A comprehensive efficiency statistics system for industrial robots and industrial equipment

Abstract

The present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment. By collecting sensor data and production data, the overall equipment efficiency of the industrial robots and industrial equipment is calculated based on the sensor data and production data, including three evaluation indicators: availability, performance efficiency and production quality. Based on the evaluation indicators and in combination with the production processes of the industrial robots and industrial equipment, production efficiency loss points are analyzed. Based on the production efficiency loss points and in combination with historical data, potential efficiency influencing factors of the industrial robots and industrial equipment are determined. This system can fully understand the operating status of the equipment, promptly discover the root cause of the production efficiency loss, take corresponding measures to improve production efficiency and optimize resource allocation, realize industrial modernization, and improve production efficiency and quality control.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment efficiency analysis, and in particular to a comprehensive efficiency statistics system for industrial robots and industrial equipment. Background Art

[0002] With the development of science and technology, automated factories are being used more and more widely. Industrial robots and industrial equipment, as production tools of automated factories, have brought extraordinary significance to the production efficiency of factories.

[0003] The significance of the comprehensive efficiency statistics of industrial equipment lies in measuring the ratio of the actual production capacity of the equipment to its theoretical production capacity. As an independent measurement tool, it can reflect the actual production capacity of the equipment and is an important indicator for evaluating equipment performance.

[0004] Overall Equipment Effectiveness (OEE) is not only an index that measures the effective operation of production facilities, its calculation results are universal and can even be compared across industries. It can also serve as a key performance indicator and efficiency indicator for lean production. OEE statistics can fully demonstrate its actual value, improving production efficiency while reducing both visible and invisible losses, achieving cost control and quality control. For example, through predictive equipment maintenance and operation, a factory's equipment production efficiency will increase by over 50%. This ensures that every piece of production equipment and every production link operates at the best possible performance within its scope.

[0005] In addition, with the large-scale promotion and popularization of the Industrial Internet of Things, the rapid realization of the value of equipment OEE will depend entirely on whether the company has implemented the equipment Internet of Things and connected all factory equipment with information technology.

[0006] To sum up, the comprehensive efficiency statistics of industrial equipment are not only an important tool for measuring equipment performance, but also a key means to achieve industrial modernization, improve production efficiency and quality control. Therefore, the comprehensive efficiency statistics of industrial robots and industrial equipment are particularly important. Summary of the Invention

[0007] The present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, which is used to solve the problems raised in the background technology.

[0008] A comprehensive efficiency statistics system for industrial robots and industrial equipment, including:

[0009] Data acquisition module, used to connect with sensors and controllers of industrial robots and industrial equipment to collect sensor data and production data;

[0010] The indicator evaluation module is used to calculate the overall equipment efficiency of industrial robots and industrial equipment based on sensor data and production data, including three evaluation indicators: availability, performance efficiency, and production quality;

[0011] A loss analysis module is used to analyze and obtain production efficiency loss points based on the evaluation indicators and the production processes of industrial robots and industrial equipment;

[0012] The factor determination module is used to determine the potential efficiency influencing factors of industrial robots and industrial equipment based on production efficiency loss points and combined with historical data.

[0013] Preferably, the data acquisition module includes:

[0014] A parameter determination unit, configured to determine data acquisition parameters for sensors of industrial robots and industrial equipment based on the sensors of the sensors, and to determine data acquisition parameters for controllers of the sensors of industrial robots and industrial equipment based on the controllers of the sensors;

[0015] An instruction generation unit, configured to generate an acquisition instruction for the sensor according to the data acquisition parameters of the sensor and the acquisition requirements, and to generate an acquisition instruction for the controller according to the data acquisition parameters of the controller and the acquisition requirements;

[0016] The data acquisition unit is used to collect data from the sensor and the controller based on the acquisition instructions for the sensor and the acquisition instructions for the controller to obtain sensor data and production data.

[0017] Preferably, the indicator evaluation module includes:

[0018] A standardization unit is used to determine the data standard features of the sensor data and production data based on the calculation algorithm of the three evaluation indicators of availability, performance efficiency and production quality, and standardize the sensor data and production data based on the data standard features to obtain standard data;

[0019] The computing unit is used to obtain the availability, performance efficiency, and production quality of industrial robots and industrial equipment based on standard data and combined with computing algorithms.

