CN117350604A - Multi-dimensional intelligent analysis processing system for report - Google Patents
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Abstract
The invention relates to the field of data analysis and processing, in particular to a report multidimensional intelligent analysis and processing system which comprises an operation production report generation module, an operation production data analysis module, a working hour data acquisition module, a production efficiency analysis module, an energy consumption data monitoring analysis module, a scrapping influence degree analysis module, a production line analysis module and a management database.
Description
Technical Field
The invention relates to the field of data analysis and processing, in particular to a report multidimensional intelligent analysis and processing system.
Background
The report multidimensional processing is a data analysis and display technology for analyzing and summarizing a large amount of data to know the condition and trend of a service and helping to make corresponding decisions, and is widely applied to various fields, the traditional report processing only provides simple summarization and display, complex analysis requirements cannot be met, the report multidimensional processing provides more comprehensive and deep data analysis by classifying and grouping the data according to different dimensions, and a user can select different dimensions for analysis according to the requirements so as to acquire more detailed data insight.
The existing report analysis system can utilize a multidimensional data analysis technology to carry out deep analysis on workshop data from different angles and different dimensions, and display analysis results in the form of charts, instrument panels and the like in a data visualization mode, so that a user can conveniently and intuitively know the production condition of a workshop, but the existing report analysis system still has some defects, and the defects are particularly shown: 1. only the scrapping influence degree coefficient of the whole product is analyzed, detailed analysis is not carried out on the specific influence of scrapping conditions, the specific influence of scrapping on production cannot be accurately identified, and the further analysis and optimization capabilities are limited.
2. The system aims at a sequential production process workshop, workshop production is a dynamic change process, update and analysis of production data need to be carried out in real time, and the existing system may not have enough capability of collecting and processing the real-time data, so that a data analysis result cannot timely respond to the change of the workshop production process.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides a report multi-dimensional intelligent analysis processing system which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: the invention provides a report multi-dimensional intelligent analysis processing system, which comprises: the operation production data acquisition module is used for acquiring an operation production report of the workshop and reading operation production data of the workshop in a preset period from the operation production report, wherein the operation production data comprises the production total amount, the qualification rate and the rejection rate of workshop products.
And the operation production data analysis module is used for analyzing and obtaining the operation production qualification rate χ of the workshop according to the qualification rate and the rejection rate of the workshop product in a preset period.
The working hour data acquisition module is used for carrying out video monitoring on the working process of workshop staff in a preset period through the monitoring camera, extracting working hour of each staff in the preset period and corresponding yield of working hour of each staff from the monitoring video, and further analyzing and obtaining total working hour of the workshop in the preset period.
The production efficiency analysis module is used for obtaining the unit working hour and the total working hour of the scrapped product of the product according to the total working hour of the workshop in the preset period, the scrapping rate of the workshop product, the working hour of each staff and the corresponding yield of each staff, and further comprehensively analyzing the unit working hour and the total working hour of the scrapped product according to the unit working hour and the total working hour of the product to obtain the production efficiency delta of the workshop in the preset period.
The energy consumption data monitoring and analyzing module is used for monitoring the electric quantity consumed by the workshop in a preset period, recording the electric quantity as the total energy consumption of the workshop in the preset period, further analyzing the total energy consumption of the workshop according to the total energy consumption of the workshop in the preset period to obtain the power consumption of a single product and the total power consumption of scrapped products of the workshop, and further analyzing to obtain the energy consumption utilization rate E of the workshop.
And the scrapping influence degree analysis module is used for analyzing and obtaining scrapping influence degree coefficients of products according to the operation production qualification rate of the workshop, the production efficiency of the workshop and the energy consumption utilization rate of the workshop in a preset period.
The production analysis module is used for analyzing the production evaluation coefficient in the workshop period according to the scrapping influence degree coefficient of the product and the operation production qualification rate of the workshop, comparing the production evaluation coefficient in the workshop period with a preset production evaluation coefficient threshold value, and further obtaining the production condition in the workshop period.
The production line analysis module is used for analyzing and obtaining the production line evaluation index of the factory according to the production evaluation coefficients in each workshop period, comparing the production line evaluation index with a preset production evaluation coefficient threshold value, and further obtaining the production condition of the production line of the factory and feeding back the production condition to the system.
