Production equipment efficiency analysis system based on big data governance analysis platform

Abstract

The invention relates to the technical field of equipment production efficiency analysis, and provides a production equipment efficiency analysis system based on a big data governance analysis platform, and the system comprises a time loss analysis module which is used for collecting the operation data of production equipment and analyzing the time loss of the production equipment; the equipment use efficiency calculation module is used for calculating the equipment use efficiency of the production equipment based on the equipment availability rate, the equipment operation rate and the equipment pure operation rate; the relative efficiency calculation module is used for querying an input index and an output index of the production equipment and carrying out data envelope analysis on the production equipment to obtain a relative efficiency score of the production equipment; the production efficiency calculation module is used for calculating the production efficiency of the production equipment based on the product qualification rate, the equipment use efficiency and the relative efficiency score; and the production efficiency influence analysis module is used for constructing a production efficiency analysis report of the production equipment based on the production efficiency and the influence factors. Factors influencing the production efficiency of the equipment can be deeply excavated.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment production efficiency analysis, and in particular to a production equipment efficiency analysis system and method based on a big data governance analysis platform. Background Art

[0002] In today's digital age, the development of big data governance and analysis platforms has brought new insights and decision-making support capabilities to corporate production management. Especially in the field of production equipment efficiency analysis, systems based on big data governance and analysis platforms have attracted much attention for their accuracy, comprehensiveness and intelligence.

[0003] At present, traditional production equipment efficiency analysis methods mainly rely on manual records and simple data statistics. Although these methods can reflect the operation of the equipment to a certain extent, they have obvious limitations. Among them, manual records are not only time-consuming and laborious, but also difficult to ensure the accuracy of data, which easily leads to the problem of inaccurate efficiency analysis of production equipment; simple data statistics may not be able to deeply explore the potential problems in the operation of the equipment, resulting in the inability to explore the factors that affect the production efficiency of the equipment, thus affecting the accuracy of the analysis of the production equipment. Summary of the invention

[0004] The present invention provides a production equipment efficiency analysis system and method based on a big data governance and analysis platform, the main purpose of which is to improve the accuracy of intelligent control of a grinding and repairing machine.

[0005] To achieve the above objectives, the present invention provides a production equipment efficiency analysis system based on a big data governance analysis platform, comprising: a time loss analysis module, an equipment utilization efficiency calculation module, a relative efficiency calculation module, a production efficiency calculation module, and a production efficiency impact analysis module.

[0006] The time loss analysis module is used to collect the operation data of the production equipment, perform data preprocessing on the operation data to obtain preprocessed data, transmit the preprocessed data to the big data governance and analysis platform, and then analyze the time loss of the production equipment based on the preprocessed data using the big data governance and analysis platform;

[0007] The equipment utilization efficiency calculation module is used to calculate the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss, and calculate the equipment utilization efficiency of the production equipment based on the equipment availability, the equipment operation rate and the equipment pure operation rate;

[0008] The relative efficiency calculation module is used to query the input index and output index of the production equipment, and based on the input index and output index, perform data envelopment analysis on the production equipment to obtain the relative efficiency score of the production equipment;

[0009] The production efficiency calculation module is used to perform quality analysis on the products produced by the production equipment according to the pre-processed data to obtain a product qualification rate, and calculate the production efficiency of the production equipment based on the product qualification rate, the equipment use efficiency and the relative efficiency score;

[0010] The production efficiency impact analysis module is used to query the operating environment, equipment maintenance data and management data of the production equipment, determine the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, and construct a production efficiency analysis report for the production equipment based on the production efficiency and the influencing factors.

[0011] Optionally, performing data preprocessing on the operating data to obtain preprocessed data includes:

[0012] Performing data cleaning on the operation data to obtain cleaned data;

[0013] Performing data integration on the cleaned data to obtain integrated data;

[0014] The integrated data is subjected to data standardization processing to obtain preprocessed data.

[0015] Optionally, analyzing the time loss of the production equipment using the big data governance analysis platform based on the pre-processed data includes:

[0016] identifying time data in the preprocessed data;

[0017] Classifying the time data to obtain classified time data;

[0018] Using the big data governance and analysis platform to perform time series analysis, correlation analysis, and cluster analysis on the classified time data to obtain comprehensive analysis results;

[0019] The comprehensive analysis result is taken as the time loss of the production equipment.

[0020] Optionally, the calculating of the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss includes:

[0021] Querying the loss factor of the time loss;

[0022] Based on the loss factors, the time loss is divided into downtime, delay time and waiting time;

[0023] Calculating the equipment availability of the production equipment based on the downtime;

[0024] Calculating the equipment operation rate of the production equipment based on the delay time;

[0025] Based on the waiting time, the equipment pure operation rate of the production equipment is calculated.

