Mechanical processing production line production resource optimization management method and system
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- FUJIAN KEYE CNC TECH CO LTD
- Filing Date
- 2026-01-13
- Publication Date
- 2026-06-02
Smart Images
Figure CN121504103B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of production line scheduling management technology, specifically relating to a method and system for optimizing production resources in machining production lines. Background Technology
[0002] Machining production lines typically consist of multiple CNC machine tools, tooling systems, and various types of machining operations. Their production rhythm is influenced by multiple factors, including equipment status, tool life, process sequence, and job switching. In actual production, fluctuations in the performance of individual machine tools, the uncertainty of tool wear, changes in the effective period of compensation parameters, and resource differences between different operations all directly impact the feasibility of scheduling. Traditional scheduling methods usually build scheduling models based on fixed machining durations and static resource states. These models struggle to reflect real-time dynamic characteristics such as the thermal steady-state changes of machine tools over different time periods, changes in the validity period of compensation versions, and the remaining tool life. This leads to a mismatch between the scheduling plan and the actual on-site conditions, resulting in problems such as downtime, resource conflicts, and process delays.
[0003] Furthermore, during machining operations, adjustments to tools, fixtures, or compensation parameters are often required during changeovers. Differences in resource configurations directly impact changeover time. Existing methods struggle to quantify these resource differences, typically relying on empirical values to estimate changeover times, leading to scheduling biases. Simultaneously, tools, as critical machining resources, experience frequent lifespan changes. If tool status updates are not timely, the scheduling scheme may assign tools nearing their lifespan limits, causing machining interruptions or quality fluctuations. On the other hand, when equipment status changes or resource inconsistencies occur during scheduling execution, traditional scheduling methods often require recalculating the entire schedule, which is time-consuming and disrupts continuous production line operation. Summary of the Invention
[0004] This invention provides a method and system for optimizing production resources in machining production lines, which solves the technical problem in related technologies that scheduling cannot be matched in real time with machine tool status, tool life and job switching resource differences, resulting in scheduling failure, processing conflicts and reduced production line efficiency.
[0005] This invention provides a method for optimizing production resources management in a machining production line, comprising the following steps:
[0006] Step 1: Collect equipment status configuration data, tool resource data, and operating parameter data; determine the remaining available tool quantity based on the tool resource data;
[0007] Step 2: Determine the machine tool-level joint feasible window based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and determine the working machine tool-level joint feasible window in combination with the remaining available tool quantity;
[0008] Step 3: Construct resource packages based on the tool magazine loading table, clamping scheme, and compensation set; generate resource package signatures; and determine the switching time based on the resource package signatures corresponding to adjacent operations on the same machine tool.
[0009] Step 4: Based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the switching time, the remaining available tools, and the working parameter data, establish machine allocation relation variables, execution relation variables, start and end time variables, and hard constraints.
[0010] Step 5: Determine the comprehensive optimization target based on the sum of the global completion time, the switching time between adjacent operations on the same machine tool, and the number of resource package reinstallations;
[0011] Step 6: Adopt a deterministic process that includes a construction phase and an improvement phase, and determine a scheduling scheme based on the comprehensive optimization objective;
[0012] Step 7: Issue the scheduling plan and perform consistency verification. After the work block is completed, update the remaining available tool quantity, machine tool-level joint feasible window, and work machine tool-level joint feasible window.
[0013] Furthermore, data on equipment status configuration, tool resource data, and operational parameters are collected; based on the tool resource data, the remaining available tool quantity is determined, including:
[0014] Equipment status configuration data includes: shift availability time, thermal steady-state range, compensation version, and effective range of compensation version;
[0015] Tool resource data includes: the number of tools already used and the maximum allowed number of tools;
[0016] The operational parameter data includes: selectable machine tools, required cutting tools, tool consumption, and processing time;
[0017] The remaining usable quantity of tools is obtained by calculating the difference between the maximum allowable quantity of tools and the number of tools already used.
[0018] Furthermore, based on the shift availability time, thermal steady-state range, and effective range of the compensation version in the equipment status configuration data, a machine tool-level joint feasible window is determined, and combined with the remaining available tool quantity, a working machine tool-level joint feasible window is determined, including:
[0019] The time interval that simultaneously falls within the available shift time, the thermal steady-state interval, and the effective interval of the compensation version is determined as the machine tool-level joint feasible window for the corresponding machine tool;
[0020] For each combination of job and machine tool, the tool consumption and remaining available tool quantity of the job are compared according to the job parameter data. When the remaining available tool quantity is not less than the tool consumption, the job and the corresponding machine tool-level joint feasible window are set as the machine tool-level joint feasible window of the machine tool. When the remaining available tool quantity is less than the tool consumption, the job and the corresponding machine tool-level joint feasible window are set as an empty set.
[0021] Further, a resource package signature is generated, and the switchover time is determined, including:
[0022] Step 11: For adjacent work pairs on the same machine tool, read the resource package signatures of the adjacent work respectively, parse the resource package signatures into tool magazine loading table signatures, clamping scheme signatures and compensation version signatures, and compare them one by one to obtain the tool magazine loading table difference indicator, clamping scheme difference indicator and compensation version difference indicator. The difference indicator values include 0 and 1.
[0023] Step 12: The additional time is obtained by weighted summation of the tool magazine loading table difference indicator, clamping scheme difference indicator and compensation version difference indicator, and then the basic switching time is added to obtain the switching time.
[0024] Step 13: Based on the switching time, construct a switching time mapping relationship, using the job identifier and machine tool identifier of adjacent job pairs as index keys, and the corresponding switching time as the mapping value for associated storage.
