CN115269570A - Quality analysis method and system based on zero-defect engineering big data - Google Patents
Quality analysis method and system based on zero-defect engineering big data Download PDFInfo
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Abstract
The invention discloses a quality analysis method and a system based on zero-defect engineering big data, which are used for collecting quality data inspected by a quality inspection post, zero-defect quality data inspected manually and mutually, other additionally-recorded quality data and additional quality data to form a quality database; associating the data with a product production order, a product bar code and after-sale feedback data respectively; screening data for quality analysis to form a quality analysis database; and generating an analysis chart according to a formula, an operation function and a chart of the quality tool, analyzing and judging the data according to a judgment principle of the quality tool, labeling the identified abnormal data, and sending reminding and pushing. The method is based on zero-defect engineering big data, various scientific quality tools are 'embedded' into an informatization system, scientific analysis and scientific judgment are carried out on the quality big data, regularity contained in the quality data is mined, and potential problem points and risk points in the product manufacturing process are identified.
Description
Technical Field
The invention relates to the technical field of zero defect data processing, in particular to a quality analysis method and system based on zero defect engineering big data.
Background
At present, most of the analysis of zero defects in various manufacturing industries is performed by simple analysis and display by using simple charts such as bar charts, broken line charts, pie charts and the like, and the simple charts can only display data and do not effectively perform scientific analysis on the data; the mass big data generated in the manufacturing process is not scientifically analyzed and scientifically distinguished by using a quality tool, and potential problem points and risk points in the product manufacturing process cannot be identified.
For example, in the prior art, a patent with the patent number 201810925436 discloses a product abnormal data tracing analysis method based on large manufacturing data, which utilizes multi-source different-structure data of each production link of a manufacturing enterprise, reasonably integrates original quality data through targeted data preprocessing measurement, and constructs a structured data set convenient for large-scale parallel analysis; the method has the advantages that data characteristics are widely extracted and accurately selected, appropriate analysis measurement and analysis algorithms are selected, abnormal data generated in the production process of products are traced and analyzed, and an accurate quality abnormal data tracing and analyzing method is provided for manufacturing enterprises. However, the method can only classify, summarize and store mass data acquired in each production link, and preprocess the data by using a KNN algorithm, does not use a quality tool to carry out scientific analysis and scientific judgment, and cannot identify potential problem points and risk points in the product manufacturing process.
Disclosure of Invention
In order to overcome the above disadvantages of the prior art, the present invention provides a quality analysis method and system based on zero defect engineering big data.
The technical scheme adopted by the invention for solving the technical problems is as follows: a quality analysis method based on zero defect engineering big data comprises the following steps:
acquiring quality data including quality inspection post inspection of each production link, zero-defect quality data of manual self-inspection, other additionally-recorded quality data and additional quality data, and forming a quality database to be stored in a quality decision system;
associating the data in the quality database with a product production order, a product bar code and after-sale feedback data respectively;
screening data used for quality analysis from a quality database, forming a quality analysis database and storing the quality analysis database on an information system module, and standardizing the quality data by the information system module;
the mass big data analysis system analyzes and judges the data in the mass analysis database, and comprises the steps of generating an analysis chart according to a formula, an operation function and a chart of a mass tool, analyzing and judging the data according to the judgment principle of the mass tool, labeling the identified abnormal data, and sending reminding and pushing.
As a further improvement of the invention: the mass big data analysis system further comprises the following steps of analyzing and judging the data in the mass analysis database: and forming quality data calculation logic according to a formula, an operation function and an Excel table of the quality tool, and analyzing and judging the quality data.
As a further improvement of the invention: and identifying the important quality problems of the customers according to the after-sales feedback data, and establishing fault category plates, fault grade plates and after-sales reform classification plates according to the identification content.
As a further improvement of the invention: the step of screening data for quality analysis from the quality database, forming the quality analysis database and storing the quality analysis database on the information system module comprises the following steps: the categories of data screened include, but are not limited to, date, material name, number of failures, defect category, responsible entity, and responsible manufacturer.
As a further improvement of the invention: the mass big data analysis system further comprises the following steps of analyzing and judging data in a mass analysis database: and calculating the failure and reject ratio of the product by using a formula according to all quality data produced by the product screened from the quality analysis database by the data processing unit every day, and generating a trend chart of the daily accumulated quality data of the product by using a chart.
As a further improvement of the invention: the mass big data analysis system further comprises the following steps of analyzing and judging the data in the mass analysis database: and calculating the defect fraction defective by using a formula according to the product manufacturing defect quality data screened from the quality analysis database by the data processing unit, and manufacturing a defect quality data trend chart by using a chart product.
As a further improvement of the invention: the mass big data analysis system further comprises the following steps of analyzing and judging data in a mass analysis database: and calculating the accumulated defective rate F (t) value of the manufacturing defects, the total unqualified rate P value of the manufacturing defects and the sigma level of the product manufacturing process capacity by using a formula according to the daily manufacturing defect quality data of the products screened from the quality analysis database by the data processing unit.
As a further improvement of the invention: the data processing unit preprocesses data in the quality analysis database, identifies quality data associated with the after-market feedback data, calculates failure rates and cumulative failure rates, generates an after-market related data arrangement diagram using the bar graph and the line graph, and analyzes the quality data that needs to be improved.
A quality analysis system based on zero defect engineering big data, comprising:
the RFID system establishes a data acquisition module and an RFID system database and inputs quality data of quality inspection post inspection in each link of a production link;
the zero defect decision system receives zero defect quality data of staff self-mutual inspection;
the data supplement input module is used for inputting other quality data and additional quality data through a data supplement input unit interface;
the quality decision system is used for acquiring quality data acquired by the RFID system, zero defect quality data acquired by the zero defect decision system, other quality data and additional quality data to form a quality database, and associating the quality data of the quality database with a product production order, a product bar code and after-sale feedback data respectively;
the system comprises an information system module, a quality decision system and a quality analysis database, wherein the information system module is used for screening data used for quality analysis from the quality database of the quality decision system, storing the data as the quality analysis database and standardizing the quality data;
the mass big data analysis system identifies and receives the mass data acquired by the identification information system module through the data processing unit, screens the required data for data conversion to form an Nth mass analysis database, analyzes and judges the quality data according to a quality tool and a judgment principle, identifies abnormal data, and sends reminding and pushing.
As a further improvement of the invention: the mass big data analysis system further comprises a mass data calculation logic formed according to a formula, an operation function and an Excel table of the mass tool, an analysis chart is generated by using a chart tool, and color marking is carried out on the identified abnormal data according to the judgment principle of the mass tool.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the quality data generated in each production link of the manufacturing enterprise, zero defects found by staff self-mutual inspection every day in the production process of products and quality data detected by inspection posts set by quality departments are collected and sorted, and the quality big data is stored in an information system module through a quality decision system, so that the centralized management of the quality data is realized, and the integrity, the accuracy and the traceability of the quality data are realized; the quality tool and the difference judgment principle are utilized to analyze and judge the quality data, the regularity contained in the quality data is mined, potential problem points and risk points in the product manufacturing process are identified, and a scientific analysis method for the quality big data is provided for enterprises.
2. Standardizing the quality to prevent quality data information from being different due to artificial subjective information filling difference; and the method is also bound with the product identity code to ensure data traceability.
3. The quality tool is used for judging the abnormal points of the product production, automatic alarm prompt is carried out, and the quality management response capability is improved; the potential risk of the product is rapidly identified, and the product percent of pass is improved.
Drawings
FIG. 1 is a schematic view of the present invention.
Fig. 2 is a schematic diagram of the eight criteria of the difference.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
To solve the technical problems in the prior art, the present invention will be further described with reference to the following description and embodiments in conjunction with the accompanying drawings:
as shown in fig. 1-2, the invention discloses a quality analysis method based on zero defect engineering big data, comprising:
acquiring quality data including quality inspection post inspection of each production link, zero-defect quality data of manual self-inspection, other additionally-recorded quality data and additional quality data, and forming a quality database to be stored in a quality decision system;
wherein the other quality data is missing quality data and the like, and the additional quality data can be logistics data and the like related to product manufacture.
Associating the data in the quality database with a product production order, a product bar code and after-sale feedback data respectively;
the corresponding accuracy of the fault data and the product is realized, and the method can be used for tracing the quality state of the manufacturing process in a factory in the life cycle of the product after sale;
screening data used for quality analysis from a quality database, forming a quality analysis database and storing the quality analysis database on an information system module, and standardizing the quality data by the information system module;
through the information system module, the quality data of each production unit and each link acquired by an enterprise every day is imported into the information system module, and the data is automatically acquired and stored, so that the data can be conveniently inquired in real time, the quality data can be prevented from being lost or omitted, and a zero-defect engineering big database in the manufacturing process of enterprise products is formed.
