CN119204809B - A comprehensive efficiency statistics system for industrial robots and industrial equipment - Google Patents
A comprehensive efficiency statistics system for industrial robots and industrial equipmentInfo
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Abstract
本发明提供了一种面向工业机器人以及工业设备的综合效率统计系统，通过采集传感数据和生产数据；基于传感数据和生产数据，计算得到工业机器人以及工业设备的整体设备效率，包括可用性，性能效率和生产质量三个评价指标，基于所述评价指标，结合工业机器人以及工业设备的生产流程，分析得到生产效率损失点，基于生产效率损失点，结合历史数据，确定工业机器人以及工业设备的潜在效率影响因素，能够全面了解设备运行状态，及时发现生产效率损失的根源，采取相应措施提升生产效率并优化资源配置，实现工业现代化、提高生产效率和质量控制。
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
The invention relates to the technical field of equipment efficiency analysis, in particular to a comprehensive efficiency statistical system for industrial robots and industrial equipment.
Background
Along with the development of science and technology, the automation factories are widely applied, and industrial robots and industrial equipment are used as production tools of the automation factories, so that the industrial robot and the industrial equipment bring remarkable significance to the production efficiency of the factories.
The significance of the comprehensive efficiency statistics of the industrial equipment is that the ratio of the actual production capacity of the equipment to the theoretical production capacity is measured, and the ratio is taken as an independent measuring tool, can represent the actual production capacity of the equipment, and is an important index for evaluating the performance of the equipment.
The Overall Equipment Efficiency (OEE) is not only an index for evaluating the effective operation of the production facility, the calculation result is universal, and even different industries can be compared, and the overall equipment efficiency can also be used as a key performance index and an efficiency index of lean production. Through OEE statistics, the actual value of OEE can be comprehensively displayed, the production efficiency is improved, the visible and invisible loss is reduced, and the cost control and the quality control are realized. For example, plant production efficiency will be improved by over 50% through predictive equipment maintenance and operation. This ensures that each production facility, each production link, remains in its best state of operation within its scope.
In addition, with the large-scale promotion and popularization of the industrial internet of things, the value of the equipment OEE is quickly realized, and the value of the equipment OEE is completely dependent on whether an enterprise has performed the equipment internet of things or not, and all factory equipment is in informationized link.
In summary, the statistics of the comprehensive efficiency of the industrial equipment is not only an important tool for measuring the performance of the equipment, but also a key means for realizing industrial modernization and improving the production efficiency and quality control, so that the statistics of the comprehensive efficiency of the industrial robot and the industrial equipment is particularly important.
Disclosure of Invention
The invention provides an industrial robot and industrial equipment oriented comprehensive efficiency statistical system, which is used for solving the problems in the background technology.
An industrial robot and industrial equipment oriented comprehensive efficiency statistics system comprising:
the data acquisition module is used for being connected with the sensors and the controllers of the industrial robot and the industrial equipment to acquire sensing data and production data;
The index evaluation module is used for calculating and obtaining the overall equipment efficiency of the industrial robot and the industrial equipment based on the sensing data and the production data, and comprises three evaluation indexes including availability, performance efficiency and production quality;
the loss analysis module is used for analyzing and obtaining a production efficiency loss point by combining the production flows of the industrial robot and the industrial equipment based on the evaluation index;
And the factor determining module is used for determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the production efficiency loss points and combining the historical data.
Preferably, the data acquisition module includes:
A parameter determining unit for determining data acquisition parameters of the sensors based on the sensors of the industrial robot and the industrial equipment, and determining data acquisition parameters of the controllers based on the controllers of the sensors of the industrial robot and the industrial equipment;
the instruction generation unit is used for generating an acquisition instruction of the sensor according to the data acquisition parameters of the sensor and the acquisition requirements, and generating the acquisition instruction of the controller according to the data acquisition parameters of the controller and the acquisition requirements;
The data acquisition unit is used for carrying out data acquisition on the sensor and the controller based on the acquisition instruction of the sensor and the acquisition instruction of the controller to obtain sensing data and production data.
Preferably, the index evaluation module includes:
the standardized unit is used for determining data standard characteristics of the sensing data and the production data based on the calculation algorithms of three evaluation indexes of availability, performance efficiency and production quality, and standardizing the sensing data and the production data based on the data standard characteristics to obtain standard data;
And the calculating unit is used for being based on the standard data. And combining a calculation algorithm to obtain the availability, performance efficiency and production quality of the industrial robot and industrial equipment.
