Optimization of production planning
By reading and analyzing production planning data, machine operation capability information and employee availability information, and using optimization modules to determine the optimized allocation between employees and machines, the inefficiency problem caused by the fixed production planning in the existing technology is solved, and dynamic production planning is realized Optimization improves the efficiency of production flow.
Patent Information
- Application Number
- CN202380048304.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2022-06-21
- Filing Date
- 2023-06-21
- Publication Date
- 2025-02-07
AI Technical Summary
In existing industrial production, production planning is usually performed prior or offline, resulting in fixed allocation of employees to machines or work areas, which is inefficient and difficult to adapt to dynamic changes in the production process.
Through a device and computer-implemented method, production planning data, machine operation capability information and employee availability information are read, and optimization modules are used to determine the percentage of optimization allocation between employees and machines, and based on this, the optimized production planning data, including production steps, is determined. time series.
Dynamic allocation of employees and production processes is achieved, efficiency of production flow is improved, complexity of production planning is reduced, and production planning data is allowed to be adaptively recalculated.
Smart Images
Figure CN119404205A_ABST
Abstract
Description
[0001] The invention relates to a device and a computer-implemented method for optimizing a production plan for producing at least one product, wherein employees are assigned to operate machines for producing the at least one product, and also to a computer program product.
[0002] In industrial production, personnel are usually assigned to different machines in advance, for example for operation or monitoring. In addition, it is determined which production steps are to be completed on the respective machines within a predetermined time period. This production planning is usually done a priori or offline. Here, employees are fixedly assigned to machines or work areas for an observation period. Usually, this planning and dispatching is inefficient, for example, it can deteriorate the production process.
[0003] The technical problem to be solved by the present invention is therefore to optimize the production planning for the production of one or more products.
[0004] This object is achieved by the measures specified in the independent claim. Advantageous developments of the invention are specified in the dependent claims.
[0005] According to a first aspect, the invention relates to a device for optimizing a production plan for producing at least one product, wherein employees are assigned to operate machines for producing the at least one product,
[0006] Wherein, the device comprises:
[0007] a) an interface, which is arranged to read out planning data for production as well as information on the capabilities of the machine operators and the availability of employees,
[0008] b) a first optimization module, which is configured to determine an optimized percentage distribution of employees to the respective machines for a predetermined time period based on the planning data, the capacity information and the availability information,
[0009] c) a second optimization module, which is configured to determine optimized production planning data, wherein an optimized time sequence for employees and machines corresponding to the production steps according to the planning data is determined based on the percentage distribution and the number of employees required for the production steps,
[0010] and
[0011] d) An output module, which is configured to output optimized production planning data so as to produce at least one product according to the optimized production planning data.
[0012] The device is particularly suitable for optimizing production planning for the production of a large number of products, wherein the product is composed of a plurality of components, for example. The production of a single component is carried out, for example, in predetermined production steps on different machines, which are respectively operated or monitored by a staff member.
[0013] The planning data for production can, for example, indicate the amount that can be produced within a predetermined time period based on the production capacity of existing or required machines. The planning data therefore preferably include a production capacity survey. The competence information of the employees in terms of machine operation, for example, relates to the education or professional qualifications of the employees related to machine operation. In particular, the competence information of the employees can include qualification profiles. The availability information of the employees includes information about shifts and individual working times. The availability information is preferably provided at the shift level.
[0014] In particular, planning data, capacity information and availability information can be read out as one data set or several data sets and made available for further production optimization.
[0015] The advantage of the invention is that employees are not fixedly assigned to workstations or machines, but rather a simultaneous assignment of employees and production processes is performed. To this end, production fine planning is optimized in two optimization steps. This leads to an improvement in production flow, also reduces complexity and allows adaptive recalculation of production planning data.
[0016] In an embodiment of the device, the first optimization module can determine the optimal allocation of employees to corresponding machines through a mixed integer optimization problem.
[0017] In particular, a MILP or MINLP optimization problem is proposed, the goal of which is to achieve maximum processing for a predetermined observation period. In particular, a simple comparison of the employee's qualification profile with the machine requirements can first be carried out.
