58 results about "Lean manufacturing" patented technology

The invention belongs to the technical field of lean manufacturing monitoring, and particularly relates to an anomaly detection and processing method for a production process of an intelligent factory, and the method comprises the steps: constructing a dual monitoring node chain and a layered anomaly association evaluation node chain based on a preset production process flow chain, and collecting the operation state and process parameter data of equipment in real time; the hierarchical anomaly association assessment node chain analyzes the equipment health degree through the operation state assessment sub-chain, mines a cross-process anomaly propagation relationship through the whole-process technology anomaly assessment sub-chain, generates a whole-process association anomaly assessment space, fuses real-time data and historical anomaly strategy index information based on a distributed algorithm, and finally performs the whole-process association anomaly assessment on the basis of the real-time data and the historical anomaly strategy index information. Dynamically constructing a difference exception processing strategy library, and realizing processing strategy synchronous feedback of positioning exception; according to the invention, through a dual monitoring architecture and hierarchical association evaluation analysis, the problems of fuzzy abnormal propagation path and response lag are solved, and the real-time performance and processing accuracy of abnormal detection are improved.

The invention discloses a car tire building drum error analysis method and system, and relates to the technical field of data processing, and the method comprises the steps: collecting technological parameter data in a tire building process in real time through a plurality of sensor combinations, and carrying out the preprocessing of the collected data; based on the preprocessed data, characteristic parameters corresponding to the tire building drum error are extracted through a signal processing technology; based on the extracted characteristic parameters, using a data mining technology and a machine learning algorithm to analyze a relationship between each process parameter and a geometric error of the forming drum, constructing an error analysis model, using the error analysis model to carry out error prediction, feeding back a prediction result to production equipment in real time, and adjusting the corresponding process parameters; the car tire building drum error analysis system comprises a data acquisition module, a data transmission module and an algorithm module. An efficient, intelligent and accurate solution is provided for tire building drum error analysis, and intelligent and lean production development of the tire manufacturing industry is promoted.

The invention provides a lean production-oriented self-adaptive digital intelligent scheduling method and system, and relates to the technical field of data processing, and the method comprises the steps: taking an initial resource allocation scheme as the basis of task sequence optimization, constructing a time detection line on a time axis, detecting the overlapping condition of different tasks in an execution period, and recognizing resource conflict points; generating a preliminary scheduling plan under the condition of meeting the equipment capacity and man-hour constraint; based on multi-source data of a production site, evaluating the preliminary scheduling plan, updating scheduling parameters, and generating an optimized scheduling scheme; and converting the optimized scheduling scheme into an equipment control instruction, and transmitting the equipment control instruction to a control terminal of a production unit to complete closed-loop optimization of production resources. Reasonable adaptation and efficient scheduling of production resources can be achieved, the production efficiency is improved, and resource waste and conflicts are reduced.

The invention relates to a lean production multi-objective optimization intelligent control method based on an adaptive simulation genetic algorithm, and the method specifically comprises the following steps: 1, constructing a multi-objective optimization algorithm under a constraint condition that n decision vectors belong to an n * m cube R matrix space in an X decision unit, all sub-objective functions of the material-to-weight ratio, the temperature, the CO2, the NH3 and the H2S reach the minimum lean production multi-objective optimization premise as much as possible; a Pareto optimal solution of multi-target minimization is determined by adopting segmentation-parallel selection-combination in a swarm intelligence hybrid optimization algorithm; measuring the concentration ratio of individuals in the population by adopting three parameters, namely a maximum adaptive value fitmax, a minimum adaptive value fitmin and an average adaptive value fitave of the population, and exploring by adopting a first maximum variation rate operation, a second minimum crossover rate operation and a second copy operation; performing development by firstly performing minimum variation rate operation, then performing maximum crossover rate operation and then performing copying operation; the improved Monte Carlo simulation is adopted, the global optimization ability of the genetic algorithm is improved, and the core of the adaptive simulation genetic algorithm is integrated.