Preferably, the computing unit includes:
the processing unit is used for processing the standard data according to the data attribute and the time sequence based on the calculation algorithm to obtain a target standard value;
And the calculating unit is used for calculating the target standard value according to the calculating algorithm to obtain the availability, the performance efficiency and the production quality of the industrial robot and the industrial equipment.
Preferably, the loss analysis module includes:
The comparison unit is used for comparing the usability, the performance efficiency and the production quality with preset evaluation standards to obtain usability differences, performance efficiency differences and production quality differences;
A flow determining unit for determining local production flows corresponding to the availability, the performance efficiency and the production quality from the production flows of the industrial robot and the industrial equipment, respectively;
The suspicious determining unit is used for determining a first suspicious point based on the availability difference and combining the local production flow, determining a second suspicious point based on the performance efficiency difference and combining the local production flow, and determining a third suspicious point based on the production quality difference and combining the local production flow;
A weight determining unit for acquiring common suspicious points from the first suspicious point, the second suspicious point and the third suspicious point, and determining an availability influence weight, a performance efficiency influence weight and a production quality influence weight based on the difference magnitudes of the availability difference, the performance efficiency difference and the production quality difference;
the adjusting unit is used for determining the loss type of the common suspicious points, and carrying out weighted adjustment on the analysis recognition model based on the availability influence weight, the performance efficiency influence weight and the production quality influence weight to obtain a target analysis recognition model;
The selection unit is used for inputting the evaluation index data corresponding to the common suspicious points into the target analysis recognition model for verification to obtain the recognition result of the common suspicious points, and selecting the production efficiency loss points from the common suspicious points based on the recognition result.
Preferably, the adjusting unit includes:
the parameter acquisition unit is used for selecting an analysis and identification model corresponding to the loss type from the data model library and acquiring model parameters related to availability, performance efficiency and production quality in the analysis and identification model;
And the weighting adjustment unit is used for carrying out weighting adjustment on the model parameters based on the availability influence weight, the performance efficiency influence weight and the production quality influence weight to obtain a target analysis and identification model.
Preferably, the selecting unit includes:
The judging unit is used for determining efficiency loss values for the common suspicious points in the identification result and judging whether the efficiency loss values are larger than preset loss values or not;
If yes, determining the common suspicious points as production efficiency loss points;
otherwise, it is determined that the common suspicious point is not a production efficiency loss point.
Preferably, the factor determining module includes:
A correlation acquisition unit, configured to acquire first production operation data having a first correlation with a production efficiency loss point, acquire second production operation data having a second correlation with the production efficiency loss point, acquire first historical data related to the first production operation data from the historical data, and acquire second historical data related to the second production operation;
the matching analysis unit is used for dividing the first historical data according to a time sequence to obtain an operation data sequence, acquiring a change trend of the operation data sequence, matching the change trend with the efficiency loss characteristics of the production efficiency loss points, judging whether the change trend exceeds the efficiency loss characteristics according to a matching result, if so, giving a first weight to the change trend, and if not, giving a second weight to the change trend;
The weighting processing unit is used for carrying out weighting processing on the first production operation data based on the weight of the variation trend to obtain first target production operation data, and processing the second production operation data according to the first target production operation data based on the operation association between the first production operation data and the second production operation data to obtain second target production data;
the factor determining unit is used for acquiring the target change trend of the second historical data, determining the influence condition of the second target production data on the trend of the target change trend, determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the data characteristics of the second target production data, determining potential occurrence probability based on the target change trend, and verifying and adjusting the potential occurrence probability based on the influence condition on the trend of the target change trend to obtain the target potential occurrence probability.
Preferably, the weighting processing unit processes the second production operation data according to the first target production operation data based on the operation association between the first production operation data and the second production operation data, to obtain second target production data, and includes:
Based on the operation association, determining a data expansion rule, and expanding the second production operation data based on the first target production operation data according to the data expansion rule to obtain second target production data.