[0025] Furthermore, based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the switching time, the remaining available tool quantity, and the operation parameter data, machine allocation relation variables, execution relation variables, start and end time variables, and hard constraints are established, including:
[0026] Step 21: Establish machine allocation relationship variables for each job and each machine tool. The machine allocation relationship variables can take values of 0 and 1. When a job is assigned to the corresponding machine tool, the value is 1; otherwise, the value is 0. The sum of the machine allocation relationship variables for the same job on all machine tools is constrained to be 1.
[0027] Step 22: Establish execution relationship variables for any two jobs on the same machine tool. The execution relationship variable can take values of 0 and 1. A value of 1 indicates that the two jobs associated with the execution relationship variable are executed sequentially on the same machine tool, with the former being the job executed first and the latter being the job executed later. It is agreed that the start time of the job executed later is no earlier than the sum of the end time and the corresponding switching time of the job executed first. A value of 0 indicates that the two jobs have no order on the machine tool. Establish start and end time variables to record the start and end times of each job.
[0028] Step 23: Based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the remaining available tool quantity, and the operation parameter data, construct three types of hard constraints, including: time constraints, which constrain the start and end times of each operation to fall within the corresponding working machine tool-level joint feasible window; tool resource constraints, which constrain the sum of the products of the tool consumption of the same tool for all operations and the machine allocation relation variable to not exceed the remaining available tool quantity of that tool; and machine tool operation constraints, which, combined with the execution relation variable, limit the same machine tool to execute only one operation at any given time.
[0029] Furthermore, the comprehensive optimization objectives are determined based on the sum of the global completion time, the switching time between adjacent operations on the same machine tool, and the number of resource package reinstallations, including:
[0030] Step 31: Select the maximum end time from the end times of all jobs and set the maximum end time as the global completion time;
[0031] Step 32: Based on the execution relation variable and the corresponding switching time, sum up the corresponding switching time for each pair of jobs on all machine tools whose execution relation variable is 1, and determine the sum of the switching times of adjacent jobs on the same machine tool as the sum of ...
[0032] Step 33: Based on the execution relation variables and the resource package signature difference indicators corresponding to adjacent jobs, calculate the sum of the resource package signature difference indicators for all job pairs where the execution relation variables are 1. Determine the summation result as the number of resource package reinstallations. Then, determine the weighted sum of the global completion time, the switching time of adjacent jobs on the same machine tool, and the number of resource package reinstallations as the comprehensive optimization target.
[0033] Furthermore, a deterministic process including a construction phase and an improvement phase is adopted, and a scheduling scheme is determined based on the comprehensive optimization objective, including:
[0034] Step 41: In the construction phase, based on the machine allocation relation variables, execution relation variables, switching time, and the joint feasible window at the machine tool level, select machine tools, start time, and end time for each job in sequence according to the preset sorting rules to generate an initial scheduling scheme that meets the hard constraints.
[0035] Step 42: In the improvement phase, taking the initial scheduling scheme as input, and under the premise of keeping the hard constraints in place, the execution order and start time of the jobs on the same machine tool are adjusted, and after each adjustment, it is determined whether to retain the adjustment based on the calculation result of the comprehensive optimization objective, so as to obtain the improved scheduling scheme.
[0036] Step 43: Perform constraint consistency verification on the improved scheduling scheme. When all hard constraints are satisfied and the comprehensive optimization objective meets the preset convergence conditions, the improved scheduling scheme is determined as the final scheduling scheme, and the machine tool allocation result, execution order, start time and end time of each job are output.
[0037] Furthermore, the scheduling plan is issued and consistency verification is performed. After the work block is completed, the remaining available tool quantity, machine tool-level joint feasibility window, and work machine tool-level joint feasibility window are updated, including:
[0038] Step 51: Send the machine tool allocation results, start time, end time and corresponding resource package signature of each job in the scheduling plan to each machine tool control unit, and read the equipment status configuration data of the machine tool. Compare the equipment status configuration data with the resource package signature item by item. If the two are consistent, the job is allowed to be executed according to the start time. If they are inconsistent, mark it as a consistency check failure and prevent the job from starting.
[0039] Step 52: After the work blocks that constitute the same continuous machining sequence are completed, the number of used tools corresponding to each operation in the work block is accumulated according to the tool consumption of each operation. The difference between the accumulated result and the upper limit of the tool allowance is determined as the remaining available tool quantity after the work block, and the remaining available tool quantity is written into the tool resource data.
[0040] Step 53: Based on the remaining available tool quantity and equipment status configuration data after the completion of the work block, update the intersection of the shift available time, thermal steady-state interval, and effective interval of the compensation version for each machine tool to form an updated machine tool-level joint feasible window; and determine the tool feasibility conditions of each machine tool for unexecuted work based on the updated remaining available tool quantity, set the work machine tool-level joint feasible window of the work that meets the tool feasibility conditions and the corresponding machine tool as the updated machine tool-level joint feasible window, otherwise set it as an empty set.
[0041] Furthermore, when the consistency check is marked as failed, the schedule status is restored using the abnormal state rollback rule, including: based on the job identifier and machine tool identifier of the abnormality, locating the feasible schedule status recorded before the abnormality occurred, restoring the machine allocation relation variable, execution relation variable, start time and end time of the corresponding job in the schedule status to the values before the abnormality occurred, forming the rolled-back schedule status;
[0042] After the scheduling status is restored after the rollback is completed, some jobs are rescheduled for the unexecuted jobs of the machine tool where the anomaly occurred. This includes keeping the machine allocation relationship variables, execution relationship variables, and start and end time variables of the jobs that are not affected by the anomaly unchanged, and only for the unexecuted jobs of the machine tool where the anomaly occurred, recalculating the start and end times of the corresponding jobs based on the updated remaining tool availability, machine tool-level joint feasible window, and working machine tool-level joint feasible window to form an updated local scheduling structure.
