CN115857460A - Lean production method based on industrial simulation software digital analysis - Google Patents
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Abstract
The invention discloses a lean production method based on industrial simulation software digital analysis, which specifically comprises the following steps: installing industrial simulation software on a discrete intelligent production workshop control platform, and according to workshop layout parameters of a production workshop, information of various intelligent devices and personnel allocation information, setting up a real-virtual proportion as 1:1, the whole production field is completely visualized. According to the invention, a three-dimensional production scene of the discrete manufacturing industry is set up and operated through simulation software, the real-time value flow condition of the whole production supply chain is conveniently calculated and simulated, the production management can be timely adjusted and optimized through a simulation result, and the production management is more transparent, efficient and intelligent.
Description
Technical Field
The invention relates to the field of discrete manufacturing, in particular to a lean production method based on industrial simulation software digital analysis.
Background
In the discrete manufacturing industry, the production characteristics of multiple varieties and small batches are ubiquitous. The production process and processing time of each product are different, and after reaching a certain scale, production scheduling, order management, process change and inventory control become very difficult. In the whole processing process, due to factors such as scheduled production, production execution, process equipment and the like, the problems of long production period, large product inventory, poor product consistency and the like are caused, and meanwhile, the production cost is greatly increased. In the traditional method, a large amount of manpower and material resources are consumed by manually drawing a value flow graph VSM, each processing action of each procedure is timed, measurement errors exist, the effect of lean activities is directly influenced, and the method can only draw the value flow graph aiming at a certain type of products to improve the production flow of the type of products and cannot adapt to the analysis requirements of various products.
With the development of the intelligent manufacturing technology, the information technology is utilized to collect field data, and a system platform is built through simulation software, so that the dynamic value flow condition of the whole production supply chain can be conveniently calculated and simulated. The Digital VSM can reflect the real situation of the site in real time and flexibly simulate the optimized value flow diagram, thereby calculating the average delivery time of production, the inventory of products in process and the value-added ratio of the overall production. Different value flow diagrams can be drawn for any variety of products, the application range is wide, and lean production and intelligent manufacturing are combined to enable production management to be more transparent, efficient and intelligent. The patent application with the publication number of CN101923600A discloses a logistics simulation method for a steelmaking continuous casting workshop, which can realize the functions of modeling of a steelmaking continuous casting project, analysis and synthesis of a scheduling strategy and the like, thereby providing decision support for a steelmaking process flow design link. The patent application with publication number CN106210093A discloses a "3D intelligent scheduling method based on logistics simulation software", which is a method for calculating and analyzing by a logistics simulation model and extracting a simulation control command of the logistics simulation model to an AGV logistics system, and solves the problem that the triggering condition of the logistics simulation software cannot be matched with the actual control system condition.
However, the above patent still performs simulation and emulation in terms of product logistics turnover path and efficiency, and establishes a mathematical model to solve the optimal path and strategy. These methods do not reflect and calculate the product value flow and the value-added ratio from the lean production global perspective, and cannot obtain the data description of the actual optimization effect from the field information.
Disclosure of Invention
The invention aims to provide a lean production method which can effectively utilize information technology to acquire field data, build a three-dimensional production scene of a discrete manufacturing industry through simulation software and operate, conveniently calculate and simulate the real-time value flow condition of the whole production supply chain and contribute to more transparence, high efficiency and intellectualization of production management.