[0020] Preferably, the computing unit includes:

[0021] a processing unit for processing the standard data in chronological order according to the data attributes based on the calculation algorithm to obtain a target standard value;

[0022] The calculation unit is used to calculate the target standard value according to the calculation algorithm to obtain the availability, performance efficiency and production quality of the industrial robot and industrial equipment.

[0023] Preferably, the loss analysis module includes:

[0024] A comparison unit is used to compare the usability, performance efficiency and production quality with the preset evaluation standards to obtain the usability difference, performance efficiency difference and production quality difference;

[0025] A process determination unit, configured to determine local production processes corresponding to availability, performance efficiency, and production quality from the production processes of industrial robots and industrial equipment;

[0026] a suspicious determination unit, configured to determine a first suspicious point based on availability differences in combination with a local production process, determine a second suspicious point based on performance efficiency differences in combination with the local production process, and determine a third suspicious point based on production quality differences in combination with the local production process;

[0027] a weight determination unit, configured to obtain a common suspicious point from the first suspicious point, the second suspicious point, and the third suspicious point, and determine an availability impact weight, a performance efficiency impact weight, and a production quality impact weight based on the difference in availability, the performance efficiency difference, and the production quality difference;

[0028] An adjustment unit is used to determine the loss type of the common suspicious point, and to perform weighted adjustment on the analysis and identification model based on the availability impact weight, the performance efficiency impact weight, and the production quality impact weight to obtain a target analysis and identification model;

[0029] The selection unit is used to input the evaluation index data corresponding to the common suspicious points into the target analysis and recognition model for verification, obtain the recognition results of the common suspicious points, and select the production efficiency loss points from the common suspicious points based on the recognition results.

[0030] Preferably, the adjustment unit includes:

[0031] A parameter acquisition unit is used to select an analysis and identification model corresponding to the loss type from the data model library, and obtain model parameters related to availability, performance efficiency and production quality in the analysis and identification model;

[0032] The weighted adjustment unit is used to perform weighted adjustment on the model parameters based on the availability impact weight, the performance efficiency impact weight and the production quality impact weight to obtain a target analysis and identification model.

[0033] Preferably, the selection unit includes:

[0034] A judging unit, configured to determine an efficiency loss value for a common suspicious point in the identification result, and to judge whether the efficiency loss value is greater than a preset loss value;

[0035] If so, determining the common suspicious point as a production efficiency loss point;

[0036] Otherwise, it is determined that the common suspicious point is not a production efficiency loss point.

[0037] Preferably, the factor determination module includes:

[0038] a correlation acquisition unit, configured to acquire first production operation data having a first correlation with the production efficiency loss point, acquire second production operation data having a second correlation with the production efficiency loss point, and acquire first historical data related to the first production operation data and acquire second historical data related to the second production operation data from historical data;

[0039] a matching analysis unit, configured to divide the first historical data into an operation data sequence according to a chronological order, obtain a change trend of the operation data sequence, match the change trend with an efficiency loss characteristic of a production efficiency loss point, and determine, based on a matching result, whether the change trend exceeds the efficiency loss characteristic; if so, assign a first weight to the change trend; otherwise, assign a second weight to the change trend;

[0040] a weighted processing unit, configured to perform weighted processing on the first production operation data based on a weight of a change trend to obtain first target production operation data, and based on an operational association between the first production operation data and the second production operation data, process the second production operation data according to the first target production operation data to obtain second target production data;

[0041] A factor determination unit is used to obtain the target change trend of the second historical data, and determine the influence of the second target production data on the trend direction of the target change trend; based on the data characteristics of the second target production data, determine the potential efficiency influencing factors of industrial robots and industrial equipment; based on the target change trend, determine the potential occurrence probability; based on the influence on the trend direction of the target change trend, verify and adjust the potential occurrence probability to obtain the target potential occurrence probability.

[0042] Preferably, the weighted processing unit processes the second production operation data according to the first target production operation data based on the operational association between the first production operation data and the second production operation data to obtain the second target production data, including:

[0043] Based on the operation association, a data expansion rule is determined, and according to the data expansion rule, the second production operation data is expanded based on the first target production operation data to obtain the second target production data.

