Process control method based on key characteristics of short-term product

Abstract

The invention discloses a process control method based on key characteristics of a short-term product, and the method comprises the following steps: S1, carrying out the collection of sample data in a trial production process, and obtaining a plurality of groups of sample data; s2, calculating an average value # imgabs0 # range R and a range average value # imgabs1 # of each group of samples, and then calculating an initial process capability index Ppk; s3, confirming that the initial process capability index Ppk is greater than or equal to a set threshold value, and calculating a control chart control limit and an intra-group range early warning limit; s4, judging whether the production process is in a stable controlled state or not; and S5, solidifying the control limit value of the control chart for analysis as the control limit of the control chart for control, sampling according to a mass production sampling rule, calculating a mass production process capability index Cpk, and entering daily mass production control. According to the method, each sample in the subgroup can be controlled, the dispersion variation in the group and the distribution difference between the groups can be quickly and visually identified, the deviation degree of the actual machining center can be clearly obtained, and a supporting basis is provided for deviation correction and process capability improvement in the manufacturing process.

Description

Technical Field

[0001] The present invention relates to the field of production control, and in particular to a process control method based on key characteristics of short-term products. Background Art

[0002] At present, if the key quality characteristic values ​​of the processing process of short-term products are only controlled by using the quality tool SPC measurement control chart (such as mean-range chart) in a rigid manner, the control chart is not intuitive. For example, the quality tool SPC can monitor whether the mean of each group of samples meets the control limit range and is under control in the mean chart, but it cannot monitor whether each sample value in each group meets the control limit range, and there is a certain probability of missing the detection of over-limit samples. The quality tool SPC range chart can obtain the specific values ​​of each group of ranges, but it cannot intuitively observe the size of the interval of each group of range distribution and the degree of deviation from the central value. Therefore, it cannot effectively guide the continuous improvement of the process capability of products with short production cycles (such as only half a year of life) and a large number of processing batches in a short period of time. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a process control method based on the key characteristics of short-term products. It is possible to establish a control method suitable for the key quality characteristic values ​​of the short-term product processing process, to control each sample in the subgroup, and to quickly and intuitively identify the dispersion variation within the group and the distribution difference between groups, to clearly know the degree of deviation of the actual processing center, and to provide a supporting basis for manufacturing process correction and process capability improvement.

[0004] The object of the present invention is achieved through the following technical solution: A process control method based on key characteristics of short-term production products, comprising the following steps:

[0005] A process control method based on key characteristics of short-term products, characterized by comprising the following steps:

[0006] S1. When it is confirmed that the key process is operated in accordance with the standard, the trial production process is first entered, and sample data of key quality characteristics are collected during the trial production process. Multiple groups of samples are obtained for each key quality characteristic;

[0007] S2. For each critical quality characteristic, calculate the average value of each group of samples Range R and Range Mean Then calculate the initial process capability index Ppk;

[0008] S3. For each key quality characteristic, determine whether the production process can stably produce products that meet the specification requirements, that is, determine whether the following conditions are met: the initial process capability index Ppk ≥ the set threshold; the set threshold is 1.33, and for automotive parts it is 1.67;

[0009] If not, return to step S1;

[0010] If yes, fill multiple groups of sample data into the analysis control chart, calculate and obtain the control limit and the intra-group range warning limit of the analysis control chart;

[0011] S4. Determine whether the production process is in a stable and controlled state based on the analysis and drawing, that is, whether there are four process abnormality patterns; if any process abnormality pattern appears, the process is considered unstable;

[0012] S5. Fix the control limit values ​​of the analytical control chart as the control limit of the control chart. After the first piece of each batch of products passes the inspection during mass production, continuously extract samples of sample size n at fixed time intervals, fill the test values ​​into the control chart, and automatically calculate the average value. Range R and Range Mean At the same time, the mass production process capability index Cpk is calculated and mass production control is entered.