And the management database is used for storing the qualified value of the production evaluation coefficient and the production line evaluation index threshold value in the workshop period of the factory.
Preferably, the specific analysis process of the operation production data acquisition module is as follows: and acquiring an operation production report of a workshop, reading the qualified product quantity, the scrapped product quantity and the production total quantity of workshop products in a preset period, marking the qualified product quantity as qualified quantity alpha of the workshop products, and meanwhile, dividing the scrapped product quantity of the workshop products by the production total quantity of the workshop products to obtain the scrapping rate of the workshop products, and marking the scrapping rate as beta.
Preferably, the specific analysis process of the operation production qualification rate of the workshop is as follows: reading the qualification rate alpha of workshop products and the rejection rate beta of workshop products, substituting the qualification rate alpha and the rejection rate beta into a formulaObtaining the operation production qualification rate X of a workshop in a preset period, wherein alpha is 0 、β 0 Respectively representing preset expected goods quantity and product allowable rejection rate phi 1 、φ 2 And e is expressed as a natural constant.
Preferably, the specific analysis method for the total working hours of the workshops in the preset period is as follows: video monitoring is carried out on the working process of workshop staff in a preset period through a monitoring camera arranged in a workshop, the monitoring video is recorded as workshop working video in the preset period, the number of staff used for production is respectively extracted from the workshop working video in the preset period, each staff is identified and tracked through a target detection and tracking technology, so that the production time length and the corresponding production product number of each staff are obtained, the production time length and the corresponding production yield of each staff are recorded as the working time of each staff, and the working time of each staff is recorded as the corresponding production yield of each staff through a formulaAnd (3) obtaining the product yield in unit time of the workshop, accumulating the corresponding yields of the working hours of each staff to obtain the total work amount of the workshop, dividing the total work amount of the workshop by the product yield in unit time of the workshop to obtain the total work amount of the workshop, and recording the total work amount of the workshop in a preset period.
Preferably, the specific analysis method of the production efficiency of the workshop comprises the following steps: reading total working hours of workshops, rejection rate of workshop products, working hours of staff and corresponding output of working hours of staff in a preset period, and passing through a formulaThe unit working hour of the product is obtained and is marked as t', and the total working hour of the scrapped product of the workshop is obtained by multiplying the total working hour of the workshop in the preset period and the scrapping rate of the workshop product and is marked as t Scrapping At the same time, the product qualification rate alpha of the workshop is read and substituted into the formula +.>Obtaining the production efficiency delta of the workshop in a preset period, wherein t is Qualified product Representing the set unit man-hour of single qualified product, eta 1 The correction factor indicating the production efficiency of the preset shop, e indicating the natural constant.
Preferably, the specific analysis method of the workshop energy consumption utilization rate comprises the following steps: monitoring the electric quantity consumed by the workshop in a preset period, recording the electric quantity as the total energy consumption of the workshop in the preset period, simultaneously reading the total workshop product quantity and the rejection rate of the workshop product in the preset period of the workshop, dividing the total workshop product quantity in the preset period of the workshop by the total workshop product quantity in the preset period of the workshop to obtain the single-piece product electric consumption A' of the workshop, and multiplying the total workshop product rejection rate by the total workshop product electric consumption A in the preset period of the workshop to obtain the total workshop scrapped product electric consumption A Scrapping By the formulaObtaining the energy consumption utilization rate E of the workshopMiddle eta 2 And representing a preset workshop energy consumption utilization correction factor.
Preferably, the specific analysis method of the scrapping influence degree coefficient of the product comprises the following steps: the operation production qualification rate χ of the workshop, the production efficiency delta of the workshop and the energy consumption utilization rate E of the workshop are respectively read and substituted into a formulaAnalyzing to obtain scrapping influence degree coefficient psi of the product, wherein χ 0 、δ 0 、E 0 Respectively representing a preset operation production qualification rate, a workshop production efficiency reference value and a workshop energy consumption utilization rate reference value, a) 1 、a 2 、a 3 Weight factors respectively expressed as operation production qualification rate of workshop, production efficiency of workshop and energy consumption utilization rate of workshop, and a 1 +a 2 +a 3 ＝1，η 3 The correction factor, e, representing the coefficient of the degree of influence of rejection of the product is expressed as a natural constant.