[0043] This invention provides a production resource optimization management system for machining production lines, comprising:
[0044] The data acquisition and calculation module collects equipment status configuration data, tool resource data, and operational parameter data; it then determines the remaining available tool quantity based on the tool resource data.
[0045] The feasible window generation module determines the machine tool-level joint feasible window based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and determines the working machine tool-level joint feasible window in combination with the remaining available tool quantity;
[0046] The resource package and switching calculation module constructs a resource package based on the tool magazine loading table, clamping scheme, and compensation set, generates a resource package signature, and determines the switching time based on the resource package signatures corresponding to adjacent operations on the same machine tool.
[0047] The scheduling constraint construction module establishes machine allocation relationships, execution relationships, time constraints, and hard constraints based on machine tool-level joint feasible windows, working machine tool-level joint feasible windows, switching time, remaining available tools, and operation parameter data.
[0048] The target generation module is optimized to determine the comprehensive optimization target based on the sum of the global completion time, the switching time of adjacent operations on the same machine tool, and the number of resource package reinstallations.
[0049] The deterministic scheduling generation module adopts a deterministic process that includes a construction phase and an improvement phase, and determines the scheduling scheme based on time constraints and comprehensive optimization objectives.
[0050] The execution and status update module is issued, the scheduling scheme is issued and consistency verification is performed, and the remaining available tool quantity, machine tool-level joint feasible window and working machine tool-level joint feasible window are updated after the work block is completed.
[0051] The beneficial effects of this invention are as follows: By constructing structured models of machine tool status, tool life, and operational requirements, this invention builds machine tool-level and operational machine tool-level joint feasible windows, achieving precise quantification of the executable time domain of the machining production line and overcoming the problem of mismatch between scheduling and actual equipment status in existing technologies. This invention generates resource package signatures based on tool magazine loading tables, clamping schemes, and compensation versions, and quantifies job switching costs through difference indicators, making the switching time model more refined and avoiding scheduling deviations caused by traditional experience-based estimations.
[0052] This invention establishes machine allocation relationships, execution relationships, start and end time variables, and three types of hard constraints, ensuring the scheduling model is strictly feasible in terms of time, resources, and equipment occupancy. Based on this, a comprehensive optimization objective is constructed by comprehensively considering the global completion time, the sum of adjacent job switching times, and the number of resource package reloading times, enabling the scheduling results to achieve a balance between efficiency and resource stability. Through a deterministic process of construction and improvement phases, this invention can generate stable, reproducible, and constraint-satisfied scheduling solutions.
[0053] Furthermore, this invention enhances the robustness of the scheduling execution process through consistency verification, abnormal state rollback, and local job rescheduling mechanisms, achieving dynamic matching between the schedule and the actual execution environment, ensuring the continuity and reliability of the production process, and improving the overall resource utilization and production management level of the machining production line. Attached Figure Description
[0054] Figure 1 This is a flowchart of the production resource optimization management method for machining production lines according to the present invention. Detailed Implementation
[0055] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.
[0056] It should be noted that, unless otherwise defined, the technical or scientific terms used in one or more embodiments of the present invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in one or more embodiments of the present invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.
[0057] like Figure 1 As shown, the method for optimizing production resources in a machining production line includes the following steps:
[0058] Step 1: Collect equipment status configuration data, tool resource data, and operating parameter data; determine the remaining available tool quantity based on the tool resource data;
[0059] Step 2: Determine the machine tool-level joint feasible window based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and determine the working machine tool-level joint feasible window in combination with the remaining available tool quantity;
[0060] Step 3: Construct resource packages based on the tool magazine loading table, clamping scheme, and compensation set; generate resource package signatures; and determine the switching time based on the resource package signatures corresponding to adjacent operations on the same machine tool.
[0061] Step 4: Based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the switching time, the remaining available tools, and the working parameter data, establish machine allocation relation variables, execution relation variables, start and end time variables, and hard constraints.
[0062] Step 5: Determine the comprehensive optimization target based on the sum of the global completion time, the switching time between adjacent operations on the same machine tool, and the number of resource package reinstallations;
[0063] Step 6: Adopt a deterministic process that includes a construction phase and an improvement phase, and determine a scheduling scheme based on the comprehensive optimization objective;
[0064] Step 7: Issue the scheduling plan and perform consistency verification. After the work block is completed, update the remaining available tool quantity, machine tool-level joint feasible window, and work machine tool-level joint feasible window.
[0065] In one embodiment of the present invention, equipment status configuration data, tool resource data, and operating parameter data are collected; the remaining available tool quantity is determined based on the tool resource data, including:
[0066] The equipment status configuration data includes: shift availability time, thermal steady-state interval, compensation version, and effective interval of the compensation version. The equipment status configuration data is a key set of data describing the machine tool's operating status and effective working boundary. The thermal steady-state interval refers to the time interval during which the machine tool's temperature stabilizes and geometric errors and machining accuracy remain within a preset allowable range after startup preheating or continuous operation. The compensation version refers to a preset parameter configuration scheme for issues such as machine tool thermal drift, geometric errors, and tool wear; different compensation versions correspond to different machining condition adaptation requirements. The effective interval of the compensation version refers to the time range within which the corresponding compensation version can stably perform error compensation and ensure that machining accuracy meets process requirements.
