Production data analysis method and system applied to digital factory

Abstract

The invention relates to the field of digital factories, in particular to a production data analysis method and system applied to a digital factory, and aims to solve the problems that the digital factory is insufficient in production data utilization degree, still depends on manual data viewing and is subjected to manual management and control in application. Comprising a production batch management module, a local area network switching module, a production data acquisition module, a quality inspection data acquisition module and a comprehensive data output module, according to the invention, not only is the production data of a digital factory collected, output and displayed, but also the production data, the production frequency information and the quality inspection result are subjected to fusion processing, so that a defective product condition, a production efficiency condition, a raw material storage condition and the like which are used for verifying the production quality, the production progress and other information of a production line are obtained; in order to greatly improve the utilization degree of the collected data and realize deep analysis of production data based on autonomous judgment interaction, the invention provides the production data analysis method and system applied to the digital factory.

Description

Technical Field

[0001] This invention relates to the field of digital factories, specifically to a production data analysis method and system applied to digital factories. Background Technology

[0002] With the rapid development of artificial intelligence technology, people are using it more and more widely. In the industrial field, people use the Internet of Things + artificial intelligence to dynamically monitor production data in the industrial field, thereby realizing real-time monitoring of the production status in the industry. Based on this, the concept of digital factory has been proposed.

[0003] A digital factory refers to a new production organization method that uses data related to the entire product lifecycle as a basis to simulate, evaluate, and optimize the entire production process in a computer virtual environment, and further extends this to the entire product lifecycle. It is a product of the combination of modern digital manufacturing technology and computer simulation technology, and has its own distinct characteristics. Its emergence has injected new vitality into basic manufacturing industries, primarily serving as a bridge between product design and manufacturing. In the design phase, the application of CAD and PDM systems is quite widespread; in the production phase, related information systems such as ERP have also achieved considerable adoption.

[0004] However, existing digital factories still suffer from insufficient mining of production data. Production data collection and output remain at the surface level, resulting in insufficient data analysis capabilities of the digital factory itself. They still rely on manual viewing of production data and human control based on it. For example, the digital factory management method proposed in the existing patent application CN2016108260307, ​​although it can access the production process through a digital system, mainly focuses on data collection, output, and coordination and communication of materials and equipment, with insufficient utilization of production data.

[0005] To address the aforementioned technical problems, this application proposes a solution. Summary of the Invention

[0006] This invention not only collects, outputs, and displays production data from digital factories, but also integrates and processes production data, production frequency information, and quality inspection results to obtain information such as defective products, production efficiency, and raw material reserves for verifying production line quality and progress. This significantly improves the utilization of the collected data and enables in-depth analysis of production data based on autonomous judgment and interaction. It addresses the problem of insufficient utilization of production data in digital factories, which still rely on manual data viewing and control. Therefore, this invention proposes a production data analysis method and system applicable to digital factories.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A production data analysis method applied to digital factories includes the following steps:

[0009] Step 1: Obtain production batch information, production information, and quality inspection results;

[0010] Step 2: Output raw data of production batch information, production information, and quality inspection results, and display them through a production data dashboard;

[0011] Step 3: Verify the data acquisition frequency and confirm the integrity of the information transmission results;

[0012] Step 4: Conduct a comprehensive analysis based on production batch information, production information, and quality inspection results to obtain results such as quality inspection ratio, defect dispersion, pass rate, raw material reserve, and production progress.

[0013] Step 5: Output the results obtained in Step 4 and display them through the production data dashboard;

[0014] Step Six: Back up the raw data from Step Two and the results from Step Four using a disaster recovery backup server.

[0015] A production data analysis system for digital factories includes a production batch management module, a local area network exchange module, a production data acquisition module, a quality inspection data acquisition module, and a comprehensive data output module. The production batch management module can acquire production batches and record production batch information.

[0016] The production data acquisition module is used to collect specific production information during the production process and send the production information to the local area network exchange module and the quality inspection data acquisition module.

[0017] The quality inspection data acquisition module can acquire production information and generate a product quality inspection plan based on the production information. After the quality inspection is completed, it collects the quality inspection results of the product and sends the quality inspection results to the local area network exchange module.

[0018] After acquiring production information and quality inspection results, the local area network switching module verifies the receiving frequency of production information and quality inspection results, generates information feedback integrity results, and simultaneously sends production information, quality inspection results, and production batches to the integrated data output module.

[0019] After acquiring production information and quality inspection results, the integrated data output module analyzes the production batch information, production information, and quality inspection results to obtain production control results. At the same time, it acquires production batches through the local area network exchange module and outputs the corresponding production batches and production control results.

[0020] In a preferred embodiment of the present invention, the production batch management module obtains the production batch by manual input, wherein the production batch information includes the production plan time, the production plan quantity, and the production quality requirements.

[0021] The specific production information collected by the production data acquisition module includes production quantity, production progress, raw material reserves, and single product production speed.

[0022] The quality inspection data acquisition module obtains the following quality inspection results: product pass rate, product quality inspection ratio, and defective product dispersion.

[0023] In a preferred embodiment of the present invention, the production data acquisition module obtains the defect dispersion in the following way:

[0024] The quality inspection data acquisition module performs quality inspection on the product and obtains the quality inspection result as good or defective. At the same time, the production data acquisition module obtains the production time of the product. If the quality inspection result is defective, the defective signal and the corresponding production time are recorded together. If the quality inspection result is good, the good signal and the corresponding production time are recorded together.

[0025] The quality inspection data acquisition module statistically analyzes all defective product signals and creates a time axis. Based on the production time corresponding to the defective product signal, the defective product signal is recorded on the time axis. The quality inspection data acquisition module calculates the interval between quality inspections of adjacent defective product signal points on the time axis to obtain the defective product occurrence interval. It also calculates the standard deviation of the defective product occurrence interval and uses the ratio of the standard deviation to the mean of the defective product occurrence interval as the defective product dispersion.

[0026] In a preferred embodiment of the present invention, the production data acquisition module obtains the production progress by: obtaining the planned production quantity and planned production time through the production batch management module; obtaining the quantity progress by the ratio of the production quantity to the planned production quantity in the production information; and obtaining the time progress by the ratio of the time elapsed for the current batch of products to the planned production time.

[0027] The production data acquisition module can compare quantity progress and time progress. If the quantity progress is greater than or equal to the time progress, the quantity progress is used as the production progress. If the quantity progress is less than the time progress, the quantity progress is used as the production progress and an inefficiency signal is generated at the same time.

[0028] In a preferred embodiment of the present invention, after acquiring production information, the quality inspection data acquisition module calculates the ratio of the preset quality inspection time to the single product production speed, and rounds the calculation result up to obtain the minimum sample interval.

[0029] Meanwhile, the quality inspection data acquisition module obtains the preset quality inspection sampling ratio and compares the quality inspection sampling ratio with the reciprocal of the minimum sample interval. If the quality inspection sampling ratio is less than the reciprocal of the minimum sample interval, the quality inspection work is carried out according to the quality inspection sampling ratio. If the quality inspection sampling ratio is greater than the reciprocal of the minimum sample interval, the quality inspection work is carried out according to the reciprocal of the minimum sample interval and recorded as the new quality inspection ratio.

[0030] In a preferred embodiment of the present invention, when the local area network switching module acquires production information and quality inspection results, it records the acquisition frequency of production information and quality inspection results, compares the acquisition frequency with the set frequency, and confirms the integrity of the information transmission result based on the comparison result.

[0031] When the local area network switching module sends production information and quality inspection results to the integrated data output module, it also sends the production information and quality inspection results to the database for backup storage via a dedicated network.

[0032] In a preferred embodiment of the present invention, the method by which the integrated data output module obtains the production control results is as follows:

[0033] The integrated data output module compares the product qualification rate with the set production quality requirements to obtain the qualification rate result;

[0034] The integrated data output module comprehensively analyzes raw material reserves, single-product production speed, and production progress. Based on the production progress, it obtains the remaining production progress, calculates the raw material sufficiency through raw material reserves, and calculates the remaining reserve time through single-product production speed and raw material reserves. The remaining reserve time and raw material sufficiency are used as the raw material reserve result.

[0035] In a preferred embodiment of the present invention, the integrated data output module comprehensively analyzes the production speed of a single product, the production progress, the planned production time, and the planned production quantity. It calculates the remaining production quantity by using the production progress and the planned production quantity, calculates the production time required by using the remaining production quantity and the production speed of a single product, obtains the remaining time by combining the time progress of the planned production time and the production progress, and compares the production time required by the production time with the remaining time to obtain the production progress result.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] In this invention, during the production process of a digital factory, production data is collected and displayed on a dashboard. Simultaneously, data backup is performed, and data integration between manual labor and the production line is completed. Furthermore, based on a computer model, the acquired production data, production frequency information, and quality inspection results are fused and processed to obtain information such as defective products, production efficiency, and raw material reserves for verifying production line quality and progress. This significantly improves the utilization of the collected data, enhances the intelligence level of the digital factory, and enables in-depth analysis of production data based on autonomous judgment and interaction. Attached Figure Description

[0038] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0039] Figure 1 This is a system block diagram of the present invention;

[0040] Figure 2 This is a system flowchart of the present invention. Detailed Implementation

[0041] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0042] Example 1: Please refer to Figure 1 - Figure 2 As shown, a production data analysis method applied to a digital factory includes the following steps:

[0043] Step 1: Acquire production batch information, production information, and quality inspection results through a digital system, and transmit the data via a dedicated internal network;

[0044] Step 2: Output the raw data from the collected production batch information, production information, and quality inspection results, and display it through the production data dashboard;

[0045] Step 3: Verify the data acquisition frequency to confirm whether it meets the preset return frequency. If it meets the preset return frequency, the information return is confirmed to be complete. If it does not meet the preset return frequency, the information return is confirmed to be incomplete, and an early warning reminder is generated.

[0046] Step 4: Conduct a comprehensive analysis based on production batch information, production information, and quality inspection results to obtain the quality inspection ratio, the defect dispersion by the interval between defective products, the pass rate by the quality inspection results, and the raw material reserve and production progress results by the raw material reserves, production progress, single product production speed, and production plan.

[0047] Step 5: Output the results obtained in Step 4 and display them through the production data dashboard;

[0048] Step Six: Back up the original data from Step Two and the results from Step Four using a disaster recovery backup server.

[0049] Example 2: Please refer to Figure 1 - Figure 2 As shown, a production data analysis method applied to a digital factory includes a production batch management module, a local area network exchange module, a production data acquisition module, a quality inspection data acquisition module, and a comprehensive data output module. The production batch management module can acquire production batches and record production batch information. The production batch management module acquires production batches by manual input, and the production batch information includes production plan time, production plan quantity, and production quality requirements.

[0050] The production data acquisition module is used to collect specific production information during the production process and send the production information to the local area network exchange module and the quality inspection data acquisition module. The specific production information collected by the production data acquisition module includes production quantity, production progress, raw material reserves, and single product production speed.

[0051] The quality inspection data acquisition module can acquire production information and generate product quality inspection plans based on the production information. After the quality inspection is completed, it collects the quality inspection results of the products and sends the quality inspection results to the local area network exchange module. The quality inspection results acquired by the quality inspection data acquisition module include product pass rate, product quality inspection ratio, and defect dispersion.

[0052] The production data acquisition module obtains the defect dispersion in the following way:

[0053] The quality inspection data acquisition module performs quality inspection on the product and obtains the quality inspection result as good or defective. At the same time, the production data acquisition module obtains the production time of the product. If the quality inspection result is defective, the defective signal and the corresponding production time are recorded together. If the quality inspection result is good, the good signal and the corresponding production time are recorded together.

[0054] The quality inspection data acquisition module statistically analyzes all defective product signals and creates a timeline. Based on the production time corresponding to each defective product signal, the module records the signals on the timeline. The module calculates the interval between adjacent defective product signal points on the timeline to obtain the defective product occurrence interval. It also calculates the standard deviation of the defective product occurrence interval and uses the ratio of the standard deviation to the mean of the defective product occurrence interval as the defective product dispersion. The specific calculation formula is as follows: Where L is the defect dispersion, C is the standard deviation, q0 is the mean interval of defect occurrence, qi is the interval of defect occurrence in the i-th group, and N is the number of defect samples.

[0055] The production data acquisition module obtains production progress by: acquiring the planned production quantity and planned production time through the production batch management module; obtaining the quantity progress by the ratio of the production quantity to the planned production quantity in the production information; and obtaining the time progress by the ratio of the time elapsed for the current batch of products to the planned production time.

[0056] The production data acquisition module can compare quantity progress and time progress. If the quantity progress is greater than or equal to the time progress, the quantity progress is used as the production progress. If the quantity progress is less than the time progress, the quantity progress is used as the production progress and an inefficiency signal is generated at the same time.

[0057] After acquiring production information, the quality inspection data acquisition module calculates the ratio of the preset quality inspection time to the production speed of a single product, and rounds the result up to obtain the minimum sample interval.

[0058] Meanwhile, the quality inspection data acquisition module obtains the preset quality inspection sampling ratio and compares the quality inspection sampling ratio with the reciprocal of the minimum sample interval. If the quality inspection sampling ratio is less than the reciprocal of the minimum sample interval, the quality inspection operation is carried out according to the quality inspection sampling ratio. If the quality inspection sampling ratio is greater than the reciprocal of the minimum sample interval, the quality inspection operation is carried out according to the reciprocal of the minimum sample interval and recorded as the new quality inspection ratio. The quality inspection operation is carried out according to the new quality inspection ratio.

[0059] After acquiring production information and quality inspection results, the local area network switching module records the acquisition frequency of production information and quality inspection results and compares the acquisition frequency with the set frequency. Based on the comparison result, it confirms the integrity of the information transmission. If it meets the preset transmission frequency, it confirms that the information transmission is complete. If it does not meet the preset transmission frequency, it confirms that the information transmission is incomplete and generates an early warning reminder.

[0060] Meanwhile, the local area network (LAN) exchange module directly sends production information, quality inspection results, and production batches to the integrated data output module. When the LAN exchange module sends production information and quality inspection results to the integrated data output module, it also sends the production information and quality inspection results to the database for backup storage via a dedicated network.

[0061] After acquiring production information and quality inspection results, the integrated data output module analyzes the production batch information, production information, and quality inspection results to obtain production control results. At the same time, it acquires production batches through the local area network exchange module and outputs the corresponding production batches and production control results.

[0062] The method by which the integrated data output module obtains production control results is as follows:

[0063] The integrated data output module compares the product qualification rate with the set production quality requirements to obtain the qualification rate result;

[0064] The comprehensive data output module performs a comprehensive analysis of raw material reserves, single product production speed, and production progress. Based on the production progress, it obtains the remaining production progress, calculates the raw material sufficiency through raw material reserves, and calculates the remaining reserve time through single product production speed and raw material reserves. The remaining reserve time and raw material sufficiency are used as the raw material reserve results.

[0065] The integrated data output module comprehensively analyzes the production speed, production progress, production plan time, and production plan quantity of a single product. It calculates the remaining production quantity by using the production progress and production plan quantity, calculates the production time required by using the remaining production quantity and the production speed of a single product, obtains the remaining time by combining the production plan time and the time progress in the production schedule, and obtains the production progress result by comparing the production time required and the remaining time.

[0066] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A production data analysis method applied to a digital factory, characterized by, Comprise the following steps: Step one: production batch information, production information and quality inspection results are obtained; Step two: the original data output of production batch information, production information and quality inspection results, through the production data board display; Step three: the data acquisition frequency is checked, and the information back transmission integrity result is confirmed; Step four: according to production batch information, production information and quality inspection results, the quality inspection proportion, the defective product dispersion degree, the qualified rate result, the raw material reserve result and the production progress result are obtained; Step five: the results obtained in step four are output, and the production data board is displayed; Step six: the original data in step two and the results in step four are backed up by the disaster prevention backup server.

2. A production data analysis system applied to a digital factory, characterized by, Comprise production batch management module, local area network exchange module, production data acquisition module, quality inspection data acquisition module and comprehensive data output module, the production batch management module can obtain the production batch, and record the production batch information; The production data acquisition module is used for collecting the specific production information in the production process, and sending the production information to the local area network exchange module and the quality inspection data acquisition module; The quality inspection data acquisition module can obtain production information, and generate product quality inspection plan according to production information, collect product quality inspection results after quality inspection, and send quality inspection results to the local area network exchange module; The local area network exchange module checks the receiving frequency of production information and quality inspection results after obtaining production information and quality inspection results, generates information back transmission integrity result, and sends production information, quality inspection results and production batch to the comprehensive data output module; The comprehensive data output module obtains production information and quality inspection results, analyzes production batch information, production information and quality inspection results, obtains production control result, and obtains production batch through the local area network exchange module and outputs the production batch and production control result.

3. The production data analysis system applied to a digital factory according to claim 2, characterized by, The production batch management module obtains the production batch in the mode of manual input, wherein the production batch information includes production plan time, production plan quantity and production quality requirement; The specific production information collected by the production data acquisition module includes production quantity, production progress, raw material reserve, single product production speed; The quality inspection results obtained by the quality inspection data acquisition module include product qualified rate, product quality inspection proportion and defective product dispersion degree.

4. The production data analysis system applied to a digital factory according to claim 3, characterized by, The production data acquisition module obtains the defective product dispersion degree in the following mode: The quality inspection data acquisition module inspects the product and obtains the quality inspection result as good product or defective product, and obtains the production time of the product through the production data acquisition module, if the quality inspection result is defective product, the defective product signal and the corresponding production time are recorded together, if the quality inspection result is good product, the good product signal and the corresponding production time are recorded together; The quality inspection data acquisition module counts all the defective product signals and creates a time axis, records the defective product signals on the time axis according to the production time corresponding to the defective product signals, calculates the interval of quality inspection of adjacent defective product signal points on the time axis to obtain a defective product occurrence interval, and calculates the standard deviation of the defective product occurrence interval, taking the ratio of the standard deviation to the mean value of the defective product occurrence interval as the defective product dispersion.

5. The production data analysis system applied to a digital factory according to claim 2, characterized by, The production data acquisition module obtains the production schedule in the following manner: obtaining the production plan quantity and production plan time through the production batch management module, obtaining the quantity progress through the ratio of the production quantity in the production information to the production plan quantity, and obtaining the time progress through the ratio of the time taken by the current batch of products to the production plan time. The production data acquisition module can compare the quantity progress and the time progress, and if the quantity progress is greater than or equal to the time progress, the quantity progress is taken as the production progress, and if the quantity progress is less than the time progress, the quantity progress is taken as the production progress while generating an insufficient efficiency signal.

6. The production data analysis system applied to a digital factory according to claim 2, characterized by, After obtaining the production information, the quality inspection data acquisition module calculates the ratio of the preset quality inspection time to the single product production speed, takes the calculation result as an integer, and obtains the minimum sample interval. Meanwhile, the quality inspection data acquisition module obtains the preset quality inspection sampling ratio, compares the quality inspection sampling ratio with the reciprocal of the minimum sample interval, and if the quality inspection sampling ratio is less than the reciprocal of the minimum sample interval, quality inspection work is performed according to the quality inspection sampling ratio, and if the quality inspection sampling ratio is greater than the reciprocal of the minimum sample interval, quality inspection work is performed according to the reciprocal of the minimum sample interval, and a new quality inspection ratio is recorded.

7. The production data analysis system applied to a digital factory according to claim 2, characterized by, The local area network exchange module records the acquisition frequency of the production information and the quality inspection result when obtaining the production information and the quality inspection result, compares the acquisition frequency with the set frequency, and confirms the information feedback integrity result according to the comparison result. The local area network exchange module sends the production information and the quality inspection result to the comprehensive data output module, and simultaneously sends the production information and the quality inspection result to the database through a special network for backup storage.

8. The production data analysis system applied to a digital factory according to claim 1, characterized by, The comprehensive data output module obtains the production control result in the following manner: The comprehensive data output module compares the product pass rate with the set production quality requirement to obtain a pass rate result. The comprehensive data output module comprehensively analyzes the raw material reserves, the single product production speed, and the production progress, obtains the remaining production progress according to the production progress, calculates the raw material sufficiency degree through the raw material reserves, calculates the remaining reserve time through the single product production speed and the raw material reserves, and takes the remaining reserve time and the raw material sufficiency degree as the raw material reserve result.

9. The production data analysis system applied to a digital factory according to claim 8, characterized by, The comprehensive data output module analyzes the single product production speed, the production progress, the production plan time and the production plan quantity, calculates the residual production quantity through the production progress and the production plan quantity, calculates the production required time through the residual production quantity and the single product production speed, obtains the residual time through the time progress in the production plan time and the production progress, compares the production required time and the residual time, and obtains the production progress result.

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