4388 results about "Manufacturing systems" patented technology

The invention relates to the technical field of intelligent manufacturing, in particular to an intelligent production scheduling method and system for a manufacturing system, and the method comprises the following steps: collecting an equipment state, a material neat rate and an order emergency degree in real time based on dynamic production data, and calculating an equipment availability coefficient, a material guarantee index and an order priority score through feature analysis; and forming a dynamic production feature set. The system constructs a production scheduling optimization model through work order-equipment matching degree calculation and process priority optimization, and performs multi-objective optimization solution by adopting an NSGA-III algorithm to realize the optimal combination of equipment utilization rate, order delivery rate and inventory balance. Meanwhile, an arbitration mechanism is introduced to coordinate process priority conflicts, and the scheme is verified through time, space and dynamic adaptability, so that feasibility and stability of production scheduling execution are ensured. According to the invention, the production scheduling efficiency of the manufacturing system can be improved, the equipment utilization rate can be improved, the order delivery delay rate can be reduced, and the adaptive ability to the change of the production environment can be enhanced.

The invention discloses an adaptive task division and decision joint optimization-based cloud edge computing resource collaborative scheduling method for a complex manufacturing system. The method comprises the following steps of 1, constructing a hierarchical cloud-edge collaborative computing network model; constructing a multi-objective optimization model, and defining an objective function and constraint conditions; 2, dynamically predicting and calculating a resource state through a resource sensing module based on an LSTM neural network, and generating a node resource prediction matrix; 3, dividing a calculation task generated by the manufacturing system into fine-granularity, medium-granularity and coarse-granularity subtask sets by adopting a multi-granularity subtask division algorithm (MSPA), and mapping the subtasks to corresponding calculation nodes; 4, constructing a task unloading decision model based on the D3QN, and dynamically selecting unloading nodes and an execution sequence of the subtasks in combination with a multi-objective optimization reward function; and 5, iteratively optimizing parameters of the D3QN model through a target network updating mechanism and a self-adaptive exploration strategy to realize real-time dynamic adjustment of a task scheduling decision.

Additive manufacturing systems and related methods are disclosed. In some embodiments, a first motion stage may be used to move a recoater and an optics assembly. The optics assembly may be configured to direct laser energy from one or more laser energy sources towards a build plate. The recoater may be configured to form a layer of precursor material on the build plate. In some embodiments, a secondary housing formed of a composite material may be used.

A friction stir additive manufacturing system is provided. In one aspect, the system includes a spindle configured to rotate about a central axis, and a housing configured to receive at least a portion of the spindle, the housing configured to remain stationary relative to the spindle. The housing includes a wire inlet extending between an exterior surface of the housing and an interior surface of the housing, and a track extending from the wire inlet and partially around a circumference of an interior surface of the housing. The system also includes a feeding system configured to receive a wire from a roller and feed the wire through the wire inlet and into the track of the housing.

A friction stir additive welding screw is provided. In one aspect, the friction stir additive welding screw includes a first portion configured to be coupled to a friction stir additive welding device, and a second portion configured to penetrate a work-piece. The second portion includes a plurality of large threads, each large thread extending in a generally longitudinal direction. The second portion also includes a plurality of fine threads positioned along an edge of each large thread, and a plurality of teeth at a tip of second portion.

Disclosed is a wheel cylinder and a drum brake having the same, in which the number of position as well as other elements accompanied with the piston may be reduced, resulting in reduced manufacturing cost.

A friction stir additive welding device configured to join a first work-piece and second work-piece is provided. In one aspect, the device includes a nosecone including a channel extending along a central axis and configured to receive a rotating screw. The device also includes a slot including a first opening in an outer sidewall of the nosecone, a second opening in a wall of the channel of the nosecone, and a passageway through the nosecone between the first opening and the second opening. The slot is configured to receive a portion of a structure positioned between the first work-piece and the second work-piece.

A friction stir additive welding device configured to join a first work-piece and second work-piece is provided. In one aspect, the device includes a nosecone having a sidewall extending from a first end to a second end, a channel extending from the first end to the second end along a longitudinal axis of the nosecone, and a screw positioned within the channel. The first end is configured to couple the nosecone to a robotic arm and the second end has a surface configured to be advanced along a weld line between the first and second work-pieces. A central axis of the screw defines an angle that is less than 90 degrees relative to a plane that is perpendicular to surfaces of the first and second work-pieces as the surface of the nosecone advances along the weld line.