Preferably, the specific analysis process of the production condition in the workshop period is as follows: reading the operation production qualification rate χ of a workshop and the rejection influence degree coefficient ψ of a product, and substituting the operation production qualification rate χ and the rejection influence degree coefficient ψ into a formula θ= [ (e-2) χ *ψ] -1 *η 4 Obtaining a production evaluation coefficient theta, eta in a workshop period 4 The correction factor indicating the production evaluation coefficient in the shop cycle, and e indicates the natural constant.
Comparing the production evaluation coefficient in the workshop period with a preset production evaluation coefficient threshold value, if the production evaluation coefficient in the workshop period is larger than or equal to the preset production evaluation coefficient threshold value, the production condition in the workshop period is qualified, the production activity of the next process workshop can be carried out, and if the production evaluation coefficient in the workshop period is smaller than the preset production evaluation coefficient threshold value, the production condition in the workshop period is unqualified, the production of the workshop is stopped, and an early warning notice is sent to a platform.
Preferably, the specific analysis method of the production line evaluation index of the factory comprises the following steps: for each workshop in the factory according to the method of producing evaluation coefficient in analysis workshop periodAnalyzing to obtain production evaluation coefficient of each workshop period, and recording as theta i I represents the number of the ith workshop, i=1, 2,..n, comparing the number with a preset production evaluation coefficient fit value in a workshop period, substituting the production evaluation coefficient fit value into a formula if the production evaluation coefficient fit value in a workshop period is smaller than the preset production evaluation coefficient fit value in the workshop period, wherein the production line evaluation index of the factory is 0, and substituting the production evaluation coefficient fit value in each workshop period into the formula if the production evaluation coefficient fit value in each workshop period is larger than the preset production evaluation coefficient fit value in the workshop periodObtaining a factory production line evaluation index->
Preferably, the specific analysis method of the production condition of the factory comprises the following steps: reading a production line evaluation index of a factory, comparing the production line evaluation index of the factory with a preset production line evaluation index threshold, if the production line evaluation index of the factory is larger than or equal to the preset production line evaluation index threshold, indicating that the production condition of the production line of the factory is qualified, and if the production evaluation coefficient in a workshop period is smaller than the preset production line evaluation index threshold, indicating that the production condition of the production line of the factory is unqualified, and feeding the production condition back to the system.
Compared with the prior art, the invention has the following beneficial effects: 1. the system obtains the scrapping influence degree coefficient of the product by analyzing the operation production qualification rate of the workshop, the production efficiency of the workshop and the energy consumption utilization rate of the workshop, and can convert the scrapping condition of the product into a specific numerical value, thereby better evaluating the influence degree of scrapping of the product on workshop production, being beneficial to quantitatively analyzing and comparing the problem of workshop production, and taking measures to improve the product quality and reduce the scrapping rate.
2. The system analyzes and obtains the production evaluation coefficient in the workshop period according to the scrapping influence degree of the product and the operation production data of the workshop, so that the production condition in the workshop period is known, and warning is provided or production is stopped in time when the production condition is unqualified, so that continuous production of unqualified products can be avoided, waste of waste products and resources is reduced, and the problem that the data analysis result cannot respond to the change condition of the workshop production process in time is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram illustrating a system module connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a report multidimensional intelligent analysis processing system includes an operation production data acquisition module, an operation production data analysis module, a man-hour data acquisition module, a production efficiency analysis module, an energy consumption data monitoring analysis module, a scrapping influence degree analysis module, a production line analysis module and a management database.
The management database is connected with the operation production data analysis module, the working hour data acquisition module, the production analysis module and the production line analysis module, the operation production data analysis module is connected with the production analysis module, the scrapping influence degree analysis module and the operation production data acquisition module, the operation production data acquisition module is connected with the working hour data acquisition module and the production efficiency analysis module, the scrapping influence degree analysis module is connected with the production efficiency analysis module, the production analysis module and the energy consumption data monitoring analysis module, and the production line analysis module is connected with the production analysis module and the energy consumption data monitoring analysis module.
The operation production data acquisition module is used for acquiring an operation production report of the workshop and reading operation production data of the workshop in a preset period from the operation production report, wherein the operation production data comprises the production total amount, the qualification rate and the rejection rate of workshop products.