Preferably, the factor determining unit verifies and adjusts the potential occurrence probability based on the influence condition on the trend of the target change trend, to obtain the target potential occurrence probability, and the factor determining unit includes:
Judging whether the influence condition is in the predicted trend of the target change trend or not;
If yes, determining the potential occurrence probability as the target potential occurrence probability;
Otherwise, determining the trend difference between the predicted trend and the target change trend, and determining an adjustment value of the potential occurrence probability based on the trend difference to obtain the target potential occurrence probability.
Compared with the prior art, the invention has the following beneficial effects:
The method comprises the steps of acquiring sensing data and production data, calculating and obtaining the overall equipment efficiency of the industrial robot and the industrial equipment based on the sensing data and the production data, wherein the overall equipment efficiency comprises three evaluation indexes including availability, performance efficiency and production quality, analyzing and obtaining production efficiency loss points by combining production processes of the industrial robot and the industrial equipment based on the evaluation indexes, determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the production efficiency loss points and combining historical data, comprehensively knowing the equipment operation state, finding the root cause of the production efficiency loss in time, adopting corresponding measures to improve the production efficiency, optimizing resource allocation, and realizing industrial modernization and improvement of the production efficiency and quality control.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objects and other advantages of the application may be realized and obtained by means of the instrumentalities particularly pointed out in the specification.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of an industrial robot and industrial equipment oriented comprehensive efficiency statistics system in an embodiment of the invention;
FIG. 2 is a block diagram of a data acquisition module according to an embodiment of the present invention;
fig. 3 is a block diagram of the index evaluation module according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1:
The embodiment of the invention provides an integrated efficiency statistical system for an industrial robot and industrial equipment, as shown in fig. 1, comprising:
the data acquisition module is used for being connected with the sensors and the controllers of the industrial robot and the industrial equipment to acquire sensing data and production data;
The index evaluation module is used for calculating and obtaining the overall equipment efficiency of the industrial robot and the industrial equipment based on the sensing data and the production data, and comprises three evaluation indexes including availability, performance efficiency and production quality;
the loss analysis module is used for analyzing and obtaining a production efficiency loss point by combining the production flows of the industrial robot and the industrial equipment based on the evaluation index;
And the factor determining module is used for determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the production efficiency loss points and combining the historical data.
In this embodiment, the sensed data and the production data include run and down time, cycle time, quantity production, etc.
In this embodiment, the production efficiency loss points are, for example, equipment failure, operation failure, slow tact, and the like.
In this embodiment, the potential efficiency influencing factor is a factor that may become a point of loss of production efficiency.
The design scheme has the advantages that the overall equipment efficiency of the industrial robot and the industrial equipment is calculated and obtained based on the sensing data and the production data, the overall equipment efficiency comprises three evaluation indexes including availability, performance efficiency and production quality, the production efficiency loss point is obtained by analyzing based on the evaluation indexes and combining the production flow of the industrial robot and the industrial equipment, the potential efficiency influence factors of the industrial robot and the industrial equipment are determined based on the production efficiency loss point and combining historical data, the equipment running state can be comprehensively known, the root cause of the production efficiency loss can be timely found, the corresponding measures are taken to improve the production efficiency, the resource allocation is optimized, the industrial modernization is realized, and the production efficiency and the quality control are improved.
Example 2:
Based on embodiment 1, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, as shown in fig. 2, where the data acquisition module includes:
A parameter determining unit for determining data acquisition parameters of the sensors based on the sensors of the industrial robot and the industrial equipment, and determining data acquisition parameters of the controllers based on the controllers of the sensors of the industrial robot and the industrial equipment;
the instruction generation unit is used for generating an acquisition instruction of the sensor according to the data acquisition parameters of the sensor and the acquisition requirements, and generating the acquisition instruction of the controller according to the data acquisition parameters of the controller and the acquisition requirements;
The data acquisition unit is used for carrying out data acquisition on the sensor and the controller based on the acquisition instruction of the sensor and the acquisition instruction of the controller to obtain sensing data and production data.
In this embodiment, the data acquisition parameters include acquisition frequency, acquisition time point, and the like.
In this embodiment, the acquisition requirements include data accuracy, and the like.
The design scheme has the beneficial effects that the acquisition instruction of the sensor is generated by combining the acquisition requirement according to the data acquisition parameters of the sensor, the acquisition instruction of the controller is generated by combining the acquisition requirement according to the data acquisition parameters of the controller, the data acquisition is performed on the sensor and the controller based on the acquisition instruction of the sensor and the acquisition instruction of the controller, so that the sensing data and the production data are obtained, and a data basis is provided for comprehensive efficiency statistics.
Example 3:
based on embodiment 1, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, as shown in fig. 3, where the index evaluation module includes:
the standardized unit is used for determining data standard characteristics of the sensing data and the production data based on the calculation algorithms of three evaluation indexes of availability, performance efficiency and production quality, and standardizing the sensing data and the production data based on the data standard characteristics to obtain standard data;
And the calculating unit is used for being based on the standard data. And combining a calculation algorithm to obtain the availability, performance efficiency and production quality of the industrial robot and industrial equipment.
In this embodiment, the calculation algorithms of the three evaluation indexes of availability, performance efficiency and production quality are preset according to the historical data conditions.
The design scheme has the beneficial effects that the data standard characteristics of the sensing data and the production data are determined through the calculation algorithm based on three evaluation indexes of availability, performance efficiency and production quality, the data standard characteristics are based on the data standard characteristics, the standard data is obtained by normalizing the sensing data and the production data, the calculation efficiency and the calculation accuracy are improved in terms of data quality, and a high-quality data base is provided for calculation of the indexes.
Example 4:
Based on embodiment 3, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, where the computing unit includes:
the processing unit is used for processing the standard data according to the data attribute and the time sequence based on the calculation algorithm to obtain a target standard value;
And the calculating unit is used for calculating the target standard value according to the calculating algorithm to obtain the availability, the performance efficiency and the production quality of the industrial robot and the industrial equipment.
In this embodiment, the target standard value is, for example, an average value, a median value, or the like in time series.
The design scheme has the beneficial effects that the standard data is processed according to the time sequence based on the calculation algorithm according to the data attribute to obtain the target standard value, the target standard value is calculated according to the calculation algorithm, the availability, the performance efficiency and the production quality of the industrial robot and the industrial equipment are obtained, the correctness of the data in the index process is ensured, and the correctness of the index is ensured.
Example 5:
based on embodiment 1, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, where the loss analysis module includes:
The comparison unit is used for comparing the usability, the performance efficiency and the production quality with preset evaluation standards to obtain usability differences, performance efficiency differences and production quality differences;
A flow determining unit for determining local production flows corresponding to the availability, the performance efficiency and the production quality from the production flows of the industrial robot and the industrial equipment, respectively;
The suspicious determining unit is used for determining a first suspicious point based on the availability difference and combining the local production flow, determining a second suspicious point based on the performance efficiency difference and combining the local production flow, and determining a third suspicious point based on the production quality difference and combining the local production flow;
A weight determining unit for acquiring common suspicious points from the first suspicious point, the second suspicious point and the third suspicious point, and determining an availability influence weight, a performance efficiency influence weight and a production quality influence weight based on the difference magnitudes of the availability difference, the performance efficiency difference and the production quality difference;
the adjusting unit is used for determining the loss type of the common suspicious points, and carrying out weighted adjustment on the analysis recognition model based on the availability influence weight, the performance efficiency influence weight and the production quality influence weight to obtain a target analysis recognition model;
The selection unit is used for inputting the evaluation index data corresponding to the common suspicious points into the target analysis recognition model for verification to obtain the recognition result of the common suspicious points, and selecting the production efficiency loss points from the common suspicious points based on the recognition result.
In this embodiment, the generation flow includes operation data, production process data, and production result data.
In this embodiment, the common suspicious point may be a loss efficiency point, requiring further judgment.
In this embodiment, the analysis identifies the model to perform weighting adjustments, specifically, determination of a loss function for the model, determination of a validation set, determination of the number of model layers, and so forth.
The design scheme has the beneficial effects that the availability, the performance efficiency and the production quality are based on analysis, the model parameters are adjusted according to the analysis result, the applicability of the obtained model is ensured, the evaluation index data corresponding to the common suspicious points are finally input into a target analysis recognition model for verification, the recognition result of the common suspicious points is obtained, the production efficiency loss points are selected from the common suspicious points based on the recognition result, and the accurate judgment of the production efficiency loss points is realized.
Example 6:
Based on embodiment 5, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, where the adjusting unit includes:
the parameter acquisition unit is used for selecting an analysis and identification model corresponding to the loss type from the data model library and acquiring model parameters related to availability, performance efficiency and production quality in the analysis and identification model;
And the weighting adjustment unit is used for carrying out weighting adjustment on the model parameters based on the availability influence weight, the performance efficiency influence weight and the production quality influence weight to obtain a target analysis and identification model.
