CN111177937A - Rapid response-oriented race production system model construction method - Google Patents

Rapid response-oriented race production system model construction method Download PDF

Info

Publication number
CN111177937A
CN111177937A CN202010004511.6A CN202010004511A CN111177937A CN 111177937 A CN111177937 A CN 111177937A CN 202010004511 A CN202010004511 A CN 202010004511A CN 111177937 A CN111177937 A CN 111177937A
Authority
CN
China
Prior art keywords
worker
race
production
order
unit
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010004511.6A
Other languages
Chinese (zh)
Other versions
CN111177937B (en
Inventor
湛荣鑫
李冬妮
李俊杰
靳洪博
郑宏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Institute of Technology BIT
Original Assignee
Beijing Institute of Technology BIT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Institute of Technology BIT filed Critical Beijing Institute of Technology BIT
Priority to CN202010004511.6A priority Critical patent/CN111177937B/en
Publication of CN111177937A publication Critical patent/CN111177937A/en
Application granted granted Critical
Publication of CN111177937B publication Critical patent/CN111177937B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06316—Sequencing of tasks or work
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Marketing (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Primary Health Care (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention relates to a rapid response oriented race production system model construction method, and belongs to the technical field of advanced manufacturing production system construction. A set of symbolic description game such as a production system construction model is defined, and the method specifically comprises the following steps: establishing a race construction stage model, completing the distribution between workers and processes, and constructing a race unit; and secondly, establishing a race scheduling stage model to complete scheduling among race units. The method solves the problems of production task distribution and matching production among workers caused by worker difference under the actual condition, the constructed match production system has reconfigurability and good response capability, can stably and efficiently cope with the fluctuation market with the characteristics of multiple varieties, small batch and variable batch, and enables the utilization rate of the workers to be kept at a high level.