[0026] Optionally, performing data envelopment analysis on the production equipment based on the input index and the output index to obtain a relative efficiency score of the production equipment includes:

[0027] Using the production equipment as a production decision unit;

[0028] Constructing input index parameters and output index parameters corresponding to each unit in the production decision unit;

[0029] Constructing a linear programming model of the production equipment based on the production decision unit, the input index parameter and the output index parameter;

[0030] Based on the linear programming model, a relative efficiency score of the production equipment is calculated.

[0031] Optionally, constructing a linear programming model of the production equipment based on the production decision unit, the input index parameter and the output index parameter includes:

[0032] Constructing an input vector corresponding to the input indicator parameter;

[0033] Constructing an output vector corresponding to the output indicator parameter;

[0034] A linear programming model of the production equipment is constructed based on the production decision unit, the input vector and the output vector.

[0035] Optionally, performing quality analysis on the products produced by the production equipment according to the preprocessed data to obtain a product qualification rate includes:

[0036] Based on the preprocessed data, determining a sample product corresponding to the production equipment;

[0037] Query the evaluation criteria of the sample products;

[0038] The qualified rate of the sample products is calculated based on the evaluation criteria to obtain the product qualified rate.

[0039] Optionally, determining factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data includes:

[0040] Classifying the production equipment by efficiency to obtain efficiency-graded production equipment;

[0041] Selecting influencing key features from the operating environment, the equipment maintenance data and the management data;

[0042] Calculate the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics;

[0043] Based on the correlation coefficient, construct a production efficiency prediction curve of the production equipment;

[0044] Acquiring real-time data of the production equipment;

[0045] Analyzing the efficiency deviation of the production equipment based on the real-time data and the production efficiency prediction curve;

[0046] The deviation influencing factors of the efficiency deviation are identified to determine the influencing factors of the production efficiency of the production equipment.

[0047] Optionally, the calculating the correlation coefficient between the efficiency graded production equipment and the influencing key features includes:

[0048] Query the production efficiency and key influencing features of the efficiency graded production equipment;

[0049] Constructing a regression function for the efficiency graded production equipment;

[0050] Taking the production efficiency as the dependent variable of the regression function;

[0051] Taking the key influencing features as independent variables of the regression function;

[0052] The dependent variable and the independent variable are combined with the regression function to calculate the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics.

[0053] A production equipment efficiency analysis method based on a big data governance analysis platform, characterized in that the method comprises:

[0054] Collecting operation data of production equipment, performing data preprocessing on the operation data to obtain preprocessed data, transmitting the preprocessed data to a big data governance and analysis platform, and then analyzing the time loss of the production equipment using the big data governance and analysis platform based on the preprocessed data;

[0055] Based on the time loss, calculate the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment, and based on the equipment availability, the equipment operation rate and the equipment pure operation rate, calculate the equipment utilization efficiency of the production equipment;

[0056] Querying the input index and output index of the production equipment, and performing data envelopment analysis on the production equipment based on the input index and output index to obtain a relative efficiency score of the production equipment;

[0057] Performing a quality analysis on the products produced by the production equipment according to the preprocessed data to obtain a product qualification rate, and calculating the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score;

[0058] Query the operating environment, equipment maintenance data and management data of the production equipment, determine the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, and construct a production efficiency analysis report for the production equipment based on the production efficiency and the influencing factors.

[0059] The present invention can understand the operating status, performance and other aspects of the equipment by collecting the operating data of the production equipment; the present invention can accurately understand the performance of the equipment in actual production by calculating the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss, judge whether the equipment reaches the expected operating level, and compare the performance of equipment on different models and different production lines, provide reference for equipment selection and procurement, and can also reasonably arrange production tasks according to indicators such as equipment availability to avoid over-reliance on a certain equipment and causing production delays; the present invention can help users evaluate the performance and benefits of production equipment by querying the input indicators and output indicators of the production equipment, so as to make reasonable decisions, such as equipment selection, investment decisions and production planning arrangements; the present invention can measure the performance and efficiency of the production equipment by performing quality analysis on the production products of the production equipment according to the preprocessing data, and obtaining the product qualification rate; finally, the present invention can understand which factors affect the production equipment during operation by querying the operating environment, equipment maintenance data and management data of the production equipment. Therefore, the present invention can deeply explore the factors affecting the production efficiency of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A functional module diagram of a production equipment efficiency analysis system based on a big data governance analysis platform provided by one embodiment of the present invention;

[0061] Figure 2 A flowchart of a production equipment efficiency analysis method based on a big data governance analysis platform is provided for one embodiment of the present invention.