[0067] Tool resource data includes: the number of tools used and the maximum allowable number of tools. Tools are the equipment used directly in machining production lines for cutting, grinding, drilling, milling, and other machining operations on workpieces. They are core production resources for achieving material removal, shape forming, and precision assurance. The number of tools used refers to the cumulative number of workpieces processed by a particular tool since it was put into use, obtained in real time through production line records or tool management systems. The maximum allowable number of tools refers to the maximum number of workpieces that this type of tool can process before reaching its wear limit and being unable to guarantee machining quality. It is determined by the tool material characteristics, process requirements, and equipment parameters.
[0068] The operational parameter data includes: selectable machine tools, required cutting tools, cutting tool consumption, and processing time. The selectable machine tools refer to a set of machine tools with the technological capabilities required for the operation, determined by the operation's machining accuracy requirements and the matching degree of machine tool functional parameters. The cutting tool consumption refers to the amount of corresponding cutting tools required to complete a single operation. The processing time refers to the deterministic time required to complete all machining steps on a selectable machine tool, determined by the process quota standard and actual production verification data.
[0069] The remaining usable tool quantity is obtained by calculating the difference between the maximum allowable wear limit of the tool and the number of workpieces already used. The remaining usable tool quantity directly reflects the number of workpieces that the tool can currently process. If the calculation result is negative, it indicates that the tool has exceeded its wear limit and is determined to be unusable.
[0070] This embodiment achieves data normalization and integration by clearly defining the collection scope and definition of three types of data: equipment status configuration, tool resources, and operating parameters; it achieves accurate determination of tool resource status by calculating the remaining available tool quantity through deterministic difference; the implementation process of this embodiment provides unified and accurate basic data support for the entire optimization management scheme.
[0071] In one embodiment of the present invention, a machine tool-level joint feasible window is determined based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and a working machine tool-level joint feasible window is determined in conjunction with the remaining available tool quantity, including:
[0072] The time interval that falls within the available shift time, the thermal steady-state interval, and the effective interval of the compensation version is determined as the machine tool-level joint feasible window for the corresponding machine tool. The machine tool-level joint feasible window represents the complete time range during which the machine tool is allowed to perform processing when all state conditions are met, which can provide accurate equipment time resource boundaries for subsequent scheduling.
[0073] For each combination of job and machine tool, the tool consumption and remaining available tool quantity in the job parameter data are compared. When the remaining available tool quantity is not less than the tool consumption, it means that the tool resources meet the requirements. The machine tool-level joint feasible window of the job and the corresponding machine tool is set as the machine tool-level joint feasible window of the machine tool. When the remaining available tool quantity is less than the tool consumption, the machine tool-level joint feasible window of the job and the corresponding machine tool is set to an empty set, that is, the job is not feasible on the machine tool.
[0074] This embodiment locks the effective working time of the machine tool by intersecting multiple intervals, thus achieving precise definition of the machine tool's processing capacity; it achieves feasibility screening for matching the operating machine tool by rigidly comparing the tool consumption and the remaining available quantity; and finally achieves precise matching between pre-scheduling operations and machine tools, avoiding downtime caused by machine tool status or insufficient resources in traditional scheduling, thereby improving the feasibility and efficiency of production line resource optimization management.
[0075] In one embodiment of the present invention, generating a resource package signature and determining the switching time includes:
[0076] Step 11: For adjacent work pairs on the same machine tool, read the resource package signatures of the adjacent work pairs respectively, parse the resource package signatures into tool magazine loading table signatures, clamping scheme signatures, and compensation version signatures, and compare them item by item to obtain the tool magazine loading table difference indicator, clamping scheme difference indicator, and compensation version difference indicator. The difference indicator value includes 0 and 1, where 0 indicates no difference and 1 indicates that there is a difference and the configuration needs to be switched. Through the structured representation of the difference indicator, the present invention can accurately quantify the degree of difference in resource configuration between two adjacent work pairs.
[0077] Step 12: The additional time is obtained by weighted summing of the tool magazine loading table difference indicator, clamping scheme difference indicator and compensation version difference indicator, and then the basic switching time is added to obtain the switching time. The additional time reflects the extra time consumed due to resource changes during job switching. The basic switching time is used to represent the fixed behaviors that still need to be performed during job switching even if the resource packages are completely identical, such as moving the machine tool axis position or resetting the machining parameters.
[0078] Step 13: Based on the switching time, construct a switching time mapping relationship, using the job identifier and machine tool identifier of adjacent job pairs as index keys and the corresponding switching time as mapping value for associated storage, for quick retrieval of the switching time of any job pair and its associated machine tool.
[0079] This embodiment achieves accurate identification of differences in operational resource requirements through signature parsing and item-by-item comparison; it achieves quantitative calculation of changeover time through weighted summation and overlay of base time; and it ultimately realizes transparency and traceability of changeover costs, providing reliable data support for subsequent scheduling optimization and improving the rationality and efficiency of production line resource scheduling.
[0080] In one embodiment of the present invention, based on machine tool-level joint feasible window, working machine tool-level joint feasible window, switching time, remaining tool availability, and operation parameter data, machine allocation relation variables, execution relation variables, start and end time variables, and hard constraints are established, including:
[0081] Step 21: Establish machine allocation relationship variables for each job and each machine tool. The machine allocation relationship variables can take values of 0 and 1. When a job is assigned to the corresponding machine tool, the value is 1; otherwise, the value is 0. The sum of the machine allocation relationship variables for the same job on all machine tools is constrained to be 1. That is, each job can only be processed by one machine tool to ensure that the job is only uniquely assigned.