The mass big data analysis system analyzes and judges the data in the mass analysis database, and comprises the steps of generating an analysis chart according to a formula, an operation function and a chart of a mass tool, analyzing and judging the data according to a judgment principle of the mass tool, labeling the identified abnormal data, and sending a prompt and a push.
And the data processing unit receives the quality data acquired and acquired by the information system module in real time, screens out the required data and performs data conversion to form an Nth quality analysis database.
Through a quality tool operation function and a judgment logic idea, a computer operation code is formed, an informatization analysis system is realized, and the quality data analysis efficiency is improved.
A system identification method is established through quality tool judgment rules, automatic analysis of mass big data and automatic identification of abnormal points are achieved, and the quality management response speed is improved.
And the informatization system module realizes automatic identification and automatic analysis of each plate and each category of project according to the mass big data through different screening data interfaces.
And (4) judging abnormal data points after the big data is analyzed, and automatically prompting, automatically pushing and automatically displaying the abnormal data points by the system. For example, large quality data of an enterprise manufacturing process is displayed in real time through a television large screen, a PC (personal computer) terminal, a mobile phone and a display screen; and the mass big data daily analysis result data display and automatic pushing can be realized by associating with a Microsoft Office Outlook system.
The mass big data analysis system further comprises the following steps of analyzing and judging the data in the mass analysis database: and forming a quality data calculation logic according to a formula, an operation function and an Excel table of the quality tool, and analyzing and judging the quality data.
And identifying the important quality problems of the customers according to the after-sales feedback data, and establishing fault category plates, fault grade plates and after-sales reform classification plates according to the identification content.
The step of screening data for quality analysis from the quality database, forming the quality analysis database and storing the quality analysis database on the information system module comprises the following steps: the data categories screened include, but are not limited to, date, material name, number of failures, defect category, responsible entity, and responsible manufacturer.
The mass big data analysis system further comprises the following steps of analyzing and judging data in a mass analysis database: and calculating the failure and reject ratio of the product by using a formula according to all quality data produced by the product screened from the quality analysis database by the data processing unit every day, and generating a trend chart of the daily accumulated quality data of the product by using a chart.
The formula for the quality tool includes:
the formula I is as follows:
the formula II is as follows:
the formula III is as follows:
the formula four is as follows:
the data in the quality analysis database collected by the data processing unit are used for identifying all quality data generated by the product every day, calculating the failure rate of the product by using an operation formula I, and generating a product daily accumulated quality data trend chart by using a bar chart and a line chart; and forming mass data calculation logic and method by using formulas and operation functions of various analysis tools in the mass tools and an Excel table. For example, the center line CL (i.e., P value), the UCL upper limit, and the LCL lower limit of the "cumulative product failure rate" are calculated for each day by the "control map formula".
The UCL, CL, P, LCL data were graphed using line graphs. And simultaneously, according to eight major judgment principles (see figure 2) in the quality tool control chart, carrying out color labeling on 'abnormal data' in daily accumulated quality data analysis so as to identify potential problem points and risk points of the product.
The mass big data analysis system further comprises the following steps of analyzing and judging data in a mass analysis database: and calculating the defect fraction defective by using a formula according to the product manufacturing defect quality data screened from the quality analysis database by the data processing unit, and manufacturing a defect quality data trend chart by using a chart product.
Identifying the manufacturing defect quality number of the product produced every day through a quality analysis database collected by a data processing unit, calculating the manufacturing defect reject ratio by using an operation formula, and generating a product manufacturing defect quality data trend chart by using a bar chart and a line chart; and forming mass data calculation logic and method by using Excel tables according to formulas and operation functions of various analysis tools in the mass tools. For example, the center line CL (i.e., P value), the UCL upper limit, and the LCL lower limit of the daily "number of manufacturing defects" are calculated by the "control map formula".
The UCL, CL, P, LCL data were graphed using line graphs. And simultaneously, according to eight different judgment principles in the quality tool control chart, carrying out color marking on 'abnormal data' of daily manufacturing defect quality data analysis of the product so as to identify potential problem points and risk points in the manufacturing process of the product.
The mass big data analysis system further comprises the following steps of analyzing and judging the data in the mass analysis database: and calculating the accumulated defective rate F (t) value of the manufacturing defects, the total defective rate P value of the manufacturing defects and the sigma level of the manufacturing process capacity of the products by using formulas according to the daily manufacturing defect quality data of the products screened from the quality analysis database by the data processing unit.