[0062] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0065] In fact, the server-side device deployed by the production equipment efficiency analysis system based on the big data governance and analysis platform may be composed of one or more devices. The above-mentioned production equipment efficiency analysis system based on the big data governance and analysis platform can be implemented as: business instance, virtual machine, hardware device. For example, the production equipment efficiency analysis system based on the big data governance and analysis platform can be implemented as a business instance deployed on one or more devices in the cloud node. In simple terms, the live broadcast service system can be understood as a software deployed on the cloud node, which is used to provide intelligent control services of the grinding and repairing machine to each user terminal. Alternatively, the production equipment efficiency analysis system based on the big data governance and analysis platform can also be implemented as a virtual machine deployed on one or more devices in the cloud node. The virtual machine is installed with application software for managing each user terminal. Alternatively, the production equipment efficiency analysis system based on the big data governance and analysis platform can also be implemented as a server consisting of many hardware devices of the same or different types, and one or more hardware devices are set to provide intelligent control services of the grinding and repairing machine to each user terminal.

[0066] In terms of implementation, the production equipment efficiency analysis system based on the big data governance and analysis platform and the user end are adapted to each other. That is, the production equipment efficiency analysis system based on the big data governance and analysis platform is an application installed on the cloud service platform, and the user end is a client that establishes a communication connection with the application; or the production equipment efficiency analysis system based on the big data governance and analysis platform is implemented as a website, and the user end is implemented as a web page; or the production equipment efficiency analysis system based on the big data governance and analysis platform is implemented as a cloud service platform, and the user end is implemented as a small program in the instant messaging application.

[0067] Reference Figure 1 The figure shows a functional module diagram of a production equipment efficiency analysis system based on a big data governance analysis platform provided by one embodiment of the present invention.

[0068] The production equipment efficiency analysis system 100 based on the big data governance analysis platform of the present invention can be set in a cloud server. In terms of implementation, it can be used as one or more service devices, or it can be installed as an application on the cloud (such as a server for production equipment efficiency, a server cluster, etc.), or it can also be developed as a website. According to the functions implemented, the production equipment efficiency analysis system 100 based on the big data governance analysis platform includes a time loss analysis module 101, an equipment use efficiency calculation module 102, a relative efficiency calculation module 103, a production efficiency calculation module 104, and a production efficiency impact analysis module 105. In the embodiment of the present invention, in the production equipment efficiency analysis based on the big data governance analysis platform, each of the above modules can be implemented independently and called with other modules. The call here can be understood as that a certain module can connect to multiple modules of another type and provide corresponding services to the multiple modules connected to it. In the production equipment efficiency analysis system based on the big data governance analysis platform provided by the embodiment of the present invention, there is no need to modify the program code. The scope of application of the intelligent control architecture of the grinding repair machine can be adjusted by adding modules and directly calling them, so as to achieve cluster-type horizontal expansion, so as to achieve the purpose of quickly and flexibly expanding the production equipment efficiency analysis system based on the big data governance analysis platform. In actual applications, the above modules can be set in the same device or different devices, or in a virtual device, such as a service instance in a cloud server.

[0069] In the following, in combination with specific embodiments, each component and specific workflow of the production equipment efficiency analysis system based on the big data governance analysis platform are explained respectively.

[0070] The time loss analysis module 201 is used to collect operating data of production equipment, perform data preprocessing on the operating data to obtain preprocessed data, transmit the preprocessed data to the big data governance and analysis platform, and then analyze the time loss of the production equipment based on the preprocessed data using the big data governance and analysis platform.

[0071] The embodiment of the present invention can understand the operating status, performance and other aspects of the equipment by collecting the operating data of the production equipment. The production equipment refers to various machines, equipment and tools used to manufacture products or provide services in industrial production, and the operating data refers to various information and data generated by the equipment during the production process, such as the equipment's start and stop status, operating time and fault alarm, as well as process parameters such as the equipment's temperature, pressure, speed, flow rate, etc.

[0072] Furthermore, the embodiment of the present invention performs data preprocessing on the operating data to obtain preprocessed data, which can reduce noise and interference, improve data quality, and make data analysis more accurate.

[0073] As an embodiment of the present invention, the data preprocessing of the operating data to obtain preprocessed data includes: data cleaning of the operating data to obtain cleaned data, data integration of the cleaned data to obtain integrated data, and data standardization of the integrated data to obtain preprocessed data.

[0074] Optionally, the data cleaning of the operating data to obtain the cleaned data refers to processing and correcting errors, missing values, and duplicate data in the original operating data, which can be cleaned by a missing value processing method. The data integration of the cleaned data to obtain the integrated data can be obtained by utilizing the data warehouse technology in the big data governance and analysis platform, such as Hive, Snowflake, etc., to integrate the cleaned data. The data standardization of the integrated data to obtain the preprocessed data can be obtained by utilizing the programming library in the big data governance and analysis platform, such as the Pandas library in Python.