[0044] Preferably, the factor determination unit verifies and adjusts the potential probability of occurrence based on the impact on the trend of the target change trend to obtain the target potential probability of occurrence, including:

[0045] Determine whether the impact situation is within the predicted trend of the target change trend;

[0046] If so, determine the potential probability of occurrence as the target potential probability of occurrence;

[0047] Otherwise, a trend difference between the predicted trend and the target change trend is determined, and based on the trend difference, an adjustment value for the potential occurrence probability is determined to obtain the target potential occurrence probability.

[0048] Compared with the prior art, the present invention has achieved the following beneficial effects:

[0049] By collecting sensor data and production data; based on the sensor data and production data, the overall equipment efficiency of industrial robots and industrial equipment is calculated, including three evaluation indicators: availability, performance efficiency and production quality. Based on the evaluation indicators, combined with the production process of industrial robots and industrial equipment, the production efficiency loss points are analyzed. Based on the production efficiency loss points, combined with historical data, the potential efficiency influencing factors of industrial robots and industrial equipment are determined. This can fully understand the equipment operation status, timely discover the root cause of production efficiency loss, take corresponding measures to improve production efficiency and optimize resource allocation, realize industrial modernization, improve production efficiency and quality control.

[0050] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0051] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 This is a structural diagram of a comprehensive efficiency statistics system for industrial robots and industrial equipment in an embodiment of the present invention;

[0054] Figure 2 is a structural diagram of the data acquisition module in an embodiment of the present invention;

[0055] Figure 3 4 is a structural diagram of the indicator evaluation module described in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0057] Example 1:

[0058] The embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, such as Figure 1 Shown, including:

[0059] Data acquisition module, used to connect with sensors and controllers of industrial robots and industrial equipment to collect sensor data and production data;

[0060] The indicator evaluation module is used to calculate the overall equipment efficiency of industrial robots and industrial equipment based on sensor data and production data, including three evaluation indicators: availability, performance efficiency, and production quality;

[0061] A loss analysis module is used to analyze and obtain production efficiency loss points based on the evaluation indicators and the production processes of industrial robots and industrial equipment;

[0062] The factor determination module is used to determine the potential efficiency influencing factors of industrial robots and industrial equipment based on production efficiency loss points and combined with historical data.

[0063] In this embodiment, the sensory data and production data include operating and downtime, cycle time, quantity output, etc.

[0064] In this embodiment, the production efficiency loss points include, for example, equipment failure, operational errors, slow production rhythm, etc.

[0065] In this embodiment, the potential efficiency-influencing factors are factors that may become points of production efficiency loss.

[0066] The beneficial effects of the above design scheme are: by collecting sensor data and production data; based on the sensor data and production data, the overall equipment efficiency of industrial robots and industrial equipment is calculated, including three evaluation indicators: availability, performance efficiency and production quality; based on the evaluation indicators, combined with the production process of industrial robots and industrial equipment, the production efficiency loss points are analyzed; based on the production efficiency loss points, combined with historical data, the potential efficiency influencing factors of industrial robots and industrial equipment are determined, which can fully understand the equipment operation status, timely discover the root cause of production efficiency loss, take corresponding measures to improve production efficiency and optimize resource allocation, realize industrial modernization, improve production efficiency and quality control.

[0067] Example 2:

[0068] Based on Example 1, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, such as Figure 2 As shown, the data acquisition module includes:

[0069] A parameter determination unit, configured to determine data acquisition parameters for sensors of industrial robots and industrial equipment based on the sensors of the sensors, and to determine data acquisition parameters for controllers of the sensors of industrial robots and industrial equipment based on the controllers of the sensors;

[0070] An instruction generation unit, configured to generate an acquisition instruction for the sensor according to the data acquisition parameters of the sensor and the acquisition requirements, and to generate an acquisition instruction for the controller according to the data acquisition parameters of the controller and the acquisition requirements;

[0071] The data acquisition unit is used to collect data from the sensor and the controller based on the acquisition instructions for the sensor and the acquisition instructions for the controller to obtain sensor data and production data.

