predetermined functional characteristic indicators, each indicator corresponding to a different respective predetermined functional characteristic of the arm motion transporting the substrate or of the substrate processing system, and indicating a relationship between each predetermined functional characteristic and a motion quality of the substrate transported by the movable arm; The controller is configured to determine an integrated overall measure of the overall motion quality of the substrates transported by the moveable arm from the set of predetermined performance characteristic indicators.

[0086] In accordance with one or more aspects of the disclosed embodiment, each predetermined functional characteristic includes at least one of: number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0087] In accordance with one or more aspects of the disclosed embodiment, each predetermined performance characteristic comprises at least one of substrates processed per hour and wafer slippage.

[0088] In accordance with one or more aspects of the disclosed embodiments, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0089] In accordance with one or more aspects of the disclosed embodiment, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic, including at least one of number of substrates processed per hour and wafer slippage.

[0090] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined characteristics of the system measurements is derived from arm motion.

[0091] In accordance with one or more aspects of the disclosed embodiment, the controller is configured to determine an operating value for each different respective predetermined functional characteristic from the recorded data and factor and evaluate the operating value against a corresponding reference value for each different predetermined functional characteristic.

[0092] In accordance with one or more aspects of the disclosed embodiment, each different predetermined functional characteristic depends on at least one specific control parameter of the arm or system controlled by the controller's commands.

[0093] In accordance with one or more aspects of the disclosed embodiments, the controller monitors the overall measurement indicators, identifies trends therein, and, in response to the identified trends, adaptively generates commands that effect changes to control parameters that alter dependent predetermined functional characteristics and their corresponding indicators.

[0094] In accordance with one or more aspects of the disclosed embodiment, the controller monitors a change in an overall measurement index from a transient state of at least one index of each predetermined functional characteristic in response to a controller command that alters a control parameter that determines the respective predetermined functional characteristic.

[0095] In accordance with one or more aspects of the disclosed embodiment, the controller monitors a change in an overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a change in the predetermined adverse effect of the overall measurement index, commands a change in a control parameter determining another each predetermined functional characteristic that at least partially offsets the change in the predetermined adverse effect of the overall measurement index.

[0096] In accordance with one or more aspects of the disclosed embodiments, the controller is configured to relatively compare a change in the overall measurement index from a transient state of the at least one predetermined functional characteristic index with another change in the overall measurement index from another different transient state of the at least another different predetermined functional characteristic index, and scale the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

[0097] In accordance with one or more aspects of the disclosed embodiments, the controller is programmed with adaptive control laws and / or machine learning based laws that direct changes to control parameters to produce a maximum overall metric or minimize the progression of adverse changes in the overall metric.

[0098] In accordance with one or more aspects of the disclosed embodiments, at least one of the predetermined functional characteristics is a system functional characteristic including at least one of a load lock pump and vent time, a load lock vertical lift operation time, a vibration signature of the load lock, a time interval between opening and closing of a slot valve, a time interval between successive openings of a slot valve, an opening and closing timestamp of a slot valve, a vibration signature of the slot valve, an alignment time of a substrate aligner, a historical substrate offset and reference position, a substrate temperature, a movable arm temperature, a flange temperature of a substrate transport apparatus, a vacuum level, and an airflow.

[0099] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of a motor temperature, a motor current, a motor voltage, a motor mechanical work, an end effector tracking error, an end effector acceleration overshoot, an end effector root mean square acceleration, and a dynamic model error.

[0100] In accordance with one or more aspects of the disclosed embodiment, the at least one arm motion sensor and the at least one system metrology sensor are modular metrology sensors having a common modular platform that is selectively configurable.

[0101] In accordance with one or more aspects of the disclosed embodiment the substrate processing system comprises: The frame and a substrate processing station and at least one substrate input or output station connected to the frame and forming a substrate processing echelon of the substrate processing system; a substrate transport apparatus movably mounted on the frame and configured to transport substrates along a substrate processing echelon between an input station or an output station and a substrate processing station, the substrate transport apparatus forming a transport echelon of a substrate processing system; a group of sensors including a transport echelon sensor communicatively coupled to the substrate transport apparatus arranged to sense a predetermined characteristic of the transport echelon, and a process echelon metrology sensor arranged to sense a predetermined characteristic of the process echelon metrology that is different from the predetermined characteristic of the transport echelon; a controller communicatively coupled to the transfer echelon sensors and the metrology echelon sensors, the controller configured to generate a set of predetermined functional characteristic indicators from the sensor data embodying both the predetermined characteristics of the transfer echelon and the predetermined characteristics of the process echelon metrology, each indicator corresponding to a different respective predetermined functional characteristic of a substrate transport apparatus transporting a substrate or of a substrate processing echelon, and indicating a relationship between each predetermined functional characteristic and an operational quality of a substrate transported by the substrate transport apparatus; Equipped with The controller is configured to determine, from a set of predetermined performance characteristic indicators, an integrated overall measure of the overall operational quality of substrates transported by the substrate transport apparatus.