Description

Rapid response-oriented race production system model construction method
Technical Field
The invention relates to a method for constructing a production system model, in particular to a method for constructing a quick response oriented race production system model, and belongs to the technical field of construction of advanced manufacturing production systems.
Background
According to research and statistics, the cost of the current manufacturing industry in China reaches more than 90% of that of the United states, wherein the bead triangle and the long triangle are higher than 95% of that of the United states, and the competitiveness of the traditional labor-intensive manufacturing industry gradually disappears; on the other hand, a new technological revolution and industrial revolution also cause a huge change of production modes, and with the vigorous development of the electronic information industry and the wide application of product modularization technology, the life cycle of the product is remarkably shortened. For example, in the relatively traditional automotive industry, the life cycle of a product is about 4-6 years, whereas the average life cycle of today's electronic products is only 6 months. Therefore, in the face of higher manufacturing cost, more product variety requirements, stronger personalized requirements, shorter product life cycle, and the fluctuation and uncertainty of market demand caused by the above characteristics, the manufacturing enterprise and the production system thereof must have strong rapid response capability to survive and develop in the new environment.
In a stable market environment with a long product life cycle, the main problem to be considered is how to reduce the cost and meet the requirements on varieties and yield, and the implementation of such modes as flow lines, Toyota production systems, job shops and unit manufacturing systems achieves the purposes. When the market environment is unstable, the manufacturing enterprises are required to have more powerful rapid response capability, which is difficult to satisfy by improving the supply chain on the existing mature production system. In order to cope with such a market environment change, a new production system, such as a production system, is gradually coming out and widely used. A race, such as a production system, includes a plurality of races, such as units, each of which is a small, autonomous, worker-centric assembly unit that includes several, or even one, workers and inexpensive equipment and tools. By using a race such as a production system, large companies such as Canon, Sony receive higher gains than before in such indices as cost reduction, production time reduction, and production preparation cycle reduction. The production system is suitable for assembly production of products with various, small-batch and variable-batch requirements in a fluctuating market environment, such as assembly of electronic products and precise instruments.
In such a context, race as production system construction issues arise. The current method for constructing a race production system is mainly divided into two stages, namely, the race construction and the race loading. These two phases have been separately proven for NP-hard problems. The competition construction mostly assumes that the number of competition units in the competition production system is fixed, and mainly considers how workers are distributed to the competition units; the game, like loading, decides how to distribute the product batches to the built game units. There is a common important assumption for such games as production system construction: once the game is complete as the unit is built, no further changes occur. While such a fixed model is difficult to cope with the dynamic changes of the market, for example, a production system should have the capability of dynamically adjusting its structure according to the changes of the market demands. For example, Liu et al studied the training and distribution problem of multiple potential workers in a race such as a production system, and established a multi-objective problem model that minimizes the total training costs and balances the labor time between multiple potential workers. Liu et al consider a race such as a production system construction model that optimizes economic and environmental indicators. Lian et al propose a model of a race such as a production system construction that takes into account the allocation of multipotential labor balance within and between the races.
In addition, most of the existing racing production system construction methods assume that workers are all capable, and in practical situations, it is difficult for the workers to be fully trained to be capable of working, so that the racing production system construction needs to be carried out under the condition that the workers have different skill ranges and production rates.
In order to cope with the unstable and fluctuating market environment, considering the situation that workers are not all full-functional and have different skill ranges and production rates, a rapid response oriented race production system model construction method needs to be provided.
Disclosure of Invention