[0072] In this embodiment, the data collection parameters include collection frequency, collection time point, etc.

[0073] In this embodiment, the acquisition requirements include data accuracy and the like.

[0074] The beneficial effects of the above design scheme are: by generating collection instructions for the sensor according to the data collection parameters of the sensor and the collection requirements, generating collection instructions for the controller according to the data collection parameters of the controller and the collection requirements, based on the collection instructions for the sensor and the collection instructions for the controller, data collection is performed on the sensor and the controller to obtain sensor data and production data, providing a data basis for comprehensive efficiency statistics.

[0075] Example 3:

[0076] Based on Example 1, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, such as Figure 3 As shown, the indicator evaluation module includes:

[0077] A standardization unit is used to determine the data standard features of the sensor data and production data based on the calculation algorithm of the three evaluation indicators of availability, performance efficiency and production quality, and standardize the sensor data and production data based on the data standard features to obtain standard data;

[0078] The computing unit is used to obtain the availability, performance efficiency, and production quality of industrial robots and industrial equipment based on standard data and combined with computing algorithms.

[0079] In this embodiment, the calculation algorithms for the three evaluation indicators of availability, performance efficiency and production quality are pre-set based on historical data.

[0080] The beneficial effects of the above design scheme are: through the calculation algorithm based on the three evaluation indicators of availability, performance efficiency and production quality, the data standard characteristics of the sensor data and production data are determined, and the sensor data and production data are standardized based on the data standard characteristics to obtain standard data. From the perspective of data quality, the calculation efficiency and accuracy are improved, providing a high-quality data foundation for the calculation of indicators.

[0081] Example 4:

[0082] Based on Example 3, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, wherein the calculation unit includes:

[0083] a processing unit for processing the standard data in chronological order according to the data attributes based on the calculation algorithm to obtain a target standard value;

[0084] The calculation unit is used to calculate the target standard value according to the calculation algorithm to obtain the availability, performance efficiency and production quality of the industrial robot and industrial equipment.

[0085] In this embodiment, the target standard value is, for example, an average value, a median value, etc. within a time series.

[0086] The beneficial effect of the above design scheme is: by processing the standard data in chronological order according to the data attributes based on the calculation algorithm, the target standard value is obtained, and the target standard value is calculated according to the calculation algorithm to obtain the availability, performance efficiency and production quality of industrial robots and industrial equipment, thereby ensuring the correctness of the data in the indicator process and thus ensuring the correctness of the indicator.

[0087] Example 5:

[0088] Based on Example 1, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, wherein the loss analysis module includes:

[0089] A comparison unit is used to compare the usability, performance efficiency and production quality with the preset evaluation standards to obtain the usability difference, performance efficiency difference and production quality difference;

[0090] A process determination unit, configured to determine local production processes corresponding to availability, performance efficiency, and production quality from the production processes of industrial robots and industrial equipment;

[0091] a suspicious determination unit, configured to determine a first suspicious point based on availability differences in combination with a local production process, determine a second suspicious point based on performance efficiency differences in combination with the local production process, and determine a third suspicious point based on production quality differences in combination with the local production process;

[0092] a weight determination unit, configured to obtain a common suspicious point from the first suspicious point, the second suspicious point, and the third suspicious point, and determine an availability impact weight, a performance efficiency impact weight, and a production quality impact weight based on the difference in availability, the performance efficiency difference, and the production quality difference;

[0093] An adjustment unit is used to determine the loss type of the common suspicious point, and to perform weighted adjustment on the analysis and identification model based on the availability impact weight, the performance efficiency impact weight, and the production quality impact weight to obtain a target analysis and identification model;

[0094] The selection unit is used to input the evaluation index data corresponding to the common suspicious points into the target analysis and recognition model for verification, obtain the recognition results of the common suspicious points, and select the production efficiency loss points from the common suspicious points based on the recognition results.

[0095] In this embodiment, the generation process includes operation data, production process data and production result data.

[0096] In this embodiment, the common suspicious point may be a point of loss of efficiency and requires further judgment.

[0097] In this embodiment, analyzing and identifying the model and performing weighted adjustment specifically includes determining the loss function of the model, determining the validation set, the number of model layers, etc.