In this embodiment, the database includes analysis recognition models corresponding to various loss types, and the analysis recognition models are obtained through machine algorithm and historical data training in advance.
The design scheme has the beneficial effects that the model parameters are adjusted according to analysis results by analyzing based on availability, performance efficiency and production quality, so that the applicability of the obtained model is ensured.
Example 7:
Based on embodiment 5, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, where the selection unit includes:
The judging unit is used for determining efficiency loss values for the common suspicious points in the identification result and judging whether the efficiency loss values are larger than preset loss values or not;
If yes, determining the common suspicious points as production efficiency loss points;
otherwise, it is determined that the common suspicious point is not a production efficiency loss point.
In this embodiment, the greater the efficiency loss, the greater the corresponding efficiency loss value.
In this embodiment, the preset loss value is preset according to the actual situation.
The design scheme has the beneficial effects that the efficiency loss value of the common suspicious points is determined through the identification result, whether the efficiency loss value is larger than the preset loss value is judged, if yes, the common suspicious points are determined to be production efficiency loss points, otherwise, the common suspicious points are determined not to be production efficiency loss points, and the judgment of the production efficiency loss points is realized.
Example 8:
Based on embodiment 1, the embodiment of the invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, wherein the factor determining module comprises:
A correlation acquisition unit, configured to acquire first production operation data having a first correlation with a production efficiency loss point, acquire second production operation data having a second correlation with the production efficiency loss point, acquire first historical data related to the first production operation data from the historical data, and acquire second historical data related to the second production operation;
the matching analysis unit is used for dividing the first historical data according to a time sequence to obtain an operation data sequence, acquiring a change trend of the operation data sequence, matching the change trend with the efficiency loss characteristics of the production efficiency loss points, judging whether the change trend exceeds the efficiency loss characteristics according to a matching result, if so, giving a first weight to the change trend, and if not, giving a second weight to the change trend;
The weighting processing unit is used for carrying out weighting processing on the first production operation data based on the weight of the variation trend to obtain first target production operation data, and processing the second production operation data according to the first target production operation data based on the operation association between the first production operation data and the second production operation data to obtain second target production data;
the factor determining unit is used for acquiring the target change trend of the second historical data, determining the influence condition of the second target production data on the trend of the target change trend, determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the data characteristics of the second target production data, determining potential occurrence probability based on the target change trend, and verifying and adjusting the potential occurrence probability based on the influence condition on the trend of the target change trend to obtain the target potential occurrence probability.
In this embodiment, the first correlation is greater than the second correlation, the first production operation data is used to determine a point of efficiency loss, and the second production operation data is used to determine a potential factor.
In this embodiment, a trend of change exceeding the efficiency loss characteristic indicates that the trend is aggravated, the first weight being greater than the second weight.
In this embodiment, the first production operation data is weighted based on the weight of the trend of variation, and the weight of the weighted processing is the first weight or the second weight.
The design scheme has the beneficial effects that potential efficiency influence factors and target potential occurrence probability are determined by analyzing according to historical data and effect pipe operation data, the source of production efficiency loss is found in advance, corresponding measures are taken to improve production efficiency and optimize resource allocation, and industrial modernization is realized, and production efficiency and quality control are improved.
Example 9:
Based on embodiment 8, an embodiment of the present invention provides an integrated efficiency statistics system for an industrial robot and an industrial device, where the weighting processing unit processes, based on an operation association between first production operation data and second production operation data, the second production operation data according to the first target production operation data to obtain second target production data, and includes:
Based on the operation association, determining a data expansion rule, and expanding the second production operation data based on the first target production operation data according to the data expansion rule to obtain second target production data.
In this embodiment, the data expansion rule is, for example, to expand the data type, and unify the expansion of the data amount in the data type.
The design scheme has the beneficial effects that the data expansion rule is determined based on the operation association, the second production operation data is expanded based on the first target production operation data according to the data expansion rule, the second target production data is obtained, the richness and the comprehensiveness of the obtained second target production data are ensured, and a rich data base is provided for determining potential factors.