[0102] In accordance with one or more aspects of the disclosed embodiment, a substrate transport apparatus includes a transport arm and a drive section configured to move the transport arm to transport a substrate held on an end effector of the transport arm.

[0103] In accordance with one or more aspects of the disclosed embodiment, each predetermined functional characteristic includes at least one of: number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0104] In accordance with one or more aspects of the disclosed embodiment, each predetermined performance characteristic comprises at least one of substrates processed per hour and wafer slippage.

[0105] In accordance with one or more aspects of the disclosed embodiments, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0106] In accordance with one or more aspects of the disclosed embodiment, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic, including at least one of number of substrates processed per hour and wafer slippage.

[0107] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined characteristics of the process echelon metrology is derived from substrate transport arm motion.

[0108] In accordance with one or more aspects of the disclosed embodiment the controller: Recording data from at least one of the transport echelon sensor and the process echelon metrology sensor; and From the recorded data, determining an operating value for each different respective predetermined functional characteristic, and factoring and evaluating the operating value against a corresponding reference value for each different predetermined functional characteristic. It is structured as follows.

[0109] In accordance with one or more aspects of the disclosed embodiment, each different predetermined functional characteristic depends on at least one specific control parameter of the substrate transport apparatus or substrate processing system controlled by commands of the controller.

[0110] In accordance with one or more aspects of the disclosed embodiments, the controller monitors the overall measurement indicators, identifies trends therein, and, in response to the identified trends, adaptively generates commands that effect changes to control parameters that alter dependent predetermined functional characteristics and their corresponding indicators.

[0111] In accordance with one or more aspects of the disclosed embodiment, the controller monitors a change in an overall measurement index from a transient state of at least one index of each predetermined functional characteristic in response to a controller command that alters a control parameter that determines the respective predetermined functional characteristic.

[0112] In accordance with one or more aspects of the disclosed embodiment, the controller monitors a change in an overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a change in the predetermined adverse effect of the overall measurement index, commands a change in a control parameter determining another each predetermined functional characteristic that at least partially offsets the change in the predetermined adverse effect of the overall measurement index.

[0113] In accordance with one or more aspects of the disclosed embodiments, the controller is configured to relatively compare a change in the overall measurement index from a transient state of the at least one predetermined functional characteristic index with another change in the overall measurement index from another different transient state of the at least another different predetermined functional characteristic index, and scale the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

[0114] In accordance with one or more aspects of the disclosed embodiments, the controller is programmed with adaptive control laws and / or machine learning based laws that direct changes to control parameters to produce a maximum overall metric or minimize the progression of adverse changes in the overall metric.

[0115] In accordance with one or more aspects of the disclosed embodiments, at least one of the predetermined functional characteristics is a system functional characteristic including at least one of a load lock pump and vent time, a load lock vertical lift operation time, a vibration signature of the load lock, a time interval between opening and closing of a slot valve, a time interval between successive openings of a slot valve, an opening and closing timestamp of a slot valve, a vibration signature of the slot valve, an alignment time of a substrate aligner, a historical substrate offset and reference position, a substrate temperature, a movable arm temperature, a flange temperature of a substrate transport apparatus, a vacuum level, and an airflow.

[0116] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of a motor temperature, a motor current, a motor voltage, a motor mechanical work, an end effector tracking error, an end effector acceleration overshoot, an end effector root mean square acceleration, and a dynamic model error.

[0117] In accordance with one or more aspects of the disclosed embodiment, the transport echelon sensors and the metrology echelon sensors are modular metrology sensors having respective common modular platforms that are selectively configurable.

[0118] In accordance with one or more aspects of the disclosed embodiment a method includes: Providing a substrate processing system, the substrate processing system comprising: a frame that defines a substrate transfer space within the substrate processing system; a substrate transport apparatus operably coupled to the frame, the substrate transport apparatus comprising a movable arm and a drive section configured to move the movable arm to transport a substrate held on an end effector of the arm through a transport space from a first location of the substrate processing system to a second location of the substrate processing system that is different from the first location; and a controller operatively coupled to the movable arm and the drive section to effect movement of the movable arm to different system positions; and sensing a predetermined characteristic of arm motion with at least one arm motion sensor coupled to the controller; sensing, with at least one system metrology sensor coupled to the controller, a predetermined characteristic of the system metrology that is different from the predetermined characteristic of the arm motion; using a controller to record data from at least one of the at least one arm motion sensor and the at least one system metrology sensor, and determining from the recorded data a set of predetermined functional characteristic indicators, each indicator corresponding to a different respective predetermined functional characteristic of the arm motion transporting a substrate or of the substrate processing system, and indicating a relationship between each predetermined functional characteristic and a motion quality of a substrate transported by the movable arm; determining, with the controller, from a set of predetermined performance characteristic indicators, an integrated overall measure of the overall motion quality of the substrate being transported by the movable arm; Includes.

