CN113962507A - Intelligent convenient industry-wide data analysis system and method based on SPC - Google Patents

Intelligent convenient industry-wide data analysis system and method based on SPC Download PDF

Info

Publication number
CN113962507A
CN113962507A CN202111032738.2A CN202111032738A CN113962507A CN 113962507 A CN113962507 A CN 113962507A CN 202111032738 A CN202111032738 A CN 202111032738A CN 113962507 A CN113962507 A CN 113962507A
Authority
CN
China
Prior art keywords
data
user
control chart
type
control
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202111032738.2A
Other languages
Chinese (zh)
Inventor
黄瑞
邵晓安
胡超级
黄繁秋
陈江义
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang Supcon Technology Co Ltd
Original Assignee
Zhejiang Supcon Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang Supcon Technology Co Ltd filed Critical Zhejiang Supcon Technology Co Ltd
Priority to CN202111032738.2A priority Critical patent/CN113962507A/en
Publication of CN113962507A publication Critical patent/CN113962507A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • G06F9/44521—Dynamic linking or loading; Link editing at or after load time, e.g. Java class loading
    • G06F9/44526—Plug-ins; Add-ons
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/10—Numerical modelling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Human Resources & Organizations (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Databases & Information Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Tourism & Hospitality (AREA)
  • Educational Administration (AREA)
  • Development Economics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Computer Hardware Design (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • Game Theory and Decision Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • General Factory Administration (AREA)

Abstract

The invention relates to an intelligent convenient industry-wide data analysis system based on SPC, which is characterized by comprising the following components: the data acquisition module is used for receiving data source information and a data query instruction input by a user, connecting a data source corresponding to the data source information based on the data source information, further acquiring data corresponding to the data query instruction in the data source according to the data query instruction, and taking the data as original data; the SPC module is used for processing the original data according to a control scheme preset by a user and acquiring a processing result; the control scheme preset by the user comprises the following steps: the type information of the control chart set by the user, the rule of the decimal place set by the user and the judgment criterion determined by the user.