[0082] Step 22: Establish execution relation variables for any two jobs on the same machine tool. Execution relation variables are binary variables, taking values of 0 and 1. A value of 1 indicates that the two jobs associated with the execution relation variable are executed sequentially on the same machine tool, with the former being the job executed first and the latter the job executed later. It is agreed that the start time of the later job cannot be earlier than the sum of the end time and corresponding switching time of the earlier job. A value of 0 indicates that the two jobs have no order on the machine tool. Establish start and end time variables to record the start and end times of each job; the end time is the start time plus the processing time.
[0083] Step 23: Based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the remaining available tool quantity, and the operation parameter data, construct three types of hard constraints, including: time constraints, which constrain the start and end times of each operation to fall within the corresponding working machine tool-level joint feasible window to ensure the feasibility of the operation in the time dimension; tool resource constraints, which constrain the sum of the product of the tool consumption of the same tool for all operations and the machine allocation relation variable to not exceed the remaining available tool quantity of that tool, ensuring that the scheduling results will not lead to insufficient tool life or machining failure; and machine tool operation constraints, which, combined with the execution relation variable, limit the same machine tool to execute only one operation at any given time to avoid operation overlap or machine tool resource conflict.
[0084] This embodiment achieves standardized modeling of scheduling elements by clearly defining the three types of variables and their value rules; it achieves rigid control over machine tool status, resource capacity, and work sequence by constructing multi-dimensional hard constraints; and it ultimately solves the problems of resource conflicts and processing interruptions caused by fuzzy constraints in traditional scheduling, providing rigorous constraint support for production line resource optimization management and improving the feasibility and reliability of scheduling schemes.
[0085] In one embodiment of the present invention, a comprehensive optimization objective is determined based on the sum of the global completion time, the switching time between adjacent operations on the same machine tool, and the number of resource package reinstallations, including:
[0086] Step 31: Select the maximum end time from the end times of all tasks and set this maximum end time as the global completion time; the global completion time directly reflects the total time taken for the entire production line to complete all tasks.
[0087] Step 32: Based on the execution relation variable and the corresponding switching time, sum up the corresponding switching time for each pair of jobs on all machine tools whose execution relation variable is 1, and determine the sum of the switching times of adjacent jobs on the same machine tool. The switching time is used to characterize the time consumed by adjacent jobs during resource configuration changes, job preparation and process adjustment. It comes from the result calculated based on resource package signature in the steps, so it can accurately reflect the real time cost of job switching.
[0088] Step 33: Based on the execution relation variable and the resource package signature difference indicator corresponding to adjacent jobs, calculate the sum of the resource package signature difference indicators for all job pairs where the execution relation variable is 1. The summation result is determined as the resource package reinstallation count. The resource package reinstallation count refers to the total number of times there is a difference in resource package signatures among all sequentially executed job pairs. The higher the resource package reinstallation count, the lower the stability of the scheduling scheme in terms of resource preparation, which may lead to additional machine tool downtime and manual processing costs. The weighted sum of the global completion time, the switching time of adjacent jobs on the same machine tool, and the resource package reinstallation count is determined as the comprehensive optimization objective. The scheduling process takes minimizing the comprehensive optimization objective as its core direction.
[0089] This embodiment achieves quantitative representation of production line efficiency and changeover costs by precisely defining three core indicators and clarifying the calculation logic; it realizes orderly coordination of multi-objective optimization by constructing a unified optimization target through weighted summation; and it ultimately solves the problem of efficiency and cost imbalance caused by the single objective in traditional scheduling, providing a clear direction for the global optimization of production line resources and improving the scientific nature and comprehensive benefits of resource scheduling.
[0090] In one embodiment of the present invention, a deterministic process including a construction phase and an improvement phase is employed, and a scheduling scheme is determined based on a comprehensive optimization objective, including:
[0091] Step 41: In the construction phase, based on the machine allocation relation variables, execution relation variables, switching time, and the joint feasible window at the machine tool level, the machine tool, start time, and end time are selected for each job in sequence according to the preset sorting rules to generate an initial scheduling scheme that meets the hard constraints; the preset sorting rules refer to the pre-set job sorting criteria, which are preferably the process sequence.
[0092] Step 42: In the improvement phase, the initial scheduling scheme is used as input. Under the premise of keeping the hard constraints in place, the execution order and start time of the jobs on the same machine tool are adjusted. After each adjustment, it is determined whether to retain the adjustment based on the calculation result of the comprehensive optimization objective. If the calculation result is better, the adjustment is retained; otherwise, it is discarded. The improved scheduling scheme is obtained step by step through iteration.
[0093] Step 43: Perform constraint consistency verification on the improved scheduling scheme, including verifying whether all hard constraints are simultaneously satisfied. For example, whether the job start time falls within the joint feasible window at the machine tool level, whether the machine tool executes only one job at any given time, and whether tool resources meet consumption limits. When all hard constraints are satisfied and the overall optimization objective meets the preset convergence condition, the improved scheduling scheme is determined as the final scheduling scheme, and the machine tool allocation result, execution order, start time, and end time of each job are output. The preset convergence condition refers to the standard for determining whether the optimization has reached the objective; preferably, it is set to the difference in the overall optimization objective value after multiple consecutive adjustments being less than a preset threshold.
[0094] This embodiment achieves the orderly construction and gradual optimization of scheduling schemes through a two-stage deterministic process; it ensures the feasibility and optimality of scheduling schemes through constraint consistency verification and convergence condition determination; and it ultimately solves the problems of uncertainty and insufficient optimization in traditional scheduling, providing a resource scheduling scheme with strong determinism and excellent comprehensive benefits for machining production lines, thereby improving the reliability of production line scheduling and resource utilization efficiency.