The invention provides a big data bamboo tableware manufacturing system based on production process monitoring, and relates to the field of intelligent detection systems.The big data bamboo tableware manufacturing system comprises an acquisition module, a prediction module, a preliminary distribution module, a disturbance response module, an optimization decision module and an abnormity self-inspection module. A dynamic stability index is calculated in combination with a dynamic image sequence under disturbance response, a rejection target is judged through an optimization decision-making module after scores are fused, a Bayesian method is introduced in the optimization process to dynamically adjust multiple decision-making parameters, a rejection action instruction is generated in real time, and an abnormity self-checking module monitors the rejection rate and score stability. Software and hardware signals are combined to realize multi-level fault diagnosis and system protection control; according to the invention, high-precision identification and dynamic elimination of bamboo tableware defects are realized, and the automation level and the production reliability are improved.

A friction stir additive manufacturing system configured to extrude a material is provided. In one aspect, the system includes a spindle configured to rotate about a central axis, the spindle including a conical portion having a plurality of threads at a deposition end of the spindle. The system also includes a housing configured to remain stationary relative to the spindle, the housing including a wire inlet extending through a side wall of the housing, an interior surface of the side wall defining a truncated cone terminating at a material exit, the truncated cone configured to receive the conical portion of the spindle. The system also includes a feeding system configured to feed a wire through the wire inlet and into a gap between the spindle and the truncated cone of the housing.

The invention discloses a mobile phone silica gel shell appearance detection system based on an optical image sensor, and relates to the technical field of appearance defect detection and intelligent visual identification. An image acquisition module acquires a high-quality multi-channel image through multi-angle synchronous acquisition; the dynamic light field regulation and control module realizes self-adaptive regulation of a regional light source based on reflectivity perception and a gray gradient change rate; the image processing and defect identification module fuses edge features, texture changes and a deep learning model to realize pixel-level defect classification; the material identification and shielding module identifies a non-silica gel area through multi-dimensional spectral features and eliminates interference; a time sequence defect evolution analysis module models a defect evolution track; the trend prediction module is used for predicting the extension trend of potential cracks and fatigue areas; the control feedback module realizes intelligent judgment and response linked with the manufacturing system; the system can realize high-precision and high-robustness automatic defect detection and risk prediction, and is suitable for online quality monitoring of large-batch flexible products.

The invention relates to the field of digital twinning, in particular to an intelligent decision analysis method and system for a digital twinning-based manufacturing system, and aims to improve the generalization ability and adaptability of a digital twinning model in an emerging market small sample scene through deep fusion of meta-learning and adversarial training. According to the method, the problem of prediction distortion caused by data scarcity is relieved, high-quality training samples are expanded in combination with a generative enhancement technology, a multi-target elastic scheduling mechanism is synchronously constructed, dynamic optimization and feasibility verification of a production strategy are realized in a digital twin environment, and finally a closed-loop optimized intelligent decision system is formed. According to the method, through deep fusion of meta-learning and adversarial training, by combining a generative enhancement technology to expand high-quality training samples and a synchronously constructed multi-target elastic scheduling mechanism, dynamic optimization and feasibility verification of a production strategy are realized in a digital twin environment, and finally a closed-loop optimized intelligent decision system is formed.

A method includes initiating a connection with a semiconductor manufacturing system. The method further includes generating a set of tool data items associated with the semiconductor manufacturing system. The method further includes providing a graphical user interface (GUI) presenting the set of tool data items associated with the semiconductor manufacturing system and receiving and via the GUI, user input selecting one or more of the tool data items. The method further includes adding configuration data associated with one or more of the tool data items to a data collection plan. The method further includes validating the configuration data by locating, in the manufacturing system, a configuration data file associated with the configuration data. The method further includes executing one or more data collection operations based on the data collection plan.

The invention relates to the technical field of intelligent manufacturing decisions, in particular to a digital twinning-based manufacturing system decision analysis method and system, and the method comprises the steps: deploying a plurality of Internet of Things sensors on a physical manufacturing system, and collecting a physical real-time data stream of equipment in real time; the method comprises the following steps: establishing a virtual data acquisition channel aligned with a physical manufacturing system clock, injecting a physical real-time data stream into a digital twinning creation model, and performing data preprocessing based on distributed edge calculation to delay and compress original data acquisition of the physical real-time data stream to 10ms level, the time sequence database and the NTP / GPS clock are synchronized to ensure the state alignment error lt of the physical-virtual system; compared with the prior art, the deep space-time prediction network is fused with a CNN-LSTM-attention mechanism, the accuracy of multivariable coupled KPI prediction is improved, in addition, model failure is recognized in real time through Page-Hinkley inspection, and a prediction error reaches a relatively stable state through an adaptive retraining mechanism.

An electrode manufacturing system includes a transferring part, a coating part, a drying part, and a heat treatment part. The transferring part is arranged downstream of the drying part to heat the electrode substrate to a high temperature and includes a transfer roller supports and transfers an electrode substrate in a long-sheet shape. The coating part applies an electrode slurry to an electrode current collector. The drying part dries the electrode slurry disposed on the electrode substrate. The heat treatment part is disposed downstream of the drying part along a transfer direction of the electrode substrate and applies heat to the electrode substrate to increase the adhesion of the electrode by changing the crystal phase of the PVdF binder of the electrode substrate during the heat treatment process, thereby preventing the separation of the electrode active material layer. A manufacturing method including the same is also provided.

The invention relates to a computer-aided classification method (10) for a joining geometry (12; 12a-e) of a contact joint (14) between two workpieces (16, 18) to be joined of a workpiece arrangement (20; 20a-e), comprising the method steps: - Positioning (22) a sensor (24) of a measuring system (26) in a predetermined processing position of a processing optic (28) of a laser processing machine (30) at a joining point (32) of the workpiece arrangement (20; 20a-e); - Creating (38) a geometric profile (40; 40a-e) of the workpiece arrangement (20; 20a-e) by scanning a surface (42) of the workpiece arrangement (20; 20a-e) at the joining point (32) in a measuring plane (44) transverse or perpendicular to a principal extension direction (46) of the contact joint (14); - Determining (50) the joining geometry (12; 12a-e) by evaluating and comparing the geometry profile (40; 40a-e) with stored reference profiles (52; 52a-e) for specific joining geometries (12; 12a-e). The invention also relates to a manufacturing process (60) and a manufacturing system (70).

A pickleball paddle with novel core characteristics and / or materials, and related systems, methods, and articles of manufacture are provided.

The invention discloses a scheduling evaluation method for low-entropy state operation of a discrete workshop manufacturing system, and the method comprises the following steps: 1) constructing operation conditions and following principles of the discrete workshop manufacturing system, analyzing the operation state of the discrete workshop manufacturing system, and constructing a static entropy function of the discrete workshop manufacturing system; 2) constructing a discrete workshop manufacturing system operation dynamic entropy function according to the situation that the system is in an out-of-control state and a fuzzy event occurs; 3) calculating the maximum feasible scheduling time limit of the scheduling scheme; and 4) analyzing and comparing the static entropy, the operation entropy and the maximum feasible scheduling time limit aiming at the problem of scheduling scheme selection, and selecting an execution scheme with small system entropy increase as an optimal execution scheduling scheme for guiding actual production scheduling. According to different scheduling schemes of the discrete workshop manufacturing system, the low-entropy state operation evaluation method is provided, the scheduling scheme with low uncertainty and high system order degree is selected, and low-entropy efficient ordered production of the discrete workshop manufacturing system is achieved.

The invention discloses a method and equipment for double-ultrasonic cooperative in-situ auxiliary electric arc additive manufacturing of a large metal component, an electric arc additive manufacturing system and an ultrasonic vibration auxiliary electric arc additive manufacturing system. The ultrasonic vibration auxiliary electric arc additive manufacturing system comprises two ultrasonic impact guns, an optical sensor, a temperature sensor and a calculation control system. The optical sensor collects optical characteristics of the deposition channel and the molten pool and converts the optical characteristics into electric signals to be transmitted to the calculation control system, and the temperature sensor is used for monitoring and collecting temperature information of the deposition channel and transmitting the temperature information to the calculation control system to draw an isotherm; the calculation control system adjusts the distance between the ultrasonic impact gun and the center of the molten pool according to the isotherm and the optical characteristics of the optical sensor mobile phone, and the ultrasonic power is adjusted; one of the ultrasonic peening guns applies ultrasound from the component side edge as materials are added to the component edge. By means of the multi-axis freedom degree and accuracy of the mechanical arm, double-ultrasonic vibration is applied to all positions of a large metal component in the material adding process, and the mechanical property is improved.

A self-correcting wave soldering machine for soldering a RGB in an SMT manufacturing system. The wave soldering machine includes at least one thermal infrared camera that generates thermal images of the RGB so as to provide thermal imaging processing to monitor, characterize and predict processing temperatures. The wave soldering machine generates a heat map using the thermal images and compares the heat map to a thermal gradient to provide real time profiling by digitally connecting it to heating and other mechanically controlled systems, such as flux dispensing, conveyor speed and parallelism of the wave soldering machine.

A method for a substrate measurement subsystem is provided. An indication is received that a substrate being processed at a manufacturing system has been loaded into a substrate measurement subsystem. First positional data of the substrate within the substrate measurement subsystem is determined. One or more portions of the substrate to be measured by one or more sensing components of the substrate measurement subsystem are determined based on the first positional data of the substrate and a process recipe for the substrate. Measurements of each of the determined portions of the substrate are obtained by one or more sensing components of the substrate measurement subsystem. The obtained measurements of each of the determined portions of the substrate are transmitted to a system controller.

The invention discloses a conformal antenna component manufacturing system and method based on cross-scale space-time frequency shaping femtosecond laser, and belongs to the technical field of micro-nano machining. The system comprises an ultrafast laser excitation module, a laser pulse time / frequency shaping module, a pulse detection module, an online monitoring module and a focusing high-speed scanning galvanometer module. By means of the system, high-selectivity, large-breadth and three-dimensional precision machining of conformal antenna circuit patterns is achieved, and it is ensured that a substrate is not damaged. The femtosecond laser time-frequency shaping technology is combined in the machining process, layered scanning and accurate removal of the heterogeneous multilayer structure are achieved through an adjustable pulse sequence and a high-speed galvanometer system, and the problems that in the prior art, materials are damaged, and the size precision is low are solved. The device further integrates an on-line depth monitoring function, the machining efficiency and the forming quality are remarkably improved, and the device is suitable for high-precision patterning machining of complex curved surface heterogeneous thin film materials.

The invention relates to the technical field of energy-carbon management and control of a product manufacturing process, and discloses a supply chain cluster-oriented energy-carbon management and control method of a complex product manufacturing process, which comprises the following steps of: firstly, constructing a supply chain cluster manufacturing system model of a complex product; secondly, constructing a subsystem classification model based on two core indexes of'energy consumption ratio 'and'carbon emission fluctuation', and dividing subsystems in the supply chain cluster manufacturing system into four classes; and finally, for different types of subsystems, making differentiated energy-carbon management and control strategies, including an I-class subsystem management and control strategy based on static data, II-class and III-class subsystem management and control strategies based on static-dynamic data fusion, and an IV-class subsystem management and control strategy based on dynamic data. According to the invention, an efficient solution is provided for the multi-level and diversified energy-carbon management and control requirements of supply chain leading enterprises in the complex product manufacturing process, and the precision and operability of energy-carbon management and control are remarkably improved.

A high throughput, efficient, and simplified unloading and packaging systems and methods for large-scale production of pharmaceutical units (104) using additive manufacturing. The systems and methods may unload, inspect, package, and trace pharmaceutical units, produced by an additive manufacturing system (900), that are not damaged or deformed. The unloading and packaging system can include one or more unloading and packaging devices (100). The unloading and packaging device can include a modular configuration having modules. Individual modules to be arranged in any relative order, at any location, and with any number in the unloading and packaging device. The flexibility of the modular configuration allows one or more modules to be removed or added at any given time due to, e.g., expansion, downsizing, module repair, module upgrades, etc. High throughput can be achieved by operating unloading and packaging devices independently.

Implementations disclosed describe, among other things, a system and a method of scanning a substrate with a beam of light and detecting for each of a set of locations of the substrate, a respective one of a set of intensity values associated with a beam of light reflected from (or transmitted through) the substrate. The detected intensity values are used to determine a profile of a thickness of the substrate.

A laser additive manufacturing system and method for a magnesium-based composite material. The system comprises a laser adjuster (1), a laser (2), a forming cover (3), an oxygen content adjuster (4), an inert gas cylinder (5), a powder feeder (6), a substrate (7) and a wire feeder (8), wherein the laser adjuster is used for controlling laser processing parameters of the laser; the laser is connected to a laser processing head (10) by means of an optical fiber (9); the oxygen content adjuster is in communication with the forming cover, so as to control the oxygen content of a processing environment in the forming cover; the inert gas cylinder and the powder feeder both pass through the forming cover to be connected to the laser processing head; the substrate is located inside the forming cover; the wire feeder is connected to a wire feeding head (12) by means of a wire feeding tube (11); the wire feeding head passes through the forming cover to perform laser additive manufacturing for a magnesium-based composite material, together with the laser processing head; and a real-time cooling sleeve (13) is also mounted on the wire feeding tube. Also provided are a method for preparing a magnesium-based composite material using the laser additive manufacturing system for the magnesium-based composite material, and a prepared magnesium-based composite material. By means of the manufacturing system and method, the additive processing of wires and powder is realized, and a magnesium-based composite material with a good mechanical property is prepared.

In one embodiment, a system includes a wafer-handling system of a semiconductor-manufacturing system. The wafer-handling system is configured to hold one or more wafers for processing. The system also includes one or more processing components configured to physically treat the one or more wafers; a controller configured to operate the processing components; and a text bot in communication with the semiconductor-manufacturing system and configured to respond to a user inquiry.

To provide a methane manufacturing system that can reduce energy loss.SOLUTION: A system comprises a steam generating device 11 that generates steam, an electrolysis methanation device 12 that introduces a first gas mainly composed of carbon dioxide through a first pipe P1 and also introduces the steam generated in the steam generating device 11 through a second piping P2, causing electrolysis of the steam and the Sabatier reaction to produce a second gas mainly composed of methane and oxygen-containing steam that is steam containing oxygen, and sending the second gas to a third pipe P3 and the oxygen-containing steam to a fourth pipe P4. and a return pipe P5 that supplies the oxygen-containing steam sent to the fourth pipe P4 to at least one of the steam generating device 11 and the second pipe P2.SELECTED DRAWING: Figure 1

A machine tool comprises a frame and a tool spindle mounted thereon, which is linearly movable in three translational axes relative to the frame, comprising a first horizontal axis, a second horizontal axis, and a vertical axis. The tool spindle is mounted vertically movable via a Z-slide on an X-slide along the vertical axis. The X-slide is mounted horizontally movable on a Y-slide along the first horizontal axis, and the Y-slide is mounted horizontally on the frame along the second horizontal axis. A primary workpiece holding unit, designed as a rotary spindle, and a secondary workpiece holding unit are mounted on the frame. The primary and secondary workpiece holding units are oriented towards each other and coaxially in at least one horizontal orientation.The primary workpiece holding unit is pivotable relative to the frame about a primary pivot axis oriented parallel to the second horizontal axis. The secondary workpiece holding unit is pivotable relative to the frame about a secondary pivot axis oriented parallel to the second horizontal axis. A production system utilizes such a machine tool. A process for machining bar stock utilizes such a production system.

A lipid nanoparticles manufacturing chip includes a first raw material supply flow path, a second raw material supply flow path, and a mixer portion connected to the first raw material supply flow path and the second raw material supply flow path and configured for mixing a first raw material supplied through the first raw material supply flow path and a second raw material supplied through the second raw material supply flow path. The mixer portion includes a first stabilizing unit, and a first mixing unit connected to the first stabilizing unit and configured for mixing the first raw material and the second raw material with each other. Mixing of the first raw material and the second raw material is performed more in the first mixing unit than in the first stabilizing unit.