The specific analysis process of the operation production data acquisition module is as follows: acquiring an operation production report of a workshop, reading the qualified product quantity, the scrapped product quantity and the total production quantity of workshop products in a preset period from the operation production report, marking the qualified product quantity as qualified quantity alpha of the workshop products, and meanwhile, dividing the scrapped product quantity of the workshop products by the total production quantity of the workshop products to obtain the scrapping rate of the workshop products, and marking the scrapping rate as beta; the scrappage of the workshop products can be calculated by dividing the number of scrapped products of the workshop products by the total production amount of the workshop products, the scrappage is an important index for measuring the production efficiency and quality control level of the workshop, and the low scrappage represents high efficiency and accuracy in the workshop production process.
And the operation production data analysis module is used for analyzing and obtaining the operation production qualification rate χ of the workshop according to the qualification rate and the rejection rate of the workshop product in a preset period.
The specific analysis process of the operation production qualification rate of the workshop is as follows: reading the qualification rate alpha of workshop products and the rejection rate beta of workshop products, substituting the qualification rate alpha and the rejection rate beta into a formulaObtaining the operation production qualification rate X of a workshop in a preset period, wherein alpha is 0 、β 0 Respectively representing preset expected goods quantity and product allowable rejection rate phi 1 、φ 2 The weight factors of the qualification rate and the rejection rate of workshop products are respectively represented, and e is represented as a natural constant; the method can help the workshop to find potential problems in the production process and take corresponding improvement measures through specific analysis of the operation production qualification rate, so that the production efficiency and the product quality are improved, and meanwhile, the periodic analysis is also helpful for monitoring the production condition of the workshopAnd timely adjusting and optimizing.
The working hour data acquisition module is used for carrying out video monitoring on the working process of workshop staff in a preset period through the monitoring camera, extracting working hour of each staff in the preset period and corresponding yield of working hour of each staff from the monitoring video, and further analyzing and obtaining total working hour of the workshop in the preset period.
The specific analysis method of the total working hours of the workshop in the preset period comprises the following steps: video monitoring is carried out on the working process of workshop staff in a preset period through a monitoring camera arranged in a workshop, the monitoring video is recorded as workshop working video in the preset period, the number of staff used for production is respectively extracted from the workshop working video in the preset period, each staff is identified and tracked through a target detection and tracking technology, so that the production time length and the corresponding production product number of each staff are obtained, the production time length and the corresponding production yield of each staff are recorded as the working time of each staff, and the working time of each staff is recorded as the corresponding production yield of each staff through a formulaObtaining the product yield in unit time of the workshop, accumulating the corresponding yields of the working hours of each staff to obtain the total work amount of the workshop, dividing the total work amount of the workshop by the product yield in unit time of the workshop to obtain the total work time of the workshop, and recording the total work time of the workshop in a preset period; by recording and analyzing the working hour data, the production process can be evaluated and optimized, the bottleneck and the problem in production can be found and solved, and the production efficiency and the resource utilization rate can be improved.
The production efficiency analysis module is used for obtaining the unit working hour and the total working hour of the scrapped product of the product according to the total working hour of the workshop in the preset period, the scrapping rate of the workshop product, the working hour of each staff and the corresponding yield of each staff, and further comprehensively analyzing the unit working hour and the total working hour of the scrapped product according to the unit working hour and the total working hour of the product to obtain the production efficiency delta of the workshop in the preset period.
The specific analysis method of the production efficiency of the workshop comprises the following steps: reading total working hours of workshops, rejection rate of workshop products, working hours of staff and corresponding output of working hours of staff in a preset period, and passing through a formulaThe unit working hour of the product is obtained and is marked as t', and the total working hour of the scrapped product of the workshop is obtained by multiplying the total working hour of the workshop in the preset period and the scrapping rate of the workshop product and is marked as t Scrapping At the same time, the product qualification rate alpha of the workshop is read and substituted into the formula +.>Obtaining the production efficiency delta of the workshop in a preset period, wherein t is Qualified product Representing the set unit man-hour of single qualified product, eta 1 A correction factor indicating the production efficiency of a preset workshop, e indicating a natural constant; the unit man-hour represents the total man-hour required for producing each unit product, is one of key indexes for measuring the production efficiency, a lower unit man-hour value generally represents higher production efficiency, and a higher unit man-hour value represents lower production efficiency; the total working hours of the scrapped products represent the total working hours wasted in the production process due to unqualified products, and a higher total working hours value of the scrapped products generally means quality control problems or defects in the production process; the production efficiency represents the proportion of qualified products produced by the workshop in a preset period, the production efficiency is used for evaluating the quality control condition of the workshop, and a higher production efficiency value means that the workshop can produce more qualified products under the same working hour investment.