Description

Intelligent convenient industry-wide data analysis system and method based on SPC
Technical Field
The invention relates to the technical field of production flow control, in particular to an intelligent, convenient and full-industry data analysis system and method based on SPC.
Background
Statistical Process Control (SPC) systems are currently used in most semiconductor manufacturing applications, but are less common in the conventional manufacturing industry. With the continuous development of global economy, the manufacturing industry also needs to be continuously developed and innovated. SPC is a scientific quality control method, and can effectively improve production efficiency, control production cost and improve product quality.
Enterprise informatization in various industries has been a great trend, and various informatization systems such as ERP (enterprise manufacturing resource planning), MES (manufacturing execution system), APS (advanced production planning and scheduling system) have appeared. Each system is completely independent, and secondary development of the system is forced to be carried out in most cases if system data needs to be analyzed, so that a customized interface for acquiring data is provided for the SPC system.
The prior art has the following defects: the development efficiency is low: the manufacturing industry has more factory informatization systems, different factories and different industries have different data analysis scenes and requirements, so that a plurality of analysis functions need to be customized and developed. This is very labor intensive because the analysis scenario needs to be redeveloped whenever it changes. The flexibility is not sufficient: in the manufacturing industry, particularly in petrochemical and other continuous production enterprises, due to the complex production flow, a technician often needs to change the data analysis scene when the factors such as process, equipment and the like change, so that a developer needs to develop a program again, and a user cannot adjust the analysis scene by himself. Analyzing scene limitation: the data acquisition system is only limited to an MES system, but at present, enterprise informatization is highly integrated, data of a plurality of systems need to be basic corresponding to a plurality of scene analysis, and the limitation exists if only MES data can be taken to analyze scenes and the analysis effect. Acquiring data is too complex: the key information needs to be filtered for many times for complex data, and the performance and the stability can not be ensured.
Disclosure of Invention
Technical problem to be solved
In view of the above disadvantages and shortcomings of the prior art, the present invention provides an intelligent, convenient and fast industrial-wide data analysis system and method based on SPC, which solves the technical problem of excessively complex data acquisition.
(II) technical scheme
In order to achieve the purpose, the invention adopts the main technical scheme that:
in a first aspect, an embodiment of the present invention provides an intelligent, convenient and fast industry-wide data analysis system based on SPC, where the system includes:
the data acquisition module is used for receiving data source information and a data query instruction input by a user, connecting a data source corresponding to the data source information based on the data source information, further acquiring data corresponding to the data query instruction in the data source according to the data query instruction, and taking the data as original data;
the SPC module is used for processing the original data according to a control scheme preset by a user and acquiring a processing result;
the control scheme preset by the user comprises the following steps: the type information of the control chart set by the user, the rule of the decimal place set by the user and the judgment criterion determined by the user.
Preferably, the first and second liquid crystal materials are,
the data acquisition module comprises a visual interface;
the visual interface is used for receiving data source information input by a user;
the data source information is one of database information, plug-in information, interface information and real-time database information which are used for connecting an external enterprise system;
the database information includes: database address, database type, database account and password;
the plug-in information includes: connection characters for connecting the data acquisition module with an external enterprise system are realized;
the interface information includes: interface address, account number and password of the interface;
the real-time database information includes: the version of the real-time database, the connection address of the real-time database, the connection account of the real-time database and the connection account password of the real-time database;
after the visual interface receives data source information input by a user, the data acquisition module is in matched butt joint with a database or a plug-in or an interface or a real-time database corresponding to the data source information;
the visual interface is further used for acquiring a data query instruction input by a user after the data acquisition module is matched and butted with a database or a plug-in or an interface or a real-time database corresponding to the data source information, and further the data acquisition module acquires data corresponding to the data query instruction in the database or the plug-in or the interface or the real-time database matched and butted with the data acquisition module according to the data query instruction and takes the data as original data.