Example 10:
Based on embodiment 8, the embodiment of the invention provides a comprehensive efficiency statistics system for an industrial robot and industrial equipment, wherein in the factor determining unit, based on the influence condition on trend of a target change trend, the potential occurrence probability is verified and adjusted to obtain the target potential occurrence probability, which comprises the following steps:
Judging whether the influence condition is in the predicted trend of the target change trend or not;
If yes, determining the potential occurrence probability as the target potential occurrence probability;
Otherwise, determining the trend difference between the predicted trend and the target change trend, and determining an adjustment value of the potential occurrence probability based on the trend difference to obtain the target potential occurrence probability.
In this embodiment, the predicted trend is predicted from the target variation trend.
In this embodiment, the greater the trend difference, the greater the corresponding adjustment value.
The design scheme has the beneficial effects that the potential occurrence probability of the target is obtained by determining the trend difference between the predicted trend and the target change trend and determining the adjustment value of the potential occurrence probability based on the trend difference, so that the accuracy of the obtained potential occurrence probability of the target is ensured.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present document and the equivalent arts thereof, the present application also intends to include such modifications and variations.
Claims (9)
1. An industrial robot and industrial equipment oriented comprehensive efficiency statistics system, comprising:
the data acquisition module is used for being connected with the sensors and the controllers of the industrial robot and the industrial equipment to acquire sensing data and production data;
The index evaluation module is used for calculating and obtaining the overall equipment efficiency of the industrial robot and the industrial equipment based on the sensing data and the production data, and comprises three evaluation indexes including availability, performance efficiency and production quality;
the loss analysis module is used for analyzing and obtaining a production efficiency loss point by combining the production flows of the industrial robot and the industrial equipment based on the evaluation index, and comprises the following steps:
The comparison unit is used for comparing the usability, the performance efficiency and the production quality with preset evaluation standards to obtain usability differences, performance efficiency differences and production quality differences;
A flow determining unit for determining local production flows corresponding to the availability, the performance efficiency and the production quality from the production flows of the industrial robot and the industrial equipment, respectively;
The suspicious determining unit is used for determining a first suspicious point based on the availability difference and combining the local production flow, determining a second suspicious point based on the performance efficiency difference and combining the local production flow, and determining a third suspicious point based on the production quality difference and combining the local production flow;
A weight determining unit for acquiring common suspicious points from the first suspicious point, the second suspicious point and the third suspicious point, and determining an availability influence weight, a performance efficiency influence weight and a production quality influence weight based on the difference magnitudes of the availability difference, the performance efficiency difference and the production quality difference;
the adjusting unit is used for determining the loss type of the common suspicious points, and carrying out weighted adjustment on the analysis recognition model based on the availability influence weight, the performance efficiency influence weight and the production quality influence weight to obtain a target analysis recognition model;
The selection unit is used for inputting the evaluation index data corresponding to the common suspicious points into a target analysis recognition model for verification to obtain a recognition result of the common suspicious points, and selecting the production efficiency loss points from the common suspicious points based on the recognition result;
And the factor determining module is used for determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the production efficiency loss points and combining the historical data.
2. The industrial robot and industrial equipment oriented comprehensive efficiency statistics system of claim 1, wherein the data acquisition module comprises:
A parameter determining unit for determining data acquisition parameters of the sensors based on the sensors of the industrial robot and the industrial equipment, and determining data acquisition parameters of the controllers based on the controllers of the sensors of the industrial robot and the industrial equipment;
the instruction generation unit is used for generating an acquisition instruction of the sensor according to the data acquisition parameters of the sensor and the acquisition requirements, and generating the acquisition instruction of the controller according to the data acquisition parameters of the controller and the acquisition requirements;
The data acquisition unit is used for carrying out data acquisition on the sensor and the controller based on the acquisition instruction of the sensor and the acquisition instruction of the controller to obtain sensing data and production data.
3. An industrial robot and industrial equipment oriented comprehensive efficiency statistics system as described in claim 1, the index evaluation module is characterized by comprising:
the standardized unit is used for determining data standard characteristics of the sensing data and the production data based on the calculation algorithms of three evaluation indexes of availability, performance efficiency and production quality, and standardizing the sensing data and the production data based on the data standard characteristics to obtain standard data;
and the computing unit is used for obtaining the availability, the performance efficiency and the production quality of the industrial robot and the industrial equipment by combining a computing algorithm based on the standard data.
4. An industrial robot and industrial equipment oriented comprehensive efficiency statistics system according to claim 3, characterized in that the calculation unit comprises:
the processing unit is used for processing the standard data according to the data attribute and the time sequence based on the calculation algorithm to obtain a target standard value;
And the calculating unit is used for calculating the target standard value according to the calculating algorithm to obtain the availability, the performance efficiency and the production quality of the industrial robot and the industrial equipment.
5. An industrial robot and industrial equipment oriented comprehensive efficiency statistics system according to claim 1, characterized in that the adjustment unit comprises:
the parameter acquisition unit is used for selecting an analysis and identification model corresponding to the loss type from the data model library and acquiring model parameters related to availability, performance efficiency and production quality in the analysis and identification model;
And the weighting adjustment unit is used for carrying out weighting adjustment on the model parameters based on the availability influence weight, the performance efficiency influence weight and the production quality influence weight to obtain a target analysis and identification model.
6. An industrial robot and industrial equipment oriented comprehensive efficiency statistics system according to claim 1, wherein the selection unit comprises:
The judging unit is used for determining efficiency loss values for the common suspicious points in the identification result and judging whether the efficiency loss values are larger than preset loss values or not;
If yes, determining the common suspicious points as production efficiency loss points;
otherwise, it is determined that the common suspicious point is not a production efficiency loss point.
7. An industrial robot-oriented and industrial equipment comprehensive efficiency statistics system in accordance with claim 1, wherein said factor determination module comprises:
A correlation acquisition unit, configured to acquire first production operation data having a first correlation with a production efficiency loss point, acquire second production operation data having a second correlation with the production efficiency loss point, acquire first historical data related to the first production operation data from the historical data, and acquire second historical data related to the second production operation;
the matching analysis unit is used for dividing the first historical data according to a time sequence to obtain an operation data sequence, acquiring a change trend of the operation data sequence, matching the change trend with the efficiency loss characteristics of the production efficiency loss points, judging whether the change trend exceeds the efficiency loss characteristics according to a matching result, if so, giving a first weight to the change trend, and if not, giving a second weight to the change trend;
The weighting processing unit is used for carrying out weighting processing on the first production operation data based on the weight of the variation trend to obtain first target production operation data, and processing the second production operation data according to the first target production operation data based on the operation association between the first production operation data and the second production operation data to obtain second target production data;
the factor determining unit is used for acquiring the target change trend of the second historical data, determining the influence condition of the second target production data on the trend of the target change trend, determining potential efficiency influence factors of the industrial robot and the industrial equipment based on the data characteristics of the second target production data, determining potential occurrence probability based on the target change trend, and verifying and adjusting the potential occurrence probability based on the influence condition on the trend of the target change trend to obtain the target potential occurrence probability.
8. The system of claim 7, wherein the weighted processing unit processes the second production operation data according to the first target production operation data based on an operation association between the first production operation data and the second production operation data to obtain the second target production data, and the method comprises:
Based on the operation association, determining a data expansion rule, and expanding the second production operation data based on the first target production operation data according to the data expansion rule to obtain second target production data.
9. The comprehensive efficiency statistics system for industrial robots and industrial equipment according to claim 7, wherein the factor determining unit verifies and adjusts the probability of occurrence of the target based on the influence on trend of the target trend, and obtains the probability of occurrence of the target, comprising:
Judging whether the influence condition is in the predicted trend of the target change trend or not;
If yes, determining the potential occurrence probability as the target potential occurrence probability;
Otherwise, determining the trend difference between the predicted trend and the target change trend, and determining an adjustment value of the potential occurrence probability based on the trend difference to obtain the target potential occurrence probability.
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| CN116117811A (en) * | 2023-02-07 | 2023-05-16 | 北京机科国创轻量化科学研究院有限公司 | Digital twinning-based industrial robot comprehensive performance analysis method and system |
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| US20240210935A1 (en) * | 2022-12-22 | 2024-06-27 | Delaware Capital Formation, Inc. | Predictive model for determining overall equipment effectiveness (oee) in industrial equipment |
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| CN116117811A (en) * | 2023-02-07 | 2023-05-16 | 北京机科国创轻量化科学研究院有限公司 | Digital twinning-based industrial robot comprehensive performance analysis method and system |
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