[0013] The beneficial effects of the present invention are as follows: the present invention can establish a control method suitable for key quality characteristic values ​​of short-term production process, and its control chart can realize the control of each sample in the subgroup, as well as quickly and intuitively identify the dispersion variation within the group and the distribution difference between groups, clearly know the process center shift and dispersion variation, and provide a supporting basis for manufacturing process correction and process capability improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flow chart of the method of the present invention;

[0015] Figure 2 is a schematic diagram of mode 1;

[0016] Figure 3 is a schematic diagram of mode 2;

[0017] Figure 4 is a schematic diagram of mode 3;

[0018] Figure 5 This is a schematic diagram of Mode 4. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0020] The present invention proposes a process control method (including: control chart and management rules) based on the key characteristics of short-term products to reduce the risk of missed detection and reduce production costs. The control rules are as follows: use the mean ± 3σ as the control limit of the control chart, use the mean ± (range control limit / 2) as the range warning limit of the control chart, and control each sample in the subgroup so that it can intuitively observe the distribution range of each group of samples to ensure that the production process fully meets the quality requirements. At the same time, it is also possible to understand the distribution differences between groups, clearly know the degree of deviation of the actual machining center, and provide support for manufacturing process correction and process capability improvement.

[0021] like Figure 1 As shown, a process control method based on key characteristics of short-term products includes the following steps:

[0022] S1. When it is confirmed that the key process is operated in accordance with the standard, the trial production process is first entered, and sample data of key quality characteristics are collected during the trial production process. Multiple groups of samples are obtained for each key quality characteristic;

[0023] The key quality characteristics of step S1 include one or more of product size, coating thickness, function / performance test value, and unilateral tolerance;

[0024] The trial production data is used as the data of the control chart for analysis, and its purpose is to confirm whether the trial production process is in a stable and controlled state. When confirming that the key process is in accordance with the standardized operation, for each key quality characteristic, the quality analyst randomly samples a sample of n=5 from the finished products in the production process every 4-8 hours, and a total of 30 groups of samples are drawn, with a total of 150 values, which are filled in the data table (control chart for analysis).

[0025] S2. For each critical quality characteristic, calculate the average value of each group of samples Range R and Range Mean Then calculate the initial process capability index Ppk;

[0026]

[0027] R = x max -x min

[0028]

[0029] Calculate the initial process capability index Ppk

[0030] After the quality personnel confirm that the collected data meets the normal distribution, the initial process capability index Ppk is calculated using the following Ppk calculation formula.

[0031]

[0032] σ=STDEV(x 1 ,x 2 …x 150 )

[0033] Among them, USL is the upper tolerance limit of the key quality characteristic, LSL is the lower tolerance limit of the key quality characteristic, and STDEV is the standard deviation of the n*m ​​sample measurements of the key quality characteristic.

[0034] S3. For each key quality characteristic, determine whether the initial process capability of production meets the quality requirements, that is, the initial process capability index Ppk ≥ 1.33 or the automotive parts Ppk ≥ 1.67. If so, calculate the control limits of the control chart and the intra-group range warning limits; if not, return to step S1.

[0035] The mean of 30 samples is the center line of the control chart, is the upper control limit of the control chart, is the lower control limit of the control chart.

[0036] Control Chart Center Line

[0037] Upper control limit on control chart

[0038] Lower control limit of control chart

[0039] Calculate the upper and lower limits of the extreme difference warning as follows:

[0040] Extremely bad warning upper limit

[0041] Extreme warning lower limit

[0042] in, is the subgroup mean, D 4 is a constant of 2.110, is the two-sided range control limit, is the one-sided range control limit.

[0043] S4. Determine whether the production process is in a stable and controlled state:

[0044] If yes, go to step S5;

[0045] If not, return to step S1;

[0046] For each key quality characteristic, if none of the four process abnormality modes occurs, it is considered that the production process is in a stable and controlled state, and the process goes to step S5;

[0047] If any process abnormality mode appears in any key quality characteristic, it is considered that the process is not in a stable controlled state, and the process returns to step S1;

[0048] Each group of samples in the m groups of samples is regarded as a subgroup, and the four process difference judgment modes include:

[0049] Mode 1: The maximum or minimum point in the subgroup falls outside the USL / LSL specification limit, such as Figure 2 As shown in the figure, each diamond point represents the subgroup mean, x max refers to the maximum value of the subgroup, x min refers to the minimum value of the subgroup;

[0050] Mode 2: Any point in the subgroup exceeds the extreme warning limit (UCL R / LCL R ),like Figure 3 As shown, when any point in the subgroup exceeds the extreme warning limit UCL R , LCL R When the corresponding extreme warning limit is displayed;

[0051] Mode 3: Any point in the subgroup falls within the control limit (UCL) of the control chart x / LCL x ) Figure 4 As shown;

[0052] Mode 4: The subgroup mean rises / falls for 3 consecutive points, such as Figure 5 shown.

[0053] S5. Solidify the control limit values ​​of the analysis control chart as the control limits of the control chart, take samples according to the mass production sampling requirements, calculate the mass production process capability index Cpk, and enter mass production control.

[0054] After the quality personnel have inspected the first piece of each batch of products and found them to be qualified, they will perform the following process for each key quality characteristic:

[0055] Continuously draw samples of n=5 every 4-8 hours, fill the test values ​​into the control chart, and automatically calculate the average value Range R and Range Mean Then calculate the mass production process capability Cpk.

[0056]

[0057] If Cpk meets the quality requirements, that is, Cpk ≥ 1.33 or Cpk ≥ 1.67 for automotive parts, and none of the above four process abnormality modes occurs, the production process is considered to be in a stable and controlled state and production continues.

[0058] When the arrangement of points on the control chart is abnormal (one of the four process abnormality judgment modes mentioned above), the quality engineer should promptly work with relevant departments to find the cause and take necessary corrective and preventive measures.

[0059] In an embodiment of the present application, an analytical control chart is established in the trial production stage. The sample test values ​​in the trial production stage are first entered, and the analytical control chart of the characteristic is established based on the test result values ​​of the sample. Then, the control limit values ​​of the analytical control chart are solidified as the control limits of the control control chart, and the mass production process capability index Cpk is calculated at the same time, and the conformity of the test results of the mass production sampling samples is evaluated one by one.

[0060] In the embodiment of the present application, an online process control method can also be imported, the above control rules can be imported into the quality module of the online system, an online SPC control chart can be presented, and online SPC abnormality warning and alarm can be performed:

[0061] When a discrepancy occurs in process control, the online system will push early warning and alarm information;

[0062] Relevant parties receive information and process it online in a timely manner;

[0063] If the information push is not processed within the processing time limit, the system will continue to push warnings or alarm reminders until it is completed.

[0064] The above description shows and describes a preferred embodiment of the present invention, but as mentioned above, it should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the invention concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not depart from the spirit and scope of the present invention, and should be within the scope of protection of the claims attached to the present invention.

Claims

1. A process control method based on key characteristics of short-term products, characterized by: The following steps are involved: S1. When it is confirmed that the key process is operated in accordance with the standard, the trial production process is first entered, and sample data of key quality characteristics are collected during the trial production process. Multiple groups of samples are obtained for each key quality characteristic; S2. For each critical quality characteristic, calculate the average value of each group of samples Range R and Range Mean Then calculate the initial process capability index Ppk; S3. For each key quality characteristic, determine whether the production process can stably produce products that meet the specification requirements, that is, determine whether the initial process capability index Ppk ≥ the set threshold; If not, return to step S1; If yes, fill multiple groups of sample data into the analysis control chart, calculate and obtain the control limit and the intra-group range warning limit of the analysis control chart; S4. Determine whether the production process is in a stable and controlled state based on the analysis and drawing, that is, whether there are four process abnormality patterns; if any process abnormality pattern appears, the process is considered unstable; S5. Fix the control limit values ​​of the analytical control chart as the control limit of the control chart. After the first piece of each batch of products passes the inspection during mass production, continuously extract samples of sample size n at fixed time intervals, fill the test values ​​into the control chart, and automatically calculate the average value. Range R and Range Mean At the same time, the mass production process capability index Cpk is calculated and mass production control is entered.

2. A process control method based on short-term product key characteristics according to claim 1, characterized in that: The key quality characteristics of step S1 include one or more of product size, coating thickness, function / performance test value, and unilateral tolerance.

3. A process control method based on short-term product key characteristics according to claim 2, characterized in that: The step S1 comprises: When it is confirmed that the key processes are carried out according to standardized operations, the trial production process is first entered. For each key quality characteristic, samples of a capacity of n are randomly sampled from the finished products at fixed time intervals. A total of m groups are drawn to obtain m*n values, which are filled in the data table for storage.

4. The process control method based on short-term product key characteristics according to claim 1 is characterized by: The step S2 comprises: S201. For any key quality characteristic: calculate the average value of each group of samples Range R: R=x max -x min Among them, x max refers to the maximum value in the group of samples, x min It refers to the minimum value in the group of samples; The ranges of the m groups of samples are recorded as R1, R2, ..., R m , then the mean of the range of each group of samples is for: After the quality personnel confirm that the collected data meets the normal distribution, the initial process capability index Ppk is calculated using the following Ppk calculation formula: σ=STDEV(x1,x2…x (n*m) ) in, is the mean of m groups of samples, USL is the upper tolerance limit of a predetermined key quality characteristic, LSL is the lower tolerance limit of a predetermined key quality characteristic, and STDEV is the standard deviation of the n*m ​​sample measurements of the key quality characteristic. S202. For each key quality characteristic, repeat step S201.

5. The process control method based on short-term product key characteristics according to claim 1 is characterized by: The step S3 comprises: S301. For any key quality characteristic, first determine whether the production process can stably produce products that meet the specification requirements, that is, determine whether the initial process capability index Ppk ≥ the set threshold; If yes, proceed to step S302; If not, it is considered that the initial production process capability index is insufficient, and the process returns to step S1; S302. Calculate the control limits of the control chart, including: Control Chart Center Line Upper control limit on control chart Lower control limit of control chart in, is the average value of samples from group 1 to group m; S303. For each group of samples, calculate the intra-group extreme difference warning limit, including: Extremely bad warning upper limit Extreme warning lower limit in, is the sample mean of this group, D4 is a constant of 2.110, is the two-sided range control limit, is the one-sided range control limit; S304. For each key quality characteristic, repeat steps S301 to S303.

6. The process control method based on short-term product key characteristics according to claim 1 is characterized by: In step S4, when judging whether the process is in a stable controlled state: For each key quality characteristic, if none of the four process abnormality modes occurs, it is considered that the production process is in a stable and controlled state, and the process goes to step S5; If any process abnormality mode appears in any key quality characteristic, it is considered that the process is not in a stable controlled state, and the process returns to step S1; Each group of samples in the m groups of samples is regarded as a subgroup, and the four process difference judgment modes include: Mode 1: The maximum or minimum point in the subgroup falls outside the USL / LSL specification limit; Mode 2: Any point in the subgroup exceeds the extreme warning limit UCL R / LCL R ; Mode 3: Any point in the subgroup falls within the control limit UCL of the control chart x / LCL x outside; Pattern 4: Subgroup mean rises / falls 3 points in a row.

7. The process control method based on short-term product key characteristics according to claim 1 is characterized by: The step S5 comprises: After the quality personnel have inspected the first piece of each batch of products and found them to be qualified, they will perform the following process for each key quality characteristic: Continuously extract samples of sample size n at fixed time intervals, fill the test values ​​into the control chart, and automatically calculate the average value Range R and Range Mean And at the same time calculate the mass production process capability index Cpk; Where D2 is a constant of 2.33; If Cpk meets the quality requirements, that is, the process capability index Cpk ≥ the set threshold, and the above four process abnormality modes do not appear, the production process is considered to be in a stable and controlled state, and production continues; When Cpk does not meet the quality requirements or the arrangement of points on the control chart is abnormal, one of the four process abnormality modes occurs. Find the cause immediately and take corrective and preventive measures.

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