[0018] In another embodiment of the device, the first optimization module may be configured to determine the optimal allocation of employees to the respective machines taking into account at least one of the following boundary conditions:
[0019] - Minimize employee job changes,
[0020] - the average load factor of employees,
[0021] and / or
[0022] - Comply with machine-specific standards, such as avoiding cold starts.
[0023] In another embodiment of the device, the second optimization module may be configured to determine the optimized production planning data while taking into account at least one of the following boundary conditions:
[0024] - adhere to the predetermined sequence of production steps,
[0025] - Consider the bill of materials and / or bill of process flow,
[0026] - adhere to completion dates,
[0027] - the intended production capacity of the machine,
[0028] and / or
[0029] - Minimize changeover time.
[0030] In another embodiment of the device, the second optimization module may be configured to redetermine the optimized production planning data according to the optimized percentage distribution when there is a time deviation between the production and the optimized production planning data.
[0031] Therefore, the second optimization problem can be re-solved and updated production planning data can be determined.
[0032] In another embodiment of the device, the first optimization module and / or the second optimization module may be configured to re-execute the corresponding optimization starting from the current production status.
[0033] This can be carried out in particular for production steps which are still undetermined.
[0034] In another embodiment, the device may further include a simulation module, wherein the simulation module is configured to perform a computer-aided logistics simulation of production according to the optimized production planning data and output simulation data.
[0035] In another embodiment of the device, the simulation module can be configured to take into account transport times between machines.
[0036] In another embodiment, the apparatus may include a verification module configured to verify the optimized production planning data based on the simulation data.
[0037] The optimization is therefore carried out separately from the logistics simulation. The simulation allows, for example, a check of the production planning data. The simulation also allows a refinement of the production planning data, since in particular the transport times can be taken into account.
[0038] In another embodiment, the device may further include a prediction module, which is configured to predict production-related data based on the simulation data.
[0039] For example, material or energy consumption can be calculated using simulations.
[0040] According to a second aspect, the invention relates to a computer-implemented method for optimizing a production plan for producing at least one product, wherein employees are assigned to operate machines for producing the at least one product,
[0041] The method steps include:
[0042] - read out planning data for production, capacity information on machine operation and employee availability,
[0043] - determining an optimized percentage allocation of employees to the respective machines for a predetermined time period based on planning data, capacity information and availability information,
[0044] - determining optimized production planning data, wherein an optimized time sequence for the employees and machines for the corresponding production steps according to the planning data is determined based on the percentage distribution and the number of employees required for the production steps,
[0045] and
[0046] - outputting the optimized production planning data so as to produce at least one product according to the optimized production planning data.
[0047] Furthermore, the invention relates to a computer program product directly loadable into a programmable computer, comprising program code portions for causing the computer to perform the steps of the method according to the invention when the program is executed by the computer.
[0048] The computer program product may, for example, be provided or delivered on a storage medium, such as a memory card, USB stick, CD-ROM, DVD, non-volatile / persistent storage medium or in the form of a file downloadable from a server in a network.
[0049] Embodiments of the present invention are shown by way of example in the drawings and are further explained in the following description.
[0050] Figure 1 : shows an embodiment of the apparatus for optimizing production planning according to the present invention; and
[0051] Figure 2 : An embodiment of the method for optimizing production planning according to the present invention is shown.
[0052] Corresponding parts are provided with the same reference symbols in all the figures.
[0053] In particular, the following exemplary embodiments merely illustrate how such implementation possibilities may be presented, in particular according to the teaching of the invention, since an enumeration of all such implementation possibilities is not possible and is not meaningful or necessary for an understanding of the invention.
[0054] Of course, a person skilled in the art who is aware of the (relevant) method claims in particular also knows all possibilities which are usually available in the prior art for implementing the invention, so that they do not need to be disclosed separately in the description in particular.
