9 results about "Lean manufacturing" patented technology

The application provides an intelligent inventory control management method and system based on a supply chain cooperation mechanism, applied to the technical field of supply chain management, preliminary demand prediction of a downstream partner is received, demand intention information containing customization component possibility weight and potential demand range is generated according to the prediction, after the upstream supplier receives the demand intention information, the influence of the demand intention information on future production resources is further evaluated, an evaluation result is obtained, finally, according to the evaluation result, the method performs flexible preparation in advance, including production window soft reservation, upstream material pre-communication and special mold preparation, effectively coping with the supply uncertainty of the customized components, avoiding the dilemma of standard component overstock and customized component shortage, realizing lean production and on-time delivery, and bringing significant economic benefits and competitive advantages to enterprises.

The application relates to the technical field of intelligent manufacturing teaching and training equipment, and discloses a lean production training platform based on production big data analysis, which comprises an entity production line module, a multi-source heterogeneous data acquisition system, an edge computing and control hub and a lean production training terminal. The entity production line module is used for simulating a production operation process in a real discrete manufacturing environment. The multi-source heterogeneous data acquisition system is distributedly arranged on the entity production line module and is used for collecting multi-dimensional data in a production process in real time. Through cooperation of an industrial sensor array, a machine vision unit, an RFID (Radio Frequency Identification) unit and a data aggregation terminal, multi-dimensional data such as equipment states, process parameters and material tracking are collected in real time, millisecond-level perception of whole-factor data such as people, machines, materials, methods and environments in the production process is realized, and the problems of single data dimension and rough perception granularity of a traditional training platform are fundamentally solved, so that a rich and accurate data basis is provided for lean analysis.

The application discloses a production rhythm dynamic evaluation method and system based on multi-attribute process constraints, relates to the tobacco technical field, and is suitable for the process manufacturing scene of mixed production arrangement of multiple brands. The method solves the problems of distortion of traditional static evaluation standards, broken cross-day production data, and difficulty in quantifying process coordination efficiency, provides dynamic and accurate benchmarks for production rhythm evaluation, and supports lean production landing in a tobacco silk workshop. In the method, step S1 realizes semantic alignment of production data, guarantees production shift analysis integrity; step S2 constructs a multi-attribute process constraint system, adapts to different process production requirements; step S3 generates differentiated theoretical working hour benchmarks, eliminates systematic deviation of the evaluation system; step S4 separates time deviation interference components, improves delay judgment accuracy; step S5 realizes automatic identification of delay events, reduces manual statistical lag; and step S6 locates key links of capacity constraints, and provides quantitative basis for production scheduling optimization.

This invention provides a control method and apparatus based on a lean manufacturing system, comprising: calculating the operational maturity value of a target lean manufacturing system to identify problems to be improved; constructing manufacturing strategic goals by comparing the target factory with business objectives based on pre-built quantitative indicators; streamlining the organizational structure based on pre-built lean processes, lean organizational structure, and lean departmental functions and responsibilities; constructing a multi-level key performance indicator system and a facilitating management meeting mechanism; and finally, constructing an implementation plan and controlling the target factory according to the implementation plan to achieve the optimization goals. This invention solves the problems of high deployment costs and poor application effects in existing technologies.

The application discloses a 3D printing device for detecting and regulating integrated insulating material and an intelligent manufacturing method. The device comprises a printing module, a regulating module and a detecting module used in cooperation. The printing module comprises a moving platform, a printing tank, a screen plate, a cleaning rod and a light-curing surface light source. The regulating module comprises an electrode assembly and a regulating power supply. The detecting module comprises a laser thermal excitation assembly and an infrared thermal imager. The laser thermal excitation assembly is used for applying thermal loading to a printing sample. The infrared thermal imager collects surface temperature evolution information of the printing sample in the thermal loading process and transmits the information to a data processing system. The orientation and distribution of the thermally conductive filler are regulated by using the auxiliary effect of an electric field, and the thermal conductivity distribution state of the material is detected in real time by means of a thermal wave imaging technology. According to the detection result, the parameters of the applied electric field are dynamically adjusted, the precise closed-loop control of the distribution and orientation of the filler is realized, and thus an effective path is provided for the lean manufacturing of high-thermal-conductivity-low-loss insulating material.

1. Name of the designed product: Lean pipe (4.0). 2. Use of the designed product: Pipe for lean production, modular tooling and material handling system. 3. Design points of the designed product: In shape. 4. Pictures or photos that best show the design points: Design 1 perspective view 1. 5. Design 1 is designated as the basic design.

The application discloses a pipeline lean production management system and method, and relates to the technical field of ship manufacturing. The system solves the problems existing in the traditional production mode through workshop reconstruction and process optimization. The system adopts a hierarchical real-time control architecture, which comprises an edge computing gateway, a MES server and a data acquisition module. The edge computing gateway runs a hard real-time operating system and executes millisecond-level control logic. The MES server is arranged on a management layer, runs a general operating system, and executes second-level monitoring and historical analysis. The data acquisition module is arranged on production equipment of a core machining process of a pipeline workshop and is connected with the edge computing gateway and the MES server.

This invention relates to the field of engine component testing technology, and discloses a cylinder head airtightness testing device and method, including a control cabinet. The control cabinet is installed in a corresponding position via a support mechanism at the bottom. A shock-absorbing mechanism is provided on the top of the control cabinet, and an adaptive clamping mechanism is connected to the upper part of the shock-absorbing mechanism, realizing the integration of press-fitting and leak detection, which greatly improves the testing efficiency. By integrating the two processes of seal press-fitting and airtightness testing into one, there is no need for manual transfer of the cylinder head, and the single cycle is short. Compared with traditional separate equipment, the testing efficiency is improved. At the same time, the equipment occupies less space and consumes less energy, solving the pain points of traditional process disconnection, low efficiency and large footprint, meeting the requirements of lean production and showing significant progress. By establishing a database linking press-fitting parameters and leakage rate, the accumulated data can realize intelligent optimization of process parameters, providing data support for improving the quality of seal assembly, and has outstanding substantive features.

This application discloses a mechanism- and data-driven product quality control method and related apparatus, relating to the field of product quality control technology. The method includes: acquiring multiple sets of historical measurement data; using the process characteristics and quality characteristics of each step in a preset process as nodes; calculating the comprehensive grey relational degree between nodes based on the multiple sets of historical measurement data; constructing a Bayesian network; acquiring the real-time values ​​of the process characteristics and quality characteristics of the preset steps in the preset process; using these real-time values ​​as input; and using the Bayesian network for inference to predict the predicted value of the quality characteristic of the last step in the preset process, thereby further controlling product quality. This application combines mechanism and data to control product quality, enabling accurate prediction and timely intervention of quality problems, achieving the high requirements of lean manufacturing.