The invention aims to provide a rapid response oriented match-making production system model construction method aiming at a fluctuating market environment, considering the condition that workers are not all capable of working and have different skill ranges and production rates, and the technical defect that a match-making production system cannot dynamically adjust the self structure along with the change of orders so as not to form rapid response, wherein the constructed match-making production system comprises one or more match-making units and has the capability of dynamically adjusting the self structure, the adjusted objects comprise the number of the match-making units, workers distributed to the match-making units and processes responsible for each worker, and the match-making production system has the following characteristics: (1) building an appropriate number of contests such as units; (2) assigning the constructed race units to respective production tasks; (3) each race unit is immediately disassembled as it completes its production task.
The race production system constructed according to the method meets the following conditions:
(1) the total number of workers in the production system is determined, all workers are multipotent and have differences in skill range and processing rate, and all workers have the same initial remaining working time in the same production cycle;
(2) only one product type is contained in one order, order information can be known only when the order comes, and the arrival time of each order is uncertain;
the information of the order comprises the product type and the demand;
(3) a race unit only produces one product type, one product type allowing production by multiple races such as units in a production system;
(4) a worker is allowed to be assigned to a plurality of contest units;
(5) each well-constructed race unit is non-interrupted and non-preemptive;
(6) special situations such as shortage of production materials and failure are not considered;
including a race, such as a construction phase and a race, such as a scheduling phase;
wherein, race as the construction stage, has following characteristic:
all workers have the same initial remaining work time in the same production cycle, the workers have different skill ranges and different production rates on different processes, and different workers also have different production rates on the same process;
the quick response-oriented race production system construction method comprises the following definitions:
the indices are defined as follows:
w worker index (W1., W)
I process index (I ═ 1., I)
C product type index (C1.., C)
D order index (D1., D)
S match as a unit index (S ═ 1.., S)
P may be used to construct a site index for a race unit (P1.., P)
Variables are defined as follows:
Figure BDA0002354736130000041
when order d arrives, the remaining working time of worker w
Figure BDA0002354736130000042
Unit processing time for worker w to process step i
Figure BDA0002354736130000043
Set of processes that worker w can process
Figure BDA0002354736130000051
Upper limit of types of processes involved by worker w when participating in production order d
Figure BDA0002354736130000052
If worker w1And w2Certain two adjacent processes i for processing the same order d1And i2，
Figure BDA0002354736130000053
Is the absolute value of the difference between the unit processing time of the two workers in the two procedures;
if a worker processes a plurality of adjacent processes, the time of the worker on the processes is accumulated and is equal to the unit time of the same process and is used for the variable calculation;
Figure BDA0002354736130000054
indicates worker w1And w2Certain two adjacent processes i for processing the same order d1And i2In the adjacent step i1And i2There is a balance between, no wait or idle time is generated;
tdthe arrival time of order d;
nddemand for order d;
Figure BDA0002354736130000055
a set of required processes for producing order d;
Figure BDA0002354736130000056
when order d arrives, the set of workers who are currently free to participate in processing
Figure BDA0002354736130000057
Complete order d set of game units
ptsPresence time of game unit s from construction to disassembly
ctsTime when unit s completes production task disassembly
Figure BDA0002354736130000058
The worker w produces the order d to participate in the number of processing tasks in the process i,
Figure BDA0002354736130000059
Figure BDA00023547361300000510
worker w1And w2Number of products co-processed for production order d, and worker w1Participating in process i1Production task, worker w2Participating in process i2Production task, process i1And process i2Is a neighboring process
Figure BDA00023547361300000511
The build time of a contest such as unit s in place p;
the method for constructing the race production system model comprises the following steps:
step 1) waiting for a new order when the new order does not arrive; when a new order comes, entering a competition of the step 2) as a construction stage;
step 2) in the race building stage, firstly, based on a worker-process mapping model, carrying out worker-process distribution, and based on a worker-race distribution model for optimizing the balance of the working time of workers in the race unit, completing model description of the construction of the race unit, and then constructing the race unit;
the step 2) specifically comprises the following substeps:
step 2.1) under the constraint that the working time upper limit of each worker is not exceeded, designing a feasible worker-process mapping model, and performing worker-process distribution according to the model;
wherein the worker-process assignment is a constraint satisfaction problem model embodied as (1), (2), and (3);
the step 2.1) is specifically as follows: searching a dispensing scheme
Figure BDA0002354736130000061
And assigning worker-processes based on the assignment scheme;
Figure BDA0002354736130000062
Figure BDA0002354736130000063
Figure BDA0002354736130000064
wherein, formula (1) indicates that for any order d, any procedure i of the order d needs to be distributed to a worker w capable of processing the procedure; equation (2) ensures that the amount of work assigned to any worker does not exceed the worker's initial remaining work time; the expression (3) indicates that the process type of any worker w participating in the production of any order d cannot exceed the limit