[0055] Figure 1A device 100 for optimizing production planning for producing at least one product is shown, wherein an employee W is assigned to operate a machine for producing the at least one product. The corresponding machine is, for example, configured to produce at least a portion of the product. For example, the product may consist of a plurality of product components that are produced, processed and / or assembled in separate production steps. Individual production steps may be performed on the corresponding machines. For example, a large number of products may be produced. For example, different machines are required for production, which are respectively operated by employees. One employee may also operate multiple machines. The device may provide an optimized production plan, which optimally allocates individual production steps and employees to machines to achieve efficient production.
[0056] The device 100 includes an interface 101, a first optimization module 102, a second optimization module 103 and an output module 104. The device 100 may also optionally include a simulation module 105, a verification module 106 and / or a prediction module 107. In addition, the device 100 may include at least one processor. The device 100 may include software and hardware components in particular; for example, a module of the device may be designed as a software component. For example, it may be an auxiliary system.
[0057] The interface 101 is configured to read planning data PD for production. The planning data PD indicates, for example, the number of products to be produced with a predetermined machine within a predetermined time period. The planning data can be imported from an online system (SAP, MES). Furthermore, capability information CI for machine operation and availability information AI for employees are read via the interface 101. Preferably, capability information and availability information are available for each employee. The planning data PD, capability information CI and availability information AI are sent to a first optimization module 102.
[0058] The first optimization module 102 is configured to determine an optimized percentage allocation PA of employees W to the corresponding machines for a predetermined time period based on the planning data PD, the capacity information CI and the availability information. This is preferably solved by a mixed integer optimization problem. The optimization module 102 preferably takes the following boundary conditions into account during the optimization:
[0059] - Minimize employee job changes,
[0060] - the average load factor of one or all employees,
[0061] and / or
[0062] - Comply with machine-specific standards, such as avoiding cold starts or downtime.
[0063] The optimized percentage allocation PA of the employees relative to the respective machines is transmitted as input to the second optimization module 103 .
[0064] The second optimization module 103 is configured to determine optimized production planning data PD_opt. Here, an optimized time sequence for the employees W and machines for the corresponding production steps according to the planning data PD is determined based on the percentage distribution PA and the number of employees W required for the production steps. Thus, a time distribution or sequence formation (scheduling) is determined. The goal is time optimization.
[0065] The second optimization module 103 preferably considers the following boundary conditions:
[0066] - adhere to the predetermined sequence of production steps,
[0067] - Consider the bill of materials and / or bill of process flow,
[0068] - adhere to completion dates,
[0069] - the intended production capacity of the machine,
[0070] and / or
[0071] - Minimize changeover time.
[0072] The optimized production planning data PD_opt may then be outputted so as to carry out production of at least one product according to the optimized production planning data.
[0073] In the event that production deviates from the optimized production planning data, the second optimization module 103 may determine new optimized production planning data according to the optimized percentage allocation PA.
[0074] In addition, the first optimization module 102 and / or the second optimization module 103 may re-execute the corresponding optimization for the still undetermined production steps starting from the current production status.
[0075] The optimized production planning data PD_opt may also be transmitted to the simulation module 105 and the verification module 106 .
[0076] The simulation module 105 is configured to perform a computer-aided logistics simulation of production based on the optimized production planning data PA. In particular, the transport times between machines can be taken into account. The simulation module 105 provides corresponding simulation data SIM.
[0077] The simulation data SIM may be transmitted to a verification module 106. The verification module 106 is arranged to verify the optimized production planning data PD_opt according to the simulation data SIM. The planning may thus be further refined.
[0078] Furthermore, the simulation data SIM can be transmitted to a prediction module 107. The prediction module 107 is configured to predict production-related data PROD based on the simulation data SIM. For example, machine operating times, material consumption or energy consumption can be determined based on the simulation data.
[0079] Figure 2 A computer-implemented method for optimizing a production plan for producing at least one product is shown, wherein an employee W is assigned to operate a machine for producing the at least one product. In particular, the method can be implemented, for example, according to Figure 1 The device is executed.
[0080] The method comprises the following method steps:
[0081] In a first step S1 , planning data for production, capability information on machine operation and availability information of employees are read in.