[0095] In one embodiment of the present invention, a scheduling scheme is issued and a consistency check is performed. After the work block is completed, the remaining available tool quantity, the machine tool-level joint feasible window, and the working machine tool-level joint feasible window are updated, including:
[0096] Step 51: The machine tool allocation results, start time, end time, and corresponding resource package signature for each job in the scheduling plan are sent to each machine tool control unit. The machine tool's equipment status configuration data is read and compared item by item with the resource package signature. If they match, the job is allowed to execute according to the start time. If they do not match, it is marked as a consistency check failure and the job is prevented from starting, thus avoiding processing quality defects or equipment failures due to configuration mismatch. Here, a job block refers to a set of jobs that are executed in a continuous processing sequence on the same machine tool and are adapted to the same resource package. Continuous processing can reduce the cost of frequent switching. The machine tool control unit is the core component that receives scheduling instructions, controls machine tool operation, and provides feedback on equipment status. The consistency check is used to verify whether the actual machine tool configuration matches the scheduling requirements.
[0097] Step 52: After the work blocks that constitute the same continuous machining sequence are completed, the number of used tools corresponding to each operation in the work block is accumulated according to the tool consumption of each operation. The difference between the accumulated result and the upper limit of the tool allowance is determined as the remaining available tool quantity after the work block. The remaining available tool quantity is written into the tool resource data to ensure that the tool resource status is accurate in real time.
[0098] Step 53: Based on the remaining available tool quantity and equipment status configuration data after the completion of the work block, update the intersection of the shift available time, thermal steady-state interval, and effective interval of the compensation version for each machine tool to form an updated machine tool-level joint feasible window; and determine the tool feasibility conditions of each machine tool for the unexecuted work based on the updated remaining available tool quantity, i.e., the remaining available tool quantity is not less than the tool consumption of the work, and set the work machine tool-level joint feasible window corresponding to the work that meets the tool feasibility conditions as the updated machine tool-level joint feasible window, otherwise set it as an empty set.
[0099] This embodiment achieves precise matching between scheduling requirements and actual machine tool configuration through pre-execution consistency verification; it achieves real-time synchronization of resource status and feasible boundaries by dynamically updating the remaining available tool quantity and joint feasible window after the completion of the work block; ultimately solving the problems of processing interruption, quality risks and scheduling failure caused by inconsistent configuration and delayed resource status updates in traditional production lines, and improving the real-time performance and reliability of production resource optimization management in machining production lines.
[0100] In one embodiment of the present invention, when the consistency check is marked as failed, the schedule state is restored using the abnormal state rollback rule, including: locating the feasible schedule state recorded before the abnormality occurred based on the job identifier and machine tool identifier of the abnormality, restoring the machine allocation relation variable, execution relation variable, start time and end time of the corresponding job in the schedule state to the values before the abnormality occurred, forming the rolled-back schedule state, ensuring that the schedule part unaffected by the abnormality can continue to be executed;
[0101] After the scheduling status is restored after the rollback is completed, partial job rescheduling is performed on the unexecuted jobs of the machine tool where the anomaly occurred. This is used to update only the local scheduling structure affected by the anomaly, thereby avoiding the time overhead and execution uncertainty caused by resolving the global schedule. This includes keeping the machine allocation relationship variables, execution relationship variables, and start and end time variables of the jobs that are not affected by the anomaly unchanged. Only for the unexecuted jobs of the machine tool where the anomaly occurred, the start and end times of the corresponding jobs are recalculated based on the updated remaining tool availability, machine tool-level joint feasible window, and working machine tool-level joint feasible window, forming an updated local scheduling structure that seamlessly connects with other unadjusted scheduling parts.
[0102] This embodiment minimizes the impact of anomalies by accurately locating them and restoring them to a feasible scheduling state; it achieves high efficiency in scheduling adjustments by only rescheduling the unexecuted tasks of the abnormal machine tools; and it ultimately solves the problems of long production line interruption time and low efficiency caused by full rescheduling in traditional anomaly handling, ensuring the continuity of production resource optimization management in the machining production line and improving the anti-interference ability and execution stability of the scheduling scheme.
[0103] This invention provides a production resource optimization management system for machining production lines, comprising:
[0104] The data acquisition and calculation module collects equipment status configuration data, tool resource data, and operational parameter data; it then determines the remaining available tool quantity based on the tool resource data.
[0105] The feasible window generation module determines the machine tool-level joint feasible window based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and determines the working machine tool-level joint feasible window in combination with the remaining available tool quantity;
[0106] The resource package and switching calculation module constructs a resource package based on the tool magazine loading table, clamping scheme, and compensation set, generates a resource package signature, and determines the switching time based on the resource package signatures corresponding to adjacent operations on the same machine tool.
[0107] The scheduling constraint construction module establishes machine allocation relationships, execution relationships, time constraints, and hard constraints based on machine tool-level joint feasible windows, working machine tool-level joint feasible windows, switching time, remaining available tools, and operation parameter data.
[0108] The target generation module is optimized to determine the comprehensive optimization target based on the sum of the global completion time, the switching time of adjacent operations on the same machine tool, and the number of resource package reinstallations.
[0109] The deterministic scheduling generation module adopts a deterministic process that includes a construction phase and an improvement phase, and determines the scheduling scheme based on time constraints and comprehensive optimization objectives.