The technical scheme of the invention is as follows: a lean production method based on industrial simulation software digital analysis specifically comprises the following steps:
step 1, installing industrial simulation software on a discrete intelligent production workshop control platform, and according to workshop layout parameters of a production workshop and information and personnel allocation information of various intelligent devices, setting up a real-virtual ratio as 1:1, completely visualizing the whole production field;
and 2, defining N products in the production workshop as follows: the product is marked by P, i represents the product variety, i =1,2,3,4.. N, pi represents the ith product;
step 3, arranging and summarizing real-time production and processing information of the N products in the MES, wherein the real-time production and processing information comprises data which are closely related to the line changing time, the production takt of each procedure, the production process route, the production quality and the production and processing of the products, and a production and processing information flow of each product is formed;
step 4, arranging and summarizing production plan information of the N products in the MES, wherein the production plan information comprises production plan issuing date, estimated work starting time, estimated completion time and actual work starting time, and the actual completion time and the production plan are closely related to data to form production plan information flow of each product;
step 5, arranging and summarizing production logistics information of the N products in the MES, wherein the production logistics information comprises a material preparation flow, a production line changing flow, a production processing flow, a production turnover flow, a production warehousing flow, and data closely related to a production process, a production packaging and delivery flow and a production process, so as to form production logistics of each variety;
step 6, under the framework of the simulation model established in the step 1, on the basis of the steps 2,3,4 and 5, respectively docking production and processing information flow, production plan information flow and production logistics data in the MES system into a database of industrial simulation software, starting a simulation operation mode, and simulating the operation condition of the production workshop;
step 7, comparing the simulation operation condition of the step 6 with the actual operation condition, and confirming the timeliness and the accuracy of the model frame construction and the operation logic;
step 8, on the basis of the step 7, designing and building a Digital value flow graph Digital-VSM template base through industrial simulation software, wherein the template base can display production processing information flow, production plan information flow, production logistics and lean production parameter indexes of the product in real time according to different product varieties, and the lean production parameter indexes comprise value-added ratio, production period and product-in-process inventory, wherein:
the increment ratio VA is the ratio of the time used by the increment part in the whole production time during the processing and production of the product, VA = the actual processing time/the whole production time,
the production period TPc/t, total Product Cycle Time-TPc/t, is an index for measuring intelligent production fluency, and refers to the longest Time path (critical path) from receiving raw materials to delivering products,
WIP in work-in-process inventory: in the production process, the total number of parts of the semi-finished product before each procedure is reduced;
step 9, rapidly identifying problem points existing in the production process according to a Digital-VSM template library, finding an improvement direction, then flexibly performing optimized production scheduling sequence, procedure adjustment, process optimization, equipment movement and personnel allocation lean management activities in the built three-dimensional production scene to obtain the best optimized future Digital-VSM, applying the best optimized future Digital-VSM to actual production and effectively improving the production efficiency in real time;
step 10, setting alarm thresholds of VA, TPc/t and WIP lean indexes in a Slide window of Using Visual objects Module; if the alarm threshold value is reached in the real-time production, alarm information is sent out to remind a manager to timely make a lean improvement activity and implement the lean improvement activity.
According to a further technical scheme, the operation state in the step 7 refers to the real-time state of the product start-up time, the product production flow, the processing time of the product in different procedures and the operation state of different adding devices; and (3) inputting the contents including production and processing information, production plan information and production logistics information, outputting and comparing the contents including order completion period, production quantity, equipment utilization rate, quantity of products in process and personnel working efficiency, and feeding back to personnel compiling the interface program in the step 6 to modify and perfect verification in time if the simulation result deviates from the actual result so as to ensure the consistency of the built three-dimensional model and the actual workshop operation scene.