[0082] In a next step S2 , an optimized percentage distribution of the employees to the respective machines for a predetermined time period is determined based on the planning data, the capacity information and the availability information.
[0083] In a next step S3 , optimized production planning data are determined, wherein an optimized time sequence for the respective production steps for employees and machines is determined according to the planning data based on the percentage distribution and based on the number of employees required for the production steps.
[0084] In the next step S4, the optimized production planning data are output. For example, the optimized production planning data can be provided to the corresponding employees. For example, the optimized production planning data can be provided to the corresponding employees individually. This provision can be performed, for example, on an intelligent device. An overview of the optimized production planning data can also be provided to the shift supervisor.
[0085] Subsequently, S5, the product can be produced according to the optimized production planning data.
[0086] All described and / or illustrated features can advantageously be combined with one another within the scope of the invention. The invention is not restricted to the exemplary embodiments described.
Claims
1. A device (100) for optimizing a production plan for producing at least one product, wherein: a worker (W) is assigned to operate a machine for producing said at least one product, Wherein, the device comprises: a) an interface (101) configured to read planning data (PD) for production as well as competence information (CI) and availability information (AI) of employees (W) regarding machine operation, b) a first optimization module (102) configured to determine an optimized percentage allocation (PA) of employees to respective machines for a predetermined time period based on the planning data, the capacity information and the availability information, c) a second optimization module (103) configured to determine optimized production planning data (PD_opt), wherein an optimized time sequence for employees (W) and machines for the production steps according to the planning data (PD) is determined based on the percentage distribution (PA) and the number of employees required for the production steps, and d) An output module (104), which is configured to output optimized production planning data (PD_opt) so as to produce at least one product according to the optimized production planning data.
2. The device according to claim 1, wherein: The first optimization module (102) determines the optimal allocation of employees to corresponding machines through a mixed integer optimization problem.
3. The device according to claim 1 or 2, wherein: The first optimization module (102) is configured to determine an optimal allocation of employees to corresponding machines while taking into account at least one of the following boundary conditions: - Minimize employee job changes, - the average load factor of employees, and / or - Comply with machine-specific standards.
4. The device according to claim 1, wherein: The second optimization module (103) is configured to determine optimized production planning data while considering at least one of the following boundary conditions: - adhere to the predetermined sequence of production steps, - Consider the bill of materials and / or bill of process flow, - adhere to completion dates, - the intended production capacity of the machine, and / or - Minimize changeover time.
5. The device according to any one of the preceding claims, wherein The second optimization module (103) is configured to redetermine the optimized production planning data according to the optimized percentage distribution when there is a time deviation between the production and the optimized production planning data.
6. The device according to any one of the preceding claims, wherein: The first optimization module (102) and / or the second optimization module (103) are configured to re-execute the corresponding optimization starting from the current production status.
7. The device according to any of the preceding claims, further comprising a simulation module (105), wherein: The simulation module is configured to perform a computer-aided material flow simulation of production according to the optimized production planning data and output simulation data (SIM).
8. The device according to claim 7, wherein: The simulation module (105) is arranged to take into account the transportation time between machines.
9. The device according to claim 7 or 8, further comprising a verification module (106), which is configured to verify the optimized production planning data based on simulation data (SIM).
10. The device according to claim 7, further comprising a prediction module (107) configured to predict production-related data (PROD) based on simulation data (SIM).
11. A computer-implemented method for optimizing a production plan for producing at least one product, wherein: an employee is assigned to operate a machine for producing said at least one product, The method steps include: - read (S1) planning data for production, capacity information on machine operation and employee availability information, - determining (S2) an optimized percentage allocation of employees to the respective machines for a predetermined time period based on the planning data, the capacity information and the availability information, - determining (S3) optimized production planning data, wherein an optimized time sequence for the employees and machines for the corresponding production steps according to the planning data is determined based on the percentage distribution and based on the number of employees required for the production steps, and - outputting (S4) the optimized production planning data so as to produce at least one product according to the optimized production planning data.
12. A computer program product directly loadable into a programmable computer, comprising program code portions adapted to perform the method steps according to claim 11.