Multi-device and multi-task cutting scheduling method and system

Abstract

The invention provides a multi-device and multi-task cutting scheduling method. The method comprises the following steps: S10, receiving and analyzing tasks; s20, performing priority analysis; s30, equipment state monitoring and scheduling; s40, controlling the cutting process; according to the invention, through an intelligent scheduling algorithm and a substation type control strategy, efficient execution of multiple tasks is realized, and the production efficiency is improved; a high-precision positioning device and a cutting device are adopted, sensor monitoring and optimal path planning are combined, the cutting precision and quality are ensured, and precise cutting is achieved; through a substation type control strategy, time sequence correlation but mutual independent operation of each device is realized, and the overall cooperation efficiency is improved; an optimal path algorithm is adopted for cutting path planning, so that the cutting time is shortened, and the cutting efficiency is improved; rich data analysis functions are provided, production decision optimization is supported, and the overall competitiveness is improved.

Description

Technical Field

[0001] This invention relates to the field of cutting equipment technology, specifically to a multi-device, multi-task cutting scheduling method and system. Background Technology

[0002] With the rapid development of the textile industry, fabric cutting, as a crucial step in the production of apparel and home textiles, directly impacts the market competitiveness of products through its efficiency and quality. Multifunctional fabric cutting tables, as core equipment in modern cutting technology, not only need to efficiently and accurately complete the cutting of various fabrics but also require excellent multi-tasking capabilities to adapt to rapidly changing market demands and personalized customization trends, especially in production environments where multiple machines operate collaboratively. A company may have multiple identical cutting machines, and rationally allocating tasks to each machine under multi-tasking conditions is essential. Therefore, designing a cutting scheduling method and system that can efficiently schedule multiple tasks, optimize resource utilization, and improve overall production efficiency has become crucial for the transformation and upgrading of the textile industry.

[0003] Existing multi-device, multi-task shaving and scheduling devices have the following main problems:

[0004] ① Poor integration, making seamless integration with existing enterprise IT infrastructure difficult; high complexity in scheduling issues, poor timing coordination among multiple devices, prone to malfunctions; ② Insufficient system scalability and flexibility, problems in equipment scheduling, lack of reasonable application strategies for tailored tasks and equipment, low equipment utilization, and difficulty in adapting to future enterprise development; ③ Lack of intelligent and automated support, excessive manual intervention, affecting scheduling efficiency and accuracy. Therefore, the design of a new system should focus on addressing these issues to improve scheduling efficiency and effectiveness. Summary of the Invention

[0005] The purpose of this invention is to solve the aforementioned problems existing in the prior art. This invention provides the following technical solution:

[0006] A multi-device, multi-task simplification and scheduling method includes the following steps:

[0007] S10. Task reception and parsing: Receive cutting tasks from the production management system, parse task requirements and fabric characteristics, including fabric type, cutting shape, and size.

[0008] S20. Priority Analysis: Determine task priorities based on task requirements;

[0009] S30, Equipment Status Monitoring and Scheduling;

[0010] Specifically, the steps are as follows: S31, real-time monitoring of the working status of the cutting machine tool; S32, scheduling the cutting tasks of the cutting machine tool according to the task priority, equipment working status and fabric characteristics; S33, scheduling the sharpening device to perform blade maintenance tasks according to the real-time monitoring of the working status of the cutting machine tool and the cutting tasks.

[0011] S40, Cutting process control;

[0012] Specifically, the steps include: S41, planning the cutting path using the optimal path algorithm according to the scheduled cutting task, and conveying the fabric; S42, adjusting the cutting parameters according to the planned cutting path and performing cutting; S43, performing blade maintenance according to the scheduled blade maintenance task; S44, adopting a substation control strategy to achieve timing control and coordination of the fabric conveying device, high-precision positioning device, cutting device and sharpening device; S45, data recording and analysis.

[0013] Further optimized, in step S20, the task priority analysis includes: S201, identifying different delivery date requirements; S202, classifying different levels according to delivery date requirements and confirming the priority of cutting batches; S203, confirming the process requirements for each batch based on the analyzed task requirements and fabric characteristics, the process requirements including equipment requirements, cuttable size requirements, punching and blade requirements, negative pressure and cooling requirements; S204, obtaining the task time based on the process requirements, determining whether each batch meets the delivery date requirements and providing feedback.

[0014] Further preferably, in step S31, the working state of the cutting machine tool includes the working states of the fabric conveying device, the high-precision positioning device, the cutting device, and the sharpening device.

[0015] S32 specifically includes the following steps: The cutting task is first formulated according to the priority level, and a cutting plan is formulated according to the confirmed process requirements and the corresponding cutting equipment is arranged. The cutting task is formulated for each level.

[0016] S33 specifically includes the following steps: The blade maintenance task is first formulated based on real-time monitoring of the working status of the cutting machine tool. When the equipment is idle and the cutting task is completed at a certain level, the sharpening device is scheduled to perform blade maintenance.

[0017] The present invention also provides a multi-device, multi-task cutting scheduling system, the system including a cutting machine tool, a sharpening device, sensors and controllers, and an alarm device. The cutting machine tool includes a fabric conveying device, a high-precision positioning device, and a cutting device. The sharpening device is independently set on one side of the cutting head of the cutting device. The sensors and controller include a position sensor and a pressure sensor.

[0018] Further optimization includes a multi-task scheduling module, a substation control module, an optimal path planning module, an equipment monitoring and maintenance module, and a data management and analysis module. The multi-task scheduling module receives cutting tasks and performs intelligent scheduling based on factors such as task priority and equipment status. The substation control module implements time-related but independent control of the fabric conveying device, high-precision positioning device, cutting device, and sharpening device. The optimal path planning module plans the cutting path using an optimal path algorithm based on the cutting task requirements and fabric characteristics. The data management and analysis module stores cutting task data and equipment status data.

[0019] This invention discloses a multi-device, multi-task cutting scheduling method and system. Through intelligent scheduling algorithms and a station-based control strategy, it achieves efficient execution of multiple tasks, improving production efficiency. It employs high-precision positioning and cutting devices, combined with sensor monitoring and optimal path planning, to ensure cutting accuracy and quality, achieving precise cutting. The station-based control strategy enables time-related but independent operations of each device, improving overall collaborative efficiency. The optimal path algorithm is used for cutting path planning, reducing cutting time and improving cutting efficiency. It provides rich data analysis functions to support production decision optimization and enhance overall competitiveness.

[0020] This solution integrates fabric conveying devices, high-precision positioning devices, cutting devices, and sharpening devices, and combines intelligent scheduling algorithms, substation control strategies, optimal path planning algorithms, and data analysis functions to construct an efficient, accurate, and automated multi-device, multi-task cutting scheduling system, providing strong technical support for the modern textile industry. Attached Figure Description

[0021] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] The preferred embodiments of the present invention will now be described in further detail with reference to the accompanying drawings.

[0024] Example 1:

[0025] This invention provides a multi-device, multi-task cutting scheduling method. Each device is a terminal. Due to the requirements of the cutting process, each cutting task may not be optimized when it is issued. The system will re-optimize the cutting sequence or cutting method based on experience and technical requirements to improve cutting efficiency. This invention adopts a station-based control strategy and combines an optimal path algorithm for cutting path planning to achieve time-related but independent operations, meeting the requirements of modern textile industry for high precision, high efficiency, and multi-task processing capabilities in fabric cutting. The specific solution is as follows:

[0026] S10. Task reception and parsing: Receive cutting tasks from the production management system, parse task requirements and fabric characteristics, including fabric type, cutting shape, and size.

[0027] S20. Priority Analysis; Determine task priorities based on task requirements; Task priority analysis includes: S201. Identifying different delivery time requirements; S202. Dividing into different levels according to delivery time requirements and confirming the priority of cutting batches; S203. Based on the analyzed task requirements and fabric characteristics, confirming the process requirements for each batch, including equipment requirements, cuttable size requirements, punching and blade requirements, negative pressure and cooling requirements; S204. Obtaining task time based on process requirements, determining whether each batch meets the delivery time requirements and providing feedback.

[0028] S30, Equipment Status Monitoring and Scheduling;

[0029] Specifically, the steps include: S31, real-time monitoring of the working status of the cutting machine tool; the working status of the cutting machine tool includes the working status of the fabric conveying device, high-precision positioning device, cutting device, and sharpening device. S32, scheduling the cutting tasks of the cutting machine tool according to the task priority, equipment working status, and fabric characteristics; the formulation of the cutting tasks is first carried out according to the priority level, and a cutting plan is formulated according to the confirmed process requirements, and corresponding cutting equipment is arranged, completing the cutting task formulation for each level. S33, scheduling the sharpening device to perform blade maintenance tasks based on real-time monitoring of the cutting machine tool's working status and cutting tasks; the formulation of the blade maintenance tasks is first based on real-time monitoring of the cutting machine tool's working status, and when the equipment is idle and a cutting task at one level is completed, the sharpening device is scheduled to perform blade maintenance.

[0030] S40, Cutting process control;

[0031] Specifically, the steps include: S41, planning the cutting path using the optimal path algorithm according to the scheduled cutting task, and conveying the fabric; S42, adjusting the cutting parameters according to the planned cutting path and performing cutting; S43, performing blade maintenance according to the scheduled blade maintenance task; S44, adopting a substation control strategy to achieve timing control and coordination of the fabric conveying device, high-precision positioning device, cutting device and sharpening device; S45, data recording and analysis.

[0032] The station-based control strategy used in this invention treats each device as an independent terminal, each executing its own cutting task. In practical applications, multiple identical devices A, B, and C are introduced. Under the multi-task scheduling of similar process requirements, assuming device A is in a task, the task can be scheduled to B or C. Similarly, if B is in a maintenance state, the task will be assigned to C. After B's maintenance state ends, the task will continue to be scheduled to B, achieving uninterrupted and continuous optimization of the operation.

[0033] This invention discloses a multi-device, multi-task cutting scheduling method and system. Through intelligent scheduling algorithms and a station-based control strategy, it achieves efficient execution of multiple tasks, improving production efficiency. It employs high-precision positioning and cutting devices, combined with sensor monitoring and optimal path planning, to ensure cutting accuracy and quality, achieving precise cutting. The station-based control strategy enables time-related but independent operations of each device, improving overall collaborative efficiency. The optimal path algorithm is used for cutting path planning, reducing cutting time and improving cutting efficiency. It provides rich data analysis functions to support production decision optimization and enhance overall competitiveness.

[0034] Example 2

[0035] This embodiment provides a multi-device, multi-task cutting scheduling system. The system includes a cutting machine tool, a sharpening device, sensors and controllers, and an alarm device. The cutting machine tool includes a fabric conveying device, a high-precision positioning device, and a cutting device. The sharpening device is independently installed on one side of the cutting head of the cutting device. The sensors and controller include a position sensor and a pressure sensor.

[0036] It also includes a multi-task scheduling module, a substation control module, an optimal path planning module, an equipment monitoring and maintenance module, and a data management and analysis module. The multi-task scheduling module receives cutting tasks and performs intelligent scheduling based on factors such as task priority and equipment status. The substation control module implements time-related but independent control of the fabric conveying device, high-precision positioning device, cutting device, and sharpening device. The optimal path planning module plans the cutting path using an optimal path algorithm based on the cutting task requirements and fabric characteristics. The data management and analysis module stores cutting task data and equipment status data.

[0037] This embodiment integrates a fabric conveying device, a high-precision positioning device, a cutting device, and a sharpening device, and combines intelligent scheduling algorithms, substation control strategies, optimal path planning algorithms, and data analysis functions to construct an efficient, accurate, and automated multi-device, multi-task cutting scheduling system, providing strong technical support for the modern textile industry.

[0038] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A multi-device, multi-task skewing and scheduling method, characterized in that, Includes the following steps: S10. Task reception and parsing: Receive cutting tasks from the production management system, parse task requirements and fabric characteristics, including fabric type, cutting shape, and size. S20. Priority Analysis: Determine task priorities based on task requirements; S30, Equipment Status Monitoring and Scheduling; Specifically, the steps are as follows: S31, real-time monitoring of the working status of the cutting machine tool; S32, scheduling the cutting tasks of the cutting machine tool according to the task priority, equipment working status and fabric characteristics; S33, scheduling the sharpening device to perform blade maintenance tasks according to the real-time monitoring of the working status of the cutting machine tool and the cutting tasks. S40, Cutting process control; Specifically, the steps include: S41, planning the cutting path using the optimal path algorithm according to the scheduled cutting task, and conveying the fabric; S42, adjusting the cutting parameters according to the planned cutting path and performing cutting; S43, performing blade maintenance according to the scheduled blade maintenance task; S44, adopting a substation control strategy to achieve timing control and coordination of the fabric conveying device, high-precision positioning device, cutting device and sharpening device; S45, data recording and analysis.

2. The multi-device, multi-task skewing and scheduling method according to claim 1, characterized in that, In step S20, the task priority analysis includes: S201, identifying different delivery date requirements; S202, classifying different levels according to delivery date requirements and confirming the priority of cutting batches; S203, confirming the process requirements for each batch based on the analyzed task requirements and fabric characteristics, including equipment requirements, cuttable size requirements, punching and blade requirements, negative pressure and cooling requirements; S204, obtaining the task time based on the process requirements, determining whether each batch meets the delivery date requirements and providing feedback.

3. The multi-device, multi-task skewing and scheduling method according to claim 2, characterized in that, In step S31, the working state of the cutting machine tool includes the working state of the fabric conveying device, the high-precision positioning device, the cutting device, and the sharpening device. S32 specifically includes the following steps: The cutting task is first formulated according to the priority level, and a cutting plan is formulated according to the confirmed process requirements and the corresponding cutting equipment is arranged. The cutting task is formulated for each level. S33 specifically includes the following steps: The blade maintenance task is first formulated based on real-time monitoring of the working status of the cutting machine tool. When the equipment is idle and the cutting task is completed at a certain level, the sharpening device is scheduled to perform blade maintenance.

4. A multi-device, multi-task pruning and scheduling system, employing the multi-device, multi-task pruning and scheduling method as described in any one of claims 1-3, characterized in that, The system includes a cutting machine tool, a sharpening device, sensors and controllers, and an alarm device. The cutting machine tool includes a fabric conveying device, a high-precision positioning device, and a cutting device. The sharpening device is independently installed on one side of the cutting head of the cutting device. The sensors and controller include a position sensor and a pressure sensor.

5. The multi-device, multi-task pruning and scheduling system according to claim 4, characterized in that, It also includes a multi-task scheduling module, a substation control module, an optimal path planning module, an equipment monitoring and maintenance module, and a data management and analysis module. The multi-task scheduling module receives cutting tasks and performs intelligent scheduling based on factors such as task priority and equipment status. The substation control module implements time-related but independent control of the fabric conveying device, high-precision positioning device, cutting device, and sharpening device. The optimal path planning module plans the cutting path using an optimal path algorithm based on the cutting task requirements and fabric characteristics. The data management and analysis module stores cutting task data and equipment status data.

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