[0075] Furthermore, the embodiment of the present invention can analyze the time loss of the production equipment based on the pre-processed data using the big data governance analysis platform, and can adjust and optimize the production process in a targeted manner by accurately understanding in which links and time periods the equipment has time loss. For example, if it is found that the time the equipment waits for raw materials in a certain process is too long, the timeliness and coordination of the raw material supply can be optimized to reduce unnecessary waiting time. Among them, the big data governance analysis platform refers to a comprehensive solution for managing and analyzing large amounts of data, which can help users effectively collect, organize, store, process and analyze massive amounts of data to provide valuable insights and decision support.

[0076] As an embodiment of the present invention, the time loss of the production equipment is analyzed based on the preprocessed data using the big data governance and analysis platform, including: identifying the time data in the preprocessed data, classifying the time data to obtain classified time data, and using the big data governance and analysis platform to perform time series analysis, correlation analysis, and cluster analysis on the classified time data to obtain a comprehensive analysis result, and using the comprehensive analysis result as the time loss of the production equipment.

[0077] Optionally, the identifying of the time data in the pre-processed data is obtained by reading the equipment's startup time, downtime, standby time, failure time, maintenance time and processing time, and the data classification of the time data is performed to obtain the classified time data, which is classified through java data annotation, such as classifying the equipment's time loss according to different reasons, such as equipment failure, planned maintenance, operational errors, shortage of raw materials, etc. The using of the big data governance and analysis platform to perform time series analysis, correlation analysis and cluster analysis on the classified time data to obtain a comprehensive analysis result refers to observing the distribution of time loss in different time periods, whether there are periodic or seasonal patterns, and exploring the relationship between equipment time loss and other factors, such as the urgency of production tasks, the operator's experience level, the service life of equipment, etc., and clustering production equipment with similar time loss characteristics to discover common problems and targeted solutions, which can be obtained through comprehensive analysis of pre-configured time series functions and clustering analysis functions.

[0078] The equipment utilization efficiency calculation module 202 is used to calculate the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss, and calculate the equipment utilization efficiency of the production equipment based on the equipment availability, the equipment operation rate and the equipment pure operation rate.

[0079] The embodiment of the present invention calculates the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss, so as to accurately understand the performance of the equipment in actual production, judge whether the equipment reaches the expected operation level, and compare the performance of equipment of different models and on different production lines, so as to provide a reference for equipment selection and procurement, and reasonably arrange production tasks according to indicators such as equipment availability to avoid production delays caused by over-reliance on a certain equipment.

[0080] As an embodiment of the present invention, the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment are calculated based on the time loss, including: querying the loss factor of the time loss, dividing the time loss into downtime, delay time and waiting time based on the loss factor, calculating the equipment availability of the production equipment based on the downtime; calculating the equipment operation rate of the production equipment based on the delay time; and calculating the equipment pure operation rate of the production equipment based on the waiting time.

[0081] Among them, the loss factor refers to the reason for the loss of equipment working time, such as maintenance, bad weather and power outages, which can be obtained by querying the downtime data records of the production equipment in the pre-processed data. Based on the loss factor, the time loss is divided into downtime, delay time and waiting time. The external factors in the loss factors, such as mechanical shutdown and mechanical failure, are taken as downtime, the loss factors due to the working environment, such as bad weather and equipment cleaning, are taken as delay time, and the waiting factors in the loss factors, such as waiting time caused by personnel operation, are taken as waiting time.

[0082] Further, as an optional embodiment of the present invention, the equipment availability of the production equipment is calculated based on the downtime; the equipment operation rate of the production equipment is calculated based on the delay time; and the equipment pure operation rate of the production equipment is calculated based on the waiting time, including: based on the downtime, using the following formula to calculate the equipment availability of the production equipment:

[0083]

[0084] And, 0≤i≤M

[0085] Among them, α represents the equipment availability of production equipment in a period of time, T 总 Represents the total production time of the production equipment in a period of time, T 总 A i It represents the i-th downtime of the production equipment in the total production time within a period of time, M represents the number of downtimes of the production equipment,

[0086] Based on the delay time, the equipment operation rate of the production equipment is calculated using the following formula:

[0087]

[0088] And, 0≤j≤U

[0089] Among them, β represents the equipment operation rate of the production equipment in a period of time, T 运 It indicates the total operating time of the production equipment in a period of time, U indicates the number of cycle working times of the production equipment, and GT i,j represents the jth operation of the production equipment in the i-th time period;

[0090] Based on the waiting time, the equipment pure operation rate of the production equipment is calculated using the following formula:

[0091]

[0092] Among them, γ represents the pure operation rate of the equipment, U represents the number of cycle working times of the production equipment, and GT i,j represents the jth operation of the production equipment in the i-th time period, D ij It represents the j-th waiting time of the production equipment in the i-th time period.