[0110] The execution and status update module is issued, the scheduling scheme is issued and consistency verification is performed, and the remaining available tool quantity, machine tool-level joint feasible window and working machine tool-level joint feasible window are updated after the work block is completed.
[0111] It should be noted that the interval and threshold sizes are set for ease of comparison. The size of the threshold depends on the amount of sample data and the base number set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless calculations, and the formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.
[0112] The embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of the present embodiments, all of which are within the protection scope of the present embodiments.
Claims
1. A method for optimizing production resources in a machining production line, characterized in that, Includes the following steps: Step 1: Collect equipment status configuration data, tool resource data, and operating parameter data; determine the remaining available tool quantity based on the tool resource data; Step 2: Determine the machine tool-level joint feasible window based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and determine the working machine tool-level joint feasible window in combination with the remaining available tool quantity; Step 3: Construct resource packages based on the tool magazine loading table, clamping scheme, and compensation set; generate resource package signatures; and determine the switchover time based on the resource package signatures corresponding to adjacent operations on the same machine tool, including: Step 11: For adjacent work pairs on the same machine tool, read the resource package signatures of the adjacent work respectively, parse the resource package signatures into tool magazine loading table signatures, clamping scheme signatures and compensation version signatures, and compare them one by one to obtain the tool magazine loading table difference indicator, clamping scheme difference indicator and compensation version difference indicator. The difference indicator values include 0 and 1. Step 12: The additional time is obtained by weighted summation of the tool magazine loading table difference indicator, clamping scheme difference indicator and compensation version difference indicator, and then the basic switching time is added to obtain the switching time. Step 13: Based on the switching time, construct a switching time mapping relationship, using the job identifier and machine tool identifier of adjacent job pairs as index keys, and the corresponding switching time as the mapping value for associated storage; Step 4: Based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the switching time, the remaining available tools, and the operation parameter data, establish machine allocation relation variables, execution relation variables, start and end time variables, and hard constraints, including: Step 21: Establish machine allocation relationship variables for each job and each machine tool. The machine allocation relationship variables can take values of 0 and 1. When a job is assigned to the corresponding machine tool, the value is 1; otherwise, the value is 0. The sum of the machine allocation relationship variables for the same job on all machine tools is constrained to be 1. Step 22: Establish execution relationship variables for any two jobs on the same machine tool. The execution relationship variable can take values of 0 and 1. A value of 1 indicates that the two jobs associated with the execution relationship variable are executed sequentially on the same machine tool, with the former being the job executed first and the latter being the job executed later. It is agreed that the start time of the job executed later is no earlier than the sum of the end time and the corresponding switching time of the job executed first. A value of 0 indicates that the two jobs have no order on the machine tool. Establish start and end time variables to record the start and end times of each job. Step 23: Based on the machine tool-level joint feasible window, the working machine tool-level joint feasible window, the remaining available tool quantity, and the operation parameter data, construct three types of hard constraints, including: time constraints, which constrain the start and end times of each operation to fall within the corresponding working machine tool-level joint feasible window; tool resource constraints, which constrain the sum of the products of the tool consumption of the same tool for all operations and the machine allocation relation variable to not exceed the remaining available tool quantity of that tool; and machine tool operation constraints, which, combined with the execution relation variable, limit the same machine tool to execute only one operation at any given time. Step 5: Determine the comprehensive optimization target based on the sum of the global completion time, the switching time between adjacent operations on the same machine tool, and the number of resource package reinstallations; Step 6: Adopt a deterministic process that includes a construction phase and an improvement phase, and determine a scheduling scheme based on the comprehensive optimization objective; Step 7: Issue the scheduling plan and perform consistency verification. After the work block is completed, update the remaining available tool quantity, machine tool-level joint feasible window, and work machine tool-level joint feasible window.
2. The method for optimizing production resources in a machining production line according to claim 1, characterized in that, Collect equipment status configuration data, tool resource data, and operational parameter data; The remaining available tool quantity is determined based on tool resource data, including: Equipment status configuration data includes: shift availability time, thermal steady-state range, compensation version, and effective range of compensation version; Tool resource data includes: the number of tools already used and the maximum allowed number of tools; The operational parameter data includes: selectable machine tools, required cutting tools, tool consumption, and processing time; The remaining usable quantity of tools is obtained by calculating the difference between the maximum allowable quantity of tools and the number of tools already used.
3. The method for optimizing production resources in a machining production line according to claim 1, characterized in that, Based on the shift availability time, thermal steady-state range, and effective range of the compensation version in the equipment status configuration data, a machine tool-level joint feasible window is determined, and the operating machine tool-level joint feasible window is determined in conjunction with the remaining available tool quantity, including: The time interval that simultaneously falls within the available shift time, the thermal steady-state interval, and the effective interval of the compensation version is determined as the machine tool-level joint feasible window for the corresponding machine tool; For each combination of job and machine tool, the tool consumption and remaining available tool quantity of the job are compared according to the job parameter data. When the remaining available tool quantity is not less than the tool consumption, the job and the corresponding machine tool-level joint feasible window are set as the machine tool-level joint feasible window of the machine tool. When the remaining available tool quantity is less than the tool consumption, the job and the corresponding machine tool-level joint feasible window are set as an empty set.
