Dynamic scheduling method for intelligent loom workshop

Abstract

The invention belongs to the technical field of intelligent manufacturing production line collaborative management and control, and particularly relates to a dynamic scheduling method for an intelligent loom workshop. A dynamic scheduling model is constructed, a self-adaptive rescheduling strategy based on a workpiece tolerance coefficient is designed, disturbance events are analyzed, orders are used as disturbance factors, grade classification is performed on the orders, and workpiece deviation time is introduced into a multi-target static scheduling model to construct the dynamic scheduling model; on-line identification is carried out on different types of order disturbances by using a workpiece tolerance coefficient and periodic rescheduling, and a corresponding rescheduling strategy is proposed to solve a dynamic scheduling problem; according to the scheduling method provided by the invention, steady-state balance of production scheduling of the weaving workshop caused by frequent rescheduling of the order tasks is effectively maintained, and the adaptive rescheduling scheme averagely reduces a lot of workpiece deviation time compared with complete rescheduling.

Description

Technical Field

[0001] The present invention belongs to the technical field of collaborative management and control of intelligent manufacturing production lines, and specifically relates to a dynamic scheduling method for an intelligent loom workshop. Background Technique

[0002] Workshop scheduling is an important link in the production manufacturing process and an important control objective for efficient production scheduling in manufacturing enterprises. The workshop scheduling result plays an important role in the reasonable allocation of production resources and the reasonable operation of the processing process, and directly affects the economic benefits of the enterprise.

[0003] The textile process includes two parts: the spinning process and the manufacturing process. Each process is complex and has a long production cycle, which puts higher requirements on the workshop production scheduling management level. And the weaving process is an important part of it. Therefore, it is of great significance to conduct in-depth research on the weaving workshop scheduling method in its theoretical and application directions. At the same time, in the order-based production scheduling of the weaving workshop, there are the complexity of process equipment and the dynamic nature of production conditions. Therefore, it is more necessary and of practical engineering application value to solve the scheduling problem under dynamic events in the weaving workshop.

[0004] In the actual production process of the weaving workshop, sudden situations such as emergency order insertion, machine failure, and raw material supply delay often occur. Traditional dynamic scheduling mechanisms often lack sufficient flexibility to quickly adapt to these changes, resulting in a decline in scheduling efficiency. And the scheduling system of the weaving workshop may lack a real-time monitoring and rapid response mechanism, and cannot adjust the scheduling plan in real time according to the current production status, making the scheduling decision lag behind the actual production.

[0005] Therefore, this application proposes a dynamic scheduling method for an intelligent loom workshop. Summary of the Invention

[0006] In order to make up for the deficiencies of the existing technology and solve the technical problems in the background technique, the present invention proposes a dynamic scheduling method for an intelligent loom workshop.

[0007] The present invention is achieved through the following technical solutions:

[0008] A dynamic scheduling method for an intelligent loom workshop, the dynamic scheduling method includes the following steps:

[0009] Step 1: Generate an initial scheduling plan with the completion time, total energy consumption, and number of car shuttles as scheduling objectives and execute it;

[0010] Step 2: Determine whether a disturbance event occurs. If so, continue to the next step; otherwise, jump to Step 4;

[0011] Step 3: Determine the level of the current order disturbance event, calculate the workpiece delay tolerance coefficient of the current order disturbance event. If the workpiece delay tolerance coefficient is greater than 100%, jump to Step 5; otherwise, adjust the current scheduling cycle time.

[0012] Step 4: Determine whether it is the cycle scheduling time. If so, proceed to the next step; otherwise, continue to execute the current latest scheduling plan.

[0013] Step 5: Adopt corresponding dynamic scheduling methods for different levels of order disturbance events.

[0014] Step 6: Establish a dynamic scheduling optimization model with the completion time, total energy consumption, number of shunting operations, and workpiece deviation time as the objectives. Solve it based on the improved grey wolf algorithm to generate a rescheduling plan, update the latest scheduling plan, and execute it.

[0015] Step 7: Determine whether all workpieces are completed. If so, end; otherwise, jump to Step 2.

[0016] Preferably, the level of the order disturbance event is based on the impact of the order disturbance event on the production line. It is divided into three levels, which are, from low to high, minor disturbance events, moderate disturbance events, and severe disturbance events.

[0017] Preferably, the minor disturbance event is a disturbance event that reduces the effectiveness of the current scheduling plan, has little impact on actual production, and reduces the original tasks.

[0018] The moderate disturbance event is a disturbance event that requires adjustment of the current scheduling plan and increases the original tasks.

[0019] The severe disturbance event is a disturbance event that requires urgent scheduling of the original processing order, has a greater impact, and changes the original tasks.

[0020] Preferably, the minor disturbance event includes order cancellation; the moderate disturbance event includes order insertion; the severe disturbance event includes urgent order.

[0021] Preferably, the dynamic scheduling method adopts a combination of periodic rescheduling and event-driven rescheduling. The periodic rescheduling performs a rescheduling process on the scheduling system at regular time intervals to achieve the scheduling of invisible disturbance events; the event-driven rescheduling is driven by events and realizes the scheduling of visible disturbance events.

[0022] The dynamic scheduling problem of a weaving workshop considering the influence of disturbance factors is studied, and an adaptive rescheduling strategy based on the workpiece tolerance coefficient is formulated to determine the scheduling time point. Preferably, the determination of the scheduling time is based on the adaptive rescheduling strategy of the workpiece tolerance coefficient, which is specifically as follows:

[0023] Construct a set \(R\) of disrupted order workpieces and the current scheduling cycle time \(T\). p Set it as the completion time of the initial scheduling plan; when an order disruption event occurs, determine the current order disruption event level and calculate the workpiece tolerance coefficient \(S\) of the current disruption event.

[0024] The workpiece tolerance coefficient \(S\), the current scheduling cycle time \(T\). p And the disruption level coefficient \(\alpha\). r They are respectively obtained from the following formulas (1), (2) and (3):

[0025]

[0026] In the above formula, \(\eta\) represents the workpiece tolerance configuration coefficient, which is determined according to the current production situation of the manufacturing system; \(r\) represents the disruption level coefficient of each disrupted workpiece. Represents the average processing time of the process corresponding to the disrupted workpiece; \(T\) represents the remaining time of the current scheduling, and \(R\) represents the set of workpieces of the current disruption event.

[0027]

[0028] In the above formula, \(\beta\) represents the scheduling cycle coefficient, which is adjusted according to the productivity of the current manufacturing system, \(T\). p , represents the time of the previous scheduling cycle.

[0029]

[0030] In the above formula, \(\alpha\). r Represents the value of the current disruption level coefficient, indicating the anti-interference degree of the manufacturing system to order disruption events of different degrees. The larger the disruption level coefficient, the faster the response to disruptions, and it can be appropriately adjusted according to the actual situation.

[0031] Preferably, when the workpiece tolerance coefficient \(S>100\%\), the current order disruption event has a greater impact on the production line, and the initial scheduling plan can no longer meet the current production requirements. To ensure the normal progress of subsequent production, an event scheduling strategy is adopted to trigger dynamic scheduling to determine the current dynamic scheduling time point.

[0032] When the workpiece tolerance coefficient \(S\leq100\%\), the current order disruption event has a smaller impact on the production line and is within an acceptable range. To reduce the number of dynamic scheduling times, the initial scheduling plan will continue to be executed while changing the current scheduling cycle time \(T\). p , until the cycle scheduling triggers dynamic scheduling, then the cycle scheduling time point is the current dynamic scheduling time point.

[0033] Preferably, the dynamic scheduling methods include right-shift rescheduling, local rescheduling, and complete rescheduling.

[0034] The severe disturbance events are solved by complete rescheduling;

[0035] For the moderate disturbance events, local rescheduling is first attempted, and then compared with the complete rescheduling scheme, and the scheme with a smaller change amount is selected;

[0036] For the slight disturbance events, compare the scheduling change amounts P of the right shift rescheduling and the complete rescheduling, and select the scheme with a smaller change amount as the new scheduling plan, and its P is obtained by Equation (4);

[0037]

[0038] In the above formula, M pik represents the coefficient of the processing machine selected before and after scheduling, T represents the initial maximum completion time, and T L represents the maximum completion time after scheduling, and γ 1 and γ 2 are the balance coefficients of the completion time and the selection of the processing machine;

[0039] Among them, M pik is obtained by Equation (5):

[0040]

[0041] In the above formula, M ikj represents the processing machine selected before scheduling, and M i , kj represents the processing machine selected after scheduling.

[0042] Preferably, the construction of the dynamic scheduling optimization model is specifically as follows: set constraints on the time states of workpieces and equipment:

[0043] For the workpiece set:

[0044] At the moment when the disturbance event occurs, according to the current workpiece information, all workpieces are divided into completed workpieces, being processed workpieces, unprocessed workpieces, and to-be-processed workpieces;

[0045] The unprocessed workpieces refer to the warp beam workpieces that have been in the scheduling scheme but have not been processed yet;

[0046] The to-be-processed workpieces refer to the new workpieces for which the scheduling plan has not been arranged yet;

[0047] For the workpieces being processed, if the current process has been started, the remaining processing time of this process is regarded as the release time of the current workpiece; if the current process has not been started, the start time of the current rescheduling moment is set as the release time of the current workpiece;

[0048] For the processing equipment set:

[0049] For the equipment processing the workpiece, the remaining completion time of the current process is the release time of the equipment, while for the set of workpieces and equipment in other states, the rescheduling moment is used as their release time.

[0050] Preferably, the scheduling satisfies the flexible feature and is optimized by adding the target of minimizing the deviation time of the workpiece.

[0051] The processing of textiles in the workshop needs to go through four processes in sequence, and there are parallel machines for some processes to choose from. With the development of different types of product demands, a single variety of textiles cannot meet the actual needs. The processing time of the same process for different varieties is different, and there are choices of processing equipment, indicating that the scheduling needs to meet the flexible feature. The weaving workshop not only needs to meet the above-mentioned constraints such as completion time, energy consumption, and the number of car shunting, but also needs to face the impacts brought by disturbance factors such as changes in workshop orders. Therefore, the target of minimizing the deviation time of the workpiece is added as the optimization target.

[0052] The beneficial effects of the present invention are:

[0053] The present invention analyzes the existing scheduling methods, determines the pre-reactive scheduling as the dynamic scheduling method for the workshop, and inductively analyzes the disturbance events in different states, classifies different disturbance orders into levels, and then designs an adaptive rescheduling strategy based on the determination of the workpiece tolerance coefficient on the basis of the pre-reactive scheduling theory to solve the dynamic scheduling problem under different disturbance orders;

[0054] In addition, the scheduling methods for different levels of disturbances effectively maintain the steady-state balance of the production scheduling in the weaving workshop due to frequent rescheduling of order tasks, and the average deviation time of the adaptive rescheduling scheme for workpieces is much less than that of the complete rescheduling. Description of the Drawings

[0055] Figure 1 is the overall flowchart in the present invention;

[0056] Figure 2 is the schematic diagram of the scheduling management interface in the present invention;

[0057] Figure 3 is the schematic diagram of the emergency order insertion rescheduling interface in the present invention. Detailed Embodiments

[0058] The following further elaborates the present invention in combination with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. The experimental methods without specific conditions noted in the following embodiments are usually in accordance with conventional conditions or the conditions recommended by the manufacturer.

[0059] Unless otherwise defined, all professional and scientific terms used herein have the same meaning as those familiar to persons skilled in the art. The reagents or raw materials used in the present invention can be obtained through conventional channels. Unless otherwise specified, the reagents or raw materials used in the present invention are used in accordance with the conventional methods in the art or in accordance with the product instructions. In addition, any methods and materials similar or equivalent to the described content can be applied to the method of the present invention. The present invention will be further described below with reference to the accompanying drawings of the specification and specific embodiments. The preferred implementation methods and materials described in the present invention are for illustrative purposes only.

[0060] A dynamic scheduling method for an intelligent loom workshop includes determining when to perform rescheduling and how to execute rescheduling, thereby proposing a strategy based on the workpiece delay tolerance coefficient for dynamically determining the timing of rescheduling; after determining the dynamic scheduling time point, then judging the current disturbance event level, and finally selecting the most appropriate scheduling method.

[0061] The present invention summarizes and analyzes the existing scheduling methods and determines the pre-reactive scheduling as the dynamic scheduling method for the loom workshop.

[0062] That is, first, an initial scheduling plan is produced according to the ideal state of the workshop, and then a rescheduling plan is generated according to the type of disturbance event to adjust the original scheduling plan.

[0063] At the same time, for the actual workshop production and manufacturing, considering the cancellation, insertion, and replacement of orders as disturbance factors, different order disturbances have different impacts on the workshop scheduling. The order disturbances of different order types are classified into disturbance events of different levels, and the workpiece tolerance coefficient is calculated according to the disturbance level as the basis for rescheduling, and finally which scheduling method to select. For order time disturbances, they are divided into three levels according to the impact degree of the order disturbance event on the production line:

[0064] (1) A disturbance event that reduces the effect of the current scheduling plan but has a small impact on the actual production and reduces the original tasks is called a minor disturbance event, such as canceling an order, etc.;

[0065] (2) A disturbance event that requires adjustment of the current scheduling plan and increases the original tasks is called a medium disturbance event, such as inserting an order, etc.;

[0066] (3) A disturbance event that not only requires urgent scheduling of the original processing order, has a greater impact, and changes the original tasks is called an urgent disturbance event, such as an urgent order.

[0067] And there are mainly three methods for determining the rescheduling moment:

[0068] Periodic rescheduling, event-driven rescheduling, and hybrid scheduling.

[0069] Periodic rescheduling refers to the process of rescheduling the system at regular time intervals, which can ensure that the scheduling system processes the disturbance events occurring within each scheduling period. It is generally applied to the scheduling problems where implicit disturbance events occur.

[0070] Event-driven scheduling can effectively handle the occurrence of explicit disturbances, but it is often difficult to respond to implicit disturbances that are difficult to measure.

[0071] Hybrid rescheduling is a scheduling method that combines periodic rescheduling and event-driven rescheduling. The dynamic scheduling process in the weaving workshop divides random disturbance events into two types: explicit disturbances and implicit disturbances.

[0072] Therefore, the method for determining the rescheduling time in the weaving workshop is hybrid rescheduling.

[0073] Therefore, as Figure 1 , it specifically includes the following steps:

[0074] Step 1: Generate an initial scheduling plan with the completion time, total energy consumption, and number of vehicle adjustments as scheduling objectives and execute it;

[0075] Step 2: Determine whether there is a disturbance event. If so, proceed to the next step; otherwise, jump to Step 4;

[0076] Step 3: Determine the level of the disturbance event for the current order, calculate the tolerance coefficient of workpiece delay for the disturbance event of the current order. If the tolerance coefficient of workpiece delay is greater than 100%, jump to Step 5; otherwise, adjust the time of the current scheduling period;

[0077] Step 4: Determine whether it has reached the periodic scheduling time. If so, proceed to the next step; otherwise, continue to execute the current latest scheduling plan;

[0078] Step 5: Adopt corresponding dynamic scheduling methods for different levels of order disturbance events;

[0079] Step 6: Establish a dynamic scheduling optimization model with the completion time, total energy consumption, number of vehicle adjustments, and workpiece deviation time as objectives, solve it based on the improved grey wolf algorithm to generate a rescheduling plan, update the latest scheduling plan and execute it;

[0080] Step 7: Determine whether all workpieces are completed. If they are, end; otherwise, jump to Step 2.

[0081] When disturbance events such as emergency order insertion occur in the workshop, click on the Figure 2 dynamic event processing box, select the type of disturbance event in the selection bar, and the system can process the dynamic working condition changes according to the selected disturbance event category.

[0082] When there is a problem that the special disturbance event or excessive disturbance causes an excessive delay in the actual completion time, a prompt will automatically pop up on the current interface asking whether to perform rescheduling. Enterprise staff can judge whether to execute the rescheduling strategy according to the needs of the workshop. The processing process of the emergency order insertion disturbance event is expanded below.

[0083] When an emergency order insertion disturbance event occurs, by clicking the emergency order insertion button in the dynamic event processing box, you can jump to the interface of the emergency work order to be processed, as Figure 3 shown. After checking the work orders for emergency processing, you can manually execute rescheduling. The scheduling system will integrate the current workshop order progress and equipment status and consider the target deviation after the plan change to generate a reasonable rescheduling plan.

[0084] Technical effects:

[0085] By constructing a dynamic scheduling model for the weaving workshop, designing an adaptive rescheduling strategy based on the workpiece tolerance coefficient, analyzing the disturbance events and taking the order as the disturbance factor, classifying the orders by level, introducing the workpiece deviation time into the multi-objective static scheduling model to construct a dynamic scheduling model; using the workpiece tolerance coefficient and periodic rescheduling to online identify different types of order disturbances, and proposing corresponding rescheduling strategies to solve the dynamic scheduling problem;

[0086] In summary, it can effectively maintain the steady-state balance of the production scheduling in the weaving workshop caused by frequent rescheduling of order tasks, and the technical effect that the average workpiece deviation time of the adaptive rescheduling plan is much less than that of the complete rescheduling.

[0087] The parts not described in this invention are applicable to the prior art.

Claims

1. A dynamic scheduling method for an intelligent loom workshop, characterized in that: The dynamic scheduling method comprises the following steps: Step 1: Generate an initial scheduling plan based on completion time, total energy consumption and shunting times as scheduling targets and execute it; Step 2: Determine whether a disturbance event occurs. If yes, proceed to the next step; otherwise, jump to step 4. Step 3: Determine the level of the current order disturbance event and calculate the workpiece delay tolerance coefficient of the current order disturbance event. If the workpiece delay tolerance coefficient is greater than 100%, jump to step 5, otherwise adjust the current scheduling cycle time; Step 4: Determine whether the periodic scheduling time has been reached. If so, proceed to the next step; otherwise, continue to execute the current latest scheduling plan; Step 5: Adopt corresponding dynamic scheduling methods for different levels of order disturbance events; Step 6: Establish a dynamic scheduling optimization model with completion time, total energy consumption, shunting times and workpiece deviation time as targets, generate a rescheduling plan based on the improved grey wolf algorithm, update the latest scheduling plan and execute it; Step 7: Determine whether all workpieces are completed. If they are completed, end; otherwise, jump to step 2.

2. The dynamic scheduling method of an intelligent loom workshop according to claim 1 is characterized in that: The order disturbance event level is divided into three levels according to the impact of the order disturbance event on the production line, and from low to high, they are slight disturbance event, moderate disturbance event and severe disturbance event.

3. The dynamic scheduling method of an intelligent loom workshop according to claim 2 is characterized in that: The minor disturbance event refers to a disturbance event that reduces the effect of the current scheduling plan, has little impact on actual production, and reduces the original task; The moderate disturbance event is a disturbance event that requires adjustment to the current scheduling plan and improves the original task; The severe disturbance event is a disturbance event that requires expedited scheduling of the original processing order, has a large impact, and causes changes to the original task.

4. The dynamic scheduling method of an intelligent loom workshop according to claim 3 is characterized in that: The minor disturbance event includes canceling an order; the moderate disturbance event includes inserting an order; and the severe disturbance event includes expedited orders.

5. The dynamic scheduling method of an intelligent loom workshop according to claim 1 is characterized in that: The dynamic scheduling method adopts a combination of periodic rescheduling and event-driven rescheduling. The periodic rescheduling is to rescheduling the scheduling system once at a certain time interval to achieve the scheduling of invisible disturbance events; the event-driven rescheduling is to drive the scheduling of explicit disturbance events with events.

6. The dynamic scheduling method of an intelligent loom workshop according to claim 1 is characterized in that: The scheduling time is determined based on the workpiece tolerance coefficient adaptive rescheduling strategy, which is as follows: Construct the disturbance order workpiece set R, the current scheduling cycle time T p Set to the completion time of the initial scheduling plan; When an order disturbance event occurs, determine the current order disturbance event level and calculate the workpiece tolerance coefficient S of the current disturbance event; Workpiece tolerance coefficient S, current scheduling cycle time T p and the disturbance level coefficient α r They are obtained from the following formulas (1), (2) and (3): In the above formula, η represents the workpiece tolerance configuration coefficient, which is determined according to the current production situation of the manufacturing system; r represents the disturbance level coefficient of each disturbed workpiece; represents the average processing time of the corresponding process of the disturbed workpiece; T represents the remaining time of the current schedule, and R represents the set of workpieces of the current disturbance event; In the above formula, β represents the scheduling cycle coefficient, which is adjusted according to the current manufacturing system productivity, T p , indicating the last scheduling cycle time; In the above formula, α r It indicates the current value of the disturbance level coefficient, which indicates the degree of resistance of the manufacturing system to order disturbance events of different degrees. The larger the disturbance level coefficient, the faster the response to the disturbance. It can be adjusted appropriately according to the actual situation.

7. A dynamic scheduling method for an intelligent loom workshop according to claim 6, characterized in that: When the workpiece tolerance coefficient S>100%, the current order disturbance event has a greater impact on the production line, and the initial scheduling plan can no longer meet the current production needs. In order to ensure that subsequent production can proceed normally, the event scheduling strategy is used to trigger dynamic scheduling and determine the current dynamic scheduling time point; When the workpiece tolerance coefficient S ≤ 100%, the impact of the current order disturbance event on the production line is small and within an acceptable range. In order to reduce the number of dynamic scheduling times, the initial scheduling plan will continue to be executed, while changing the current scheduling cycle time T p , until the periodic scheduling triggers the dynamic scheduling, then the periodic scheduling time point is the current dynamic scheduling time point.

8. The dynamic scheduling method of an intelligent loom workshop according to claim 3 is characterized in that: The dynamic scheduling methods include right shift rescheduling, partial rescheduling and full rescheduling; The severe disturbance event is resolved by complete rescheduling; For the moderate disturbance event, first try the partial rescheduling, then compare it with the complete rescheduling plan and choose the plan with the smaller change; For the minor disturbance event, the scheduling change P of right-shift rescheduling and complete rescheduling is compared, and the plan with the smaller change is selected as the new scheduling plan, where P is obtained by formula (4); In the above formula, M pik represents the coefficient of machine selection before and after scheduling, T represents the initial maximum completion time, T L represents the maximum completion time after scheduling, γ1 and γ2 are the balance coefficients between completion time and processing machine selection; Among them, M pik From formula (5), we can get: In the above formula, M ikj represents the processing machine selected before scheduling, M i , kj Indicates the processing machine selected after scheduling.

9. The dynamic scheduling method of an intelligent loom workshop according to claim 1 is characterized in that: The construction of the dynamic scheduling optimization model is specifically as follows: setting constraints on the time status of workpieces and equipment: For an artifact collection: At the moment of disturbance event, all workpieces are divided into processed workpieces, workpieces being processed, workpieces not processed, and workpieces to be processed according to the current workpiece information; The unprocessed workpiece refers to a warp beam workpiece that is already in the scheduling plan but has not yet been processed; The workpiece to be processed refers to a new workpiece for which a scheduling plan has not yet been arranged; For the workpiece being processed, if the current process has been started, the remaining processing time of the process is regarded as the release time of the current workpiece; if the current process has not been started, the start time of the current rescheduling moment is set as the release time of the current workpiece; For processing equipment collection: For the equipment that is processing the workpiece, the remaining completion time of the current process is the release time of the equipment, while the workpiece and equipment sets in other states use the rescheduling moment as their release time.

10. A dynamic scheduling method for an intelligent loom workshop according to claim 9, characterized in that: The scheduling satisfies the flexible feature and is optimized by adding the goal of minimizing the workpiece deviation time.

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