Preferably, the first and second liquid crystal materials are,
the data in the data source comprises the inspection results of the external enterprise system for inspecting the sample according to different indexes;
the data query instruction is to acquire data meeting preset filtering conditions;
the preset filtering conditions comprise: index name, detection time and sample.
Preferably, the first and second liquid crystal materials are,
the SPC module includes:
the control scheme management unit is used for receiving a control scheme set by a user;
the type information of the control chart set by the user comprises the type of the control chart selected by the user in a plurality of preset control chart types and/or the setting information corresponding to the type of the control chart selected by the user;
the plurality of control chart types includes: the method comprises the following steps of (1) average-standard deviation control chart, average-range control chart, median-range control chart, single-value-mobile range control chart, defect numerical control chart, unit defect numerical control chart, unqualified product numerical control chart and defective rate control chart;
setting information corresponding to the average-standard deviation control chart, the average-range control chart, the median-range control chart and the single-value-mobile range control chart comprises an upper limit value and a lower limit value set by a user, a target value set by the user and the number set by the user;
setting information corresponding to a defect numerical control drawing, a unit defect numerical control drawing, a defective product numerical control drawing and a defective rate control diagram comprises a rule for grouping the original data;
the user-selected judgment criterion is a judgment criterion selected by the user in a preset judgment criterion library;
the difference criterion base comprises a plurality of preset difference criterion;
the execution unit is used for acquiring a calculation mode type selected by a user from a first calculation mode type and a second calculation mode type which are preset, processing the original data based on the calculation mode type selected by the user and a control scheme set by the user, and acquiring a processing result.
Preferably, the first and second liquid crystal materials are,
the SPC module further comprises: a difference criterion unit;
the judgment criterion library is stored in the judgment criterion unit;
wherein the discriminant criterion library includes: a first criterion;
the first discriminant criterion includes: in the single-value-moving range diagram, if the average value of the grouped original data exceeds the upper limit value and the lower limit value set by the user, the original data is abnormal data.
Preferably, the first and second liquid crystal materials are,
processing the original data based on the calculation mode type selected by the user and the control scheme set by the user to obtain a processing result, which specifically comprises:
correspondingly grouping the original data according to the type of the control chart in the control scheme to obtain a plurality of groups;
acquiring a corresponding calculation result according to the type of the calculation mode selected by the user;
according to the calculation result, carrying out data difference judgment on the original data according to the criterion determined by the user in a difference judgment criterion library according to the difference judgment criterion, and obtaining a difference judgment result;
and returning the original data after data judgment to the visual interface.
Preferably, the original data is correspondingly grouped according to the type of the control chart in the control scheme to obtain a plurality of groups; the method specifically comprises the following steps:
if the type of the control chart in the control scheme is one of a mean-standard deviation control chart, a mean-range control chart, a median-range control chart and a single-value-mobile range control chart, grouping the number set by the user as subgroup capacity to obtain a plurality of groups;
and if the type of the control chart in the control scheme is one of a defect numerical control drawing, a unit defect numerical control drawing, a defective product numerical control drawing and a defective product rate control chart, grouping according to the defective product number and the random inspection number to obtain a plurality of groups.
Preferably, the first and second liquid crystal materials are,
obtaining a corresponding calculation result according to the calculation mode type selected by the user, specifically comprising:
if the type of the calculation mode selected by the user is the first calculation mode, determining a preset calculation coefficient corresponding to the subgroup capacity and the control chart type according to the subgroup capacity and the control chart type, and further calling a preset MATLAB calculation tool to acquire a control line by adopting the calculation coefficient;
the control lines comprise horizontal lines of a first value and a second value, respectively;
the first numerical value is obtained by formula (1), wherein formula (1) is:
Q＝A+kS；
wherein Q is a first value;
a is the mean value of the original data;
s is the standard deviation of the original data;
k is a preset calculation coefficient corresponding to the subgroup capacity and the control chart type;
the second value is obtained by formula (2), where formula (2) is:
W＝A-kS；
wherein W is a second value;