The energy consumption data monitoring and analyzing module is used for monitoring the electric quantity consumed by the workshop in a preset period, recording the electric quantity as the total energy consumption of the workshop in the preset period, further analyzing the total energy consumption of the workshop according to the total energy consumption of the workshop in the preset period to obtain the power consumption of a single product and the total power consumption of scrapped products of the workshop, and further analyzing to obtain the energy consumption utilization rate E of the workshop.
The specific analysis method of the workshop energy consumption utilization rate comprises the following steps: monitoring the electric quantity consumed by the workshop in a preset period, recording the electric quantity as the total energy consumption of the workshop in the preset period, simultaneously reading the total workshop product quantity and the rejection rate of the workshop product in the preset period of the workshop, dividing the total energy consumption in the preset period of the workshop by the total workshop product quantity in the preset period of the workshop to obtain the single-piece product power consumption A' of the workshop,obtaining total power consumption A of scrapped products of the workshop by multiplying total power consumption of the workshop within a preset period of the workshop by scrappage of products of the workshop Scrapping By the formulaObtaining the energy consumption utilization rate E of the workshop, wherein eta 2 Representing a preset workshop energy consumption utilization factor; the energy utilization rate of the workshop can be estimated by calculating the energy utilization rate of the workshop, so that the efficiency level of the workshop when consuming energy can be known and measured, and the energy utilization rate of the workshop can be used as a basis for improving and optimizing the energy management of the workshop.
And the scrapping influence degree analysis module is used for analyzing and obtaining scrapping influence degree coefficients of products according to the operation production qualification rate of the workshop, the production efficiency of the workshop and the energy consumption utilization rate of the workshop in a preset period.
The specific analysis method of the scrapping influence degree coefficient of the product comprises the following steps: the operation production qualification rate χ of the workshop, the production efficiency delta of the workshop and the energy consumption utilization rate E of the workshop are respectively read and substituted into a formulaAnalyzing to obtain scrapping influence degree coefficient psi of the product, wherein χ 0 、δ 0 、E 0 Respectively representing a preset operation production qualification rate, a workshop production efficiency reference value and a workshop energy consumption utilization rate reference value, a) 1 、a 2 、a 3 Weight factors respectively expressed as operation production qualification rate of workshop, production efficiency of workshop and energy consumption utilization rate of workshop, and a 1 +a 2 +a 3 ＝1，η 3 A correction factor for indicating the scrapping influence degree coefficient of the product, wherein e is expressed as a natural constant; the scrapping influence degree of the product can be estimated more comprehensively by comprehensively considering the operation production qualification rate, the production efficiency and the energy consumption utilization rate of the workshop, and the workshop can take corresponding improvement measures according to the scrapping influence degree coefficient conveniently, so that the product quality and the production efficiency are improved.
The production analysis module is used for analyzing the production evaluation coefficient in the workshop period according to the scrapping influence degree coefficient of the product and the operation production qualification rate of the workshop, comparing the production evaluation coefficient in the workshop period with a preset production evaluation coefficient threshold value, and further obtaining the production condition in the workshop period.
The specific analysis process of the production condition in the workshop period is as follows: reading the operation production qualification rate χ of a workshop and the rejection influence degree coefficient ψ of a product, and substituting the operation production qualification rate χ and the rejection influence degree coefficient ψ into a formula θ= [ (e-2) χ *ψ] -1 *η 4 Obtaining a production evaluation coefficient theta, eta in a workshop period 4 A correction factor representing a production evaluation coefficient in a workshop period, e representing a natural constant; by more accurately evaluating the production capacity and efficiency of the plant by considering the operation production qualification rate of the plant and the scrapping influence degree coefficient of the product, the actual production condition of the plant can be more comprehensively reflected, and more specific data can be provided for decision making and improvement.
Comparing the production evaluation coefficient in the workshop period with a preset production evaluation coefficient threshold value, if the production evaluation coefficient in the workshop period is larger than or equal to the preset production evaluation coefficient threshold value, indicating that the production condition in the workshop period is qualified, and carrying out the production activity of the workshop in the next process, if the production evaluation coefficient in the workshop period is smaller than the preset production evaluation coefficient threshold value, indicating that the production condition in the workshop period is unqualified, stopping the production of the workshop, and sending an early warning notice to a platform; by timely stopping production and sending an early warning notice to the platform, a management layer can quickly make a decision to stop the production of the workshop, so that the problems of larger loss and other potential problems caused by quality problems are prevented from being further enlarged, and corresponding measures are taken to conduct problem investigation and correction.
The production line analysis module is used for analyzing and obtaining the production line evaluation index of the factory according to the production evaluation coefficients in each workshop period, comparing the production line evaluation index with a preset production evaluation coefficient threshold value, and further obtaining the production condition of the production line of the factory and feeding back the production condition to the system.
The specific analysis method of the production line evaluation index of the factory comprises the following steps: analyzing each workshop in the factory according to the method for producing the evaluation coefficient in the analysis workshop period to obtainProduction evaluation coefficient in each workshop period is recorded as theta i I represents the number of the ith workshop, i=1, 2,..n, comparing the number with a preset production evaluation coefficient fit value in a workshop period, substituting the production evaluation coefficient fit value into a formula if the production evaluation coefficient fit value in a workshop period is smaller than the preset production evaluation coefficient fit value in the workshop period, wherein the production line evaluation index of the factory is 0, and substituting the production evaluation coefficient fit value in each workshop period into the formula if the production evaluation coefficient fit value in each workshop period is larger than the preset production evaluation coefficient fit value in the workshop periodObtaining a factory production line evaluation indexBy analyzing the production line evaluation index of the factory, a measurable and comparison mode for production of each workshop is provided, the factory is helped to find out problem workshops and pay attention to improving the workshops with low efficiency, and meanwhile, by setting a qualified value, targets and standards can be set for the factory, so that the workshops are promoted to improve the production efficiency and the product quality.
The specific analysis method of the production condition of the factory comprises the following steps: reading a production line evaluation index of a factory, comparing the production line evaluation index of the factory with a preset production line evaluation index threshold, if the production line evaluation index of the factory is larger than or equal to the preset production line evaluation index threshold, indicating that the production condition of the production line of the factory is qualified, and if the production evaluation coefficient in a workshop period is smaller than the preset production line evaluation index threshold, indicating that the production condition of the production line of the factory is unqualified, and feeding the production condition back to the system; the performance situation of the production line can be known in time by reading the production line evaluation index of the factory and comparing the production line evaluation index with the preset evaluation index threshold value, the improvement and the optimization of the production process of the factory are promoted, the efficiency and the quality are improved, meanwhile, the actual performance and the improvement direction of the production line can be known by the factory through feeding back the unqualified production situation, and therefore the overall production efficiency is improved.
And the management database is used for storing the qualified value of the production evaluation coefficient and the production line evaluation index threshold value in the workshop period of the factory.
The system generates the operation production report by acquiring the operation production data of the workshops, analyzes the operation production qualification rate, the production efficiency and the workshop energy consumption utilization rate of the workshops according to the operation production report, further analyzes the production conditions of the workshops in a period, analyzes the production conditions of the workshops in the period of the factory to obtain the production conditions of the factory production line, can find problems and potential improvement spaces in the production process, helps to better manage the workshop production conditions, optimizes the production flow, and improves the product quality and the production efficiency.
While embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention, which is also intended to be covered by the present invention.