The invention discloses a data perception and process datamation modeling method for lean manufacturing of an intelligent factory, and the method comprises the following steps: configuring a data collection module, and collecting data in real time from a sensor of a production line, a machine vision system for detecting the surface defects of a product, a PLC controller, and an ERP system; the acquired data is transmitted to a data acquisition server through an industrial Ethernet, and data acquisition software running on the data acquisition server is responsible for analysis and storage; after the data is cleaned and sorted through a data fusion module, a mixed deep learning model of a convolutional neural network (CNN) and a long short-term memory (LSTM) network is adopted to process the sorted real-time data, and the mixed deep learning model outputs various triples for knowledge graph modeling, including entities, relationships and attribute information; constructing a knowledge graph based on the output of the deep learning model, and determining the relationship between entities; an intelligent query module is used for querying the knowledge graph in real time and interacting with a user in a natural language form; and a fault early warning module is adopted to monitor data in real time.

The invention relates to the technical field of machining, and discloses a circular knife double-asynchronous collaborative die cutting process and equipment for a multi-glue-layer blue film structure, and the process comprises the following steps: obtaining material parameters and pattern data, and carrying out pretreatment and real-time visual alignment on the multi-glue-layer blue film structure; and the central control module operates an algorithm according to the data, generates and drives the first circular cutter die cutting unit and the second circular cutter die cutting unit to perform asynchronous collaborative die cutting, and peels off waste materials. The system comprises a material conveying module, a visual alignment module, a first circular cutter die cutting unit, a second circular cutter die cutting unit, a central control module and a waste stripping module. By the adoption of the scheme, die cutting alignment precision and efficiency are improved, material loss and production cost are reduced, traditional die cutting errors and material deformation are avoided, cutting quality is optimized, and a technical basis is provided for lean production of electronic product parts.

The invention belongs to the technical field of automobile manufacturing, and particularly discloses an intelligent flexible production scheduling method and system for automobile orders, and the method comprises the following steps: collecting order demands of a user; according to the order delivery time requirement of a user, reversely deducing production plans of a coating workshop and a welding workshop by taking the general assembly workshop as a starting point to obtain a production plan of a production line; according to the demand within a period of sales, in combination with the material arrival rhythm, the workshop capacity and the sales demand successive date factor, daily production vehicles are discharged, and according to the selected daily production vehicle distribution result and the final assembly lean production proportion requirement, constraint conditions are set, and coating production sorting and scheduling calculation are carried out; and on the basis of the scheduling, a welding vehicle queue plan is generated in combination with a coating workshop production plan in a user order demand. By adopting the technical scheme, production scheduling is carried out by using a production scheduling reverse pushing mode based on the production characteristics of the automobile orders, flexible production scheduling of the automobile orders is realized, and the efficiency is improved.

A steelmaking process quality monitoring and analysis system, comprising: an application layer, wherein the application layer comprises adaptive process quality monitoring and analysis modules for steelmaking procedures, and the process quality monitoring and analysis modules are used for implementing process quality monitoring and analysis during a steelmaking process; a control layer, wherein the control layer comprises control modules corresponding to the steelmaking procedures in the application layer; and an equipment layer, wherein the equipment layer comprises hardware equipment corresponding to the adaptive process quality monitoring and analysis modules for the steelmaking procedures in the application layer. The present invention is applicable to process quality monitoring and analysis for procedures in a steelmaking workshop; a process quality monitoring and analysis system for steelmaking procedures is constructed, and process equipment parameter data structures and analysis models are constructed, such that scaling factor algorithms, process quality monitoring and analysis models and adaptive process quality monitoring and analysis algorithms for steelmaking procedures are implemented, thereby providing feasible technical support for the improvement of the steelmaking process quality and the product quality, and realizing lean production in steelmaking workshops.

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 explosive injection shaping cutter for the initiating explosive device comprises a cutter mounting body, a plurality of shaping blades are fixedly mounted at the bottom of the cutter mounting body, and asymmetric double-angle blades are arranged on the two sides of each shaping blade. The medicine injection shaping cutter is simple in structure, has the characteristics that the weight of the cutter is suitable for manual operation, safety is guaranteed, the cutter is provided with multiple blades and the asymmetric double-angle blade structure is adopted, the cutter can better adapt to medicine surface appearances under different complex conditions, shaping precision is high, medicine surface slicking work is easily completed, production quality and efficiency are both improved, and the cutter conforms to the lean production principle.