According to a further technical scheme, the specific operation steps of building the Digital-VSM template library in the step 8 are as follows:
(1) The industrial simulation software takes Flexsim as an example, adopts a plurality of Discrete Objects to build universal symbols and icons of the Digital-VSM, and displays the production processing information flow, the production plan information flow and the production logistics of the Digital-VSM in a three-dimensional way through the interaction function of the Discrete Objects and an external three-dimensional figure;
(2) The method comprises the steps that the whole logic of the Digital-VSM is built through a FlexScript writing code or a ProcessFlow module, a flowing logic relation is built between the symbol and the icon of the Digital-VSM, when Pi product information is input into a three-dimensional simulation model and production operation is started, a simulation system automatically identifies and calls a code program of a Pi product, so that a Digital-VSM board corresponding to the Pi product is highlighted, and N types of products corresponding to the Digital-VSM reflecting field real conditions are realized;
(3) In a Digital value flow graph Digital-VSM, writing three elements of value-added ratio, production period and product inventory into a logic code in a code writing window built in Slide of Using Visual objects Module in industrial simulation software (taking Flexsim as an example), and establishing a one-to-one corresponding relation;
(4) The method comprises the steps of simulating and calculating three element data of VA, TPc/t and WIP under real-time and real conditions in simulation software by utilizing field big data which are butt-jointed and collected from MES, and visually and three-dimensionally presenting the three element data in a Slide window of Using Visual objects Module in a billboard mode.
In a further technical scheme, the problem point in the step 9 includes whether the production plan is accurate, whether the production and processing flow is reasonable, whether the processing beats of different procedures are abnormal, whether the deviation of production process parameters is large, and whether the processing running state of equipment is smooth.
According to the further technical scheme, before the intelligent manufacturing Digital workshop is put into production, a lean production method based on Digital analysis of industrial simulation software is used, on the basis of sorting and summarizing big data of an MES (manufacturing execution system), the production processing information flow, the production plan information flow and the production logistics data of a product are fitted by utilizing the expert Fit function of the industrial simulation software, then the Digital-VSM is obtained, the optimal future Digital-VSM is obtained through analysis and improvement, and the cost before and after the production is reduced.
The invention has the beneficial effects that:
1. the MES system is used for collecting various effective data of a production field, and then the effective data are butted to a three-dimensional production scene of a discrete manufacturing industry built by simulation software and run, so that the real-time value flow condition of the whole production supply chain can be conveniently calculated and simulated, on the basis, the problems existing in the production program are timely found, analyzed and improved, and the production management is more transparent, efficient and intelligent.
2. The lean production and the intelligent manufacturing are combined, so that the production management is more transparent, efficient and intelligent; the concrete points are as follows:
(1) The value flow graph Digital-VSM of any variety of products can be displayed rapidly, the drawing efficiency is high, and the application range is wide; the production data comes from a production site, the accuracy is high, and the accuracy of a value flow graph Digital-VSM is high;
(2) Dynamically displaying a Digital-VSM (value-flow graph) in real time, and flexibly and quickly guiding lean production work of a production workshop;
(3) The three-dimensional scene synchronously shows the conditions of the whole production field, and the visual monitoring of the production process is realized.
Drawings
FIG. 1 is a schematic diagram of a lean production method for implementing analysis of a digitized value flow graph using industrial simulation software according to the present invention,
FIG. 2 is a schematic diagram of a process for constructing a Digital-VSM template according to the present invention,
FIG. 3 shows the logic of the production and processing flow of different products in the SMT intelligent manufacturing shop according to the embodiment of the present invention.
Detailed description of the preferred embodiments
The invention will be further illustrated by the following non-limiting examples, which are to be understood.
Example 1: an SMT intelligent manufacturing workshop is taken as an example and combined with industrial simulation software Flexsim.