[0098] The beneficial effects of the above design scheme are: by analyzing based on availability, performance efficiency and production quality, adjusting the model parameters according to the analysis results to ensure the applicability of the obtained model, and finally inputting the evaluation index data corresponding to the common suspicious points into the target analysis and identification model for verification, obtaining the identification results of the common suspicious points, and selecting the production efficiency loss points from the common suspicious points based on the identification results, thereby achieving accurate judgment of the production efficiency loss points.

[0099] Example 6:

[0100] Based on Example 5, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, wherein the adjustment unit includes:

[0101] A parameter acquisition unit is used to select an analysis and identification model corresponding to the loss type from the data model library, and obtain model parameters related to availability, performance efficiency and production quality in the analysis and identification model;

[0102] The weighted adjustment unit is used to perform weighted adjustment on the model parameters based on the availability impact weight, the performance efficiency impact weight and the production quality impact weight to obtain a target analysis and identification model.

[0103] In this embodiment, the data model library includes analysis and identification models corresponding to various loss types, which are pre-trained through machine algorithms and historical data.

[0104] The beneficial effect of the above design scheme is: by analyzing based on availability, performance efficiency and production quality, the model parameters are adjusted according to the analysis results to ensure the applicability of the obtained model.

[0105] Example 7:

[0106] Based on Example 5, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, wherein the selection unit includes:

[0107] A judging unit, configured to determine an efficiency loss value for a common suspicious point in the identification result, and to judge whether the efficiency loss value is greater than a preset loss value;

[0108] If so, determining the common suspicious point as a production efficiency loss point;

[0109] Otherwise, it is determined that the common suspicious point is not a production efficiency loss point.

[0110] In this embodiment, the greater the efficiency loss, the greater the corresponding efficiency loss value.

[0111] In this embodiment, the preset loss value is pre-set according to actual conditions.

[0112] The beneficial effect of the above design scheme is: by determining the efficiency loss value of the common suspicious point in the identification result, it is judged whether the efficiency loss value is greater than the preset loss value. If so, the common suspicious point is determined to be a production efficiency loss point; otherwise, the common suspicious point is determined not to be a production efficiency loss point, thereby realizing the judgment of the production efficiency loss point.

[0113] Example 8:

[0114] Based on Example 1, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment, wherein the factor determination module includes:

[0115] a correlation acquisition unit, configured to acquire first production operation data having a first correlation with the production efficiency loss point, acquire second production operation data having a second correlation with the production efficiency loss point, and acquire first historical data related to the first production operation data and acquire second historical data related to the second production operation data from historical data;

[0116] a matching analysis unit, configured to divide the first historical data into an operation data sequence according to a chronological order, obtain a change trend of the operation data sequence, match the change trend with an efficiency loss characteristic of a production efficiency loss point, and determine, based on a matching result, whether the change trend exceeds the efficiency loss characteristic; if so, assign a first weight to the change trend; otherwise, assign a second weight to the change trend;

[0117] a weighted processing unit, configured to perform weighted processing on the first production operation data based on a weight of a change trend to obtain first target production operation data, and based on an operational association between the first production operation data and the second production operation data, process the second production operation data according to the first target production operation data to obtain second target production data;

[0118] A factor determination unit is used to obtain the target change trend of the second historical data, and determine the influence of the second target production data on the trend direction of the target change trend; based on the data characteristics of the second target production data, determine the potential efficiency influencing factors of industrial robots and industrial equipment; based on the target change trend, determine the potential occurrence probability; based on the influence on the trend direction of the target change trend, verify and adjust the potential occurrence probability to obtain the target potential occurrence probability.

[0119] In this embodiment, the first correlation is greater than the second correlation, the first production operation data is used to determine the efficiency loss point, and the second production operation data is used to determine the potential factor.

[0120] In this embodiment, a change trend exceeding the efficiency loss characteristic indicates that the trend is getting worse, and the first weight is greater than the second weight.

[0121] In this embodiment, the first production operation data is weighted based on the weight of the change trend, and the weight of the weighted processing is the first weight or the second weight.

[0122] The beneficial effects of the above design scheme are: by analyzing historical data and effect management operation data, determining potential efficiency influencing factors and potential probability of target occurrence, it is possible to discover the root causes of production efficiency loss in advance, take corresponding measures to improve production efficiency and optimize resource allocation, realize industrial modernization, improve production efficiency and quality control.