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 present invention provides a method for investigating the process capability of mass production, which is based on the established production line and production program, based on the results of technological transformation, and aimed at the whole machine assembly test and parts manufacturing. According to the production mode of the production line and parts, relevant data collection, questionnaire design, actual production cycle calculation, equipment load rate measurement, process capability analysis, capacity short board analysis, etc. are carried out. By measuring and analyzing the specifications, the process capability short boards such as equipment and the lack of production resources such as tooling are supplemented, the lean manufacturing process is improved, and the purpose of improving the process capability and meeting the mass production requirements is achieved.

The utility model discloses a wall switch flexible lean production line which comprises a workbench, the top of the workbench is provided with a material sliding plate, the back of the workbench is provided with an adjusting assembly, and the back of the workbench is provided with a front end fixed feeding material frame. The adjusting assembly comprises a plurality of front-end feeding movable material frames arranged on the back face of the workbench, and a front-back laser marking machine is arranged on the back face of the workbench. Through the design of the front-end fixed feeding material frame, the front-end feeding movable material frame and the placing table, when different products are produced, the position of the front-end feeding movable material frame and the position of the placing table of which the top is provided with the positive and negative laser marking machine are moved according to the production process of the products; therefore, the positions of the material frame and the positive and negative laser marking machines on the whole production line are adjusted according to needs to adapt to production procedures of different products, and the space occupied by the production line is saved.

The utility model belongs to the technical field of controller shell structures, and particularly relates to a lean-production anda lamp shell, which comprises a bottom shell, a surface shell and a PCB (printed circuit board), the PCB is arranged in the bottom shell and the surface shell, a silica gel key is arranged between the inner side of the surface shell and the PCB, the size of the silica gel key is the same as that of the PCB, and the silica gel key is arranged in the bottom shell. A silica gel protection edge is integrally formed on the PCB side of the periphery of the silica gel key, and a silica gel bottom pad clamped into the silica gel protection edge is arranged on the back face of the PCB. An embedded groove is formed in the outer side of the face shell, a plastic sticker is bonded in the embedded groove, the bottom shell and the face shell are connected in a clamped mode, and a sealing gasket is bonded in a clamping groove formed in the inner side of the face shell. The shell has the advantages that through the close matching design of the silica gel keys, the silica gel protection edges and the silica gel bottom pads, all-around protection is provided for the PCB, the PCB is effectively prevented from being damaged when the shell falls off or is subjected to external pressure, and meanwhile the requirement for the size of the lamp shell is not increased.

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.

The present invention belongs to the field of open-pit mine production technology, and in particular, relates to a method for positioning an electric shovel based on density clustering. The method uses the scheduling work plan of each shift, GPS dynamic positioning data, and the operation time and trajectory of the shovel, rock crushing tipping point, and ore crushing tipping point of the transport vehicle to calculate the vehicle-shovel correspondence, and uses the DBSCAND algorithm to obtain the preliminary positioning information of the electric shovel. The GPR algorithm is then used to predict the trajectory of the failure position of the electric shovel and the transport vehicle, analyze the data of the vanishing point of the electric shovel signal and the vanishing point of the transport vehicle signal, and perform least squares curve fitting on multiple predicted values. Each intersection of the predicted trajectory is mapped on the line connecting the failure position of the electric shovel and the transport vehicle, and the point with the maximum mapping density is taken as the accurate operating position of the electric shovel. Based on the existing equipment, this method uses a suitable algorithm for calculation, and can obtain the accurate position of the electric shovel without the need for reinvestment in equipment, providing reference data for production scheduling and further realizing lean production in mines.