Identifying the daily manufacturing defect quality data of the product through a quality analysis database collected by a data processing unit, calculating a manufacturing defect accumulated reject ratio F (t) value and a manufacturing defect total non-yield P value by using an operational formula, and calculating the following steps by using the computational formula: zbench = Normsinv (1-P) calculates the sigma level of the enterprise product manufacturing process capability. The formula applied is:
Y＝P(x＝0)＝e-DPU。
the data processing unit preprocesses data in the quality analysis database, identifies quality data associated with the after-market feedback data, calculates failure rates and cumulative failure rates, generates an after-market related data arrangement diagram using the bar graph and the line graph, and analyzes the quality data that needs to be improved.
Because data such as fault materials, defect description, fault information and the like in the mass big data are huge, a mass tool is used for analyzing a certain unit data singly, an analysis result chart cannot be displayed completely, and meanwhile, the final quality improvement target 'customer satisfaction improvement' cannot be achieved.
The invention utilizes the operation function and the different judgment logic thought of the quality tool to form the computer operation code, and writes a data calculation program, a chart display program, a data different judgment rule program, a color variation program, an interface prompt function program and the like through different codes, thereby realizing an information analysis system and improving the quality data analysis efficiency.
And a system identification method is established through the abnormal judgment rule of the quality tool, so that the automatic analysis of mass big data and the automatic identification of abnormal points are realized, and the quality management response speed is improved.
Abnormal data points judged after the big data are analyzed through an informatization system, and functions of automatic reminding, automatic pushing and abnormal automatic display of analysis results are achieved through a prompt interface, color change, mail pushing and the like.
Through establishing different screening data interfaces, analysts select different time periods, different products, different material names, different production units and the like according to required results to carry out scientific quality analysis on the data, and automatic identification and automatic analysis of each plate and each category project according to mass big data are realized.
And the quality big data analysis result is displayed in real time by opening the terminal connection address through a television big screen, a PC (personal computer) terminal, a mobile phone and a display screen, so that the quality big data of the enterprise product is analyzed in real time and displayed in real time.
The mass big data daily analysis result data display and automatic pushing are realized by associating with a Microsoft Office Outlook system.
And abnormal data points judged after the big data are analyzed are automatically reminded, pushed and displayed through data connection with other system ports.
The RFID system records data, zero defect records data, and an Excel form can also be used for collecting quality data and recording the quality data into a quality data informatization system.
Example 1
A quality analysis system based on zero defect engineering big data, comprising:
the RFID system establishes a data acquisition module and an RFID system database, and records quality data of quality inspection post inspection in each link of a production link through a data recording unit interface;
the zero defect decision system receives zero defect quality data of staff self-checking through a zero defect data connection unit at a terminal;
the data supplement input module is used for inputting other quality data and additional quality data through a data supplement input unit interface;
the quality decision system is used for acquiring quality data acquired by the RFID system, zero defect quality data acquired by the zero defect decision system, other quality data and additional quality data to form a quality database, and associating the quality data of the quality database with a product production order, a product bar code and after-sale feedback data respectively;
the system comprises an information system module, a quality decision system and a quality analysis database, wherein the information system module is used for screening data used for quality analysis from the quality database of the quality decision system, storing the data as the quality analysis database and standardizing the quality data;
the method has the advantages that by establishing the standardized information content of the system, the mass quality data content is ensured not to be too complicated, and the quality data analysis is convenient to be accurate; establishing a data identification rule to realize that an informatization system can automatically identify and automatically judge abnormal data; and a multi-link confirmation flow of system quality data is established, and the accuracy, integrity, correctness and the like of the data are confirmed in a multi-link manner by staff corresponding to the enterprise quality department for the quality data which is specially checked and the quality data which is self-checked, so that the validity and reliability of the quality data analysis are ensured.
The mass big data analysis system identifies and receives the mass data acquired by the identification information system module through the data processing unit, screens the required data for data conversion to form an Nth mass analysis database, analyzes and judges the quality data according to a quality tool and a judgment principle, identifies abnormal data, and sends reminding and pushing.
The quality tool formula and the operation function are utilized, the Excel table is combined, the calculation formula and the function form a quality data calculation rule, the large quality data are scientifically analyzed and scientifically distinguished, regularity contained in the quality data is mined, and potential problem points and risk points in the product manufacturing process are identified.
The mass big data analysis system also comprises a mass data calculation logic formed according to a formula, an operation function and an Excel table of the mass tool, an analysis chart is generated by using a chart tool, and color marking is carried out on the identified abnormal data according to the judgment principle of the mass tool. .
The previous description is only exemplary of the invention, and is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A quality analysis method based on zero defect engineering big data is characterized by comprising the following steps:
acquiring quality data including quality inspection post inspection of each production link, zero-defect quality data of manual self-inspection, other supplementary input quality data and additional quality data, and forming a quality database to be stored in a quality decision system;
respectively associating data in the quality database with a product production order, a product bar code and after-sale feedback data;
screening data used for quality analysis from a quality database, forming a quality analysis database, storing the quality analysis database on an information system module, and standardizing the quality data by the information system module;
the mass big data analysis system analyzes and judges the data in the mass analysis database, and comprises the steps of generating an analysis chart according to a formula, an operation function and a chart of a mass tool, analyzing and judging the data according to a judgment principle of the mass tool, labeling the identified abnormal data, and sending a prompt and a push.
2. The method for quality analysis based on zero defect engineering big data as claimed in claim 1, wherein the analyzing and judging the data in the quality analysis database by the quality big data analyzing system further comprises: and forming quality data calculation logic according to a formula, an operation function and an Excel table of the quality tool, and analyzing and judging the quality data.
3. The quality analysis method based on zero defect engineering big data as claimed in claim 1, further comprising identifying the customer focus on quality problems according to the after-sales feedback data, and establishing the fault category blocks, fault grade blocks, and after-sales reforming classification blocks according to the identification content.
4. The method for quality analysis based on zero defect engineering big data as claimed in claim 1, wherein the step of screening the data for quality analysis from the quality database to form a quality analysis database and storing the quality analysis database on the information system module comprises: the data categories screened include, but are not limited to, date, material name, number of failures, defect category, responsible entity, and responsible manufacturer.
5. The quality analysis method based on the zero defect engineering big data as claimed in claim 1, wherein the quality big data analysis system further comprises: and calculating the failure rate of the product by using a formula according to all quality data produced by the product screened from the quality analysis database by the data processing unit every day, and generating a trend chart of the daily accumulated quality data of the product by using a chart.
6. The method of claim 1, wherein the analyzing and determining the data in the quality analysis database by the quality big data analyzing system further comprises: and calculating the defect fraction defective by using a formula according to the product manufacturing defect quality data screened from the quality analysis database by the data processing unit, and manufacturing a defect quality data trend chart by using a chart product.
7. The quality analysis method based on the zero defect engineering big data as claimed in claim 6, wherein the quality big data analysis system further comprises: and calculating the accumulated defective rate F (t) value of the manufacturing defects, the total unqualified rate P value of the manufacturing defects and the sigma level of the product manufacturing process capacity by using a formula according to the daily manufacturing defect quality data of the products screened from the quality analysis database by the data processing unit.
8. The method of claim 3, wherein the data processing unit preprocesses data in the quality analysis database, identifies quality data associated with the after-market feedback data, calculates failure rates and cumulative failure rates, generates an after-market related data arrangement diagram using the bar graph and the line graph, and analyzes the quality data to be improved.
9. A quality analysis system based on zero defect engineering big data is characterized by comprising:
the RFID system establishes a data acquisition module and an RFID system database and inputs quality data of quality inspection post inspection in each link of a production link;
the zero defect decision system receives zero defect quality data of staff self-mutual inspection;
the data supplement input module is used for inputting other quality data and additional quality data through a data supplement input unit interface;
the quality decision system is used for acquiring quality data acquired by the RFID system, zero defect quality data acquired by the zero defect decision system, other quality data and additional quality data to form a quality database, and associating the quality data of the quality database with a product production order, a product bar code and after-sale feedback data respectively;
the system comprises an information system module, a quality decision system and a quality analysis database, wherein the information system module is used for screening data used for quality analysis from the quality database of the quality decision system, storing the data as the quality analysis database and standardizing the quality data;
the mass big data analysis system identifies and receives the mass data acquired by the identification information system module through the data processing unit, screens the required data for data conversion to form an Nth mass analysis database, analyzes and judges the quality data according to a quality tool and a judgment principle, identifies abnormal data, and sends reminding and pushing.
10. The mass analysis system based on zero defect engineering big data of claim 9, further comprising a mass data calculation logic formed according to a formula, an operation function and an Excel table of a mass tool, an analysis chart generated by using a chart tool, and color labeling of the identified abnormal data according to a discriminant principle of the mass tool.
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