[0123] Example 9:

[0124] Based on Example 8, this embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment. The weighted processing unit processes the second production operation data according to the first target production operation data based on the operational association between the first production operation data and the second production operation data to obtain the second target production data, including:

[0125] Based on the operation association, a data expansion rule is determined, and according to the data expansion rule, the second production operation data is expanded based on the first target production operation data to obtain the second target production data.

[0126] In this embodiment, the data expansion rule is, for example, to expand the data type and to unify the expansion of the data amount in the data type.

[0127] The beneficial effect of the above design scheme is: by determining data expansion rules based on operation associations, according to the data expansion rules, the second production operation data is expanded based on the first target production operation data to obtain the second target production data, thereby ensuring the richness and comprehensiveness of the obtained second target production data and providing a rich data basis for the determination of potential factors.

[0128] Example 10:

[0129] Based on Example 8, an embodiment of the present invention provides a comprehensive efficiency statistics system for industrial robots and industrial equipment. In the factor determination unit, based on the impact on the trend of the target change trend, the potential probability of occurrence is verified and adjusted to obtain the target potential probability of occurrence, including:

[0130] Determine whether the impact situation is within the predicted trend of the target change trend;

[0131] If so, determine the potential probability of occurrence as the target potential probability of occurrence;

[0132] Otherwise, a trend difference between the predicted trend and the target change trend is determined, and based on the trend difference, an adjustment value for the potential occurrence probability is determined to obtain the target potential occurrence probability.

[0133] In this embodiment, the predicted trend is obtained based on the target change trend prediction.

[0134] In this embodiment, the greater the trend difference, the greater the corresponding adjustment value.

[0135] The beneficial effect of the above design scheme is: by determining the trend difference between the predicted trend and the target change trend, based on the trend difference, determining the adjustment value of the potential occurrence probability, obtaining the target potential occurrence probability, and ensuring the accuracy of the obtained target potential occurrence probability.

[0136] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of this application document and its equivalents, the present invention is intended to include these modifications and variations.

Claims

1. A comprehensive efficiency statistics system for industrial robots and industrial equipment, characterized by: include: Data acquisition module, used to connect with sensors and controllers of industrial robots and industrial equipment to collect sensor data and production data; The indicator evaluation module is used to calculate the overall equipment efficiency of industrial robots and industrial equipment based on sensor data and production data, including three evaluation indicators: availability, performance efficiency, and production quality; The loss analysis module is used to analyze the production efficiency loss points based on the evaluation indicators and the production processes of industrial robots and industrial equipment, including: A comparison unit is used to compare the usability, performance efficiency and production quality with the preset evaluation standards to obtain the usability difference, performance efficiency difference and production quality difference; A process determination unit, configured to determine local production processes corresponding to availability, performance efficiency, and production quality from the production processes of industrial robots and industrial equipment; a suspicious determination unit, configured to determine a first suspicious point based on availability differences in combination with a local production process, determine a second suspicious point based on performance efficiency differences in combination with the local production process, and determine a third suspicious point based on production quality differences in combination with the local production process; a weight determination unit, configured to obtain a common suspicious point from the first suspicious point, the second suspicious point, and the third suspicious point, and determine an availability impact weight, a performance efficiency impact weight, and a production quality impact weight based on the difference in availability, the performance efficiency difference, and the production quality difference; An adjustment unit is used to determine the loss type of the common suspicious point, and to perform weighted adjustment on the analysis and identification model based on the availability impact weight, the performance efficiency impact weight, and the production quality impact weight to obtain a target analysis and identification model; a selection unit, configured to input the evaluation index data corresponding to the common suspicious points into a target analysis and recognition model for verification, obtain recognition results of the common suspicious points, and select production efficiency loss points from the common suspicious points based on the recognition results; The factor determination module is used to determine the potential efficiency influencing factors of industrial robots and industrial equipment based on production efficiency loss points and combined with historical data.

2. A comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 1, characterized in that: The data acquisition module includes: A parameter determination unit, configured to determine data acquisition parameters for sensors of industrial robots and industrial equipment based on the sensors of the sensors, and to determine data acquisition parameters for controllers of the sensors of industrial robots and industrial equipment based on the controllers of the sensors; An instruction generation unit, configured to generate an acquisition instruction for the sensor according to the data acquisition parameters of the sensor and the acquisition requirements, and to generate an acquisition instruction for the controller according to the data acquisition parameters of the controller and the acquisition requirements; The data acquisition unit is used to collect data from the sensor and the controller based on the acquisition instructions for the sensor and the acquisition instructions for the controller to obtain sensor data and production data.

3. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 1, characterized in that: The indicator evaluation module includes: A standardization unit is used to determine the data standard features of the sensor data and production data based on the calculation algorithm of the three evaluation indicators of availability, performance efficiency and production quality, and standardize the sensor data and production data based on the data standard features to obtain standard data; The computing unit is used to obtain the availability, performance efficiency and production quality of industrial robots and industrial equipment based on standard data and combined with computing algorithms.

4. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 3, characterized in that: The computing unit comprises: a processing unit for processing the standard data in chronological order according to the data attributes based on the calculation algorithm to obtain a target standard value; The calculation unit is used to calculate the target standard value according to the calculation algorithm to obtain the availability, performance efficiency and production quality of the industrial robot and industrial equipment.

5. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 1, characterized in that: The adjustment unit includes: A parameter acquisition unit is used to select an analysis and identification model corresponding to the loss type from the data model library, and obtain model parameters related to availability, performance efficiency and production quality in the analysis and identification model; The weighted adjustment unit is used to perform weighted adjustment on the model parameters based on the availability impact weight, the performance efficiency impact weight and the production quality impact weight to obtain a target analysis and identification model.

6. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 1, characterized in that: The selection unit includes: A judging unit, configured to determine an efficiency loss value for a common suspicious point in the identification result, and to judge whether the efficiency loss value is greater than a preset loss value; If so, determining the common suspicious point as a production efficiency loss point; Otherwise, it is determined that the common suspicious point is not a production efficiency loss point.

7. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 1, characterized in that: The factor determination module includes: a correlation acquisition unit, configured to acquire first production operation data having a first correlation with the production efficiency loss point, acquire second production operation data having a second correlation with the production efficiency loss point, and acquire first historical data related to the first production operation data and acquire second historical data related to the second production operation data from historical data; a matching analysis unit, configured to divide the first historical data into an operation data sequence according to a chronological order, obtain a change trend of the operation data sequence, match the change trend with an efficiency loss characteristic of a production efficiency loss point, and determine, based on a matching result, whether the change trend exceeds the efficiency loss characteristic; if so, assign a first weight to the change trend; otherwise, assign a second weight to the change trend; a weighted processing unit, configured to perform weighted processing on the first production operation data based on a weight of a change trend to obtain first target production operation data, and based on an operational association between the first production operation data and the second production operation data, process the second production operation data according to the first target production operation data to obtain second target production data; A factor determination unit is used to obtain the target change trend of the second historical data, and determine the influence of the second target production data on the trend direction of the target change trend; based on the data characteristics of the second target production data, determine the potential efficiency influencing factors of industrial robots and industrial equipment; based on the target change trend, determine the potential occurrence probability; based on the influence on the trend direction of the target change trend, verify and adjust the potential occurrence probability to obtain the target potential occurrence probability.

8. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 7, characterized in that: The weighted processing unit processes the second production operation data according to the first target production operation data based on the operational association between the first production operation data and the second production operation data to obtain the second target production data, including: Based on the operation association, a data expansion rule is determined, and according to the data expansion rule, the second production operation data is expanded based on the first target production operation data to obtain the second target production data.

9. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 7, characterized in that: In the factor determination unit, based on the impact on the trend of the target change trend, the potential probability of occurrence is verified and adjusted to obtain the target potential probability of occurrence, including: Determine whether the impact situation is within the predicted trend of the target change trend; If so, determine the potential probability of occurrence as the target potential probability of occurrence; Otherwise, a trend difference between the predicted trend and the target change trend is determined, and based on the trend difference, an adjustment value for the potential occurrence probability is determined to obtain the target potential occurrence probability.

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