if the type of the calculation mode selected by the user is a second calculation mode, calling a preset MATLAB calculation tool to acquire a first numerical value Q by adopting a formula (3) and a second numerical value W by adopting a formula (4), and further acquiring a control line according to the first numerical value and the second numerical value;
the formula (3) is:
Q＝A+3S；
the formula (4) is:
Q＝A-3S。
preferably, the first and second liquid crystal materials are,
the SPC module further comprises: an exception handling unit and a coefficient management unit;
the exception handling unit is used for marking the data with the exception judgment result as the exception into red;
the color recovery method is also used for recovering the color of abnormal data to be normal after acquiring the reason information of abnormal data input by a manager;
wherein the preset calculation coefficient is stored in the coefficient management unit.
In a second aspect, the present invention provides an intelligent and convenient industrial-wide data analysis method based on SPC, which is executed by any one of the systems described above.
(III) advantageous effects
The invention has the beneficial effects that:
compared with the prior art, the intelligent and convenient industrial-wide data analysis system based on SPC can acquire data from various data sources such as a relational database, a real-time database and a Web Service which are connected with an external enterprise system by adopting the data acquisition module, so that cross-system data acquisition is realized.
According to the intelligent and convenient industrial-wide data analysis system based on SPC, the data acquisition module provides a visual interface, so that a user can adjust the data source and the corresponding analysis data by himself, the flexible switching of analysis scenes is realized, and the data are filtered more simply and conveniently.
Drawings
FIG. 1 is a schematic structural diagram of an SPC-based intelligent convenient industry-wide data analysis system according to the present invention;
fig. 2 is a schematic structural diagram of an SPC module in the SPC-based intelligent convenient industrial wide data analysis system of the present invention.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
In order to better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Referring to fig. 1, the present embodiment provides an intelligent, convenient and industrial wide data analysis system based on SPC, the system includes:
the data acquisition module is used for receiving data source information and a data query instruction input by a user, connecting a data source corresponding to the data source information based on the data source information, further acquiring data corresponding to the data query instruction in the data source according to the data query instruction, and taking the data as original data.
And the SPC module is used for processing the original data according to a control scheme preset by a user and acquiring a processing result.
The control scheme preset by the user comprises the following steps: the type information of the control chart set by the user, the rule of the decimal place set by the user and the judgment criterion determined by the user.
In a specific application, the rule of decimal place set by the user is used for determining the accuracy of the original data and the calculation result, and assuming that the rule of decimal place of the control scheme is set to be 2, the original data is 9.998, 9.2139 and 9.1, the original data returned to the page after processing is 10.00, 9.21 and 9.10, the calculated average value is 9.4373, and the returned to the front end is 9.44 retaining two decimal places.
In a specific application, the results of SPC processing are also shown by Echart charts.
In practical application of this embodiment, the data acquisition module includes a visualization interface.
The visual interface is used for receiving data source information input by a user.
The data source information is one of database information, plug-in information, interface information and real-time database information which are used for connecting an external enterprise system.
The database information includes: database address, database type, database account and password.
The plug-in information includes: and connection characters for connecting the data acquisition module with an external enterprise system are realized.
The interface information includes: interface address, account number and password of the interface.
The real-time database information includes: the version of the real-time database, the connection address of the real-time database, the connection account number of the real-time database and the connection account number password of the real-time database.
After the visual interface receives data source information input by a user, the data acquisition module is in matched butt joint with a database or a plug-in or an interface or a real-time database corresponding to the data source information.
The visual interface is further used for acquiring a data query instruction input by a user after the data acquisition module is matched and butted with a database or a plug-in or an interface or a real-time database corresponding to the data source information, and further the data acquisition module acquires data corresponding to the data query instruction in the database or the plug-in or the interface or the real-time database matched and butted with the data acquisition module according to the data query instruction and takes the data as original data.
In practical application of this embodiment, the data in the data source includes the test results of the external enterprise system performing tests on the sample according to different indexes.