Figure BDA0002354736130000065
Step 2.2) establishing a worker-race allocation model for optimizing the work time balance of workers in the race unit, and completing the model description of the construction of the race unit;
definition EdThe basic definition of a graph containing all possible processing paths for processing a certain product type, combined with a cost flow graph, is EdSetting a virtual starting point before the first procedure and setting a virtual finishing point after the last procedure;
the model for completing the construction of the game unit is described as follows:
for any order d:
Figure BDA0002354736130000071
the following constraints need to be satisfied:
Figure BDA0002354736130000072
Figure BDA0002354736130000073
Figure BDA0002354736130000074
Figure BDA0002354736130000075
Figure BDA0002354736130000076
wherein, the formula (4) is an objective function of the race building stage, and represents an absolute value of the difference of unit processing time between all two adjacent processes of the order d by selecting different workers to build the race unit; equations (5) and (6) indicate that the production capacity of the race constructed for order d should be consistent with the demand of order d; the formulas (7) and (8) represent the worker w1And w2Co-production order d and worker w1Participating in process i1Production task, worker w2Participating in process i2Production task, process i1And process i2Are adjacent processes, in which case their collective production task size cannot exceed the production task size decided upon during the build phase
Figure BDA0002354736130000077
And
Figure BDA0002354736130000078
the formula (9) indicates that the yield must be 0 or more;
step 2.3) constructing a game unit, which specifically comprises the following substeps:
step 2.3A) initializes the worker-process mapping list on each process, puts all workers that can process the process into the corresponding list, sets the product throughput to 0,
Figure BDA0002354736130000079
set to 0;
step 2.3B) worker sequencing: for each procedure, sorting the list according to the non-decreasing sequence of the unit processing time;
step 2.3C), sequentially checking each process, and returning False if the worker-process mapping list is empty; otherwise, the process task is distributed to the first worker in the worker-process mapping list, and the residual processing time of the worker is deducted, the value is the unit processing time of the worker on the process, and the corresponding value is the unit processing time of the worker on the process
Figure BDA0002354736130000081
Increasing by 1;
step 2.3D), after the last process is detected, the product production is increased by 1, and if the product production is less than the product demand of the order, the step 2.3C) is returned; otherwise, recording and outputting
Figure BDA0002354736130000082
Step 2.3E) utilizing a network simplex method to calculate worker-match unit allocation, record and output
Figure BDA0002354736130000083
Step 3) race as a scheduling stage, specifically comprising the following substeps:
step 3.1) establishing a model description of the race scheduling stage, specifically:
considering the situation that one worker may be allocated to participate in the production tasks of a plurality of game units in the game building stage, and any worker can only participate in one game unit at the same time, the scheduling among the game units is completed:
the model of the race scheduling phase is described as follows:
minmax1≤s≤Scts(10)
the constraints (11), (12) and (13) need to be satisfied:
Figure BDA0002354736130000084
Figure BDA0002354736130000085
Figure BDA0002354736130000086
wherein, the formula (10) is an objective function of the race scheduling stage, and represents that the maximum completion time of the race unit in the race production system is minimized; equation (11) calculates the earliest time any contest unit s completes its production task; equation (12) ensures that two different contest units that require the same worker to participate in production cannot exist at the same time; equation (13) ensures that only one race unit can exist on a field at any one time;
step 3.2) scheduling the race units based on the model description of step 3.1);
step 3.2A) initialization: putting all the match units to be scheduled into an unscheduled list, setting the scheduled list to be empty, and setting the time to be 0;
step 3.2B) when the non-scheduling list is not empty, according to ptsSequencing the match units in the non-scheduling list by a non-increasing principle; otherwise, jumping to step 3.2F);
step 3.2C), if n idle sites exist, moving the first n-bit competition units in the unscheduled list from the unscheduled list to the scheduled list;
step 3.2D) detecting n match units newly put into the scheduled list, and if the match units in any other scheduled list have worker occupation, moving the match units to the unscheduled list again; after the detection and operation of n race units are completed, increasing the time by 1;
step 3.2E), if a new match unit needs to be scheduled, adding the new match unit to the unscheduled list, detecting and removing all match units completing the processing tasks in the scheduled list, and returning to the step 3.2B);
and 3.2F) stopping, and outputting the result.
Advantageous effects
Compared with the existing production system construction method, the race production system construction method facing the quick response has the following beneficial effects:
1. the method considers the problem of constructing a race production system facing rapid response aiming at a fluctuating market environment, considers the condition that workers are not all full-purpose and have different skill ranges and production rates, and solves the problems of production task allocation and matched production among the workers caused by the difference of the workers under the actual condition;
2. the method considers the characteristics of multiple varieties, small batch and variable batch of the fluctuation market and the subsequent problems of low efficiency of workers, slow conversion of varieties of produced products and the like, has stable and efficient performance, keeps the utilization rate of the workers at a higher level all the time in the fluctuation market environment, and can realize rapid adjustment of the varieties of the products;
3. the method endows the race production system with reconfigurability, so that the race production system shows good response capability.
Drawings
FIG. 1 is a flow chart of a method of constructing a rapid response oriented race production system of the present invention;
FIG. 2 is a schematic diagram of an exemplary order 1 potential processing path E in a method for constructing a rapid response oriented race production system according to the present invention1。
Detailed Description
The following describes a preferred embodiment of a method for constructing a quick response-oriented race production system according to the present invention with reference to the accompanying drawings and examples.
Example 1
The embodiment of the invention realizes the method for constructing a quick response-oriented race production system, which is specifically realized according to the execution steps in the inventive content, as shown in fig. 1.
Meanwhile, experiments are carried out on the method provided by the invention, and the experimental result shows that by using the method provided by the invention, the constructed race production system has good quick response capability and capability of dynamically adjusting the body structure of the race in the face of fluctuating market environment, and the utilization rate of workers is kept at a higher level.
Here, illustrating the processing path of the processed product, as shown in FIG. 2, order 1 requires 2 processes, which are process 1 and process 1, respectively2, worker 1 and worker 2 can process procedure 1, and worker 3 and worker 4 can process procedure 2, all the dotted lines representing the processing paths, all the worker nodes, the starting point and the ending point together constitute E1；
The following simulation experiments were performed for this example:
the experimental parameter settings are shown in table 1. A total of 5 (product type grade) × 5(mu) × 5(cf) ═ 125 sets of different parameter combinations were generated, and according to the central limit theorem, 30 cases were generated for each parameter combination, so a total of 3750 cases were tested.
The environment of the simulation experiment is as follows:
(1) operating the system: microsoft Windows 764 bit
(2)CPU：3.10GHz Core i5-2400
(3) Memory: 4GB
(4) And (3) developing environment: pycharm
(5) And (3) developing a language: python
TABLE 1 parameter table
Figure BDA0002354736130000111
Figure BDA0002354736130000121
A total of 3 different experimental results were shown and analyzed, respectively: 1) in a fluctuating market environment, the effects of different product type parameter settings on the number of units, the worker utilization rate, and the order completion time in the SPS, for example, are shown in table 2; 2) under fluctuating market conditions, different product demand settings have an impact on the number of units, e.g., in an SPS, and the utilization of workers, with the results shown in table 3; 3) in a fluctuating market environment, different market fluctuation factor settings have an effect on worker utilization, with the results shown in table 4.
TABLE 2 influence of product type level
Figure BDA0002354736130000122
Figure BDA0002354736130000131
TABLE 3 Effect of product demand
Product demand 10 20 30 40 50
Number of race units 10.2 11.2 14.3 14.0 14.5
Worker utilization rate 76.4％ 78.0％ 80.0％ 75.9％ 81.2％
TABLE 4 influence of market volatility coefficient
Product demand 0.1 0.3 0.5 0.7 0.9
Worker utilization rate 79.1％ 82.3％ 82.6％ 80.0％ 79.2％
From the above results, it appears that: (1) the utilization rate of workers of the constructed race production system is always kept at a higher level along with the change of the product type level, the demand and the fluctuation coefficient; (2) the change of the number of game units shows that the constructed game production system can deal with different market environments by constructing and disassembling game units with different numbers and structures so as to dynamically adjust the overall structure of the system in order to efficiently complete production tasks (such as maintaining higher utilization rate of workers); (3) as the grade of the product types is increased, that is, the products become more diversified, the completion time of the race production system is rather decreased, showing the excellent parallel processing capability of the race production system.
The above three observation results jointly verify the aforementioned three beneficial effects of the present invention.
It should be understood that the present embodiments are only specific examples for implementing the invention, and should not be used for limiting the protection scope of the invention. It is intended that all equivalent modifications and variations of the above-described aspects be included within the scope of the present invention as claimed, without departing from the spirit and scope of the invention.