[0093] Furthermore, the embodiment of the present invention can reasonably allocate production resources by calculating the equipment utilization efficiency of the production equipment based on the equipment availability, the equipment operation rate and the equipment pure operation rate, avoid excessive use of certain equipment while other equipment is idle, and discover bottlenecks in the production process, so as to make targeted improvements and adjustments to make production smoother and more efficient.

[0094] As an embodiment of the present invention, the calculating the equipment utilization efficiency of the production equipment based on the equipment availability, the equipment operation rate and the equipment pure operation rate includes: calculating the equipment utilization efficiency of the production equipment based on the equipment availability, the equipment operation rate and the equipment pure operation rate in combination with the following formula:

[0095] δ=α×β×γ

[0096] Among them, δ represents the equipment utilization efficiency, α represents the equipment availability, β represents the equipment operation rate, and γ represents the equipment pure operation rate.

[0097] The relative efficiency calculation module 203 is used to query the input index and output index of the production equipment, and perform data envelopment analysis on the production equipment based on the input index and output index to obtain the relative efficiency score of the production equipment.

[0098] The embodiment of the present invention can help users evaluate the performance and benefits of production equipment by querying the input indicators and output indicators of the production equipment, so as to make reasonable decisions, such as equipment selection, investment decisions and production planning arrangements. The specific indicator definition and measurement method may vary from industry to industry and enterprise to enterprise, and need to be determined and analyzed according to actual conditions. For example, in river cleaning equipment, the input indicator may be equipment procurement cost, equipment operation and maintenance cost, and operator training cost, and the output indicator may be equipment cleaning efficiency, cleaning quality, and equipment reliability.

[0099] Furthermore, the embodiment of the present invention performs data envelopment analysis on the production equipment based on the input indicators and output indicators to obtain a relative efficiency score of the production equipment, which can help users select the optimal production equipment, or determine how to adjust the use of the equipment to improve efficiency. For example, in river cleaning, it can also be used to compare the river cleaning efficiency in different regions or different time periods, and to evaluate the upgrade or improvement effect of equipment.

[0100] As an embodiment of the present invention, data envelopment analysis is performed on the production equipment based on the input index and the output index to obtain a relative efficiency score of the production equipment, including: taking the production equipment as a production decision unit, constructing input index parameters and output index parameters corresponding to each unit in the production decision unit, constructing a linear programming model of the production equipment based on the production decision unit, the input index parameters and the output index parameters, and calculating the relative efficiency score of the production equipment based on the linear programming model.

[0101] The use of the production equipment as a production decision unit refers to the object whose efficiency is evaluated. For example, in river cleaning, the river cleaning equipment is used as a decision unit.

[0102] Optionally, the input indicator parameters and output indicator parameters corresponding to each unit in the production decision unit are obtained by querying the input indicators and output indicators corresponding to the production equipment to obtain specific data, and then using the script to generate corresponding parameters. The input indicators in the river cleaning scenario can be manpower input, material input and financial input, and the output indicators in the river cleaning scenario can be the length of the cleaned river, the weight of the garbage and debris cleaned up, and the degree of improvement in the river water quality.

[0103] Further, as another optional embodiment of the present invention, the linear programming model of the production equipment is constructed based on the production decision unit, the input index parameter and the output index parameter, including: constructing an input vector corresponding to the input index parameter, constructing an output vector corresponding to the output index parameter, and constructing the linear programming model of the production equipment based on the production decision unit, the input vector and the output vector in combination with the following formula:

[0104]

[0105] Where F represents the linear programming model, φ * represents the maximum efficiency score of the production decision-making unit, φ represents the actual efficiency score of the production decision-making unit, n represents the number of decision-making units, X j represents the input vector of the jth decision-making unit, X K represents the input vector of the kth decision-making unit whose efficiency is being evaluated, Y j represents the output vector of the jth decision unit, Y K represents the output vector of the kth decision-making unit whose efficiency is being evaluated, Q j Represents the combined weight variable of the jth decision unit.

[0106] Optionally, the relative efficiency score of the production equipment can be calculated based on the linear programming model by using professional mathematical programming solution software, such as LINGO, MATLAB, etc., to solve the above linear programming model. For example, there are two production equipment A and B, and their input indicators (manpower, materials, time) and output indicators (product quantity, quality) are different. Through data envelopment analysis, the relative efficiency score of equipment A is 0.8, and the relative efficiency score of equipment B is 1. This shows that equipment B is more efficient than equipment A in obtaining output by utilizing input resources.

[0107] The production efficiency calculation module 204 is used to perform quality analysis on the products produced by the production equipment according to the preprocessed data to obtain the product qualification rate, and calculate the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score.

[0108] The embodiment of the present invention can measure the performance and efficiency of the production equipment by performing quality analysis on the products produced by the production equipment according to the pre-processed data to obtain the product qualification rate. Among them, the product qualification rate refers to the ratio of the number of qualified products produced in a certain period to the total number of products. It should be noted that the meaning of the product qualification rate is different in different scenarios. For example, in the river cleaning scenario, "product" can be understood as the state of the river after cleaning, and the "qualified rate" can be the degree to which the river reaches the expected standard after cleaning, such as the completeness of garbage removal: if the complete removal of all visible garbage is set as the qualified standard, then the qualified rate is the proportion of river sections that actually meet this standard to the total cleaned sections. For example, 10 sections of the river were cleaned, and 8 of them were completely free of visible garbage, and the qualified rate was 80%.

[0109] As an embodiment of the present invention, the quality analysis of the products produced by the production equipment is performed according to the pre-processed data to obtain the product qualification rate, including: based on the pre-processed data, determining the sample products corresponding to the production equipment, querying the evaluation criteria of the sample products, and calculating the qualification rate of the sample products based on the evaluation criteria to obtain the product qualification rate.

[0110] Optionally, the determination based on the preprocessed data that the sample products corresponding to the production equipment can be obtained by a random sampling method, the querying of the evaluation criteria for the sample products can be obtained by querying the evaluation rules of the production industry corresponding to the production equipment, the calculation of the pass rate of the sample products based on the evaluation criteria, and the product pass rate can be obtained by calculating the percentage of the number of qualified products and the total number of products. The specific calculation rules should be calculated according to industry rules, such as the product pass rate of the above-mentioned river cleaning.

[0111] Furthermore, the embodiment of the present invention calculates the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score, so as to understand the output capacity of the equipment per unit time, thereby judging whether the equipment is in a good operating state.

[0112] As an embodiment of the present invention, the calculating the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score includes: calculating the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score in combination with the following formula:

[0113] ω=μ×δ×τ

[0114] Among them, ω represents production efficiency, μ represents product qualification rate, δ represents equipment utilization efficiency, and τ represents relative efficiency score.

[0115] The production efficiency impact analysis module 205 is used to query the operating environment, equipment maintenance data and management data of the production equipment, determine the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, and construct a production efficiency analysis report for the production equipment based on the production efficiency and the influencing factors.

[0116] The embodiment of the present invention can understand which factors affect the operation of the production equipment by querying the operating environment, equipment maintenance data and management data of the production equipment. Among them, the operating environment refers to the external conditions and factors of the production equipment during operation, such as the physical environment and power supply, etc., the equipment maintenance data refers to various information and records related to equipment maintenance, such as maintenance plans, maintenance operation records and fault records, etc., and the management data refers to relevant information related to the comprehensive management of production equipment, such as equipment asset value, equipment usage records and operator information, etc., which can be queried through the pre-processed data.

[0117] Furthermore, the embodiment of the present invention can clarify the specific direction in which the production equipment needs to be improved by determining the factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, so as to take targeted measures to improve production efficiency.

[0118] As an embodiment of the present invention, determining the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data includes: performing efficiency classification on the production equipment to obtain efficiency graded production equipment, selecting influencing key features from the operating environment, the equipment maintenance data and the management data, calculating the correlation coefficient between the efficiency graded production equipment and the influencing key features, constructing a production efficiency prediction curve of the production equipment based on the correlation coefficient, acquiring real-time data of the production equipment, analyzing the efficiency deviation of the production equipment based on the real-time data and the production efficiency prediction curve, and identifying the deviation influencing factors of the efficiency deviation to determine the influencing factors of the production efficiency of the production equipment.

[0119] Optionally, the efficiency classification of the production equipment to obtain efficiency graded production equipment can be divided into different groups according to a preset efficiency index threshold, and the selection of influencing key features from the operating environment, the equipment maintenance data and the management data can be determined by correlation analysis, feature importance evaluation and other methods.

[0120] The production efficiency prediction curve of the production equipment can be constructed by the linear regression function. The efficiency deviation of the production equipment can be analyzed based on the real-time data and the production efficiency prediction curve by inputting the real-time data into a trained machine learning model, comparing it with the prediction curve, and identifying the efficiency deviation. The deviation influencing factors of the efficiency deviation can be identified to determine the influencing factors of the production efficiency of the production equipment. The cause of the deviation can be determined by a decision tree algorithm, such as equipment aging, operating errors, changes in the external environment, etc.