A lean production method for realizing analysis of a digital value flow graph by using industrial simulation software specifically comprises the following steps:
step 1, installing industrial simulation software Flexsim on a control platform of an SMT intelligent manufacturing workshop, and according to workshop layout parameters of the SMT intelligent manufacturing workshop and information and personnel allocation information of various intelligent devices, setting up a real-to-virtual ratio as 1:1, completely visualizing the whole production field;
step 2, defining N products in the production workshop as follows: the product is identified by P, the product variety is denoted by i, i =1,2,3,4.. N, pi represents the ith product;
step 3, arranging and summarizing real-time production and processing information of the N products in the MES, wherein the real-time production and processing information comprises data which are closely related to the line changing time, the production takt of each procedure, the production process route, the production quality and the production and processing of the products, and a production and processing information flow of each product is formed;
step 4, arranging and summarizing the production plan information of the N products in the MES system, wherein the production plan information comprises production plan issuing date, estimated start time, estimated completion time, actual start time, actual completion time and actual completion time
Data closely related to the production plan form a production plan information flow of each variety of products;
step 5, arranging and summarizing production logistics information of the N products in the MES, wherein the production logistics information comprises a material preparation flow, a production line changing flow, a production processing flow, a production turnover flow, a production warehousing flow, and data closely related to a production process, a production packaging and delivery flow and a production process, so as to form production logistics of each variety;
step 6, under the framework of the simulation model built in the step 1, on the basis of the big data sorted in the steps 2,3,4 and 5, respectively docking the production and processing information flow, the production plan information flow and the production logistics data of the MES system into a database of industrial simulation software, starting a simulation operation mode, and simulating the operation condition of the SMT intelligent manufacturing workshop; the production information flow of the MES system can be in online or offline connection with the data of the industrial simulation software through programming interface software or abstract implementation, but is not limited to the mode;
step 7, comparing the simulation operation condition of the step 6 with an actual operation condition, wherein the input comprises production processing information, production plan information and production logistics information content, the output comparison content comprises order completion period, production quantity, equipment utilization rate, quantity of products being manufactured and personnel working efficiency content, and the timeliness and the accuracy of model frame construction and operation logic are confirmed;
step 8, designing and building a Digital value flow diagram Digital-VSM template library through Flexsim on the basis of the step 7, wherein the template library comprises all production and processing processes of SMT intelligent manufacturing workshop products and can display production and processing information flow, production plan information flow and production logistics parameter indexes of the products;
the specific operation steps for building the Digital-VSM template library are as follows:
(1) Flexibly adopting a plurality of Discrete Objects to build a universal symbol and icon library of the Digital-VSM in a Flexsim software window, and displaying the production processing information flow, the production plan information flow and the production logistics of the Digital-VSM in a three-dimensional way through the interaction function of the Discrete Objects and an external three-dimensional figure;
(2) Constructing the whole logic of the Digital-VSM through a FlexScript writing code or a ProcessFlow module, establishing a flowing relation between the symbols and the icons of the Digital-VSM in the step 8, and realizing that the Digital-VSM is a certain product P; when the product starts to run in the simulation model, the simulation system automatically identifies and calls a code program of the Pi product, so that Digital-VSM boards corresponding to the Pi product are displayed, and N products corresponding to N kinds of Digital-VSMs reflecting field real conditions are realized;
(3) In a code writing window built in Slide of Using Visual objects Module in a Flexsim software window, three elements of main indexes for measuring the lean degree of production management are as follows: the value-added ratio VA, the production period TPc/t, WIP of the work-in-process inventory are written in logic codes, and a one-to-one corresponding relation is established;
wherein:
increment ratio VA: when Pi product is processed and produced, the time of the value-added part of the product accounts for the whole production time, VA = actual processing time/whole production time 100%;
production cycle TPc/t: total Product Cycle Time-TPc/t, which is an index for measuring intelligent production smoothness, refers to the longest Time path (critical path) from receiving raw materials to Product shipment;
simulating and calculating in simulation software by Using field big data which is butt-jointed and collected from MES to obtain three element data of VA, TPc/t and WIP under real-time and real conditions, and visually presenting lean indexes in Slide windows of Using Visual objects Module in a billboard mode;
FIG. 3 is a logic diagram of the production and processing flow of different products in the SMT intelligent manufacturing workshop, and the built Digital-VSM template library contains all the production and processing information of the workshop: surface pasting, plug-in mounting, inspection, single board assembly, single board debugging, whole machine assembly, whole machine initial inspection, whole machine debugging, comprehensive inspection, packaging and delivery;
in step 9, N products correspond to N production processes (even if the i-th product Pi and the j-th product Pj are produced in the same process, the products do not need to be combined), as shown in the table:
n, pi represents the ith product;
the problem points existing in the production process can be quickly identified according to a Digital-VSM template library: the method comprises the steps of judging whether a production plan is accurate or not, judging whether a production processing flow is reasonable or not, judging whether processing beats of different procedures are abnormal or not, judging whether a production process parameter has large deviation or not and judging whether a device is smooth or not. Finding an improvement direction according to the problem point, then flexibly performing optimized production scheduling sequence, procedure adjustment, process optimization, equipment movement and personnel allocation lean management activities in the built three-dimensional production scene to obtain the best optimized future Digital-VSM, and quickly applying the best optimized future Digital-VSM to actual production, thereby effectively improving the production efficiency;
and step 10, setting alarm thresholds of VA, TPc/t and WIP lean indexes in a Slide window of the Using Visual objects Module, and sending alarm information to remind a manager to carry out lean improvement activities and implement if the alarm thresholds are reached in real-time production, so that the production improvement process is monitored through Digital-VSM in real time, the optimization cycle is continued, and the ideal state of lean production is maintained.
Before the intelligent manufacturing Digital workshop is put into production, the method can also utilize the industrial simulation software to realize lean production of the analysis of the Digital value flow graph, and on the basis of sorting and summarizing the big data of the MES system, the ExpertFit function of the industrial simulation software is utilized to fit the production processing information flow, the production plan information flow and the production logistics data of the product, then the Digital-VSM is obtained, the best future Digital-VSM is obtained through analysis and improvement, and the cost before and after the production is reduced to a great extent. Through the lean production indexes, the effects before and after the implementation of different lean schemes in the same unit can be longitudinally simulated and compared to determine the optimal scheme. And production management lean levels of different units in the same industry can be transversely compared through big data, and the big data are used for mutual learning and reference.
The above embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All modifications made in accordance with the spirit of the main technical scheme of the invention should be covered within the scope of the invention.
Claims (4)
1. A lean production method based on industrial simulation software digital analysis is characterized by comprising the following steps:
step 1, installing industrial simulation software on a discrete intelligent production workshop control platform, and according to workshop layout parameters of a production workshop and information and personnel allocation information of various intelligent devices, setting up a real-virtual ratio as 1:1, completely visualizing the whole production field;
step 2, defining N products in the production workshop as follows: the product is marked by P, i represents the product variety, i =1,2,3,4.. N, pi represents the ith product;
step 3, arranging and summarizing real-time production and processing information of the N products in the MES, wherein the real-time production and processing information comprises data which are closely related to the line changing time, the production takt of each procedure, the production process route, the production quality and the production and processing of the products, and a production and processing information flow of each product is formed;
step 4, arranging and summarizing production plan information of the N products in the MES, wherein the production plan information comprises production plan issuing date, estimated work starting time, estimated completion time and actual work starting time, and the actual completion time and the production plan are closely related to data to form production plan information flow of each product;
step 5, arranging and summarizing production logistics information of the N products in the MES, wherein the production logistics information comprises a material preparation flow, a production line changing flow, a production processing flow, a production turnover flow, a production warehousing flow, and data closely related to a production process, a production packaging and delivery flow and a production process, so as to form production logistics of each variety;
step 6, under the framework of the simulation model established in the step 1, respectively docking production and processing information flow, production plan information flow and production logistics data in the MES system into a database of industrial simulation software on the basis of the step 2, the step 3, the step 4 and the step 5, starting a simulation operation mode, and simulating the operation condition of the production workshop;
step 7, comparing the simulation operation condition of the step 6 with the actual operation condition, and confirming the timeliness and the accuracy of the model frame construction and the operation logic;
step 8, on the basis of the step 7, a Digital VSM template library is designed and established through industrial simulation software, the template library can display production and processing information flow, production plan information flow, production logistics and lean production parameter indexes of the product in real time according to different product varieties, and the lean production parameter indexes comprise value-added ratio, production period and product in process inventory, wherein:
the value-added ratio VA is the ratio of the time used by the value-added part in the whole production time when the product is processed and produced, VA = the actual processing time/the whole production time,
the production period TPc/t, total Product Cycle Time-TPc/t, is an index for measuring intelligent production fluency, and refers to the longest Time path (critical path) from receiving raw materials to delivering products,
WIP in work-in-process inventory: in the production process, the total number of parts of the semi-finished product before each procedure is reduced;
step 9, rapidly identifying problem points existing in the production process according to a Digital-VSM template library, finding an improvement direction, then flexibly performing optimized production scheduling sequence, procedure adjustment, process optimization, equipment movement and personnel allocation lean management activities in the built three-dimensional production scene to obtain the best optimized future Digital-VSM, applying the best optimized future Digital-VSM to actual production and effectively improving the production efficiency in real time;
step 10, setting alarm thresholds of VA, TPc/t and WIP lean indexes in a Slide window of Using Visual objects Module; if the alarm threshold value is reached in the real-time production, alarm information is sent out to remind a manager to timely make a lean improvement activity and implement the activity.
2. The lean production method based on the digital analysis of the industrial simulation software as claimed in claim 1, wherein the operation status in step 7 refers to the operation time of the product, the production flow of the product, the processing time of the product in different processes, and the real-time status of the operation status of different equipments; and (4) inputting the contents including production and processing information, production plan information and production logistics information, outputting and comparing the contents including order completion period, production quantity, equipment utilization rate, quantity of products being processed and personnel working efficiency, and if the simulation result and the actual result deviate, feeding back to personnel for programming an interface program in the step 6 to modify and perfect verification in time so as to ensure the consistency of the built three-dimensional model and the actual workshop operation scene.
3. A lean production method based on the Digital analysis of the industrial simulation software according to claim 2, wherein the specific operation steps of building the Digital-VSM template library in the step 8 are as follows:
(1) The industrial simulation software takes Flexsim as an example, adopts a plurality of Discrete Objects to build universal symbols and icons of the Digital-VSM, and displays the production processing information flow, the production plan information flow and the production logistics of the Digital-VSM in a three-dimensional way through the interaction function of the Discrete Objects and an external three-dimensional figure;
(2) The method comprises the steps that the whole logic of the Digital-VSM is built through a FlexScript code or a ProcessFlow module, the flowing logic relation is built between the symbols and the icons of the Digital-VSM, when Pi product information is input into a three-dimensional simulation model and production operation is started, a simulation system automatically identifies and calls a code program of a Pi product, so that a Digital-VSM board corresponding to the Pi product is highlighted, and N types of products corresponding to N types of Digital-VSMs reflecting the actual conditions on site are realized;
(3) In a Digital value flow graph Digital-VSM, writing three elements of value-added ratio, production period and product inventory into a logic code in a code writing window built in Slide of Using Visual objects Module in industrial simulation software (taking Flexsim as an example), and establishing a one-to-one corresponding relation;
(4) By utilizing field big data which is butt-jointed and collected from MES, the three-element data of VA, TPc/t and WIP under real-time and real conditions are simulated and calculated in simulation software, and the three-element data are visually and three-dimensionally presented in a Slide window of Using Visual objects Module in a form of a billboard.
4. The lean production method based on the industrial simulation software Digital analysis of claim 1, characterized in that before the production of the intelligent manufacturing Digital workshop, the lean production method based on the industrial simulation software Digital analysis is used to fit the production processing information flow, the production plan information flow and the production logistics data of the product by using the expert Fit function of the industrial simulation software on the basis of sorting and summarizing the big data of the MES system, and then Digital-VSM is obtained to analyze and improve the best future Digital-VSM, thereby reducing the cost before and after the production.
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| 卢阳光: "面向智能制造的数字孪生工厂构建方法与应用", 《中国博士学位论文全文数据库》 * |
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