The utility model relates to the field of optical communication, in particular to a glue tube placing frame of a dispensing system, which is applied to the packaging and manufacturing process of an optical device. Comprising a base, a collecting disc, a bearing support, a limiting sleeve and a rubber pipe. The base comprises a base through hole and a threaded hole, the collecting disc is connected with the base through hole through a boss at the lower end of a disc body, the bearing support comprises a first bearing support through hole and a second bearing support through hole, the second bearing support through hole is matched with the threaded hole of the base and connected with the threaded hole of the base through a hexagon bolt, and the limiting sleeve comprises an edge, a convex ring and a through hole. The protruding ring is located at the lower end of the through hole, the edge is located on the periphery of the through hole, the protruding ring is inserted into the first through hole of the bearing support, the edge is connected to the periphery of the first through hole of the bearing support in a clamped mode, and the rubber pipe is inserted into the through hole. The device is high in compatibility, can be compatible with rubber tubes of different specifications, has the functions of quickly placing the rubber tubes, preventing pollution and the like, improves the efficiency, reduces the manufacturing cost, and meets the lean production requirement.

The utility model discloses a raw material cleaning device for Chinese herbal medicine veterinary medicine preparation, and relates to the technical field of Chinese herbal medicine raw material cleaning, in particular to a cleaning box, a cleaning barrel is rotatably connected between the inner walls of the two sides of the cleaning box, four cleaning columns are fixedly connected in the cleaning barrel, and a cleaning groove is formed between every two adjacent cleaning columns. Four stirring shafts are rotationally connected between the inner walls of the two sides of the cleaning tank. According to the medicinal material cleaning device, medicinal materials can be stirred when being cleaned, so that the medicinal materials are in full contact with a water source, the water source washes stains on the surfaces of the medicinal materials, and the medicinal materials can be in full contact with the cleaning shaft when being stirred, so that stubborn stains on the surfaces of medicine bags are cleaned, and the cleaning quality of the medicinal materials is improved; the problems that part of existing cleaning devices are not ideal in effect, if high cleaning requirements need to be met, the cleaning speed is very low, time is consumed, and the requirement of lean production cannot be met are effectively solved.

The invention relates to the technical field of industrial Internet of Things, and discloses a user emergency insurance supply'finger singing confirmation 'digital platform system based on a component visual angle, which comprises an information acquisition module; a real-time monitoring module; a visual display module; an early warning module; the man-hour management module is used for storing and dynamically correcting the standard work man-hour of each part, and the correction is based on the deviation between the historical actual man-hour and the standard man-hour of big data mining analysis; and the collaborative confirmation module is in communication connection with the visual display module and the early warning module, and is used for distributing responsibility departments and persons in charge based on the RACI matrix for each finger singing confirmation element. According to the system, a set of efficient monitoring and early warning mechanism is established, and lean production is driven through digitization. The digital finger singing confirmation mode based on the user parts can be quickly copied and expanded to other machining centers, and has the potential of copying and popularizing user insurance supply services of other enterprises in the iron and steel manufacturing industry.

The utility model discloses plastic part detection equipment with a Type-D interface, and the plastic part detection equipment comprises vibrators, a visual test bottom, a vibrator product discharge channel, a transparent glass disc, a CCD test module, a probe, an air blowing and discharging part, a storage mechanism and a rotary motor, and the two vibrators convey products to the inner ring and the outer ring of the transparent glass disc through the product discharge channel at the same time for testing; and the tested products are conveyed to the defective product storage mechanism and the non-defective product storage mechanism for classified output. According to the invention, the defects of missing detection of a manual detection mode and confusion of different types of plastic part products are overcome, the stable detection effect of the plastic part of the Type-D interface is ensured, the detection efficiency is improved, the yield of a production line is further improved, the production operation cost can be reduced, and the goal of lean production is achieved. Under the condition that the detection quality is guaranteed, the labor cost is reduced, the operation time is short, and the operation efficiency is greatly improved.

