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CN-122019951-A - Product evaluation method, device, equipment and medium

CN122019951ACN 122019951 ACN122019951 ACN 122019951ACN-122019951-A

Abstract

The invention discloses a product evaluation method, a device, equipment and a medium, wherein the product evaluation method comprises the steps of obtaining product statistical parameters, parameter limit values and measurement statistical parameters of a measurement system, wherein the measurement system is used for carrying out product qualification measurement; based on the product statistical parameter, the parameter limit value and the measurement statistical parameter of the measurement system, determining the production risk probability of the product and the measurement risk probability of the measurement system for measuring the product, and based on the production risk probability and the measurement risk probability, obtaining the index value corresponding to the product evaluation index.

Inventors

  • LIN LIANGMING
  • Peng Kelai
  • HU ZHIQIANG

Assignees

  • 宁德时代新能源科技股份有限公司

Dates

Publication Date
20260512
Application Date
20241112

Claims (13)

  1. 1. A method of product assessment, the method comprising: acquiring a product statistical parameter, a parameter limit value and a measurement statistical parameter of a measurement system, wherein the measurement system is used for carrying out product qualification measurement; Determining the production risk probability of the product and the measurement risk probability of the measurement system for measuring the product based on the product statistical parameter, the parameter limit value and the measurement statistical parameter of the measurement system; And obtaining an index value corresponding to a product evaluation index based on the production risk probability and the measurement risk probability.
  2. 2. The method of claim 1, wherein the determining the production risk probability of the product and the measurement risk probability of the measurement system measuring the product based on the product statistics parameters, the parameter limits, and the measurement statistics parameters of the measurement system comprises: Determining normal distribution data of a product and normal distribution data of a measurement system based on the product statistical parameter, the parameter limit value and the measurement statistical parameter of the measurement system; Determining the production risk probability based on normal distribution data of the product; The measurement risk probability is determined based on normal distribution data of the measurement system.
  3. 3. The method of claim 2, wherein the product statistics include product process mean values and product process standard deviations, wherein the measurement statistics of the measurement system include measurement standard deviations of the measurement system, wherein the determining normal distribution data of the product and normal distribution data of the measurement system based on the product statistics, the parameter limits, and the measurement statistics of the measurement system comprises: determining normal distribution data of a product based on the product process mean value and the product process standard deviation; Determining a product process risk interval from normal distribution data of a product based on the parameter limit value and a measurement standard deviation of a measurement system; determining a measurement mean value of a measurement system based on subintervals in the product process risk interval; and determining normal distribution data of the measurement system based on the measurement mean value of the measurement system and the measurement standard deviation of the measurement system.
  4. 4. A method according to claim 3, wherein said determining a measurement mean of a measurement system based on said product process risk interval comprises: and determining the average value of the interval limit values of the neutron intervals in the product process risk interval as the measurement average value of the measurement system.
  5. 5. The method according to claim 3 or 4, wherein said determining said production risk probability based on normal distribution data of the product comprises: And obtaining the interval probability of the product process risk interval based on a probability density function corresponding to the normal distribution data of the product, and taking the interval probability as the production risk probability.
  6. 6. The method according to any one of claims 2-5, wherein said determining said measurement risk probability based on normal distribution data of a measurement system comprises: Determining a measurement risk interval from normal distribution data of a measurement system based on the parameter limit value; And obtaining the interval probability of the measurement risk interval based on a probability density function corresponding to normal distribution data of the measurement system, and taking the interval probability as the measurement risk probability.
  7. 7. The method according to any one of claims 3-5, wherein the obtaining an index value corresponding to a product evaluation index based on the production risk probability and the measurement risk probability includes: And obtaining an index value corresponding to the product evaluation index based on the product of the production risk probability and the measurement risk probability.
  8. 8. The method of claim 7, wherein the product process risk interval is divided into a plurality of sub-intervals, the production risk probability comprises a plurality of first sub-probabilities corresponding to the plurality of sub-intervals, the measurement risk probability comprises a plurality of second sub-probabilities corresponding to the plurality of sub-intervals, and the obtaining the index value corresponding to the product evaluation index based on the product of the production risk probability and the measurement risk probability comprises: Multiplying the first sub-probability and the second sub-probability corresponding to each sub-interval to obtain index values corresponding to the product evaluation indexes of each sub-interval, and adding the index values corresponding to the product evaluation indexes of the plurality of sub-intervals.
  9. 9. The method of any one of claims 1-8, wherein the product assessment indicator comprises at least one of: the missing killing index indicates that the production parameter of the product exceeds the parameter limit value, but the measurement result of the measurement system on the product is qualified probability; and the overstock index, wherein the overstock rate corresponding to the overstock index indicates that the production parameter of the product does not exceed the parameter limit value, but the measurement system measures the product with the unqualified result.
  10. 10. The method of any of claims 3-5, wherein the parameter limit comprises at least one of a lower product tolerance limit and an upper product tolerance limit, and wherein the product process risk interval comprises at least one of: a first missing risk interval, which is determined based on the lower limit value of the product tolerance and the standard deviation of the measurement system, wherein the first missing risk interval represents that the production parameter of the product exceeds the lower limit value of the product tolerance; a second missing risk interval, the second missing risk interval being determined based on the product tolerance upper limit and the measurement system standard deviation, the second missing risk interval representing that a production parameter of a product exceeds the product tolerance upper limit; A first overstock risk interval, the first overstock risk interval being determined based on the product tolerance lower limit and the measurement system standard deviation, the first overstock risk interval indicating that a production parameter of a product does not exceed the product tolerance lower limit; and a second overstock risk interval, wherein the second overstock risk interval is determined based on the upper limit value of the product tolerance and the standard deviation of the measurement system, and the second overstock risk interval indicates that the production parameter of the product does not exceed the upper limit value of the product tolerance.
  11. 11. A product assessment device, the device comprising: The acquisition module is used for acquiring the product statistical parameters, the parameter limit values and the measurement statistical parameters of the measurement system, wherein the measurement system is used for carrying out qualified measurement of the product; The determining module is used for determining the production risk probability of the product and the measurement risk probability of the measurement system for measuring the product based on the product statistical parameter, the parameter limit value and the measurement statistical parameter of the measurement system; the obtaining module is used for obtaining an index value corresponding to the product evaluation index based on the production risk probability and the measurement risk probability.
  12. 12. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1-10 when the computer program is executed.
  13. 13. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-10.

Description

Product evaluation method, device, equipment and medium Technical Field The present application relates to the technical field of quality, statistics, and the like, and in particular, to a product evaluation method, apparatus, device, and medium. Background With the development of intelligent manufacturing technology, users have increasingly high requirements on product quality and reliability. The over-killing rate (over-killing rate and over-killing rate) is an important index in the production process, and if the over-killing rate is high, more unqualified products can flow into the market. In the related art, the over-leak rate evaluation is represented by the formula: For the calculation evaluation, in order to evaluate the accuracy of the result, the grade of defective products (DEFECT PART PER million, DPPM) is usually required to be reached, or even the grade of defective products (DEFECT PART PER bililion, DPPB) is required to be reached, the required sample size is very huge, and the sample size is basically difficult to directly calculate through a formula, so that the evaluation result of the product is difficult to meet the accuracy requirement, the quality of the product cannot be guaranteed, and the capability of an analysis process (production process) is not facilitated. Disclosure of Invention In view of the above problems, the present application provides a method, an apparatus, a device and a medium for evaluating a product, which can directly calculate the missing killing rate of the process, facilitate the analysis of the process capability, improve the evaluation accuracy of the product, and improve the quality of the product. The application provides a product evaluation method, which comprises the steps of obtaining product statistical parameters, parameter limit values and measurement statistical parameters of a measurement system, wherein the measurement system is used for carrying out qualified measurement of products, determining production risk probability of the products and measurement risk probability of the measurement system for measuring the products based on the product statistical parameters, the parameter limit values and the measurement statistical parameters of the measurement system, and obtaining index values corresponding to product evaluation indexes based on the production risk probability and the measurement risk probability. In the technical scheme of the embodiment of the application, various data such as product statistical parameters, parameter limit values and statistical parameters of a measuring system are comprehensively considered to determine the production risk probability of the product and the measurement risk probability of the measuring system for measuring the product, so that the production process capability can be accurately estimated, the overlooking rate can be calculated more conveniently, the estimation mode does not need huge sample number, the estimation speed is higher, and the accuracy is higher. In some embodiments, determining the production risk probability of the product and the measurement risk probability of the measurement system for measuring the product based on the product statistics parameters, the parameter limits, and the measurement statistics parameters of the measurement system includes determining normal distribution data of the product and normal distribution data of the measurement system based on the product statistics parameters, the parameter limits, and the measurement statistics parameters of the measurement system, determining the production risk probability based on the normal distribution data of the product, and determining the measurement risk probability based on the normal distribution data of the measurement system. According to the technical scheme, the production risk probability and the measurement risk probability are calculated based on the normal distribution data of the product and the normal distribution data of the measurement system respectively, and the normal distribution-based mode enables the calculation of the overlooking rate to be more convenient, the normal distribution mode can achieve higher accuracy by only needing less data quantity, and even only needing more than ten samples and tens of samples. In some embodiments, the product statistics parameters include a product process mean value and a product process standard deviation, the measurement statistics parameters of the measurement system include a measurement standard deviation of the measurement system, determining normal distribution data of the product and normal distribution data of the measurement system based on the product statistics parameters, parameter limits and the measurement statistics parameters of the measurement system includes determining normal distribution data of the product based on the product process mean value and the product process standard deviation, determining a product process risk interval from t