In a specific application of this embodiment, when the data in the data source faces different external systems, the data in the data source is different, if the external system is a laboratory system, the data in the data source is analyzed by using the analysis results of various indexes of the sample as a sample, if the external system is a system of a semiconductor manufacturing enterprise, the process quality of the electronic component is analyzed as a sample, and if the external system is a system of an automobile part manufacturing enterprise, the data of various automobile parts is analyzed as a sample.
The data query instruction is to acquire data meeting preset filtering conditions.
The preset filtering conditions comprise: index name, detection time and sample.
In specific applications, for example, food processing plants need to analyze the inspection results of various food safety indexes such as DBP, DEHP, malondialdehyde, fatty acid composition, benzo (α) pyrene and the like of purchased oil and fat raw materials within a period of time, and these data are generally stored in a database of a LIMS (laboratory information management) system of the factory.
Therefore, a connection instance is configured and created in the data acquisition module, the data acquisition module is connected with the database of the LIMS system according to the database information of the LIMS system, a statement of data query (i.e., a data query instruction in the embodiment) is configured after the connection is successful, a filter condition can be identified by using a wildcard character in the query statement, if the queried data field is ambiguous or excessive, field configuration can be performed, only fields needing to participate in analysis are selected, and alias of the fields is configured.
The query statement in this embodiment is a test result of a query sample, where the filtering condition is set as an index name, a detection time, and a sample.
In practical application of this embodiment, the SPC module includes:
and the control scheme management unit is used for receiving the control scheme set by the user.
The type information of the control chart set by the user includes a type of a control chart selected by the user among a plurality of control chart types set in advance and/or setting information corresponding to the type of the control chart selected by the user.
The plurality of control chart types includes: the control method comprises the steps of average-standard deviation control chart, average-range control chart, median-range control chart, single-value-mobile range control chart, defect numerical control chart, unit defect numerical control chart, unqualified product numerical control chart and defective rate control chart.
The setting information corresponding to the average-standard deviation control chart, the average-range control chart, the median-range control chart and the single-value-mobile range control chart comprises an upper limit value and a lower limit value set by a user, a target value set by the user and the number set by the user.
The setting information corresponding to the defect numerical control drawing, the unit defect numerical control drawing, the unqualified product numerical control drawing and the unqualified product rate control drawing comprises a rule for grouping the original data.
The judgment criterion selected by the user is the judgment criterion selected by the user in a preset judgment criterion library.
The differentiation criterion library comprises a plurality of preset differentiation criteria.
In a specific application, the discriminant criterion library comprises a first discriminant criterion besides the common discriminant criterion. The judgment criteria in the judgment criteria library are provided by default through system initialization, and are newly added and deleted, and only the parameters, possible reasons, remarks and other information in the judgment criteria library are allowed to be modified.
The execution unit is used for acquiring a calculation mode type selected by a user from a first calculation mode type and a second calculation mode type which are preset, processing the original data based on the calculation mode type selected by the user and a control scheme set by the user, and acquiring a processing result.
In practical application of this embodiment, the SPC module further includes: and a judgment criterion unit.
The discrimination criterion library is stored in the discrimination criterion unit.
Wherein the discriminant criterion library includes: a first criterion.
The first discriminant criterion includes: in the single-value-moving range diagram, if the average value of the grouped original data exceeds the upper limit value and the lower limit value set by the user, the original data is abnormal data.
In practical application of this embodiment, processing the raw data based on the calculation mode type selected by the user and the control scheme set by the user to obtain a processing result specifically includes:
and correspondingly grouping the original data according to the type of the control chart in the control scheme to obtain a plurality of groups.
And acquiring a corresponding calculation result according to the calculation mode type selected by the user.
And carrying out data discrimination on the data according to the calculation result and the criterion determined by the user in the discrimination criterion library according to the discrimination criterion, and obtaining a discrimination result.
And returning the original data after data judgment to the visual interface.
In practical application of this embodiment, the original data is grouped correspondingly according to the type of the control chart in the control scheme to obtain a plurality of groups; the method specifically comprises the following steps:
and if the type of the control chart in the control scheme is one of a mean-standard deviation control chart, a mean-range control chart, a median-range control chart and a single-value-mobile-range control chart, grouping the number set by the user as the subgroup capacity to obtain a plurality of groups.
For example, if the original data has 104 entries and the number set by the user is 5, 20 groups of data will be obtained after grouping, and the last 4 entries less than one group are discarded.
And if the type of the control chart in the control scheme is one of a defect numerical control drawing, a unit defect numerical control drawing, a defective product numerical control drawing and a defective product rate control chart, grouping according to the defective product number and the random inspection number to obtain a plurality of groups.
In practical application of this embodiment, obtaining a corresponding calculation result according to the calculation mode type selected by the user specifically includes:
and if the type of the calculation mode selected by the user is the first calculation mode, determining preset calculation coefficients corresponding to the subgroup capacity and the control chart type according to the subgroup capacity and the control chart type, and further calling a preset MATLAB calculation tool to acquire a control line by adopting the calculation coefficients.
The preset MATLAB computing tool may be a MATLAB company Runtime (MATLAB Runtime environment, MCR for short) directly installed on a server where the system is located. Or installing MCR on other services, packaging and registering the called related programs into the services, and calling the services to obtain the calculation results in a network request mode.
The control lines comprise horizontal lines of a first value and a second value, respectively;
the first numerical value is obtained by formula (1), wherein formula (1) is:
Q＝A+kS；
wherein Q is a first value;
a is the mean value of the original data;
s is the standard deviation of the original data;
k is a preset calculation coefficient corresponding to the subgroup capacity and the control chart type;
the second value is obtained by formula (2), where formula (2) is:
W＝A-kS；
wherein W is a second value;
if the type of the calculation mode selected by the user is a second calculation mode, calling a preset MATLAB calculation tool to acquire a first numerical value Q by adopting a formula (3) and a second numerical value W by adopting a formula (4), and further acquiring a control line according to the first numerical value and the second numerical value;
the formula (3) is:
Q＝A+3S；
the formula (4) is:
Q＝A-3S。
in practical application of this embodiment, the SPC module further includes: an exception processing unit and a coefficient management unit.
The exception handling unit is used for marking the data with the exception judgment result as the exception into red;
for example, the original data has 100 items, and every 5 items are divided into one group, and 20 groups are provided. The calculation result of the mean value graph is the average value of each group, and the judgment criterion is to judge the 20 average values.
And the method is also used for recovering the color of the abnormal data to be normal after acquiring the reason information input by the manager aiming at the abnormal original data.
Wherein the preset calculation coefficient is stored in the coefficient management unit.
Wherein the preset calculation coefficients provide 177 initial data (source "revised 2014-mid-quality professional theory and substance (middle level)) by default for the system. If the coefficient is not sufficient for the calculation, the corresponding coefficient value can be increased.
Compared with the prior art, the intelligent and convenient industry-wide data analysis system based on SPC can acquire data from various data sources such as a relational database, a real-time database and a Web Service which are connected with an external enterprise system by adopting the data acquisition module, so that data acquisition across systems is realized.
In the intelligent and convenient industry-wide data analysis system based on SPC in the embodiment, the data acquisition module provides a visual interface, so that a user can adjust the data source and the corresponding analysis data by himself, the flexible switching of analysis scenes is realized, and the data is more concise and convenient to filter.
Since the system described in the above embodiment of the present invention is a system used for implementing the method of the above embodiment of the present invention, a person skilled in the art can understand the specific structure and the modification of the system based on the method described in the above embodiment of the present invention, and thus the detailed description is omitted here. All systems adopted by the method of the above embodiments of the present invention are within the intended scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third and the like are for convenience only and do not denote any order. These words are to be understood as part of the name of the component.
Furthermore, it should be noted that in the description of the present specification, the description of the term "one embodiment", "some embodiments", "examples", "specific examples" or "some examples", etc., means that a specific feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, the claims should be construed to include preferred embodiments and all changes and modifications that fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include such modifications and variations.

Claims (10)

1. An intelligent, convenient, industry wide data analysis system based on SPC, the system comprising:
the data acquisition module is used for receiving data source information and a data query instruction input by a user, connecting a data source corresponding to the data source information based on the data source information, further acquiring data corresponding to the data query instruction in the data source according to the data query instruction, and taking the data as original data;
the SPC module is used for processing the original data according to a control scheme preset by a user and acquiring a processing result;
the control scheme preset by the user comprises the following steps: the type information of the control chart set by the user, the rule of the decimal place set by the user and the judgment criterion determined by the user.
2. The system of claim 1,
the data acquisition module comprises a visual interface;
the visual interface is used for receiving data source information input by a user;
the data source information is one of database information, plug-in information, interface information and real-time database information which are used for connecting an external enterprise system;
the database information includes: database address, database type, database account and password;
the plug-in information includes: connection characters for connecting the data acquisition module with an external enterprise system are realized;
the interface information includes: interface address, account number and password of the interface;
the real-time database information includes: the version of the real-time database, the connection address of the real-time database, the connection account of the real-time database and the connection account password of the real-time database;
after the visual interface receives data source information input by a user, the data acquisition module is in matched butt joint with a database or a plug-in or an interface or a real-time database corresponding to the data source information;
the visual interface is further used for acquiring a data query instruction input by a user after the data acquisition module is matched and butted with a database or a plug-in or an interface or a real-time database corresponding to the data source information, and further the data acquisition module acquires data corresponding to the data query instruction in the database or the plug-in or the interface or the real-time database matched and butted with the data acquisition module according to the data query instruction and takes the data as original data.
3. The system of claim 2,
the data in the data source comprises the inspection results of the external enterprise system for inspecting the sample according to different indexes;
the data query instruction is to acquire data meeting preset filtering conditions;
the preset filtering conditions comprise: index name, detection time and sample.
4. The system of claim 3,
the SPC module includes:
the control scheme management unit is used for receiving a control scheme set by a user;
the type information of the control chart set by the user comprises the type of the control chart selected by the user in a plurality of preset control chart types and/or the setting information corresponding to the type of the control chart selected by the user;
the plurality of control chart types includes: the method comprises the following steps of (1) average-standard deviation control chart, average-range control chart, median-range control chart, single-value-mobile range control chart, defect numerical control chart, unit defect numerical control chart, unqualified product numerical control chart and defective rate control chart;
setting information corresponding to the average-standard deviation control chart, the average-range control chart, the median-range control chart and the single-value-mobile range control chart comprises an upper limit value and a lower limit value set by a user, a target value set by the user and the number set by the user;
setting information corresponding to a defect numerical control drawing, a unit defect numerical control drawing, a defective product numerical control drawing and a defective rate control diagram comprises a rule for grouping the original data;
the user-selected judgment criterion is a judgment criterion selected by the user in a preset judgment criterion library;
the difference criterion base comprises a plurality of preset difference criterion;
the execution unit is used for acquiring a calculation mode type selected by a user from a first calculation mode type and a second calculation mode type which are preset, processing the original data based on the calculation mode type selected by the user and a control scheme set by the user, and acquiring a processing result.
5. The system of claim 4,
the SPC module further comprises: a difference criterion unit;
the judgment criterion library is stored in the judgment criterion unit;
wherein the discriminant criterion library includes: a first criterion;
the first discriminant criterion includes: in the single-value-moving range diagram, if the average value of the grouped original data exceeds the upper limit value and the lower limit value set by the user, the original data is abnormal data.
6. The system of claim 5,
processing the original data based on the calculation mode type selected by the user and the control scheme set by the user to obtain a processing result, which specifically comprises:
correspondingly grouping the original data according to the type of the control chart in the control scheme to obtain a plurality of groups;
acquiring a corresponding calculation result according to the type of the calculation mode selected by the user;
according to the calculation result, carrying out data difference judgment on the original data according to the criterion determined by the user in a difference judgment criterion library according to the difference judgment criterion, and obtaining a difference judgment result;
and returning the original data after data judgment to the visual interface.
7. The system of claim 6, wherein the raw data is grouped according to the type of control chart in the control scheme to obtain a plurality of groups; the method specifically comprises the following steps:
if the type of the control chart in the control scheme is one of a mean-standard deviation control chart, a mean-range control chart, a median-range control chart and a single-value-mobile range control chart, grouping the number set by the user as subgroup capacity to obtain a plurality of groups;
and if the type of the control chart in the control scheme is one of a defect numerical control drawing, a unit defect numerical control drawing, a defective product numerical control drawing and a defective product rate control chart, grouping according to the defective product number and the random inspection number to obtain a plurality of groups.
8. The system of claim 7,
obtaining a corresponding calculation result according to the calculation mode type selected by the user, specifically comprising:
if the type of the calculation mode selected by the user is the first calculation mode, determining a preset calculation coefficient corresponding to the subgroup capacity and the control chart type according to the subgroup capacity and the control chart type, and further calling a preset MATLAB calculation tool to acquire a control line by adopting the calculation coefficient;
the control lines comprise horizontal lines of a first value and a second value, respectively;
the first numerical value is obtained by formula (1), wherein formula (1) is:
Q＝A+kS；
wherein Q is a first value;
a is the mean value of the original data;
s is the standard deviation of the original data;
k is a preset calculation coefficient corresponding to the subgroup capacity and the control chart type;
the second value is obtained by formula (2), where formula (2) is:
W＝A-kS；
wherein W is a second value;
if the type of the calculation mode selected by the user is a second calculation mode, calling a preset MATLAB calculation tool to acquire a first numerical value Q by adopting a formula (3) and a second numerical value W by adopting a formula (4), and further acquiring a control line according to the first numerical value and the second numerical value;
the formula (3) is:
Q＝A+3S；
the formula (4) is:
W＝A-3S。
9. the system of claim 8,
the SPC module further comprises: an exception handling unit and a coefficient management unit;
the exception handling unit is used for marking the data with the exception judgment result as the exception into red;
the color recovery method is also used for recovering the color of abnormal data to be normal after acquiring the reason information of abnormal data input by a manager;
wherein the preset calculation coefficient is stored in the coefficient management unit.
10. A method for intelligent and convenient industrial wide data analysis based on SPC, characterized in that said method is performed by a system according to any of the preceding claims 1-9.
CN202111032738.2A 2021-09-03 2021-09-03 Intelligent convenient industry-wide data analysis system and method based on SPC Pending CN113962507A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111032738.2A CN113962507A (en) 2021-09-03 2021-09-03 Intelligent convenient industry-wide data analysis system and method based on SPC

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111032738.2A CN113962507A (en) 2021-09-03 2021-09-03 Intelligent convenient industry-wide data analysis system and method based on SPC

Publications (1)

Publication Number Publication Date
CN113962507A true CN113962507A (en) 2022-01-21

Family

ID=79460842

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111032738.2A Pending CN113962507A (en) 2021-09-03 2021-09-03 Intelligent convenient industry-wide data analysis system and method based on SPC

Country Status (1)

Country Link
CN (1) CN113962507A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117349322A (en) * 2023-12-05 2024-01-05 摩尔元数(福建)科技有限公司 SPC real-time analysis method and system based on analysis control chart

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113139078A (en) * 2021-03-31 2021-07-20 青岛奥利普自动化控制***有限公司 Control chart generation method and electronic equipment
CN113219910A (en) * 2021-03-19 2021-08-06 苏州数杰智能技术有限公司 Full-flow production self-diagnosis and optimization system

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113219910A (en) * 2021-03-19 2021-08-06 苏州数杰智能技术有限公司 Full-flow production self-diagnosis and optimization system
CN113139078A (en) * 2021-03-31 2021-07-20 青岛奥利普自动化控制***有限公司 Control chart generation method and electronic equipment

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
"食品论坛, 什么是 SPC？质量人来学一下！", HTTPS://MP.WEIXIN.QQ.COM/S?__BIZ=MJM5MJEZNZAWMA==&MID=2651479054&IDX=3&SN=0D7A9D432C8441A89B9C0F57C9B9CDF1&CHKSM=BD5416498A239F5FE5A1D22EA0D1556D9C2D88F50889C0B1933C7B536B258E3466E646F04927&SCENE=27, 25 August 2019 (2019-08-25) *
周天成: "炼钢企业统计过程控制(SPC)***开发", 山西冶金, no. 1, 28 February 2019 (2019-02-28), pages 110 - 112 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117349322A (en) * 2023-12-05 2024-01-05 摩尔元数(福建)科技有限公司 SPC real-time analysis method and system based on analysis control chart
CN117349322B (en) * 2023-12-05 2024-03-08 摩尔元数(福建)科技有限公司 SPC real-time analysis method and system based on analysis control chart

Similar Documents

Publication Publication Date Title
EP3165984B1 (en) An event analysis apparatus, an event analysis method, and an event analysis program
US11170332B2 (en) Data analysis system and apparatus for analyzing manufacturing defects based on key performance indicators
CN111177134B (en) Data quality analysis method, device, terminal and medium suitable for mass data
Bors et al. Capturing and visualizing provenance from data wrangling
CN114356940B (en) Power grid data management system and method
CN111400288A (en) Data quality inspection method and system
US10901875B2 (en) Evaluating and presenting software testing project status indicators
US20060129879A1 (en) System and method for monitoring the status and progress of a technical process or of a technical project
CN114116065B (en) Method and device for acquiring topological graph data object and electronic equipment
CN111475624B (en) Monitoring data retrieval method, device and equipment
CN113962507A (en) Intelligent convenient industry-wide data analysis system and method based on SPC
CN115587670A (en) Product quality diagnosis method and device based on index map
US9727666B2 (en) Data store query
KR20190060548A (en) Method of analyzing and visualizing the cause of process failure by deriving the defect occurrence index by variable sections
CN111858236B (en) Knowledge graph monitoring method and device, computer equipment and storage medium
US20040010441A1 (en) Metrics analyzer tool and method
CN112668314A (en) Data standard conformance detection method, device, system and storage medium
CN116362443A (en) Data management method and device for enterprise information platform
CN115689126A (en) Data processing method, device, equipment and medium
CN116701890A (en) Data quality evaluation system
JP2006244298A (en) Text mining method and device
Thaler et al. The IWi process model corpus
US8423299B2 (en) Estimation system for chemical substance included in part and estimation method for chemical substance included in part
CN115225470A (en) Business abnormity monitoring method and device, electronic equipment and storage medium
KR102217092B1 (en) Method and apparatus for providing quality information of application

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination