Processing instruction issuing and equipment running state monitoring method based on MES system
Patent Information
- Application Number
- CN202611168744.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-04
- Publication Date
- 2026-10-30
AI Technical Summary
[0004]加工任务执行过程中，当设备运行状态发生变化后，现有MES系统又缺少结合设备接续关系以及设备实时运行状态的动态调整机制，难以对后续加工设备的接续顺序进行实时优化，容易造成设备负载分布不均衡、加工等待时间延长以及任务流转灵活性不足，进而影响整体加工效率
[0007]本发明中提供的技术方案，至少具有如下技术效果或优点：针对现有MES系统在加工任务调度过程中存在设备接续协同性不足、设备运行状态与加工任务接续过程缺少联动以及加工任务动态调整能力不足的问题，通过获取加工任务工序执行记录与加工设备运行状态参数，统计不同加工设备之间的工序接续关系，并结合加工设备实时运行状态动态计算设备接续优先值，实现加工任务接续顺序的动态优化调整，提高加工设备之间的协同接续能力以及整体加工效率。具体而言，通过对加工任务工序执行记录进行分析，提取加工任务在不同加工设备之间形成的设备接续关系对，并基于设备接续关系对计算各加工设备之间的加工协同关联值，用于表征不同加工设备之间的加工接续关联程度；基于各加工设备之间的加工协同关联值构建设备工序接续关联矩阵，为后续候选设备筛选以及设备接续优先值计算提供关联基础；根据当前加工任务对应的当前工序以及设备工序接续关联矩阵，确定当前执行加工设备对应的候选设备以及对应的加工协同关联值，并结合各加工设备的实时运行状态参数计算各候选设备的设备接续优先值，实现对后续加工设备的动态优选；按照各候选设备的设备接续优先值确定目标设备，并向目标设备下发加工指令，实现加工任务在不同加工设备之间的动态接续调度；在目标设备执行加工过程中，当各候选设备的任一运行状态参数超过对应阈值时，重新计算各候选设备的设备接续优先值，实现加工任务接续过程中的动态调整能力，提高加工任务流转的实时性与灵活性。
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Abstract
Description
Technical Field
[0001] This invention relates to the field of production and manufacturing control technology, specifically to a method for issuing processing instructions and monitoring equipment operating status based on a MES system. Background Technology
[0002] MES (Manufacturing Execution System) is a core system used to manage processing tasks, process flow, and equipment operation in the manufacturing process. It has been widely used in machining, automated production lines, and discrete manufacturing. Existing MES systems typically issue processing instructions to processing equipment according to a preset process route and perform task flow according to a fixed process sequence.
[0003] Existing MES systems primarily allocate processing steps based on preset process paths or the current availability of equipment during task scheduling. They lack correlation analysis of the process succession relationships between different processing devices during actual production, making it difficult to dynamically select subsequent processing equipment based on historical equipment flow patterns. While existing MES systems can collect operational status information such as equipment load and continuous operating time, this information is mainly used for equipment monitoring and is not linked to the processing task succession process. Therefore, even when some processing equipment is operating under high load or for extended periods, it may still receive new processing tasks.
[0004] During the execution of processing tasks, when the operating status of the equipment changes, the existing MES system lacks a dynamic adjustment mechanism that combines the equipment succession relationship and the real-time operating status of the equipment. It is difficult to optimize the succession sequence of subsequent processing equipment in real time, which can easily lead to uneven equipment load distribution, extended processing waiting time, and insufficient flexibility in task flow, thereby affecting the overall processing efficiency. Summary of the Invention
[0005] To address the aforementioned issues, this invention proposes a method for issuing processing instructions and monitoring equipment operating status based on a MES system. By constructing a process sequence association relationship between equipment and combining it with the real-time operating status of the processing equipment to dynamically calculate the priority of candidate equipment, the method achieves dynamic optimization and adjustment of the processing task sequence, thereby improving the collaborative continuity capability between processing equipment and the overall processing efficiency.
[0006] To achieve the above objectives, this invention provides a method for issuing processing instructions and monitoring equipment operating status based on a MES system, comprising the following steps: Obtain the process execution records of the processing tasks in the MES system, and collect the operating status parameters of each processing device in real time; Based on the process execution records of the processing tasks, the process succession relationship between different processing equipment is statistically analyzed to form equipment succession relationship pairs, and the processing synergy correlation value between each processing equipment is calculated based on the equipment succession relationship pairs; Based on the processing collaboration correlation values between each processing equipment, construct the equipment process succession correlation matrix; Based on the current process corresponding to the current processing task and the equipment process succession association matrix, determine the candidate equipment for the current processing equipment, as well as the processing collaboration association value between the current processing equipment and each candidate equipment. Combined with the real-time operating status parameters of each processing equipment, calculate the equipment succession priority value of each candidate equipment. The candidate devices are sorted according to their priority values, the target device is determined, and a processing instruction is issued to the target device. During the processing of the target equipment, when any operating status parameter of each candidate equipment exceeds the corresponding threshold, the equipment succession priority value of each candidate equipment is recalculated, and the processing instruction is reissued through the MES system.
[0007] The technical solution provided in this invention has at least the following technical effects or advantages: Addressing the problems of insufficient equipment continuity coordination, lack of linkage between equipment operating status and processing task continuity process, and insufficient dynamic adjustment capability of processing tasks in existing MES systems during processing task scheduling, this invention obtains processing task execution records and processing equipment operating status parameters, statistically analyzes the continuity relationships between different processing equipment, and dynamically calculates equipment continuity priority values based on the real-time operating status of the processing equipment. This enables dynamic optimization and adjustment of the processing task continuity sequence, improving the collaborative continuity capability between processing equipment and overall processing efficiency. Specifically, by analyzing the execution records of processing tasks, the system extracts equipment succession pairs formed between different processing devices. Based on these pairs, it calculates the processing collaboration correlation value between each processing device to characterize the degree of processing succession correlation between different devices. A device process succession correlation matrix is constructed based on the processing collaboration correlation values, providing a foundation for subsequent candidate device selection and equipment succession priority calculation. According to the current process corresponding to the current processing task and the equipment process succession correlation matrix, the system determines the candidate devices and their corresponding processing collaboration correlation values corresponding to the currently executing processing device. It then calculates the equipment succession priority value for each candidate device based on the real-time operating status parameters of each processing device, enabling dynamic optimization of subsequent processing devices. The system determines the target device according to the equipment succession priority value of each candidate device and issues processing instructions to the target device, achieving dynamic succession scheduling of processing tasks between different processing devices. During the processing of the target device, if any operating status parameter of a candidate device exceeds the corresponding threshold, the equipment succession priority value of each candidate device is recalculated, enabling dynamic adjustment during the processing task succession process and improving the real-time performance and flexibility of processing task flow.
[0008] Compared with existing technologies, this invention achieves dynamic optimization of the sequence of processing tasks by associating the processing task sequence with the equipment operating status parameters, thereby improving the collaborative continuity capability between processing equipment, equipment utilization, and overall processing efficiency. Attached Figure Description
[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0010] Figure 1 A flowchart illustrating a method for issuing processing instructions and monitoring equipment operating status based on a MES system, provided in this application embodiment; Detailed Implementation This invention introduces statistical analysis of processing task sequence relationships and calculation of equipment collaborative correlation values, and combines equipment operating status parameters to dynamically determine the priority value of processing equipment sequence. It proposes a method for issuing processing instructions and monitoring equipment operating status based on the MES system, which solves the problems of lack of quantitative expression of processing equipment sequence relationships, lack of participation of equipment operating status in scheduling decisions, and inability to dynamically adjust the sequence of processing tasks according to equipment status in the traditional MES scheduling process, resulting in uneven equipment load distribution and low processing task flow efficiency.
[0011] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.
[0012] It should be noted that the terms "first," "second," etc., used in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices.
[0013] Example 1, as Figure 1 As shown, a method for issuing processing instructions and monitoring equipment operating status based on a MES system includes the following steps: S1. Obtain the process execution records of the processing tasks in the MES system, and collect the operating status parameters of each processing device in real time. Furthermore, the processing task execution record includes the processing task identifier, process number, process execution sequence, and corresponding processing equipment number; the operating status parameters include equipment operating load and equipment running time.
[0014] Specifically, firstly, the MES system generates processing tasks based on production plans or work order information and assigns a unique processing task identifier to each task. The MES system then issues process execution instructions to the corresponding processing equipment according to the processing task identifier and records the process execution to form a processing task process execution record. This record includes the processing task identifier, process number, process execution sequence, and the corresponding processing equipment number. The processing task process execution records are then stored in association according to the processing task identifier, so that each processing task identifier corresponds to a complete set of process execution records.
[0015] Meanwhile, through the device data acquisition interface connected to the MES system, the operating status parameters of each processing device are obtained in real time. The operating status parameters include the operating load and the running time. The operating status parameters are associated with the corresponding processing device based on the processing device number to form a set of operating status parameter data for each processing device.
[0016] S2. Based on the processing task execution records, statistically analyze the process succession relationships between different processing equipment to form equipment succession relationship pairs, and calculate the processing collaboration correlation value between each processing equipment based on the equipment succession relationship pairs. Furthermore, based on the processing task execution records, the process sequence relationships between different processing equipment are statistically analyzed to form equipment sequence relationship pairs, including... The process execution records for each processing task are arranged in the order of process execution to obtain the process execution sequence corresponding to that processing task. For each processing task, the corresponding processing equipment number is extracted according to the execution order of adjacent processes to form equipment succession pairs.
[0017] Furthermore, based on the equipment connection relationship, the processing coordination correlation value between each processing device is calculated, including: Summarize the equipment succession pairs corresponding to all processing tasks, count the number of times each pair of processing equipment appears in all processing tasks, and count the total number of times each processing equipment appears as a preceding processing equipment in all processing tasks. Based on the statistical results, calculate the process succession relationship value between processing equipment in the equipment succession pair. The processing collaboration correlation value between the processing equipment is obtained by comprehensively calculating the connection relationship value between two processing equipment in the equipment connection relationship pair.
[0018] Specifically, based on the processing task identifier, the process execution records of processing tasks belonging to the same processing task are merged, so that the process execution records of the same processing task are concentrated in the same group; within each processing task group, the process execution records are sorted according to the process execution order to obtain the processing task process execution sequence corresponding to the processing task. The processing task process execution sequence is used to characterize the actual flow order of the processing equipment involved in the execution of the processing task. For each processing task, the sequence of operations is sequentially scanned. According to the sequential relationship between two adjacent operations, the corresponding processing equipment number is extracted to form a pair of equipment succession relationships (i,j), where i represents the number of the preceding processing equipment and j represents the number of the following processing equipment. The pair of equipment succession relationships (i,j) represents the actual flow relationship from the previous processing equipment to the next processing equipment during the execution of the processing task. Summarize all equipment succession pairs corresponding to processing tasks. For each equipment succession pair (i,j), count the number of times it appears in all processing tasks, N(i,j). N(i,j) represents the actual number of times the process flow from processing equipment i to processing equipment j occurs during the execution of all processing tasks. At the same time, count the total number of times processing equipment i appears as a preceding processing equipment in all equipment succession pairs, N(i). N(i) represents the actual number of times processing equipment i participates in subsequent processes as a "preceding processing equipment" during the execution of all processing tasks. Based on the statistical results, calculate the process succession value R(i,j) of any equipment succession pair (i,j), R(i,j) = N(i,j) / N(i), where R(i,j) represents the probability of processing equipment i succeeding processing equipment j. In the boundary case, when N(i)=0, R(i,j) is 0. For processing equipment i and processing equipment j in the equipment connection relationship pair (i,j), the connection relationship value R(i, j) of processing equipment i to processing equipment j and the connection relationship value R(j, i) of processing equipment j to processing equipment i are combined and calculated to obtain the processing collaboration association value C(i, j) of processing equipment i and processing equipment j; C(i, j) = R(i, j) + R(j, i), C(i, j) is used to characterize the degree of bidirectional collaboration between the two processing equipment. The larger the value, the higher the frequency of mutual connection between the two in the processing task flow.
[0019] Finally, a set of processing collaboration association values between processing equipment is obtained and stored in the MES system database in the form of equipment succession relationship pairs. Each record includes the preceding processing equipment number, the subsequent processing equipment number and the corresponding C(i,j) value.
[0020] S3. Based on the processing collaboration correlation values between each processing device, construct an equipment process succession correlation matrix. Specifically, based on the processing equipment number and the corresponding processing collaboration association value C(i,j), an M×M two-dimensional matrix is constructed, where the row index of the matrix corresponds to the previous processing equipment number, the column index corresponds to the subsequent processing equipment number, and M represents the maximum sequence number of the processing equipment number; For each device connection pair (i,j), its processing collaboration association value C(i,j) is filled into the position of the i-th row and j-th column of the matrix, which represents the collaboration strength of processing device i connecting to processing device j. For device connection pairs (i,j) that do not appear, that is, processing device i and processing device j do not flow in all processing tasks, the corresponding matrix element is set to 0, indicating that there is no connection collaboration between the two. Finally, a complete equipment process sequence association matrix is obtained. Each matrix element contains a processing collaboration association value C(i,j), which is used to characterize the degree of bidirectional collaboration between any two processing devices. The equipment process sequence association matrix is stored in the MES system database in structured data form. When a processing task is completed or a new processing task is added, the processing collaboration association value C(i,j) is recalculated and the corresponding elements of the matrix are updated.
[0021] S4. Based on the current process corresponding to the current processing task and the equipment process succession association matrix, determine the candidate equipment for the currently executing processing equipment, as well as the processing collaboration association value between the currently executing processing equipment and each candidate equipment. Combined with the real-time operating status parameters of each processing equipment, calculate the equipment succession priority value for each candidate equipment. Further, the equipment succession priority value of each candidate device is calculated, including, Based on the processing task execution records in the MES system, the current processing task and the currently executing processing equipment are obtained through the processing task identifier; Based on the equipment process sequence association matrix, candidate equipment for the currently executing processing equipment and the processing collaboration association values between the currently executing processing equipment and each candidate equipment are determined; Obtain the operating load and runtime of each candidate device, and calculate the load priority factor and fatigue priority factor for each candidate device respectively; Based on the processing collaboration correlation value between the current processing equipment and the candidate equipment, the load priority factor and fatigue priority factor of the candidate equipment, calculate the equipment succession priority value of each candidate equipment.
[0022] Furthermore, the load priority factor and fatigue priority factor of each candidate device are calculated, including, The operating load L and runtime T are subjected to maximum normalization, mapping the operating load L and runtime T to the normalized interval [0,1] to obtain the relative load value L of the candidate device. nor and the relative value of runtime T nor Among them, the load priority factor Lfac =1-L nor Fatigue priority factor T fac (j)=1-T nor .
[0023] Furthermore, the formula for calculating the equipment priority value P of the candidate equipment is: P = C × L fac ×T fac Where C is the processing collaboration association value between the currently executing processing equipment and the candidate equipment.
[0024] Specifically, the current processing task is obtained based on the processing task identifier in the processing task execution record issued by the MES system, and the currently executing processing device d_ is obtained based on the processing task execution record corresponding to the current processing task. cur ;d_ cur This indicates the processing equipment number for the current processing task, and its value ranges from 1 to M. Extract the currently executing processing equipment d_ from the equipment process sequence association matrix. cur The processing collaboration association value C(d_) with the processing device j in the corresponding row index cur ,j), will C(d_ cur The processing device j in the row index corresponding to (j)>0 is selected as candidate device j, and a candidate device set E_c is formed. The operating load L(j) and runtime T(j) of each candidate device j are obtained from the set of operating status parameter data of the processing equipment. The operating load L(j) and runtime T(j) are then normalized to their maximum values and mapped to the standardized interval [0,1] to obtain the relative load value L of candidate device j. nor (j) and the relative value of runtime T nor (j), where the relative load value L nor (j)=L(j) / L max L max The runtime load of the candidate device with the highest runtime load in the candidate device set E_c; the relative runtime value T. nor (j)=T(j) / T max T max The runtime of the candidate device with the longest runtime in the candidate device set E_c. Based on the relative load value L of candidate device j nor (j) and the relative value of runtime T nor (j), and calculate the load priority factor L for candidate device j respectively. fac (j) and fatigue priority factor T fac (j), Load priority factor Lfac (j)=1-L nor (j), L fac The larger the value of (j), the lower the operating load of candidate device j, and the higher its priority for continuous processing. Fatigue priority factor T fac (j)=1-T nor (j), T fac The larger the value of (j), the shorter the running time of candidate device j, and the higher the priority of continuous processing. Based on the currently executing processing equipment d_ cur Using the processing synergy correlation value between candidate equipment j and candidate equipment j, the load priority factor and fatigue priority factor of candidate equipment j, calculate the equipment succession priority value P(j) of candidate equipment j, P(j) = C(d_ cur ,j)×L fac (j)×T fac The larger P(j) is, the more suitable candidate device j is to take over the next process of the current processing task.
[0025] S5. Sort the candidate devices according to their priority values, determine the target device, and issue processing instructions to the target device. Specifically, all candidate devices in the candidate device set E_c are sorted from largest to smallest according to their corresponding device succession priority value P(j), forming an ordered list E_sorted. The devices with higher rankings indicate higher priority for subsequent processing. The first candidate device in the E_sorted list is selected as the target device D_tar, and the processing instruction corresponding to the current processing task is issued to the target device D_tar. The processing instruction includes the processing task identifier, the current process number, the process execution order, and the processing parameters. At the same time, the issuance time of the processing instruction and the target device number are recorded in the MES system for subsequent execution status tracking and operation status monitoring. The target device D_tar is then associated with the current processing task.
[0026] S6. During the processing of the target equipment, if any operating status parameter of any candidate equipment exceeds the corresponding threshold, the equipment succession priority value of each candidate equipment is recalculated, and the processing instruction is reissued through the MES system. Specifically, during the execution of the current processing task corresponding to the target device D_tar, the real-time operating status parameters of each candidate device in the candidate device set E_c are continuously acquired, including operating load and runtime. When the MES system detects that the operating load of any candidate device in the candidate device set E_c exceeds the operating load threshold or the runtime exceeds the runtime threshold, it triggers a recalculation of the currently executing processing device d_tar. curThe processing collaboration correlation value C(d_) between candidate device j and the candidate device j cur The load priority factor L of candidate device j. fac (j) and fatigue priority factor T fac (j), and recalculate the device succession priority value P(j) of candidate device j, and based on the updated device succession priority value P(j) of candidate device j, sort all candidate devices in the candidate device set E_c in descending order according to their corresponding device succession priority value P(j), determine the new target device D_tar, and issue the processing instruction corresponding to the current processing task to the new target device. At the same time, record the issuance time, target device number and updated device succession priority value of candidate device j in the MES system.
[0027] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A method for issuing processing instructions and monitoring equipment operating status based on a MES system, characterized in that, Includes the following steps, Obtain the process execution records of the processing tasks in the MES system, and collect the operating status parameters of each processing device in real time; Based on the process execution records of the processing tasks, the process succession relationship between different processing equipment is statistically analyzed to form equipment succession relationship pairs, and the processing synergy correlation value between each processing equipment is calculated based on the equipment succession relationship pairs; Based on the processing collaboration correlation values between each processing equipment, construct the equipment process succession correlation matrix; Based on the current process corresponding to the current processing task and the equipment process succession association matrix, determine the candidate equipment for the current processing equipment, as well as the processing collaboration association value between the current processing equipment and each candidate equipment. Combined with the real-time operating status parameters of each processing equipment, calculate the equipment succession priority value of each candidate equipment. The candidate devices are sorted according to their priority values for device succession, the target device is determined, and a processing instruction is issued to the target device. During the processing of the target equipment, when any operating status parameter of each candidate equipment exceeds the corresponding threshold, the equipment succession priority value of each candidate equipment is recalculated, and the processing instruction is reissued through the MES system.
2. The method for issuing processing instructions and monitoring equipment operating status based on a MES system according to claim 1, characterized in that, The processing task execution record includes the processing task identifier, process number, process execution sequence, and corresponding processing equipment number; The operating status parameters include the device operating load and the device operating duration.
3. The method for issuing processing instructions and monitoring equipment operating status based on a MES system according to claim 2, characterized in that, The step involves statistically analyzing the process sequence relationships between different processing devices based on the processing task execution records, forming device sequence relationship pairs, including... The process execution records for each processing task are arranged in the order of process execution to obtain the process execution sequence corresponding to that processing task. For each processing task, the corresponding processing equipment number is extracted according to the execution order of adjacent processes to form equipment succession pairs.
4. The method for issuing processing instructions and monitoring equipment operating status based on a MES system according to claim 3, characterized in that, The calculation of the processing coordination correlation value between each processing device based on the device connection relationship includes, Summarize the equipment succession pairs corresponding to all processing tasks, count the number of times each pair of processing equipment appears in all processing tasks, and count the total number of times each processing equipment appears as a preceding processing equipment in all processing tasks. Based on the statistical results, calculate the process succession relationship value between processing equipment in the equipment succession pair. The processing collaboration correlation value between the processing equipment is obtained by comprehensively calculating the connection relationship value between two processing equipment in the equipment connection relationship pair.
5. The method for issuing processing instructions and monitoring equipment operating status based on a MES system according to claim 4, characterized in that, The calculation of the device succession priority value for each candidate device includes, Based on the processing task execution records in the MES system, the current processing task and the currently executing processing equipment are obtained through the processing task identifier; Based on the equipment process sequence association matrix, candidate equipment for the currently executing processing equipment and the processing collaboration association values between the currently executing processing equipment and each candidate equipment are determined; Obtain the operating load and runtime of each candidate device, and calculate the load priority factor and fatigue priority factor for each candidate device respectively; Based on the processing collaboration correlation value between the current processing equipment and the candidate equipment, the load priority factor and fatigue priority factor of the candidate equipment, calculate the equipment succession priority value of each candidate equipment.
6. The method for issuing processing instructions and monitoring equipment operating status based on a MES system according to claim 5, characterized in that, The calculation of the load priority factor and fatigue priority factor for each candidate device includes, The operating load L and runtime T are subjected to maximum normalization, mapping the operating load L and runtime T to the normalized interval [0,1] to obtain the relative load value L of the candidate device. nor and the relative value of runtime T nor Among them, the load priority factor L fac =1-L nor Fatigue priority factor T fac (j)=1-T nor .
7. The method for issuing processing instructions and monitoring equipment operating status based on a MES system according to claim 6, characterized in that, The formula for calculating the device succession priority value P of the candidate device is: P = C × L fac ×T fac Where C is the processing collaboration association value between the currently executing processing equipment and the candidate equipment.