1065 results about "Manufacturing systems" patented technology

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.

The invention provides an automatic chip mounter program uploading and downloading system which can automatically complete program distribution, loading, backup and version control according to work order information issued by a production and manufacturing system, and realizes automatic and intelligent management of a whole process. The system comprises a program management server which is used for storing program ocarina files, version histories and related data of all chip mounters and carrying out data interaction with a production and manufacturing system; the work order interface module is used for receiving production work order information to be executed from the production and manufacturing system; and the chip mounter control agent module is a lightweight software or hardware agent deployed on each automatic chip mounter and is responsible for communicating with the program management server, receiving instructions and executing operations such as program downloading, uploading, loading and activating.

Provided herein is an additive manufacturing system having a build chamber, a plurality of tools and a plurality of tool bays where each tool bay is arranged to store one tool. A gantry is arranged to select one tool and removes the selected tool from a tool bay. A tool mount is slidably arranged on the gantry and to detachably couple the selected tool to the gantry. Two guide rails extend in a first direction and are arranged to receive the selected tool. The guide rails are movable along a second direction perpendicular to the first direction, so as to enable alignment of the guide rails with one of the tool bays at a time. Channel seals expand or contract based on a relative movement between the tools and the sliders.

The invention relates to a discrete manufacturing process evaluation method based on deep learning. Comprising an equipment performance data acquisition module for collecting key performance index data of various processing equipment; the equipment performance evaluation module adopts a weighted index combination and hierarchical evaluation mechanism, introduces a real-time state sensing mechanism, and evaluates the equipment performance in a multi-dimensional and multi-level manner; the process intelligent analysis module fuses historical process data and equipment performance data, constructs deep learning model input through feature extraction, and realizes identification of key difficulties of the processing process and prediction of the process success rate; and the process feasibility evaluation module combines the trained deep learning model with the equipment performance evaluation result to form the process feasibility automatic evaluation method for specific equipment and workpieces. According to the method, intelligent decision-making of equipment type selection and a process path in a manufacturing process can be realized, an enterprise is helped to realize optimization of production efficiency and product quality, and the production efficiency and the product quality of a manufacturing system are comprehensively improved.

The invention discloses a digital driving method for a full-flow manufacturing process of a high-precision shell casting, which comprises a casting stage, a heat treatment stage and a machining stage, and is characterized in that digital data streams are established among three process links of the casting stage, the heat treatment stage and the machining stage; and the output data of the previous process is used as a process adjustment basis of the subsequent process, so that a datamation-driven closed-loop manufacturing system is formed. The invention provides a set of effective systematic solution for high-precision production of thin-wall shell castings.

The invention relates to the technical field of manufacturing execution systems, in particular to an intelligent scheduling method integrating demand prediction and supply matching, which comprises the following steps of: acquiring to-be-scheduled order information and a workshop real-time resource state in a manufacturing execution system, constructing an order demand feature vector, the method comprises the following steps: acquiring an equipment precision retentivity value, a current load rate value, an energy consumption level value and an operator skill proficiency value, and constructing a resource supply capability vector; according to the method, when an urgent order insertion instruction is received, a clear decision basis is provided, a rigid scheduling locking block which must be kept unchanged and an adjustable liquid adjustable scheduling block which can be adjusted can be distinguished, only the latter is subjected to accurate splitting and backward moving operation, and the target-clear local adjustment mode is adopted, so that the operation efficiency is greatly improved. The huge calculation overhead and the violent fluctuation of the production plan caused by the traditional global rescheduling are avoided, and the agility of the manufacturing system to deal with the market change is enhanced.

Systems, devices, and methods for additive manufacturing of objects are provided. In some embodiments, a device for supporting an object during an additive manufacturing process includes a build platform having a surface, and a plurality of support structures extending above the surface of the build platform. Each support structure can be configured to couple to a portion of an additively manufactured object. The device can also include a plurality of actuators, each actuator being configured to adjust a position of a corresponding support structure relative to the build platform.

Systems and methods for designing and implementing patient-specific surgical procedures and / or medical devices are disclosed. In some embodiments, a method includes receiving intra-operative data during a surgical procedure to install a patient-specific implant in a patient. The system can compare the intra-operative data to a pre-operative plan to determine whether the implant is positioned and located according to the pre-operative plan.

In embodiments, a method includes receiving, by a processing device, first sensor data generated by a plurality of sensors of a process chamber of a manufacturing system during execution of a fabrication process. The method includes receiving, by the processing device, second sensor data generated by one or more external sensors that are not components of the process chamber during execution of the fabrication process. The method includes determining, by the processing device, environmental resource usage data indicative of an environmental resource consumption of the fabrication process run on the process chamber based on the first sensor data and the second sensor data. The method includes providing, by the processing device, the environmental resource usage data for display on a graphical user interface (GUI).

Disclosed systems and techniques are directed to improving chucking of substrates in device manufacturing systems. The techniques include identifying deformation of a substrate and applying, based on the identified deformation, a plurality of time-dependent voltage signals to a multizonal chuck to attract the substrate to the multizonal chuck. Each voltage signal of the plurality of time-dependent voltage signals is applied to one or more electrodes of the multizonal chuck. The techniques further include performing one or more processing operations in association with the substrate attracted to the multizonal chuck.

The invention discloses an integrated injection molding multi-sensor production line preparation system and method. The system comprises an equipment execution system, an electrical control system, an informatization system and a process system. The equipment execution system is configured to be used for receiving the instruction split by the electrical control system and directly executing operations including processing, detecting, testing and transferring on the integrated injection molding multi-union sensor; the equipment execution system dynamically recognizes the posture deviation of a product in real time and corrects execution parameters in real time by integrating a visual positioning module and a force control self-adaptive adjustment module when executing operation on the product; the equipment execution system adopts a semi-loop line mode to complete the overall arrangement of stations; and the electrical control system is configured to be used for connecting the informatization system and the equipment execution system, upwards receiving and disassembling an instruction of the informatization system, downwards decomposing the instruction and the process parameters and driving the equipment execution system to act through the controller. And collaborative and efficient operation of the production line is realized.

The invention provides a preset time fuzzy control method for a reentrant manufacturing system under intermittent state feedback, and the method comprises the steps: constructing a nonlinear error dynamic model, and employing a fuzzy modeling technology to represent the system as a combination of a plurality of linear subsystems; introducing a time scaling function, and transforming the error state of the global fuzzy model by using the time scaling function to obtain an error scaling state; an event triggering mechanism is designed to realize intermittent state feedback so as to reduce the communication cost; based on the Lyapunov stability theory, a sufficient condition that the system is stable within preset time is deduced, and a controller gain is obtained by solving a linear matrix inequality of the sufficient condition, so that the system still has robustness under external interference. Agile response and low-communication-cost operation of the reentrant manufacturing system within the preset deadline are realized.

According to the image sensor manufacturing method based on the guided self-assembly technology, the guided self-assembly technology is applied to a deep groove patterning process on the back face of a wafer and is combined with a photoetching technology, so that compared with a traditional deep groove patterning process utilizing a PTD or NTD photoetching technology, the deep groove patterning process has the advantages that the deep groove patterning process is simplified; according to the invention, the resolution limit of the photoetching technology can be broken through, the pixel pitch can be reduced, the cost advantage and the pixel density can be improved, the pixel resolution can be greatly improved, the edge roughness of the deep trench isolation pattern of the pixel can be improved, and the signal crosstalk between the adjacent pixels can be reduced.

The invention belongs to the technical field of intelligent control, and particularly relates to an intelligent control method of an RGV shuttle vehicle, so as to solve the technical problem of low operation efficiency of an existing scheduling method. Comprising the following steps that S1, the position, load and electric quantity information of each RGV shuttle vehicle and the task sequence, the machining progress and the material request state of each CNC machine tool are obtained in real time; s2, calculating a congestion penalty term of the predetermined driving path; s3, determining the difference between the weighted current entropy and the expected future entropy as the traffic entropy gain of the alternative task; s4, calculating a decision value of each alternative task according to a preset formula; and assigning a unique target CNC machine tool to each idle RGV shuttle vehicle based on the decision value. The idle waiting time of the machine tool is shortened, and the operation efficiency and stability of the whole manufacturing system are improved.

The invention provides a remanufacturing workshop scheduling method based on reinforcement learning and evolutionary algorithm fusion, relates to the technical field of production scheduling optimization, and solves the problem of remanufacturing system scheduling in three stages of disassembly, reprocessing and assembly. A four-dimensional decision model covering process sorting, factory distribution, machine selection and speed gear scheduling is constructed, and an initial population with diversity and high-quality characteristics is generated by adopting a multi-strategy hybrid initialization method. A reinforcement learning decision module based on Q-learning is introduced, an optimal combination is dynamically selected from various crossover operators, mutation operators and neighborhood search strategies, the crossover probability and the mutation probability are dynamically corrected according to the distribution characteristics of the Pareto leading edge, and a dual escape mechanism is integrated to enhance the capability of the algorithm to jump out of local optimum. According to the scheme, the group search advantage of the evolutionary algorithm is exerted, the dynamic optimization of the search process is realized, and an efficient and accurate scheduling solution is provided for a complex remanufacturing system.

In one embodiment, a system for controlling a matching network of a semiconductor manufacturing system is disclosed. The matching network comprises an electronically variable reactance element (EVRE) that varies its total reactance using different match configurations. A plasma chamber carries out a process upon a substrate, the process comprising process steps including at least a first process step and a second process step. A memory, for each process step, stores instructions for carrying out the process step. A control circuit, while continuously carrying out each of the process steps of the process, upon anticipation that the plasma chamber will be transitioning from the first process step to the second process step, alters the match configuration to a new match configuration based on the instructions for carrying out the second process step.

The invention discloses a high-pressure and high-ring-steel triangular steady-state steel framework plastic composite pipeline and a manufacturing system and method thereof, and relates to the technical field of steel framework plastic composite pipeline production, the high-pressure and high-ring-steel triangular steady-state steel framework plastic composite pipeline comprises a warp wire arrangement frame, and a weft wire storage rotating seat is arranged on one side of the warp wire arrangement frame; according to the full-automatic injection molding machine for the steel framework, preheating before injection molding of the steel framework is achieved, then the temperature difference between the steel framework and molten plastic is effectively reduced, the temperature difference between the steel framework and the molten plastic is effectively reduced, and the temperature difference between the steel framework and the molten plastic is effectively reduced; the situation that plastic on the outer side of the steel framework is contacted firstly during injection molding of the steel framework and is rapidly cooled and hardened to influence normal flowing of follow-up molten plastic is effectively prevented, and it is ensured that gaps on the outer side of the steel framework can be fully filled with the molten plastic in the injection molding process; the internal defects in the production process of the steel skeleton plastic composite pipe are effectively removed, and the quality of the steel skeleton plastic composite pipe product is further improved.

Systems, apparatus, computer-readable medium, and associated methods for secure additive manufacturing are disclosed. An example apparatus includes an inbound one-way data diode to receive, authenticate, and route an inbound file in a first direction within a secure additive manufacturing system, the inbound one-way data diode unable to transmit data out of the secure additive manufacturing system in a second direction. The example apparatus includes an additive manufacturing machine to build a part, the build of the part adjusted by the inbound file when authenticated by the inbound one-way data diode. The example apparatus includes an outbound one-way data diode to authenticate and transmit outbound data in the second direction to an external system outside the secure additive manufacturing system, the outbound one-way data diode unable to transmit data into the secure additive manufacturing system in the first direction.

Methods and systems for process chamber qualification for maintenance process endpoint detection are provided. Sensor data collected by sensors of manufacturing equipment of a manufacturing system during performance of one or more initial maintenance operations of a maintenance process is obtained. The obtained sensor data is provided as an input to a machine learning (ML) model and one or more outputs of the ML model are obtained. The output(s) include a current state of the manufacturing equipment based on the performance of the initial maintenance operation(s). The current state represents a distance between the obtained sensor data and target sensor data associated with a final maintenance operation of the maintenance process. A set of subsequent maintenance operations of the maintenance process is determined based on the current state of the manufacturing equipment. Performance of the set of subsequent maintenance operations at the manufacturing equipment is initiated.

Methods for fabricating layered appliances are provided. In some embodiments, a method includes generating a digital model of a polymeric shell including a plurality of tooth-receiving cavities shaped to receive and reposition a patient's teeth from a first arrangement toward a second arrangement. The polymeric shell can include an interior layer having a first stiffness, and an exterior layer having a second stiffness greater than the first stiffness. The exterior layer can include a discontinuity formed therein. The method can further include transmitting the digital model to a fabrication system configured to fabricate the polymeric shell based on the digital model.

Systems and methods analyze data received from assets in a manufacturing environment, determine a first parameter is over or under a first predetermined threshold for an asset using a first machine learning model deployed on the manufacturing system, and generate an updated parameter value to adjust the asset. The systems and methods analyze a subset of sensor data in the manufacturing system using the first machine learning model, determine an actual accuracy rate of the first machine learning model based on an output by the first machine learning model from analysis of the subset of the sensor data, and based on determining that the actual accuracy rate is below a predefined threshold corresponding to a deployed accuracy rate, trigger a retraining of the first machine learning model using at least the subset of sensor data in the camera feed as training data.

The invention relates to the field of photovoltaic technology, and discloses an interface optimization method for a front-surface seed-layer-free electrode of a photovoltaic cell and a photovoltaic device. The method comprises the following steps: placing a silicon substrate in PECVD (Plasma Enhanced Chemical Vapor Deposition) equipment, and depositing a SiOxNy composite passivation layer with the thickness of 1-10nm on the surface of a transparent conducting layer on the front surface of the silicon substrate through plasma in-situ deposition; printing low-temperature sintered copper paste of which the sintering temperature is less than or equal to 200 DEG C onto the surface of the SiOxNy composite passivation layer; and curing the printed low-temperature sintered copper paste to obtain the front copper electrode. According to the method, a front seed layer is abandoned, direct combination of a front copper electrode and a front transparent conducting layer of a silicon substrate is achieved, an efficient interface inhibition passivation tunneling layer (namely a thin SiOxNy composite passivation layer) is constructed to block a copper-silicon mutual expansion path, interface contact characteristics are optimized, low-temperature sintering type copper paste is matched, contact resistance is reduced, stability is improved, the whole process is low in temperature, and the method is suitable for large-scale production. The method is compatible with an HJT battery manufacturing system and is low in metallization cost.

A robotic fleet platform includes a fleet resources data store with a fleet resource inventory indicating additive manufacturing systems that can be provisioned with a set of fleet resources. The fleet resource inventory indicates 3D printing requirements, printing instructions, and a status of each additive manufacturing system. Provisioning rules are accessible to an intelligence layer to ensure compliance. The platform receives a request for a robotic fleet to perform a job and determines a job definition data structure defining tasks. The platform determines a robotic fleet configuration data structure that assigns additive manufacturing systems to one or more of the tasks. The platform determines a respective provisioning configuration for each of the additive manufacturing systems. The platform provisions each additive manufacturing system based on the respective provisioning configuration and the provisioning rules. The platform deploys the robotic fleet based on the robotic fleet configuration data structure to perform the job.

The invention relates to the technical field of industrial management, and discloses a composite material sharing intelligent manufacturing management system based on an industrial internet, which comprises a cross-layer state modeling and management and control strategy mapping module, the method comprises the following steps: firstly, based on multi-source process data, respectively quantifying the local cumulative strength of microdefects, the association degree of a macroscopic equipment operation sequence and the defect connectivity risk degree driven by space geometry, and aggregating the indexes into cross-layer self-organizing critical coupling state parameters; and then generating a resource scheduling weight vector and a geometric complexity load scaling coefficient through deterministic calculation, and dynamically adjusting a task allocation probability and an equipment bearing limit according to the resource scheduling weight vector and the geometric complexity load scaling coefficient. According to the method, active avoidance and decriticalization control over the critical risk of the manufacturing system are achieved, and high-quality and efficient collaborative production of complex components is guaranteed.

The present disclosure is directed to a construction element produced by additive manufacturing, an additive manufacturing system for producing the construction element and a method for manufacturing the construction element. The construction element includes an outer layer. The outer layer is configured to define or form an enclosure. The construction element further includes an inner matrix. The inner matrix is formed within the enclosure. The outer layer and the inner matrix are formed integrally, by depositing successive layers using an additive manufacturing system. The inner matrix is defined by a first layup and a second layup. The first layup is laid along a first direction and across the enclosure. The second layup is laid juxtaposing the first layup. The first layup and the second layup define a plurality of air pockets in the inner matrix. Further, a filler material is infused into at least some air pockets of the plurality of air pockets.

A manufacturing system for a multifunctional composite mala colored stone material, characterized in that: It comprises a raw material pretreatment module, a precision composite manufacturing module, a finished product post-treatment module, which are connected in sequence, and an intelligent control module that networks the respective modules; that the raw material pretreatment module contains an aggregate treatment unit and an auxiliary material treatment unit, for the aggregate treatment unit a link of “vibrating feed → jaw coarse crushing → cone medium crushing → VSI sand production-shaping → classification by means of a multi-deck circular vibrating screen” is used, through the classification aggregates are obtained in specifications of 30 meshes, 50 meshes, 80 meshes, 120 meshes, the auxiliary material treatment unit is equipped with an LM vertical mill and a drying-dehumidifying device;that the precise compound manufacturing module includes an intelligent dosing unit and a mixing modification unit, the intelligent feeding unit is controlled by a PLC control system networked with an electronic dosing scale, and the precision error of a proportional division is ≤ ± 0.5%.

The utility model provides film pressing equipment and an electrode manufacturing system. The film pressing equipment comprises a film forming roller, a fixed roller, a first calendering roller and a second calendering roller which are sequentially arranged according to a material feeding sequence, wherein the circumferential surfaces of the film forming roller, the fixed roller, the first calendering roller and the second calendering roller are all provided with wear-resistant layers, and the thicknesses of the wear-resistant layers are sequentially increased according to the material feeding sequence; the wear resistance of the surfaces of the compression rollers is enhanced, the wear degree of the surfaces of the compression rollers is reduced, the wear degree of the compression rollers can be relatively balanced, the service life of the compression rollers can be prolonged, and the film pressing equipment is ensured to run for a long time with stable performance.

The utility model discloses a synthesis device. The synthesis device comprises a base, a mounting plate, a driving part and a synthesis container, the mounting plate is rotatably connected to the base; the driving part is arranged on the base and connected with the mounting plate so as to drive the mounting plate to rotate; the synthesis container is arranged on the mounting plate, and the synthesis container can pass through the loading position and the unloading position in the process of rotating along with the mounting plate; when the synthesis container is located at the loading position, the opening direction of the synthesis container is inclined and upward relative to the horizontal direction; and when the synthesis container is positioned at the discharging position, the opening direction of the synthesis container is inclined and downward relative to the horizontal direction. According to the synthesis device, during charging, the synthesis container is rotated to the charging position through the driving piece, so that charging of materials is facilitated; and after the diffusion process is completed, the synthesis container is rotated to the unloading position through the driving part, so that the materials are conveniently unloaded, the loading and unloading operation is more convenient, and the loading and unloading efficiency is improved. The utility model also discloses a semiconductor preparation system.

A predictive analytics apparatus, engine, system and method capable of providing real time analytics in a manufacturing system that may include a data input capable of receiving raw data output from at least one machine operable to effect the manufacturing system embodiments, and a processor to execute code from a computing memory. The code may comprise an adaptor to push the received raw data to a database to processed data; an extractor to extract the processed data from the database; predictive analytics to receive the extracted processed data and apply thereto a predictive model comprised of target data for the at least one machine, and to provide feedback to the at least one machine to modify performance of the at least one machine based on the application of the predictive model; and a visualizer capable to provide at least a visualization of the feedback and the performance.

Mold element support device for a manufacturing assembly for preform elements and / or precast elements and / or prepackaged elements for a wind turbine blade is provided. The mold element support device includes multiple upper support portions for carrying a longitudinal mold element for manufacturing a preform element and / or a precast element and / or a prepackaged element. The mold element support device includes a longitudinal carrier element, in particular a carrier beam, for the longitudinal mold element and a positioning device having multiple pivotable, in particular horizontally extending, swivel arms, which are attached to the carrier element at one end and have a respective support portion attached thereto at the other end.