Claims (6)

1. A quick response-oriented race production system model construction method is characterized by comprising the following steps: including the following definitions:
the indices are defined as follows:
w worker index (W1., W)
I process index (I ═ 1., I)
C product type index (C1.., C)
D order index (D1., D)
S match as a unit index (S ═ 1.., S)
P may be used to construct a site index for a race unit (P1.., P)
Variables are defined as follows:
Figure FDA0002354736120000011
when order d arrives, the remaining working time of worker w
Figure FDA0002354736120000012
Unit processing time for worker w to process step i
Figure FDA0002354736120000013
Set of processes that worker w can process
Figure FDA0002354736120000014
Upper limit of types of processes involved by worker w when participating in production order d
Figure FDA0002354736120000015
If worker w1And w2Certain two adjacent processes i for processing the same order d1And i2，
Figure FDA0002354736120000016
Is the absolute value of the difference between the unit processing time of the two workers in the two procedures;
if a worker processes a plurality of adjacent processes, the time of the worker on the processes is accumulated and is equal to the unit time of the same process and is used for the variable calculation;
Figure FDA0002354736120000017
indicates worker w1And w2Certain two adjacent processes i for processing the same order d1And i2In the adjacent step i1And i2There is a balance between, no wait or idle time is generated;
tdthe arrival time of order d;
nddemand for order d;
Figure FDA0002354736120000021
a set of required processes for producing order d;
Figure FDA0002354736120000022
when order d arrives, the set of workers who are currently free to participate in processing
Figure FDA0002354736120000023
Complete order d set of game units
ptsPresence time of game unit s from construction to disassembly
ctsTime when unit s completes production task disassembly
Figure FDA0002354736120000024
The worker w produces the order d to participate in the number of processing tasks in the process i,
Figure FDA0002354736120000025
Figure FDA0002354736120000026
worker w1And w2Number of products co-processed for production order d, and worker w1Participating in process i1Production task, worker w2Participating in process i2Production task, process i1And process i2Is a neighboring process;
Figure FDA0002354736120000027
the build time of a contest such as unit s in place p;
the method for constructing the race production system model comprises the following steps:
step 1) waiting for a new order when the new order does not arrive; when a new order comes, entering a competition of the step 2) as a construction stage;
step 2) in the race building stage, firstly, based on a worker-process mapping model, carrying out worker-process distribution, and based on a worker-race distribution model for optimizing the balance of the working time of workers in the race unit, completing model description of the construction of the race unit, and then constructing the race unit;
the step 2) specifically comprises the following substeps:
step 2.1) under the constraint that the working time upper limit of each worker is not exceeded, designing a feasible worker-process mapping model, and performing worker-process distribution according to the model;
wherein the worker-process assignment is a constraint satisfaction problem model embodied as (1), (2), and (3);
the step 2.1) is specifically as follows: searching a dispensing scheme
Figure FDA0002354736120000028
And assigning worker-processes based on the assignment scheme;
Figure FDA0002354736120000031
Figure FDA0002354736120000032
Figure FDA0002354736120000033
wherein, formula (1) indicates that for any order d, any procedure i of the order d needs to be distributed to a worker w capable of processing the procedure; equation (2) ensures that the amount of work assigned to any worker does not exceed the worker's initial remaining work time; the expression (3) indicates that the process type of any worker w participating in the production of any order d cannot exceed the limit
Figure FDA0002354736120000034
Step 2.2) establishing a worker-race allocation model for optimizing the work time balance of workers in the race unit, and completing the model description of the construction of the race unit;
definition EdThe basic definition of a graph containing all possible processing paths for processing a certain product type, combined with a cost flow graph, is EdSetting a virtual starting point before the first procedure and setting a virtual finishing point after the last procedure;
the model for completing the construction of the game unit is described as follows:
for any order d:
Figure FDA0002354736120000035
the following constraints need to be satisfied:
Figure FDA0002354736120000036
Figure FDA0002354736120000037
Figure FDA0002354736120000038
Figure FDA0002354736120000039
Figure FDA00023547361200000310
wherein, the formula (4) is an objective function of the race building stage, and represents an absolute value of the difference of unit processing time between all two adjacent processes of the order d by selecting different workers to build the race unit; equations (5) and (6) indicate that the production capacity of the race constructed for order d should be consistent with the demand of order d; the formulas (7) and (8) represent the worker w1And w2Co-production order d and worker w1Participating in process i1Production task, worker w2Participating in process i2Production task, process i1And process i2Are adjacent processes, in which case their collective production task size cannot exceed the production task size decided upon during the build phase
Figure FDA0002354736120000041
And
Figure FDA0002354736120000042
the formula (9) indicates that the yield must be 0 or more;
step 2.3) constructing a game unit, which specifically comprises the following substeps:
step 2.3A) initializing a worker-process mapping list on each process, and putting all workers capable of processing the process into a corresponding listThe amount of product production was set to 0,
Figure FDA0002354736120000043
set to 0;
step 2.3B) worker sequencing: for each procedure, sorting the list according to the non-decreasing sequence of the unit processing time;