Claims (10)
1. The intelligent analysis processing system for the report form multidimensional is characterized by comprising the following modules:
the operation production data acquisition module is used for acquiring an operation production report of the workshop and reading operation production data of the workshop in a preset period from the operation production report, wherein the operation production data comprises the production total amount, the qualification rate and the rejection rate of workshop products;
the operation production data analysis module is used for analyzing and obtaining the operation production qualification rate χ of the workshop according to the qualification rate and the rejection rate of the workshop product in a preset period;
the working hour data acquisition module is used for carrying out video monitoring on the working process of workshop staff in a preset period through the monitoring camera, extracting working hour of each staff of the workshop in the preset period and corresponding yield of working hour of each staff from the monitoring video, and further analyzing and obtaining total working hour of the workshop in the preset period;
the production efficiency analysis module is used for obtaining unit working hours and total working hours of scrapped products of the product according to the total working hours of the workshop in a preset period, the rejection rate of the workshop product, the working hours of each staff and the corresponding yield of each staff, and further comprehensively analyzing the unit working hours and the total working hours of the scrapped products to obtain the production efficiency delta of the workshop in the preset period;
the energy consumption data monitoring and analyzing module is used for monitoring the electric quantity consumed by the workshop in a preset period, recording the electric quantity as the total energy consumption of the workshop in the preset period, further analyzing the total energy consumption of the workshop according to the total energy consumption of the workshop in the preset period to obtain the power consumption of a single product and the total power consumption of scrapped products of the workshop, and further analyzing to obtain the energy consumption utilization rate E of the workshop;
the scrapping influence degree analysis module is used for analyzing and obtaining scrapping influence degree coefficients of products according to the operation production qualification rate of the workshop, the production efficiency of the workshop and the energy consumption utilization rate of the workshop in a preset period;
the production analysis module is used for analyzing the scrapping influence degree coefficient of the product and the operation production qualification rate of the workshop to obtain a production evaluation coefficient in the workshop period, and comparing the production evaluation coefficient in the workshop period with a preset production evaluation coefficient threshold value to further obtain the production condition in the workshop period;
the production line analysis module is used for analyzing the production line evaluation index of the factory according to the production evaluation coefficients in each workshop period, comparing the production line evaluation index with a preset production evaluation coefficient threshold value, and further obtaining the production condition of the production line of the factory and feeding the production condition back to the system;
and the management database is used for storing the qualified value of the production evaluation coefficient and the production line evaluation index threshold value in the workshop period of the factory.
2. The report form multidimensional intelligent analysis processing system according to claim 1, wherein the specific analysis process of the operation production data acquisition module is as follows:
and acquiring an operation production report of a workshop, reading the qualified product quantity, the scrapped product quantity and the production total quantity of workshop products in a preset period, marking the qualified product quantity as qualified quantity alpha of the workshop products, and meanwhile, dividing the scrapped product quantity of the workshop products by the production total quantity of the workshop products to obtain the scrapping rate of the workshop products, and marking the scrapping rate as beta.
3. The report form multidimensional intelligent analysis processing system according to claim 2, wherein the specific analysis process of the operation production qualification rate of the workshop is as follows:
reading the qualification rate alpha of workshop products and the rejection rate beta of workshop products, substituting the qualification rate alpha and the rejection rate beta into a formulaObtaining the operation production qualification rate X of a workshop in a preset period, wherein alpha is 0 、β 0 Respectively representing preset expected goods quantity and product allowable rejection rate phi 1 、φ 2 And e is expressed as a natural constant.
4. The report form multidimensional intelligent analysis processing system according to claim 1, wherein the specific analysis method of the total working hours of the workshops in the preset period is as follows:
video monitoring is carried out on the working process of workshop staff in a preset period through a monitoring camera arranged in a workshop, the monitoring video is recorded as workshop working video in the preset period, the number of staff used for production is respectively extracted from the workshop working video in the preset period, each staff is identified and tracked through a target detection and tracking technology, so that the production time length and the corresponding production product number of each staff are obtained, the production time length and the corresponding production yield of each staff are recorded as the working time of each staff, and the working time of each staff is recorded as the corresponding production yield of each staff through a formulaAnd (3) obtaining the product yield in unit time of the workshop, accumulating the corresponding yields of the working hours of each staff to obtain the total work amount of the workshop, dividing the total work amount of the workshop by the product yield in unit time of the workshop to obtain the total work amount of the workshop, and recording the total work amount of the workshop in a preset period.
5. The report form multidimensional intelligent analysis processing system according to claim 4, wherein the specific analysis method of the production efficiency of the workshop is as follows:
reading total working hours of workshops, rejection rate of workshop products, working hours of staff and corresponding output of working hours of staff in a preset period, and passing through a formulaThe unit working hour of the product is obtained and is marked as t', and the total working hour of the scrapped product of the workshop is obtained by multiplying the total working hour of the workshop in the preset period and the scrapping rate of the workshop product and is marked as t Scrapping At the same time, the product qualification rate alpha of the workshop is read and substituted into the formula +.>Obtaining the production efficiency delta of the workshop in a preset period, wherein t is Qualified product Representing the set unit man-hour of single qualified product, eta 1 The correction factor indicating the production efficiency of the preset shop, e indicating the natural constant.