4. The method for optimizing production resources in a machining production line according to claim 1, characterized in that, The comprehensive optimization objectives are determined based on the sum of the global completion time, the switching time between adjacent operations on the same machine tool, and the number of resource package reinstallations, including: Step 31: Select the maximum end time from the end times of all jobs and set the maximum end time as the global completion time; Step 32: Based on the execution relation variable and the corresponding switching time, sum up the corresponding switching time for each pair of jobs on all machine tools whose execution relation variable is 1, and determine the sum of the switching times of adjacent jobs on the same machine tool as the sum of ... Step 33: Based on the execution relation variables and the resource package signature difference indicators corresponding to adjacent jobs, calculate the sum of the resource package signature difference indicators for all job pairs where the execution relation variables are 1. Determine the summation result as the number of resource package reinstallations. Then, determine the weighted sum of the global completion time, the switching time of adjacent jobs on the same machine tool, and the number of resource package reinstallations as the comprehensive optimization target.
5. The method for optimizing production resources in a machining production line according to claim 1, characterized in that, A deterministic process, including a construction phase and an improvement phase, is adopted, and a scheduling scheme is determined based on the overall optimization objective, including: Step 41: In the construction phase, based on the machine allocation relation variables, execution relation variables, switching time, and the joint feasible window at the machine tool level, select machine tools, start time, and end time for each job in sequence according to the preset sorting rules to generate an initial scheduling scheme that meets the hard constraints. Step 42: In the improvement phase, taking the initial scheduling scheme as input, and under the premise of keeping the hard constraints in place, the execution order and start time of the jobs on the same machine tool are adjusted, and after each adjustment, it is determined whether to retain the adjustment based on the calculation result of the comprehensive optimization objective, so as to obtain the improved scheduling scheme. Step 43: Perform constraint consistency verification on the improved scheduling scheme. When all hard constraints are satisfied and the comprehensive optimization objective meets the preset convergence conditions, the improved scheduling scheme is determined as the final scheduling scheme, and the machine tool allocation result, execution order, start time and end time of each job are output.
6. The method for optimizing production resources in a machining production line according to claim 1, characterized in that, Issue the scheduling plan and perform consistency verification. After the work block is completed, update the remaining tool availability, machine tool-level joint feasibility window, and work machine tool-level joint feasibility window, including: Step 51: Send the machine tool allocation results, start time, end time and corresponding resource package signature of each job in the scheduling plan to each machine tool control unit, and read the equipment status configuration data of the machine tool. Compare the equipment status configuration data with the resource package signature item by item. If the two are consistent, the job is allowed to be executed according to the start time. If they are inconsistent, mark it as a consistency check failure and prevent the job from starting. Step 52: After the work blocks that constitute the same continuous machining sequence are completed, the number of used tools corresponding to each operation in the work block is accumulated according to the tool consumption of each operation. The difference between the accumulated result and the upper limit of the tool allowance is determined as the remaining available tool quantity after the work block, and the remaining available tool quantity is written into the tool resource data. Step 53: Based on the remaining available tool quantity and equipment status configuration data after the completion of the work block, update the intersection of the shift available time, thermal steady-state interval, and effective interval of the compensation version for each machine tool to form an updated machine tool-level joint feasible window; and determine the tool feasibility conditions of each machine tool for unexecuted work based on the updated remaining available tool quantity, set the work machine tool-level joint feasible window of the work that meets the tool feasibility conditions and the corresponding machine tool as the updated machine tool-level joint feasible window, otherwise set it as an empty set.
7. The method for optimizing production resources management in a machining production line according to claim 6, characterized in that, When the consistency check is marked as failed, the schedule status is restored using the abnormal status rollback rule, including: based on the job identifier and machine tool identifier of the abnormality, locating the feasible schedule status recorded before the abnormality occurred, restoring the machine allocation relation variable, execution relation variable, start time and end time of the corresponding job in the schedule status to the values before the abnormality occurred, forming the rolled-back schedule status; After the scheduling status is restored after the rollback is completed, some jobs are rescheduled for the unexecuted jobs of the machine tool where the anomaly occurred. This includes keeping the machine allocation relationship variables, execution relationship variables, and start and end time variables of the jobs that are not affected by the anomaly unchanged, and only for the unexecuted jobs of the machine tool where the anomaly occurred, recalculating the start and end times of the corresponding jobs based on the updated remaining tool availability, machine tool-level joint feasible window, and working machine tool-level joint feasible window to form an updated local scheduling structure.
8. A production resource optimization management system for machining production lines, characterized in that, The method for optimizing production resources in a machining production line as described in any one of claims 1-7 includes: The data acquisition and calculation module collects equipment status configuration data, tool resource data, and operational parameter data; it then determines the remaining available tool quantity based on the tool resource data. The feasible window generation module determines the machine tool-level joint feasible window based on the shift availability time, thermal steady-state interval, and effective interval of the compensation version in the equipment status configuration data, and determines the working machine tool-level joint feasible window in combination with the remaining available tool quantity; The resource package and switching calculation module constructs a resource package based on the tool magazine loading table, clamping scheme, and compensation set, generates a resource package signature, and determines the switching time based on the resource package signatures corresponding to adjacent operations on the same machine tool. The scheduling constraint construction module establishes machine allocation relationships, execution relationships, time constraints, and hard constraints based on machine tool-level joint feasible windows, working machine tool-level joint feasible windows, switching time, remaining available tools, and operation parameter data. The target generation module is optimized to determine the comprehensive optimization target based on the sum of the global completion time, the switching time of adjacent operations on the same machine tool, and the number of resource package reinstallations. The deterministic scheduling generation module adopts a deterministic process that includes a construction phase and an improvement phase, and determines the scheduling scheme based on time constraints and comprehensive optimization objectives. The execution and status update module is issued, the scheduling scheme is issued and consistency verification is performed, and the remaining available tool quantity, machine tool-level joint feasible window and working machine tool-level joint feasible window are updated after the work block is completed.