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 invention provides an intelligent inventory control management method and system based on a supply chain collaboration mechanism, which are applied to the technical field of supply chain management, and the method comprises the steps: receiving the preliminary demand prediction of a downstream partner, generating demand intention information containing the possibility weight of a customized part and a potential demand range according to the prediction, and carrying out the control of the demand intention information. After an upstream supplier receives 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, flexible preparation including production window soft reservation, upstream material pre-communication and special mold preparation is carried out in advance, the supply uncertainty of customized parts is effectively dealt with, and the production efficiency is improved. The problems of overstock of standard components and shortage of customized components are avoided, lean production and on-time delivery are realized, and remarkable economic benefits and competitive advantages are brought to enterprises.

The utility model relates to the technical field of hot pot oil dish processing equipment, in particular to a full-automatic packaging system device for hot pot oil dishes. Comprising a full-automatic weighing monitoring machine, the left end and the right end of the full-automatic weighing monitoring machine correspondingly form an input end and an output end, one side of the input end of the full-automatic weighing monitoring machine is connected with a filling assembly, and one side of the output end of the full-automatic weighing monitoring machine is connected with a full-automatic cover feeding, arranging and pressing all-in-one machine; the system further comprises a labeling assembly, a boxing assembly and an automatic stacking robot. According to the full-automatic hot pot oil dish packaging system device, the full-automatic weighing monitoring machine is adopted, under the condition that the filling speed is not affected, automatic weight adjustment and automatic weight checking are achieved, gram weight control is enhanced, the sampling inspection frequency is improved, the gram weight quality risk is reduced, the average weight of products can be accurately controlled through the full-automatic weighing monitoring machine, and the production efficiency is improved. And on the premise of meeting the national standard requirements, the production cost can be reduced to the greatest extent, and lean production is facilitated.

The invention provides a rhythm assembly method for corrugated plates of a cargo containment system. The rhythm assembly method comprises the following steps that S1, a difficulty coefficient table is constructed according to the mounting positions and types of the corrugated plates; s2, obtaining the number, the installation positions and the specifications of corrugated plates according to a single cabin object quantity statistical table; s3, according to the single-cabin object quantity statistical table and the difficulty coefficient table, the total fraction of corrugated plate assembly of the whole cabin is generated; s4, determining the assembly standard grade capability of the corrugated plate; s5, the daily input necessary grade number of corrugated plate assembly is determined; and S6, making an engineering plan table and an assembly sequence table, and assembling the corrugated plates based on the engineering plan table and the assembly sequence table. According to the method, the standard operation mode of corrugated plate assembly can be constructed by applying the idea of lean production takt, the corresponding cost is effectively reduced by reducing the extra workload generated in a traditional assembly method, the corrugated plate assembly efficiency is improved, and the aims of improving the engineering productivity and shortening the period are finally achieved.

The invention discloses a clamp design method for a net-shaped hollowed-out part, and relates to the technical field of machining, and the clamp design method comprises the steps that a clamp is designed according to the shape of the net-shaped hollowed-out part, and the clamp is designed to be provided with a part main contact surface matched with the shape of the net-shaped hollowed-out part; a plurality of bosses used for clamping ribs of the net-shaped hollowed-out part are arranged on the main contact face of the part. The clamping efficiency and the machining efficiency are improved, production equipment does not need to be additionally arranged, circulation procedures are reduced, and the lean production level is greatly improved.

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.

The invention relates to new shelves for commercial shelving systems developed for storing or displaying goods, which, compared to the shelves of existing technology according to the current state of the art - shelves, shelving systems and / or shelving units - are more versatile, more environmentally friendly and manufactured using lean manufacturing, which allows for a reduction in thickness and at the same time an increase in load capacity.

The invention relates to a calculation method for calculating a target unit consumption value of a rolling and packing workshop and a method for performing real-time monitoring by using the calculation method, and belongs to the technical field of rolling and packing workshop production process monitoring. According to the method, the yield and consumption data of the unit in the production process are recorded in real time, the target unit consumption value is adopted to carry out real-time quantitative index evaluation on the yield and consumption data, the evaluation result is pushed to an operator and a production manager in real time, and when the evaluation result exceeds the early warning range, alarm information can be sent in real time, so that the production efficiency is improved. A basis is provided for operators to adjust equipment parameters in real time, and the corresponding equipment parameters are adjusted, so that the lean production level of the whole equipment is improved.