[0121] Further, as an optional embodiment of the present invention, the calculation of the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics includes: querying the production efficiency and influencing key characteristics of the efficiency graded production equipment, constructing a regression function of the efficiency graded production equipment, taking the production efficiency as the dependent variable of the regression function, taking the influencing key characteristics as the independent variable of the regression function, and calculating the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics by using the dependent variable and the independent variable in combination with the regression function.

[0122] Optionally, the regression function can be constructed by a multiple linear regression function.

[0123] Furthermore, the embodiment of the present invention can help users decide whether to invest in new equipment, upgrade existing equipment or adjust production processes to improve overall production efficiency, and optimize resource allocation by constructing a production efficiency analysis report of the production equipment based on the production efficiency and the influencing factors: clarify which equipment or production links require more human, material and financial resources to achieve reasonable allocation of resources.

[0124] The present invention can understand the operating status, performance and other aspects of the equipment by collecting the operating data of the production equipment; the present invention can accurately understand the performance of the equipment in actual production by calculating the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss, judge whether the equipment reaches the expected operating level, and compare the performance of equipment on different models and different production lines, provide reference for equipment selection and procurement, and can also reasonably arrange production tasks according to indicators such as equipment availability to avoid over-reliance on a certain equipment and causing production delays; the present invention can help users evaluate the performance and benefits of production equipment by querying the input indicators and output indicators of the production equipment, so as to make reasonable decisions, such as equipment selection, investment decisions and production planning arrangements; the present invention can measure the performance and efficiency of the production equipment by performing quality analysis on the production products of the production equipment according to the preprocessing data, and obtaining the product qualification rate; finally, the present invention can understand which factors affect the production equipment during operation by querying the operating environment, equipment maintenance data and management data of the production equipment. Therefore, the present invention can deeply explore the factors affecting the production efficiency of the equipment.

[0125] Reference Figure 2 FIG. 1 is a flow chart of a method for analyzing the efficiency of production equipment based on a big data governance and analysis platform according to an embodiment of the present invention. In this embodiment, the method for analyzing the efficiency of production equipment based on a big data governance and analysis platform includes:

[0126] Collecting operation data of production equipment, performing data preprocessing on the operation data to obtain preprocessed data, transmitting the preprocessed data to a big data governance and analysis platform, and then analyzing the time loss of the production equipment using the big data governance and analysis platform based on the preprocessed data;

[0127] Based on the time loss, calculate the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment, and based on the equipment availability, the equipment operation rate and the equipment pure operation rate, calculate the equipment utilization efficiency of the production equipment;

[0128] Querying the input index and output index of the production equipment, and performing data envelopment analysis on the production equipment based on the input index and output index to obtain a relative efficiency score of the production equipment;

[0129] Performing a quality analysis on the products produced by the production equipment according to the preprocessed data to obtain a product qualification rate, and calculating the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score;

[0130] Query the operating environment, equipment maintenance data and management data of the production equipment, determine the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, and construct a production efficiency analysis report for the production equipment based on the production efficiency and the influencing factors.

[0131] In the several embodiments provided by the present invention, it should be understood that the provided system and method can be implemented in other ways. For example, the system embodiment described above is only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0132] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. The production equipment efficiency analysis system based on the big data governance analysis platform is characterized by: The intelligent control system includes: a time loss analysis module, an equipment utilization efficiency calculation module, a relative efficiency calculation module, a production efficiency calculation module, and a production efficiency impact analysis module. The time loss analysis module is used to collect the operation data of the production equipment, perform data preprocessing on the operation data to obtain preprocessed data, transmit the preprocessed data to the big data governance and analysis platform, and then analyze the time loss of the production equipment based on the preprocessed data using the big data governance and analysis platform; The equipment utilization efficiency calculation module is used to calculate the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss, and calculate the equipment utilization efficiency of the production equipment based on the equipment availability, the equipment operation rate and the equipment pure operation rate; The relative efficiency calculation module is used to query the input index and output index of the production equipment, and based on the input index and output index, perform data envelopment analysis on the production equipment to obtain the relative efficiency score of the production equipment; The production efficiency calculation module is used to perform quality analysis on the products produced by the production equipment according to the pre-processed data to obtain a product qualification rate, and calculate the production efficiency of the production equipment based on the product qualification rate, the equipment use efficiency and the relative efficiency score; The production efficiency impact analysis module is used to query the operating environment, equipment maintenance data and management data of the production equipment, determine the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, and construct a production efficiency analysis report for the production equipment based on the production efficiency and the influencing factors.

2. A production equipment efficiency analysis system based on a big data governance analysis platform as claimed in claim 1, characterized in that: The performing data preprocessing on the operation data to obtain preprocessed data includes: Performing data cleaning on the operation data to obtain cleaned data; Performing data integration on the cleaned data to obtain integrated data; The integrated data is subjected to data standardization processing to obtain preprocessed data.