step 2.3C), sequentially checking each process, and returning False if the worker-process mapping list is empty; otherwise, the process task is distributed to the first worker in the worker-process mapping list, and the residual processing time of the worker is deducted, the value is the unit processing time of the worker on the process, and the corresponding value is the unit processing time of the worker on the process
Figure FDA0002354736120000044
Increasing by 1;
step 2.3D), after the last process is detected, the product production is increased by 1, and if the product production is less than the product demand of the order, the step 2.3C) is returned; otherwise, recording and outputting
Figure FDA0002354736120000045
Step 2.3E) utilizing a network simplex method to calculate worker-match unit allocation, record and output
Figure FDA0002354736120000046
Step 3) race as a scheduling stage, specifically comprising the following substeps:
step 3.1) establishing a model description of the race scheduling stage, specifically:
considering the situation that one worker may be allocated to participate in the production tasks of a plurality of game units in the game building stage, and any worker can only participate in one game unit at the same time, the scheduling among the game units is completed:
the model of the race scheduling phase is described as follows:
min max1≤s≤Scts(10)
the constraints (11), (12) and (13) need to be satisfied:
Figure FDA0002354736120000051
Figure FDA0002354736120000052
if s 'is constructed, s is not constructed, and s, s' has worker occupation
(12)
Figure FDA0002354736120000053
If s' is constructed, s is not constructed
(13)
Wherein, the formula (10) is an objective function of the race scheduling stage, and represents that the maximum completion time of the race unit in the race production system is minimized; equation (11) calculates the earliest time any contest unit s completes its production task; equation (12) ensures that two different contest units that require the same worker to participate in production cannot exist at the same time; equation (13) ensures that only one race unit can exist on a field at any one time;
step 3.2) scheduling the race units based on the model description of step 3.1);
step 3.2A) initialization: putting all the match units to be scheduled into an unscheduled list, setting the scheduled list to be empty, and setting the time to be 0;
step 3.2B) when the non-scheduling list is not empty, according to ptsSequencing the match units in the non-scheduling list by a non-increasing principle; otherwise, jumping to step 3.2F);
step 3.2C), if n idle sites exist, moving the first n-bit competition units in the unscheduled list from the unscheduled list to the scheduled list;
step 3.2D) detecting n match units newly put into the scheduled list, and if the match units in any other scheduled list have worker occupation, moving the match units to the unscheduled list again; after the detection and operation of n race units are completed, increasing the time by 1;
step 3.2E), if a new match unit needs to be scheduled, adding the new match unit to the unscheduled list, detecting and removing all match units completing the processing tasks in the scheduled list, and returning to the step 3.2B);
and 3.2F) stopping, and outputting the result.
2. A rapid response oriented race production system model building method as claimed in claim 1, characterized in that: the constructed race production system comprises one or more race units and has the capability of dynamically adjusting the structure of the race units, and the adjusted objects comprise the number of race units, workers distributed to the race units and the working procedures responsible for each worker.
3. A rapid response oriented race production system model building method as claimed in claim 1, characterized in that: the constructed race production system has the following characteristics: (1) building an appropriate number of contests such as units; (2) assigning the constructed race units to respective production tasks; (3) each race unit is immediately disassembled as it completes its production task.
4. A rapid response oriented race production system model building method as claimed in claim 1, characterized in that: the constructed race production system meets the following conditions:
(1) the total number of workers in the production system is determined, all workers are multipotent and have differences in skill range and processing rate, and all workers have the same initial remaining working time in the same production cycle;
(2) only one product type is contained in one order, order information can be known only when the order comes, and the arrival time of each order is uncertain;
the information of the order comprises the product type and the demand;
(3) a race unit only produces one product type, one product type allowing production by multiple races such as units in a production system;
(4) a worker is allowed to be assigned to a plurality of contest units;
(5) each well-constructed race unit is non-interrupted and non-preemptive;
(6) the special situations of shortage of production materials and failure are not considered.
5. A rapid response oriented race production system model building method as claimed in claim 1, characterized in that: including a race such as a build phase and a race such as a schedule phase.
6. A rapid response oriented race production system model building method as claimed in claim 1, characterized in that: all workers have the same initial remaining work time in the same production cycle, the workers have different skill ranges and different production rates on different processes, and different workers also have different production rates on the same process.
CN202010004511.6A 2020-01-03 2020-01-03 Rapid response-oriented race production system model construction method Active CN111177937B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010004511.6A CN111177937B (en) 2020-01-03 2020-01-03 Rapid response-oriented race production system model construction method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010004511.6A CN111177937B (en) 2020-01-03 2020-01-03 Rapid response-oriented race production system model construction method