[0119] In accordance with one or more aspects of the disclosed embodiment, each predetermined functional characteristic includes at least one of: number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0120] In accordance with one or more aspects of the disclosed embodiment, each predetermined performance characteristic comprises at least one of substrates processed per hour and wafer slippage.

[0121] In accordance with one or more aspects of the disclosed embodiments, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0122] In accordance with one or more aspects of the disclosed embodiment, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic, including at least one of number of substrates processed per hour and wafer slippage.

[0123] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined characteristics of the system measurements is derived from arm motion.

[0124] In accordance with one or more aspects of the disclosed embodiment, the method further includes determining, with the controller, from the recorded data, an operational value for each different respective predetermined functional characteristic, and factoring and evaluating the operational value against a corresponding reference value for each different predetermined functional characteristic.

[0125] In accordance with one or more aspects of the disclosed embodiment, each different predetermined functional characteristic depends on at least one specific control parameter of the arm or system controlled by the controller's commands.

[0126] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to monitor and identify trends in the overall measurement indicators, and, responsive to the identified trends, adaptively generate commands that effect changes to control parameters that alter the dependent predetermined functional characteristics and their corresponding indicators.

[0127] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to monitor a change in an overall measurement indicator from a transient state of at least one indicator of each predetermined functional characteristic in response to a controller command that alters a control parameter determining each predetermined functional characteristic.

[0128] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to monitor a change in an overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a change in the predetermined adverse effect of the overall measurement index, commanding a change in a control parameter determining another each predetermined functional characteristic that at least partially offsets the change in the predetermined adverse effect of the overall measurement index.

[0129] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to relatively compare a change in the overall measurement index from the transient state of the at least one predetermined functional characteristic index with another change in the overall measurement index from another different transient state of the at least another different predetermined functional characteristic index, and scaling the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

[0130] In accordance with one or more aspects of the disclosed embodiments, the controller is programmed with adaptive control laws and / or machine learning based laws that direct changes to control parameters to produce a maximum overall metric or minimize the progression of adverse changes in the overall metric.

[0131] In accordance with one or more aspects of the disclosed embodiments, at least one of the predetermined functional characteristics is a system functional characteristic including at least one of a load lock pump and vent time, a load lock vertical lift operation time, a vibration signature of the load lock, a time interval between opening and closing of a slot valve, a time interval between successive openings of a slot valve, an opening and closing timestamp of a slot valve, a vibration signature of the slot valve, an alignment time of a substrate aligner, a historical substrate offset and reference position, a substrate temperature, a movable arm temperature, a flange temperature of a substrate transport apparatus, a vacuum level, and an airflow.

[0132] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of a motor temperature, a motor current, a motor voltage, a motor mechanical work, an end effector tracking error, an end effector acceleration overshoot, an end effector root mean square acceleration, and a dynamic model error.

[0133] In accordance with one or more aspects of the disclosed embodiment, the at least one arm motion sensor and the at least one system metrology sensor are modular metrology sensors having a common modular platform that is selectively configurable.

[0134] In accordance with one or more aspects of the disclosed embodiment a method includes: Providing a substrate processing system, the substrate processing system comprising: Frame, a substrate processing station and at least one substrate input or output station connected to the frame and forming a substrate processing echelon of the substrate processing system; a substrate transport apparatus movably mounted on a frame and configured to transport substrates along a substrate processing echelon between an input station or an output station and a substrate processing station, the substrate transport apparatus forming a transport echelon of a substrate processing system; a group of sensors including a transport echelon sensor communicatively coupled to the substrate transport apparatus arranged to sense a predetermined characteristic of the transport echelon, and a process echelon metrology sensor arranged to sense a predetermined characteristic of the process echelon metrology that is different from the predetermined characteristic of the transport echelon; and a controller communicatively coupled to the transport echelon sensor and the measurement echelon sensor; and generating, with the controller, a set of predetermined functional characteristic indicators from the sensor data embodying both the predetermined characteristics of the transfer echelon and the predetermined characteristics of the process echelon metrology, each indicator corresponding to a different predetermined functional characteristic of the substrate transport apparatus transporting the substrate or of the substrate processing echelon, and indicating a relationship between each predetermined functional characteristic and an operational quality of the substrate transported by the substrate transport apparatus; determining, with the controller, from a set of predetermined performance characteristic indicators, an integrated overall measure of the overall operational quality of substrates transported by the substrate transport apparatus; Includes.

[0135] In accordance with one or more aspects of the disclosed embodiment, a substrate transport apparatus includes a transport arm and a drive section configured to move the transport arm to transport a substrate held on an end effector of the transport arm.

[0136] In accordance with one or more aspects of the disclosed embodiment, each predetermined functional characteristic includes at least one of: number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0137] In accordance with one or more aspects of the disclosed embodiment, each predetermined performance characteristic comprises at least one of substrates processed per hour and wafer slippage.

[0138] In accordance with one or more aspects of the disclosed embodiments, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

[0139] In accordance with one or more aspects of the disclosed embodiment, the set of predetermined functional characteristic indicators includes an indicator for at least one of each predetermined functional characteristic, including at least one of number of substrates processed per hour and wafer slippage.

[0140] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined characteristics of the process echelon metrology is derived from substrate transport arm motion.

[0141] In accordance with one or more aspects of the disclosed embodiment, the method includes, using a controller: recording data from at least one of the transport echelon sensors and the process echelon metrology sensors; determining an operational value for each different respective predetermined functional characteristic from the recorded data and factoring and evaluating the operational value against a corresponding reference value for each different respective predetermined functional characteristic; Further includes:

[0142] In accordance with one or more aspects of the disclosed embodiment, each different predetermined functional characteristic depends on at least one specific control parameter of the substrate transport apparatus or substrate processing system controlled by commands of the controller.

[0143] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to monitor and identify trends in the overall measurement indicators, and, in response to the identified trends, adaptively generate commands that effect changes to control parameters that alter the dependent predetermined functional characteristics and their corresponding indicators.

[0144] In accordance with one or more aspects of the disclosed embodiment, the method further includes monitoring, with the controller, a change in an overall measurement indicator from a transient state of at least one indicator of each predetermined functional characteristic in response to a controller command that alters a control parameter determining each predetermined functional characteristic.

[0145] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to monitor a change in an overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a change in the predetermined adverse effect of the overall measurement index, commanding a change in a control parameter determining another each predetermined functional characteristic that at least partially offsets the change in the predetermined adverse effect of the overall measurement index.

[0146] In accordance with one or more aspects of the disclosed embodiment, the method further includes using the controller to relatively compare a change in the overall measurement index from the transient state of the at least one predetermined functional characteristic index with another change in the overall measurement index from another different transient state of the at least another different predetermined functional characteristic index, and scaling the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

[0147] In accordance with one or more aspects of the disclosed embodiments, the controller is programmed with adaptive control laws that direct changes to control parameters to produce a maximum overall metric or minimize the progression of adverse changes in the overall metric.

[0148] In accordance with one or more aspects of the disclosed embodiments, at least one of the predetermined functional characteristics is a system functional characteristic including at least one of a load lock pump and vent time, a load lock vertical lift operation time, a vibration signature of the load lock, a time interval between opening and closing of a slot valve, a time interval between successive openings of a slot valve, an opening and closing timestamp of a slot valve, a vibration signature of the slot valve, an alignment time of a substrate aligner, a historical substrate offset and reference position, a substrate temperature, a movable arm temperature, a flange temperature of a substrate transport apparatus, a vacuum level, and an airflow.

[0149] In accordance with one or more aspects of the disclosed embodiment, at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of a motor temperature, a motor current, a motor voltage, a motor mechanical work, an end effector tracking error, an end effector acceleration overshoot, an end effector root mean square acceleration, and a dynamic model error.

[0150] In accordance with one or more aspects of the disclosed embodiment, the transport echelon sensors and the metrology echelon sensors are modular metrology sensors having respective common modular platforms that are selectively configurable.

[0151] It should be understood that the foregoing description is merely illustrative of aspects of the disclosed embodiments. Various substitutions and modifications may be contemplated by those skilled in the art without departing from the aspects of the disclosed embodiments. Accordingly, aspects of the disclosed embodiments are intended to embrace all such substitutions, modifications, and variations that fall within the scope of any claims appended hereto. Furthermore, the mere fact that different features are recited in mutually different dependent or independent claims does not indicate that a combination of these features cannot be used to advantage and that such combination remains within the scope of aspects of the disclosed embodiments.

Claims

1. 1. A substrate processing system, comprising: a frame that defines a substrate transport space within the substrate processing system; a substrate transport apparatus operably coupled to the frame, the substrate transport apparatus comprising a movable arm and a drive section configured to move the movable arm to transport a substrate held on an end effector of the arm through the transport space from a first location of the substrate processing system to a second location of the substrate processing system different from the first location; a controller operatively coupled to the movable arm and drive section to effect movement of the movable arm to different system positions, the controller communicatively coupled to at least one arm motion sensor and at least one system metrology sensor, the at least one arm motion sensor sensing a predetermined characteristic of arm motion, and the at least one system metrology sensor sensing a predetermined characteristic of system metrology that is different from the predetermined characteristic of the arm motion; Equipped with the controller is configured to record data from at least one of the at least one arm motion sensor and the at least one system metrology sensor, and determine from the recorded data a set of predetermined functional characteristic indicators, each indicator corresponding to a different respective predetermined functional characteristic of an arm motion transporting the substrate or of the substrate processing system, and indicating a relationship between each predetermined functional characteristic and a motion quality of the substrate transported by the movable arm; The substrate processing system, wherein the controller is configured to determine an overall overall measure of an overall operational quality of the substrate transported by the movable arm from the set of predetermined functional characteristic indicators.

2. 2. The substrate processing system of claim 1, wherein the respective predetermined functional characteristics include at least one of: number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion sway, and wafer motion vibration.

3. The substrate processing system of claim 1 , wherein each of the predetermined performance characteristics comprises at least one of substrates processed per hour and wafer slippage.

4. 2. The substrate processing system of claim 1, wherein the set of predetermined functional characteristic indicators includes an indicator for at least one of the respective predetermined functional characteristics including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion sway, and wafer motion vibration.

5. 2. The substrate processing system of claim 1, wherein the set of predetermined performance characteristic indicators includes an indicator for at least one of the respective predetermined performance characteristics including at least one of substrates processed per hour and wafer slippage.

6. The substrate processing system of claim 1 , wherein at least one of the predetermined characteristics of the system metrology is derived from arm motion.

7. 2. The substrate processing system of claim 1, wherein the controller is configured to determine an operational value for each different respective predetermined functional characteristic from the recorded data and to factor and evaluate the operational value against a corresponding reference value for each different predetermined functional characteristic.

8. 8. The substrate processing system of claim 7, wherein each different predetermined functional characteristic depends on at least one specific control parameter of the arm or the system controlled by the command of a controller.

9. 10. The substrate processing system of claim 1, wherein the controller monitors the overall measurement indicator, identifies trends therein, and, in response to the identified trends, adaptively generates commands that effect changes to control parameters that change dependent predetermined functional characteristics and their corresponding indicators.

10. 2. The substrate processing system of claim 1, wherein the controller monitors a change in the overall measurement index from a transient state of at least one index of each predetermined functional characteristic in response to a controller command that modifies a control parameter that determines the respective predetermined functional characteristic.

11. 2. The substrate processing system of claim 1, wherein the controller monitors a change in the overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a predetermined adverse change in the overall measurement index, commands a change in a control parameter determining another respective predetermined functional characteristic that at least partially offsets the predetermined adverse change in the overall measurement index.

12. 12. The substrate processing system of claim 11, wherein the controller is configured to compare a change in the overall measurement index from a transient state of at least one predetermined functional characteristic index relative to another change in the overall measurement index from another different transient state of at least another different predetermined functional characteristic index, and scale the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

13. 10. The substrate processing system of claim 1, wherein the controller is programmed with one or more of adaptive control laws and machine learning based laws that direct changes in control parameters to produce a maximum overall metric or minimize the progression of adverse changes in the overall metric.

14. 2. The substrate processing system of claim 1, wherein at least one of the predetermined functional characteristics is a system functional characteristic comprising at least one of a load lock pump and vent time, a load lock vertical lift operation time, a load lock vibration signature, a time interval between opening and closing of a slot valve, a time interval between successive openings of a slot valve, a slot valve opening and closing timestamp, a slot valve vibration signature, a substrate aligner alignment time, a historical substrate offset and reference position, a substrate temperature, a movable arm temperature, a substrate transport device flange temperature, a vacuum level, and an airflow.

15. 2. The substrate processing system of claim 1, wherein at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of a motor temperature, a motor current, a motor voltage, a motor mechanical work, an end effector tracking error, an end effector acceleration overshoot, an end effector root mean square acceleration, and a dynamic model error.

16. The substrate processing system of claim 1 , wherein the at least one arm motion sensor and the at least one system metrology sensor are modular metrology sensors having a common modular platform that is selectively configurable.

17. 1. A substrate processing system, comprising: The frame and a substrate processing station and at least one substrate input or output station connected to the frame and forming a substrate processing echelon of the substrate processing system; a substrate transport apparatus movably mounted to the frame and configured to transport substrates along the substrate processing echelon between an input station or an output station and a substrate processing station, the substrate transport apparatus forming a transport echelon of the substrate processing system; a group of sensors including a transport echelon sensor communicatively coupled to the substrate transport apparatus, the sensor positioned to sense a predetermined characteristic of the transport echelon, and a process echelon metrology sensor positioned to sense a predetermined characteristic of the process echelon metrology that is different from the predetermined characteristic of the transport echelon; a controller communicatively coupled to the transfer echelon sensors and the metrology echelon sensors, the controller configured to generate a set of predetermined functional characteristic indicators from sensor data embodying both predetermined characteristics of the transfer echelon and predetermined characteristics of the process echelon metrology, each indicator corresponding to a different respective predetermined functional characteristic of the substrate transport apparatus transporting the substrate or of the substrate processing echelon, and indicating a relationship between each predetermined functional characteristic and an operational quality of the substrate transported by the substrate transport apparatus; Equipped with The substrate processing system, wherein the controller is configured to determine an overall metric of an overall operational quality of the substrate transported by the substrate transport apparatus from the set of predetermined performance characteristic metrics.

18. 20. The substrate processing system of claim 17, wherein the substrate transport apparatus comprises a transport arm and a drive section configured to move the transport arm to transport the substrate held on an end effector of the transport arm.

19. 20. The substrate processing system of claim 17, wherein the respective predetermined functional characteristics include at least one of: number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

20. 20. The substrate processing system of claim 17, wherein the respective predetermined performance characteristics include at least one of substrates processed per hour and wafer slippage.

21. 20. The substrate processing system of claim 17, wherein the set of predetermined functional characteristic indicators includes an indicator for at least one of the respective predetermined functional characteristics including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion sway, and wafer motion vibration.

22. 20. The substrate processing system of claim 17, wherein the set of predetermined performance characteristic indicators includes an indicator for at least one of the respective predetermined performance characteristics including at least one of substrates processed per hour and wafer slippage.

23. 20. The substrate processing system of claim 17, wherein at least one of the predetermined characteristics of the process echelon metrology is derived from substrate transport arm motion.

24. The controller: recording data from at least one of the transport echelon sensors and the process echelon metrology sensors; and determining an operational value for each different respective predetermined functional characteristic from the recorded data, and factoring and evaluating the operational value against a corresponding reference value for each different predetermined functional characteristic; 20. The substrate processing system of claim 17, wherein the substrate processing system is configured as follows:

25. 25. The substrate processing system of claim 24, wherein each different predetermined functional characteristic is dependent on at least one specific control parameter of the substrate transport apparatus or the substrate processing system controlled by command of a controller.

26. 20. The substrate processing system of claim 17, wherein the controller monitors the overall measurement indicator, identifies trends therein, and, in response to the identified trends, adaptively generates commands that effect changes to control parameters that change dependent predetermined functional characteristics and their corresponding indicators.

27. 20. The substrate processing system of claim 17, wherein the controller monitors a change in the overall measurement indicator from a transient state of at least one indicator of each predetermined functional characteristic in response to a controller command that alters a control parameter that determines the respective predetermined functional characteristic.

28. 20. The substrate processing system of claim 17, wherein the controller monitors a change in the overall metric index from a transient state of at least one index of each predetermined functional characteristic, and in response to a predetermined adverse change in the overall metric index, commands a change in a control parameter determining another respective predetermined functional characteristic that at least partially offsets the predetermined adverse change in the overall metric index.

29. 29. The substrate processing system of claim 28, wherein the controller is configured to compare a change in the overall measurement index from a transient state of at least one predetermined functional characteristic index relative to another change in the overall measurement index from another different transient state of at least another different predetermined functional characteristic index, and scale the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

30. 20. The substrate processing system of claim 17, wherein the controller is programmed with one or more of adaptive control laws and machine learning based laws that direct changes to control parameters to produce a maximum overall metric or minimize the progression of adverse changes in the overall metric.

31. 20. The substrate processing system of claim 17, wherein at least one of the predetermined functional characteristics is a system functional characteristic comprising at least one of a load lock pump and vent time, a load lock vertical lift operation time, a load lock vibration signature, a time interval between opening and closing of a slot valve, a time interval between successive openings of a slot valve, a slot valve opening and closing timestamp, a slot valve vibration signature, a substrate aligner alignment time, a historical substrate offset and reference position, a substrate temperature, a movable arm temperature, a substrate transport device flange temperature, a vacuum level, and an airflow.

32. 20. The substrate processing system of claim 17, wherein at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of a motor temperature, a motor current, a motor voltage, a motor mechanical work, an end effector tracking error, an end effector acceleration overshoot, an end effector root mean square acceleration, and a dynamic model error.

33. 20. The substrate processing system of claim 17, wherein the transfer echelon sensors and the metrology echelon sensors are modular metrology sensors having respective common modular platforms that are selectively configurable.

34. 1. A method, comprising: Providing a substrate processing system, the substrate processing system comprising: a frame forming a substrate transfer space within the substrate processing system; a substrate transport apparatus operably coupled to the frame, the substrate transport apparatus comprising a movable arm and a drive section configured to move the movable arm to transport a substrate held on an end effector of the arm through the transport space from a first location of the substrate processing system to a second location of the substrate processing system different from the first location; and a controller operatively coupled to the movable arm and drive section to effect movement of the movable arm to different system positions; and sensing a predetermined characteristic of arm motion with at least one arm motion sensor coupled to the controller; using at least one system metrology sensor coupled to the controller, sensing a predetermined characteristic of a system metrology that is different from the predetermined characteristic of the arm motion; using the controller to record data from at least one of the at least one arm motion sensor and the at least one system metrology sensor, and determining from the recorded data a set of predetermined functional characteristic indicators, each indicator corresponding to a different respective predetermined functional characteristic of arm motion transporting the substrate or of the substrate processing system, and indicating a relationship between each predetermined functional characteristic and a motion quality of the substrate transported by the movable arm; determining, with the controller, from the set of predetermined functional characteristic indicators, an overall metric of the overall motion quality of the substrate being transported by the movable arm; A method comprising:

35. 35. The method of claim 34, wherein the respective predetermined functional characteristics include at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

36. 35. The method of claim 34, wherein each predetermined performance characteristic comprises at least one of substrates per hour and wafer slippage.

37. 35. The method of claim 34, wherein the set of predetermined functional characteristic indicators includes an indicator for at least one of the respective predetermined functional characteristics including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion sway, and wafer motion vibration.

38. 35. The method of claim 34, wherein the set of predetermined performance characteristic indicators includes an indicator for at least one of the respective predetermined performance characteristics including at least one of substrates processed per hour and wafer slippage.

39. 35. The method of claim 34, wherein at least one of the predetermined characteristics of the system measurements is derived from arm motion.

40. 35. The method of claim 34, further comprising using the controller to determine an operational value for each different respective predetermined functional characteristic from the recorded data, and factoring and evaluating the operational value against a corresponding reference value for each different predetermined functional characteristic.

41. 41. The method of claim 40, wherein each different predetermined functional characteristic depends on at least one specific control parameter of the arm or the system controlled by the commands of a controller.

42. 35. The method of claim 34, further comprising using the controller to monitor the overall measurement indicator, identify trends therein, and, in response to the identified trends, adaptively generate commands that effect changes to control parameters that change dependent predetermined functional characteristics and their corresponding indicators.

43. 35. The method of claim 34, further comprising using the controller to monitor a change in the overall measurement index from a transient state of at least one index of each predetermined functional characteristic in response to a controller command that alters a control parameter that determines the respective predetermined functional characteristic.

44. 35. The method of claim 34, further comprising using the controller to monitor a change in the overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a predetermined adverse change in the overall measurement index, commanding a change in a control parameter determining another respective predetermined functional characteristic that at least partially offsets the predetermined adverse change in the overall measurement index.

45. 45. The method of claim 44, further comprising using the controller to compare the change in the overall measurement index from the transient state of at least one predetermined functional characteristic index relative to another change in the overall measurement index from another different transient state of at least another different predetermined functional characteristic index, and scaling the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

46. 35. The method of claim 34, wherein the controller is programmed with one or more of adaptive control laws and machine learning based laws that direct changes to control parameters to produce a maximum overall metric or minimize progression of adverse changes in the overall metric.

47. 35. The method of claim 34, wherein at least one of the predetermined functional characteristics is a system functional characteristic comprising at least one of load lock pump and vent time, load lock vertical lift operation time, load lock vibration signature, time interval between opening and closing of a slot valve, time interval between successive opening of a slot valve, slot valve opening and closing timestamp, slot valve vibration signature, substrate aligner alignment time, historical substrate offset and reference position, substrate temperature, movable arm temperature, substrate transport apparatus flange temperature, vacuum level, and airflow.

48. 35. The method of claim 34, wherein at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of motor temperature, motor current, motor voltage, motor mechanical work, end effector tracking error, end effector acceleration overshoot, end effector root mean square acceleration, and dynamic model error.

49. 35. The method of claim 34, wherein the at least one arm motion sensor and the at least one system metrology sensor are modular metrology sensors having a common modular platform that is selectively configurable.

50. 1. A method, comprising: Providing a substrate processing system, the substrate processing system comprising: Frame, a substrate processing station and at least one substrate input or output station connected to the frame and forming a substrate processing echelon of the substrate processing system; a substrate transport apparatus movably mounted to the frame and configured to transport substrates along the substrate processing echelon between an input station or an output station and a substrate processing station, the substrate transport apparatus forming a transport echelon of the substrate processing system; a group of sensors including a transport echelon sensor communicatively coupled to the substrate transport apparatus arranged to sense a predetermined characteristic of the transport echelon, and a process echelon metrology sensor arranged to sense a predetermined characteristic of the process echelon metrology that is different from the predetermined characteristic of the transport echelon; and a controller communicatively coupled to the transport echelon sensors and the measurement echelon sensors; and generating, with the controller, a set of predetermined functional characteristic indicators from sensor data embodying both predetermined characteristics of the transfer echelon and predetermined characteristics of the process echelon metrology, each indicator corresponding to a different predetermined functional characteristic of the substrate transport apparatus or of the substrate processing echelon transporting the substrate, and indicating a relationship between each predetermined functional characteristic and an operational quality of the substrate transported by the substrate transport apparatus; determining, with the controller, from the set of predetermined performance characteristic indicators, an overall metric of the overall operational quality of the substrates transported by the substrate transport apparatus; A method comprising:

51. 51. The method of claim 50, wherein the substrate transport apparatus comprises a transport arm and a drive section configured to move the transport arm to transport the substrate held on an end effector of the transport arm.

52. 51. The method of claim 50, wherein the respective predetermined functional characteristics include at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion wobble, and wafer motion vibration.

53. 51. The method of claim 50, wherein the respective predetermined performance characteristics include at least one of substrates per hour and wafer slippage.

54. 51. The method of claim 50, wherein the set of predetermined functional characteristic indicators includes an indicator for at least one of the respective predetermined functional characteristics including at least one of number of substrates processed per hour, position loop servo gain margin, position loop servo phase margin, wafer handling error, wafer slippage, settling time, wafer handoff vibration, wafer motion sway, and wafer motion vibration.

55. 51. The method of claim 50, wherein the set of predetermined performance characteristic indicators includes an indicator for at least one of the respective predetermined performance characteristics including at least one of substrates processed per hour and wafer slippage.

56. 51. The method of claim 50, wherein at least one of the predetermined characteristics of the process echelon metrology is derived from substrate transport arm motion.

57. Using the controller, recording data from at least one of the transport echelon sensors and the process echelon metrology sensors; determining an operational value for each different respective predetermined functional characteristic from the recorded data and factoring and evaluating the operational value against a corresponding reference value for each different respective predetermined functional characteristic; 51. The method of claim 50, further comprising:

58. 58. The method of claim 57, wherein each different predetermined functional characteristic is dependent on at least one specific control parameter of the substrate transport apparatus or the substrate processing system controlled by command of a controller.

59. 51. The method of claim 50, further comprising using the controller to monitor the overall measurement indicator, identify trends therein, and, in response to the identified trends, adaptively generate commands that effect changes to control parameters that change dependent predetermined functional characteristics and their corresponding indicators.

60. 51. The method of claim 50, further comprising using the controller to monitor a change in the overall measurement index from a transient state of at least one index of each predetermined functional characteristic in response to a controller command that alters a control parameter that determines the respective predetermined functional characteristic.

61. 51. The method of claim 50, further comprising using the controller to monitor a change in the overall measurement index from a transient state of at least one index of each predetermined functional characteristic, and in response to a predetermined adverse change in the overall measurement index, commanding a change in a control parameter determining another respective predetermined functional characteristic that at least partially offsets the predetermined adverse change in the overall measurement index.

62. 62. The method of claim 61, further comprising using the controller to compare the change in the overall measurement index from the transient state of at least one predetermined functional characteristic index relative to another change in the overall measurement index from another different transient state of at least another different predetermined functional characteristic index, and scaling the at least one predetermined functional characteristic index and the at least another different predetermined functional characteristic index relative to each other from the comparison of the relative changes in the overall measurement index due to the transient state and the other different transient state.

63. 51. The method of claim 50, wherein the controller is programmed with one or more of adaptive control laws and machine learning based laws that direct changes to control parameters to produce a maximum overall metric or minimize progression of adverse changes in the overall metric.

64. 51. The method of claim 50, wherein at least one of the predetermined functional characteristics is a system functional characteristic comprising at least one of load lock pump and vent time, load lock vertical lift operation time, load lock vibration signature, time interval between opening and closing of a slot valve, time interval between successive openings of a slot valve, slot valve opening and closing timestamp, slot valve vibration signature, substrate aligner alignment time, historical substrate offset and reference position, substrate temperature, movable arm temperature, substrate transport device flange temperature, vacuum level, and airflow.

65. 51. The method of claim 50, wherein at least one of the predetermined functional characteristics is an arm mechanism functional characteristic including at least one of motor temperature, motor current, motor voltage, motor mechanical work, end effector tracking error, end effector acceleration overshoot, end effector root mean square acceleration, and dynamic model error.

66. 51. The method of claim 50, wherein the transport echelon sensor and the metrology echelon sensor are modular metrology sensors having respective common modular platforms that are selectively configurable.

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