3. The production equipment efficiency analysis system based on the big data governance analysis platform according to claim 1, characterized in that: The analyzing the time loss of the production equipment by using the big data governance analysis platform based on the pre-processed data includes: identifying time data in the preprocessed data; Classifying the time data to obtain classified time data; Using the big data governance and analysis platform to perform time series analysis, correlation analysis, and cluster analysis on the classified time data to obtain comprehensive analysis results; The comprehensive analysis result is taken as the time loss of the production equipment.

4. The production equipment efficiency analysis system based on the big data governance analysis platform according to claim 1, characterized in that: The calculating of the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment based on the time loss includes: Querying the loss factor of the time loss; Based on the loss factors, the time loss is divided into downtime, delay time and waiting time; Calculating the equipment availability of the production equipment based on the downtime; Calculating the equipment operation rate of the production equipment based on the delay time; Based on the waiting time, the equipment pure operation rate of the production equipment is calculated.

5. The production equipment efficiency analysis system based on the big data governance analysis platform according to claim 1, characterized in that: The step of performing data envelopment analysis on the production equipment based on the input index and the output index to obtain a relative efficiency score of the production equipment includes: Using the production equipment as a production decision unit; Constructing input index parameters and output index parameters corresponding to each unit in the production decision unit; Constructing a linear programming model of the production equipment based on the production decision unit, the input index parameter and the output index parameter; Based on the linear programming model, a relative efficiency score of the production equipment is calculated.

6. A production equipment efficiency analysis system based on a big data governance analysis platform as claimed in claim 5, characterized in that: The linear programming model of the production equipment is constructed based on the production decision unit, the input index parameter and the output index parameter, including: Constructing an input vector corresponding to the input indicator parameter; Constructing an output vector corresponding to the output indicator parameter; A linear programming model of the production equipment is constructed based on the production decision unit, the input vector and the output vector.

7. The production equipment efficiency analysis system based on the big data governance analysis platform according to claim 1, characterized in that: The step of performing quality analysis on the products produced by the production equipment according to the pre-processed data to obtain a product qualification rate includes: Based on the preprocessed data, determining a sample product corresponding to the production equipment; Query the evaluation criteria of the sample products; The qualified rate of the sample products is calculated based on the evaluation criteria to obtain the product qualified rate.

8. The production equipment efficiency analysis system based on the big data governance analysis platform according to claim 1, characterized in that: The determining, based on the operating environment, the equipment maintenance data and the management data, factors affecting the production efficiency of the production equipment includes: Classifying the production equipment by efficiency to obtain efficiency-graded production equipment; Selecting influencing key features from the operating environment, the equipment maintenance data and the management data; Calculate the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics; Based on the correlation coefficient, construct a production efficiency prediction curve of the production equipment; Acquiring real-time data of the production equipment; Analyzing the efficiency deviation of the production equipment based on the real-time data and the production efficiency prediction curve; The deviation influencing factors of the efficiency deviation are identified to determine the influencing factors of the production efficiency of the production equipment.

9. A production equipment efficiency analysis system based on a big data governance analysis platform as claimed in claim 8, characterized in that: The calculating of the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics comprises: Query the production efficiency and key influencing features of the efficiency graded production equipment; Constructing a regression function for the efficiency graded production equipment; Taking the production efficiency as the dependent variable of the regression function; Taking the key influencing features as independent variables of the regression function; The dependent variable and the independent variable are used in combination with the regression function to calculate the correlation coefficient between the efficiency graded production equipment and the influencing key characteristics.

10. A production equipment efficiency analysis method based on a big data governance analysis platform, characterized in that: The method comprises: Collecting operation data of production equipment, performing data preprocessing on the operation data to obtain preprocessed data, transmitting the preprocessed data to a big data governance and analysis platform, and then analyzing the time loss of the production equipment using the big data governance and analysis platform based on the preprocessed data; Based on the time loss, calculate the equipment availability, equipment operation rate and equipment pure operation rate of the production equipment, and based on the equipment availability, the equipment operation rate and the equipment pure operation rate, calculate the equipment utilization efficiency of the production equipment; Querying the input index and output index of the production equipment, and performing data envelopment analysis on the production equipment based on the input index and output index to obtain a relative efficiency score of the production equipment; Performing a quality analysis on the products produced by the production equipment according to the preprocessed data to obtain a product qualification rate, and calculating the production efficiency of the production equipment based on the product qualification rate, the equipment utilization efficiency and the relative efficiency score; Query the operating environment, equipment maintenance data and management data of the production equipment, determine the influencing factors affecting the production efficiency of the production equipment based on the operating environment, the equipment maintenance data and the management data, and construct a production efficiency analysis report for the production equipment based on the production efficiency and the influencing factors.

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