Publications (2)

Publication Number Publication Date
CN111177937A true CN111177937A (en) 2020-05-19
CN111177937B CN111177937B (en) 2021-11-12

Family

ID=70650787

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010004511.6A Active CN111177937B (en) 2020-01-03 2020-01-03 Rapid response-oriented race production system model construction method

Country Status (1)

Country Link
CN (1) CN111177937B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117436709A (en) * 2023-12-20 2024-01-23 四川宽窄智慧物流有限责任公司 Cross-region order data overall warning method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
JIE LIAN等: "A multi-skilled worker assignment problem in seru production systems", 《COMPUTERS & INDUSTRIAL ENGINEERING》 *
YANG YU等: "Seru system balancing: Definition, formulation, and exact solution", 《COMPUTERS & INDUSTRIAL ENGINEERING》 *
YONG YIN等: "The evolution of production systems from Industry 2.0 through Industry 4.0", 《INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH》 *
廉洁等: "Seru生产方式下考虑工人异质性的多能工分配模型及算法", 《运筹与管理》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117436709A (en) * 2023-12-20 2024-01-23 四川宽窄智慧物流有限责任公司 Cross-region order data overall warning method
CN117436709B (en) * 2023-12-20 2024-03-19 四川宽窄智慧物流有限责任公司 Cross-region order data overall warning method

Also Published As

Publication number Publication date
CN111177937B (en) 2021-11-12

Similar Documents

Publication Publication Date Title
CN110070248B (en) Dynamic intelligent scheduling method and device
CN110598941A (en) Bionic strategy-based dual-target scheduling method for particle swarm optimization manufacturing system
Lei et al. Memetic algorithm for solving flexible flow-shop scheduling problems with dynamic transport waiting times
CN102938102B (en) A kind of with batch processor across operation unit dispatching method
CN108171372B (en) Multi-variety production batch scheduling method with preparation time
TW202133097A (en) Method for semiconductor processing scheduling, system for semiconductor processing scheduling and non-temporary computer-readable storage medium
US20090234482A1 (en) System, program and method for calculating equipment load factor
CN114647515A (en) GPU cluster-oriented dynamic resource scheduling method
CN111177937B (en) Rapid response-oriented race production system model construction method
CN114169748A (en) Multi-robot task allocation method, system, device and readable storage medium
CN109865292A (en) A kind of game resource construction method and device based on game engine
CN108769105A (en) A kind of scheduling system of knowledge services multi-task scheduling optimization method and its structure under cloud environment
CN111798097A (en) Autonomous mobile robot task allocation processing method based on market mechanism
CN115017588A (en) Method, device, equipment and storage medium for generating sports building model
CN113848904A (en) Method for optimizing task allocation of multiple mobile robots based on punished energy consumption
CN103903070A (en) Resource demand measuring and calculating system for application system
CN113568385B (en) Production scheduling method based on multi-variety mixed flow assembly mode
CN108270833A (en) Render automatic scheduling method, the apparatus and system of cloud resource
CN110084498A (en) A kind of work dispatching method of server-side, device, computer equipment and storage medium
CN104572134B (en) A kind of optimization method and device
CN111445079B (en) Multi-fidelity simulation optimization method and equipment applied to workshop plan production
CN107122849A (en) Product checking total complete time minimization method based on SparkR
Kim Permutation-based elitist genetic algorithm using serial scheme for large-sized resource-constrained project scheduling
Zhong et al. Sequencing problem for a hull mixed-model assembly line considering manufacturing complexity
TWI826087B (en) Dispatching system and dispatching method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant