Digital twin workshop equipment operation double-loop monitoring, prediction and regulation and control method
By using a dual-loop monitoring and prediction method for equipment operation in a digital twin workshop and employing an inner-outer-loop double-triangular ring model, the problem of insufficient assessment of equipment multi-task production capacity is solved. This enables comprehensive monitoring of equipment production status and output prediction, thereby improving equipment utilization and production efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-23
- Publication Date
- 2026-03-24
AI Technical Summary
Existing technologies for real-time monitoring of equipment production capacity only focus on a single production attribute of the equipment, lacking a comprehensive assessment of the equipment's multi-task production capacity. This leads to discrepancies between production plans and actual needs, affecting equipment utilization and production efficiency.
A dual-loop monitoring, prediction, and control method for equipment operation in a digital twin workshop is adopted. Through an inner-outer-loop double-triangular-loop monitoring and prediction model, the equipment production capacity and output are described respectively, realizing real-time monitoring of equipment production status and output prediction.
It enables precise monitoring of equipment production capacity, improves equipment utilization and production efficiency, dynamically adjusts production plans, avoids equipment idleness or failure, and optimizes production management.
Smart Images
Figure CN121723705A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the fields of industrial automation, equipment management and production monitoring technology, and in particular relates to a method for dual-loop monitoring, prediction and control of equipment operation in a digital twin workshop. Background Technology
[0002] In modern manufacturing, real-time monitoring of equipment production capacity is crucial for optimizing production efficiency and ensuring on-time product delivery. However, existing methods typically focus only on a single production attribute of equipment, lacking a comprehensive assessment of its multi-tasking production capabilities. This leads to discrepancies between production plans and actual demand, impacting equipment utilization and production efficiency. Therefore, there is an urgent need for a novel real-time monitoring and prediction method capable of comprehensively evaluating the multi-tasking capabilities of equipment to achieve accurate monitoring and optimized management of equipment production capacity. Summary of the Invention
[0003] The technical problem to be solved by this invention is to overcome the shortcomings of existing real-time monitoring of equipment production capacity, and to propose a dual-loop monitoring, prediction and control method for equipment operation in a digital twin workshop, so as to effectively describe and correlate the "rated-expected-actual" production capacity of the equipment, thereby achieving accurate monitoring of equipment production capacity, and providing strong support for optimizing production management, improving equipment utilization and production efficiency.
[0004] The technical problem solved by this invention is achieved by the following technical solution: a method for dual-loop monitoring, prediction, and control of equipment operation in a digital twin workshop, comprising the following steps:
[0005] Step 1: Classify equipment production attributes, including: classifying and describing the attributes of indicators related to production capacity, production targets, and production execution in real time when the equipment participates in the production and manufacturing process;
[0006] Step 2: Construction of the inner-outer-outer double-triangular ring monitoring and prediction model, including: based on the above attribute classification, constructing a digital twin double-triangular ring monitoring and prediction model, defining the inner ring model as the equipment production capacity triangular monitoring model and the outer ring model as the equipment production quantity triangular monitoring and prediction model;
[0007] Step 3: Real-time production status monitoring of equipment based on the inner loop: Based on the constructed double-triangular ring monitoring and prediction model, the inner loop model is used to realize the real-time production status monitoring of equipment;
[0008] Step 4: Production output prediction based on the outer ring: Based on the constructed double triangular ring monitoring and prediction model, the outer ring model is used to predict production output.
[0009] The advantages of this invention compared to the prior art are:
[0010] (1) This invention proposes a double triangular ring monitoring and prediction model, which can effectively describe the three attributes of “rated-expected-actual” during the production of workshop equipment. It breaks the limitation of existing technologies that only focus on the single production attribute of equipment and find it difficult to effectively evaluate the comprehensive capabilities of equipment in multi-task scenarios, so that the operating status of equipment can be fully displayed.
[0011] (2) The present invention proposes a real-time monitoring and prediction method for equipment production capacity based on inner-outer circulation. The inner-loop equipment production capacity triangle model realizes the comprehensive consideration of the equipment's own capacity, and the outer-loop equipment production capacity triangle model realizes the comprehensive measurement of production results. It can keep track of the actual output effect and production efficiency level of the equipment in the production process at any time, and can promptly discover problems such as unreasonable equipment task allocation or overload, thereby dynamically adjusting the production plan, avoiding equipment idleness or frequent failures, greatly improving equipment utilization and production efficiency, and bringing a qualitative leap to the production management of modern manufacturing industry. Attached Figure Description
[0012] Figure 1 This is a flowchart of the method of the present invention.
[0013] Figure 2 This is a schematic diagram of the double-triangular ring monitoring and prediction model.
[0014] Figure 3 This is a schematic diagram of the equipment capacity triangular monitoring model and the distribution of intersection points in a rectangular coordinate system.
[0015] Figure 4 This is a diagram illustrating the equipment capacity status assessment based on the inner ring triangle model.
[0016] Figure 5 This is a schematic diagram of the output prediction results based on the outer ring triangle model.
[0017] Figure 6 It is a flowchart of equipment operation and maintenance and capacity control. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above objectives, this invention adopts the following technical solution.
[0019] This invention provides a method for dual-loop monitoring, prediction, and control of equipment operation in a digital twin workshop. The specific steps are shown in the attached flowchart. Figure 1 As shown.
[0020] Step 1: Classification of Equipment Production Attributes: Using digital twin-related data acquisition technology, classify and describe the three categories of attributes related to "capability-goal-execution" and "rated-expected-actual" that need to be monitored in real time when the equipment participates in the production and manufacturing process.
[0021] Production capacity-related indicators refer to the standards or quotas pre-set during equipment design. These serve as a benchmark for assessing equipment status or a basis for resource allocation, representing the output and production capacity of a certain type of product produced by the equipment within a specific time period. This includes rated production capacity and rated production volume. Monitoring and prediction of these indicators rely on digital twin virtual workshops.
[0022] Production target-related indicators: These refer to pre-set expected targets or planned quantities, formulated based on historical data, resource assessments, or business needs. They represent the capacity / quantity required for a specific production task, including expected production capacity and expected production volume. These indicators are primarily formulated by external workshop production personnel.
[0023] Production execution related indicators refer to the actual quantities generated during the execution process, reflecting objective results and representing the actual workload within a specific time period, including actual production capacity and actual production volume. These indicators primarily rely on various equipment status acquisition devices within the digital twin physical workshop for monitoring and prediction.
[0024] Step 2: Construction of the "Inner Ring-Outer Ring" Double Triangular Ring Monitoring and Prediction Model: Based on the three types of attributes mentioned above, the double triangular ring monitoring and prediction model is constructed as shown in the attached figure. Figure 2 The inner-loop model (equipment production capacity triangular monitoring model) and the outer-loop model (equipment production volume triangular prediction model) are defined, assuming that the current work performed by the equipment is as follows: , at all times .
[0025] a) Inner loop: Equipment production capacity triangular monitoring model, with the vertex being: rated production capacity. Expected production capacity Actual production capacity Rated production capacity is related to the attributes of the equipment itself and can be calculated based on the relevant parameters in the equipment technical specifications and historical production capacity status data; expected production capacity can be calculated based on production work order data provided by the Manufacturing Execution System (MES); in actual production, the equipment can collect physical production capacity in real time through the IoT sensor array on the equipment itself.
[0026] b) Outer ring: Equipment production volume triangular prediction model, with the vertex being: rated production volume. Expected production volume Actual production volume Where production volume is the integral of production capacity over the production time interval, such as... , , ,in This is the start time of production.
[0027] The inner ring attributes in the double-triangle ring monitoring and prediction model can comprehensively reflect the inherent capabilities and actual operating capabilities of the equipment in different dimensions. By comprehensively considering the attributes of these three vertices, the potential production capacity of the equipment under different production conditions can be accurately monitored.
[0028] The outer ring attributes in the double-triangular ring monitoring and prediction model can provide a comprehensive and intuitive understanding of the actual output and production efficiency of the equipment throughout the entire production process, thereby providing strong data support for production management decisions.
[0029] Step 3: Real-time Equipment Production Status Monitoring Based on the Inner Loop: Based on the constructed double-triangular loop monitoring and prediction model, the real-time production status of the equipment is monitored using the inner loop triangle. The monitoring method is as follows:
[0030] a) First, based on the expected production capacity required by workshop production personnel. Rated production capacity of equipment in a digital twin virtual workshop based on timing prediction By the ratio of the two This gives us the current equipment efficiency utilization rate.
[0031] Methods for calculating equipment efficiency utilization:
[0032] ;
[0033] b) Actual production capacity obtained through data collected within the digital twin physical workshop Rated production capacity required by workshop production personnel ratio This yields the current real-time overall efficiency of the equipment.
[0034] Method for calculating the real-time overall efficiency of equipment:
[0035] ;
[0036] c) Actual production capacity based on data collected within the digital twin physical workshop Expected production capacity required by workshop production personnel The ratio of supply to demand for the current equipment is obtained from the ratio of supply to demand.
[0037] ;
[0038] d) Based on the results of three ratios of equipment in real time in the digital twin workshop, and combined with the intersection of the two circles and the triangle, the current production status of the equipment is monitored and evaluated in the digital twin virtual workshop, and support is provided for subsequent adjustments to the production plan.
[0039] The equipment will set the vertex as: rated production capacity in real time. Expected production capacity Actual production capacity The equipment inner-ring capacity triangular prediction model is placed in a rectangular coordinate system, such as... Figure 3 As shown in (a), an isosceles triangle is obtained. Assume... For equipment condition assessment, Determined by the historical production capacity utilization status of the current equipment, workshop equipment management personnel record the equipment efficiency utilization rate at the moment when the previous batch of production capacity met the utilization requirements, based on historical production capacity utilization data. Real-time overall efficiency of equipment Then the current device state evaluation angle is This angle can be used for real-time assessment of current or future production capacity status.
[0040] Then the rated production capacity point at this time is Expected production capacity is Actual production capacity ; respectively based on expected production capacity points With the center as the point, the equipment efficiency utilization rate Draw a circle with radius 1 to represent the expected production capacity. Based on actual production capacity Centered on the circle, the equipment's real-time overall efficiency Draw a circle with the actual production capacity as the radius. With the improvement of equipment efficiency utilization... Real-time overall efficiency of equipment As the radius of the two circles changes, the intersection point of the two circles also changes, such as... Figure 3 As shown in (b);
[0041] The situation is as follows Figure 3 As shown in (c), when the equipment efficiency utilization rate At this point, assuming the circle represents the maximum expected production capacity, the real-time overall efficiency of the equipment... At this point, assume the circle represents the maximum actual production capacity. Using the maximum expected production capacity circle, the maximum actual production capacity circle, the isosceles triangle, and its median as dividing lines, we obtain the following six regions: ① represents the median of the isosceles triangle (coinciding with the Y-axis), ② represents the region from the left side of the triangle's median to the maximum actual production capacity circle (referred to as the inner left half), ③ represents the region from the right side of the triangle's median to the maximum expected production capacity circle (referred to as the inner right half), ④ represents the base of the isosceles triangle (coinciding with the X-axis), ⑤ represents the region from outside the maximum actual production capacity circle to the left side of the triangle (outer left half), and ⑥ represents the region from outside the maximum expected production capacity circle to the right side of the triangle (outer right half).
[0042] Based on the intersection points of the expected capacity circle, the actual capacity circle, and the isosceles triangle, the current equipment production status can be quickly and intuitively displayed, such as... Figure 4 The specific production situation is as follows:
[0043] Scenario 1: Supply and demand equilibrium: When the intersection of the two circles lies on the median of the triangle, it indicates that supply and demand are in balance and resource waste is minimized.
[0044] Situation ②: Supply exceeds demand: At this point, the two circles intersect at one point within the triangle, and the intersection point is within the inner left half of the region. This indicates that the production capacity exceeds expectations, and in actual production, it is necessary to adjust the inventory strategy or optimize the rationality of the production plan.
[0045] Situation ③: Supply falls short of demand: If the two circles intersect at one point within the triangle, and this intersection point is located in the right half of the triangle, it indicates that the production capacity has not met the target and the production plan needs to be adjusted to increase production output.
[0046] Scenario 4: Insufficient capacity utilization: At this point, the two circles do not intersect, indicating that the equipment's production capacity is underutilized and it is necessary to adjust the production plan and equipment production capacity in order to improve the overall capacity utilization rate of the equipment.
[0047] Scenario 5: High-load production of equipment: The two circles intersect at one point inside the triangle. At this point, the intersection point is in the outer left half of the region, indicating that the equipment is operating at a high load and the production load of the equipment needs to be adjusted in time.
[0048] Situation 6: Unreasonable task allocation: The two circles intersect at one point within the triangle. This intersection point is located in the outer right half of the triangle, indicating that the current task demand exceeds the equipment's maximum production capacity boundary, and the feasibility of the current plan needs to be verified.
[0049] Step 4: Production Output Forecasting Based on the Outer Ring: Based on the constructed double-triangular ring forecasting model, the outer ring is used to forecast production output. The forecast results are as follows: Figure 5As shown, where For the current workshop production cycle, This is the start time of production in the current production cycle.
[0050] a) Estimated rated production volume within the digital twin virtual workshop Production volume expected by workshop production staff The difference is used to predict the utilization difference of equipment capacity in the current production plan, i.e., the planned output utilization difference. The prediction method is as follows:
[0051] ;
[0052] b) Estimated rated production volume within the digital twin virtual workshop The actual production volume estimated by the digital twin physical workshop The difference is used to predict the actual capacity utilization difference when the equipment participates in actual production. The prediction method is as follows:
[0053] ;
[0054] c) Actual production volume estimated based on the digital twin physical workshop Production volume expected by workshop production staff The difference is used to predict the gap between actual production load and expected production demand, i.e., the supply-demand mismatch. The prediction method is as follows:
[0055] ;
[0056] d) Ultimately, the prediction results based on these three factors will provide support for adjusting the equipment's production plan within the digital twin virtual workshop.
[0057] Step 5: Equipment Operation and Capacity Control: Based on the above inner-loop monitoring and outer-loop prediction results, perform group operation and maintenance and adjust the production status of all equipment within the production line to ultimately achieve a balance between maximizing capacity utilization and minimizing resource waste. The flowchart for equipment operation and capacity control is as follows: Figure 6 As shown, it includes:
[0058] a) Equipment group operation and maintenance considering the monitoring results of the inner loop production status of equipment: During the production process of a single piece of equipment, the production status of the equipment at this time is displayed using the inner loop triangular model. If the equipment is in a poor production state for a long time, such as an imbalance between production supply and demand, the current equipment needs to be repaired. Furthermore, through the triangular inner loop model, the production capacity of multiple pieces of equipment in the workshop can be adjusted, and finally, the operation and maintenance of equipment group can be achieved.
[0059] b) Production status control considering the production output forecast results of the outer ring of the production line: During the overall workshop production process, the current output situation is predicted and analyzed using the outer ring triangular model. When it is found that the output cannot meet the demand, the production status is controlled for individual equipment, multiple equipment, and production lines respectively. For example, the actual capacity of a single equipment is increased to improve the actual capacity, the expected output of multiple equipment is adjusted to balance the capacity gap, and the rated capacity of the production line is adjusted to improve the production capacity. In this way, at the end of the current work cycle, the supply and demand are matched, and the production task is completed.
[0060] In summary, this invention proposes a dual-loop monitoring, prediction, and control method for equipment operation in a digital twin workshop. This method comprises five steps: equipment production attribute classification, construction of an "inner-outer loop" dual-triangular loop monitoring and prediction model, inner loop-real-time equipment production status monitoring, outer loop-production output prediction, and equipment operation and maintenance and capacity control. On one hand, it proposes a dual-triangular loop monitoring and prediction model that effectively describes the three attributes of workshop equipment during production: rated, expected, and actual. On the other hand, it proposes a real-time monitoring and prediction method for equipment production capacity based on inner and outer loops. The inner loop describes the equipment's own capabilities, while the outer loop measures the production status, providing a basis for dynamic adjustment of equipment capacity and equipment operation and maintenance.
[0061] The contents not described in detail in this specification are existing technologies known to those skilled in the art.
[0062] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A method for dual-loop monitoring, prediction, and control of equipment operation in a digital twin workshop, characterized in that, Includes the following steps: Step 1: Classify equipment production attributes, including: classifying and describing the attributes of indicators related to production capacity, production targets, and production execution in real time when the equipment participates in the production and manufacturing process; Step 2: Construction of the inner-outer-outer double-triangular ring monitoring and prediction model, including: based on the above attribute classification, constructing a digital twin double-triangular ring monitoring and prediction model, defining the inner ring model as a triangular monitoring model of equipment production capacity and the outer ring model as a triangular prediction model of equipment production volume; Step 3: Real-time production status monitoring of equipment based on the inner loop: Based on the constructed double-triangular ring monitoring and prediction model, the inner loop model is used to realize the real-time production status monitoring of equipment; Step 4: Production output prediction based on the outer ring: Based on the constructed double triangular ring monitoring and prediction model, the outer ring model is used to predict production output.
2. The method as described in claim 1, characterized in that, In step 1, the production capacity-related indicators refer to the standards or quotas set in advance during the design of the equipment. These serve as the benchmark for assessing the equipment's status or the basis for resource allocation, representing the output and production capacity of the equipment for a certain type of product within a specific time period, including rated production capacity and rated production volume. This indicator is monitored and predicted based on the digital twin virtual workshop.
3. The method as described in claim 1, characterized in that, In step 1, the production target-related indicators refer to the pre-set expected targets or planned quantities, which are formulated based on historical data, resource assessments, or business needs. They represent the capacity / quantity required for a specific production task, including expected production capacity and expected production volume. These indicators are mainly formulated by external workshop production personnel.
4. The method as described in claim 1, characterized in that, In step 1, the production execution related indicators refer to the actual quantities generated during the actual execution process, reflecting objective results and representing the actual load within a specific time period, including actual production capacity and actual production volume; these indicators mainly rely on various equipment status acquisition devices in the digital twin physical workshop to achieve monitoring and prediction.
5. The method as described in claim 1, characterized in that, In step 2, assume that the current device is performing the following tasks: , at all times ; a) In the inner loop model: the vertex of the equipment production capacity triangle model is the rated production capacity. Expected production capacity Actual production capacity ; b) In the outer ring model: the vertex of the equipment production output triangle model is the rated production capacity. Expected production volume Actual production volume .
6. The method as described in claim 5, characterized in that, Where production volume is the integral of production capacity over the production time interval, where... , , ,in This is the start time of production.
7. The method as described in claim 5, characterized in that, In step 3, the inner loop model is used to monitor the real-time production status of the equipment. The monitoring method is as follows: a) First, based on the expected production capacity required by workshop production personnel. Rated production capacity of equipment in a digital twin virtual workshop based on timing prediction By the ratio of the two This yields the equipment efficiency utilization rate at the current moment; the calculation method for equipment efficiency utilization rate is as follows: ； b) Actual production capacity obtained through data collected within the digital twin physical workshop Rated production capacity required by workshop production personnel ratio This yields the current real-time overall efficiency of the equipment. Method for calculating the real-time overall efficiency of equipment: ； c) Actual production capacity based on data collected within the digital twin physical workshop Expected production capacity required by workshop production personnel The ratio of supply to demand for the current equipment is obtained from the ratio of supply to demand. ； d) Based on three ratios in real time of the device , , The result is that the current production status of equipment can be monitored and evaluated within the digital twin virtual workshop.
8. The method as described in claim 7, characterized in that, Step 3 involves monitoring and evaluating the current production status of the equipment within the digital twin virtual workshop, specifically including: The vertex represents the rated production capacity. Expected production capacity Actual production capacity When the equipment's inner-ring capacity triangular monitoring model is placed into a rectangular coordinate system, an isosceles triangle is obtained. Let be the equipment status evaluation angle, then the equipment status evaluation angle at the current moment is . At this point, the rated production capacity point is Expected production capacity is Actual production capacity ; respectively based on expected production capacity points With the center as the point, the equipment efficiency utilization rate Draw a circle with radius equal to the desired production capacity. Based on actual production capacity Centered on the circle, the real-time comprehensive efficiency of the equipment Draw a circle with the actual production capacity as the radius. With the utilization rate of equipment efficiency Real-time overall efficiency of equipment As the efficiency of the equipment changes, the radii of the two circles also change, and the intersection point of the two circles also changes accordingly. At this point, the circle represents the maximum expected production capacity, and the real-time comprehensive efficiency of the equipment is... At this point, the circle represents the maximum actual production capacity. Using the maximum expected production capacity circle, the maximum actual production capacity circle, the isosceles triangle, and the median as dividing lines, we obtain six regions: the median of the isosceles triangle, the region from the left side of the triangle median to the maximum actual production capacity circle, the region from the right side of the triangle median to the maximum expected production capacity circle, the base of the isosceles triangle, the region from outside the maximum actual production capacity circle to the left side of the triangle, and the region from outside the maximum expected production capacity circle to the right side of the triangle.
9. The method as described in claim 8, characterized in that, Based on the intersection of the expected capacity circle, the actual capacity circle, and the isosceles triangle, the current production status of the equipment is displayed as follows: Scenario 1: Supply and demand equilibrium: When the intersection of the two circles lies on the median of the triangle, it indicates that supply and demand are in balance and resource waste is minimized. Situation ②: Supply exceeds demand: At this point, the two circles intersect at one point within the triangle. The intersection point is located within the area from the left side of the triangle's midline to the circle with the maximum actual production capacity. This indicates that the production capacity exceeds expectations, and it is necessary to adjust the inventory strategy or optimize the rationality of the production plan in actual production. Situation ③: Supply falls short of demand: If the two circles intersect at one point within the triangle, and this intersection point is located within the area from the right side of the triangle's midline to the circle with the maximum expected production capacity, it indicates that the production capacity has not met the target and the production plan needs to be adjusted to increase production output. Scenario 4: Insufficient capacity utilization: At this point, the two circles do not intersect, indicating that the equipment's production capacity is underutilized and it is necessary to adjust the production plan and equipment production capacity in order to improve the overall capacity utilization rate of the equipment. Scenario 5: High-load production of equipment: If the two circles intersect at one point inside the triangle, and this intersection point is outside the area from the circle with the maximum actual production capacity to the left side of the triangle, it indicates that the equipment is operating at a high load and the production load of the equipment needs to be adjusted in a timely manner. Situation 6: Unreasonable task allocation: If the two circles intersect at one point within the triangle, and this intersection point is outside the area from the circle of maximum expected capacity to the right side of the triangle, it indicates that the current task demand exceeds the equipment's maximum production capacity boundary, and the feasibility of the current plan needs to be verified.
10. The method as described in claim 6, characterized in that, In step 4, the prediction method is as follows: a) Estimated rated production volume within the digital twin virtual workshop Production volume expected by workshop production staff The difference is used to predict the utilization difference of equipment capacity in the current production plan, i.e., the planned output utilization difference. The prediction method is as follows: ； b) Estimated rated production volume within the digital twin virtual workshop The actual production volume estimated by the digital twin physical workshop The difference is used to predict the actual capacity utilization difference when the equipment participates in actual production. The prediction method is as follows: ； c) Actual production volume estimated based on the digital twin physical workshop Production volume expected by workshop production staff The difference is used to predict the gap between actual production load and expected production demand, i.e., the supply-demand mismatch. The prediction method is as follows: 。