6. The report form multidimensional intelligent analysis processing system according to claim 1, wherein the specific analysis method of the workshop energy consumption utilization rate is as follows:
monitoring the electric quantity consumed by the workshop in a preset period, recording the electric quantity as the total energy consumption of the workshop in the preset period, simultaneously reading the total workshop product quantity and the rejection rate of the workshop product in the preset period of the workshop, dividing the total workshop product quantity in the preset period of the workshop by the total workshop product quantity in the preset period of the workshop to obtain the single-piece product electric consumption A' of the workshop, and multiplying the total workshop product rejection rate by the total workshop product electric consumption A in the preset period of the workshop to obtain the total workshop scrapped product electric consumption A Scrapping By the formulaObtaining the energy consumption utilization rate E of the workshop, wherein eta 2 And representing a preset workshop energy consumption utilization correction factor.
7. The report form multidimensional intelligent analysis processing system according to claim 1, wherein the specific analysis method of the scrapping influence degree coefficient of the product is as follows:
the operation production qualification rate χ of the workshop, the production efficiency delta of the workshop and the energy consumption utilization rate E of the workshop are respectively read and substituted into a formulaAnalyzing to obtain scrapping influence degree coefficient psi of the product, wherein χ 0 、δ 0 、E 0 Respectively representing a preset operation production qualification rate, a workshop production efficiency reference value and a workshop energy consumption utilization rate reference value, a) 1 、a 2 、a 3 Weight factors respectively expressed as operation production qualification rate of workshop, production efficiency of workshop and energy consumption utilization rate of workshop, and a 1 +a 2 +a 3 ＝1，η 3 The correction factor, e, representing the coefficient of the degree of influence of rejection of the product is expressed as a natural constant.
8. The report form multidimensional intelligent analysis processing system according to claim 7, wherein the specific analysis process of the production condition in the workshop period is as follows:
reading the operation production qualification rate χ of a workshop and the rejection influence degree coefficient ψ of a product, and substituting the operation production qualification rate χ and the rejection influence degree coefficient ψ into a formula θ= [ (e-2) χ *ψ] -1 *η 4 Obtaining a production evaluation coefficient theta, eta in a workshop period 4 A correction factor representing a production evaluation coefficient in a workshop period, e representing a natural constant;
comparing the production evaluation coefficient in the workshop period with a preset production evaluation coefficient threshold value, if the production evaluation coefficient in the workshop period is larger than or equal to the preset production evaluation coefficient threshold value, the production condition in the workshop period is qualified, the production activity of the next process workshop can be carried out, and if the production evaluation coefficient in the workshop period is smaller than the preset production evaluation coefficient threshold value, the production condition in the workshop period is unqualified, the production of the workshop is stopped, and an early warning notice is sent to a platform.
9. The report form multidimensional intelligent analysis processing system according to claim 8, wherein the specific analysis method of the production line evaluation index of the factory is as follows:
analyzing each workshop in the factory according to the method for analyzing the production evaluation coefficients in the workshop period to obtain the production evaluation coefficients in each workshop period, and recording the production evaluation coefficients as theta i I represents the number of the ith workshop, i=1, 2,..n, comparing the number with a preset production evaluation coefficient fit value in a workshop period, substituting the production evaluation coefficient fit value into a formula if the production evaluation coefficient fit value in a workshop period is smaller than the preset production evaluation coefficient fit value in the workshop period, wherein the production line evaluation index of the factory is 0, and substituting the production evaluation coefficient fit value in each workshop period into the formula if the production evaluation coefficient fit value in each workshop period is larger than the preset production evaluation coefficient fit value in the workshop periodObtaining a factory production line evaluation index->
10. The report form multidimensional intelligent analysis processing system according to claim 9, wherein the specific analysis method of the production condition of the factory is as follows:
reading a production line evaluation index of a factory, comparing the production line evaluation index of the factory with a preset production line evaluation index threshold, if the production line evaluation index of the factory is larger than or equal to the preset production line evaluation index threshold, indicating that the production condition of the production line of the factory is qualified, and if the production evaluation coefficient in a workshop period is smaller than the preset production line evaluation index threshold, indicating that the production condition of the production line of the factory is unqualified, and feeding the production condition back to the system.
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