2 thoughts on “What does SPC mean? How to operate specific?”
Gabriel
Statistical process control (SPC for short) is a process control tool with the help of mathematical statistical methods. It analyzes and evaluates the production process, discovers the signs of systemic factors in time according to feedback information, and adopts measures to eliminate its impact, so that the process is maintained in the control state that is affected by random factors to achieve the purpose of controlling quality. It believes that when the process is only affected by random factors, the process is statistically controlled (referred to as controlling state); when the system is influenced in the process, the process is statistically out of control (referred to as out of control). Because the process fluctuations are statistically regular, when the process is controlled, the process characteristics generally obey the stable random distribution; and the process distribution will change when they are out of control. The SPC uses the statistical regularity of the process to analyze and control the process. Therefore, it emphasizes that the process is running in a state of controlling and capable, so that products and services can stably meet customer requirements. The process of implementing the SPC is generally divided into two steps: first analyze the process with the SPC tool, such as the control drawing of the analysis and analysis; The intervention to reduce the random fluctuations of the process to meet the needs of the process. The second step is to monitor the process with a control chart. The control chart is the most important tool in SPC. At present, a large number of traditional control charts based on the SHEWHART principle are used, but the control chart is not limited to this. In recent years, some advanced control tools have been gradually developed, such as the EWMA and CUSUM control charts monitored by small fluctuations, and the proportional control diagram and target control chart of small batch multi -variety production processes; Control Charts. SPC originated from the 1920s and was marked by Dr. Shewhart’s invention control map. Since its establishment, it has been promoted and applied in industries and services. Since the 1950s of the 1950s, the large amount of promotion and application of SPC in the Japanese industry has played a vital role in the rise of Japanese products; In the future, many large companies in the world have actively promoted the application of SPCs in their own internal, and also made corresponding requirements for suppliers. In ISO9000 and QS9000, the requirements for applying the SPC method in production control are also proposed.
continuous group data: XBAR-R control diagram and XBAR-S control chart.
continuous single-value data: I-MR control diagram.
The number of non -compatible products that comply with the two distribution: (The capacity of the group sample is equal to the NP control diagram, without waiting for the P control diagram)
Number of defects:: (The capacity of the group sample is equal to the C control diagram, without waiting for the U control diagram) xbar-R control chart
xbar (average control diagram) reflects the variable x over time over time Concentration trends and changes between group samples. Note that each point in the control diagram is the average value of each group, and the central line of the control chart is the average value of the packet. R (Extremely Differential Control Figure) Extremely different control diagram monitoring changes in the internal time of the group sample. The central line of the figure represents the average difference in the long -term packet sample, or R. The R control chart is only suitable for occasions with small sample capacity.
xbar-s control graph
xbar (average control diagram) reflects the variableness between the concentration trend of variable x with the concentration trend and the packet sample. This is the same as XBAR-R control chart. For the S control diagram is the value difference, the standard deviation control diagram monitors the changes in the internal time of the group sample. The central line of the figure represents the average value of the standard deviation of the long -term packet sample. The standard deviation diagram can be applied to any occasion of the group sample capacity (that is, n) greater than 2. (In order to verify whether the process is stable, 10 data values are sampled daily, and a total of 10 days.)
i-mr (Indivials and Moving Range) The single -value data changes over time. The scope of use is small in the process, and only one data can be obtained at each time. The I-MR diagram is more susceptible to interference with the X Bar-R diagram due to individual values. For example, if we want to record whether the time is controlled by the vehicle back and forth, it can record a series of continuous data values for I-MR control graph analysis.
Statistical process control (SPC for short) is a process control tool with the help of mathematical statistical methods. It analyzes and evaluates the production process, discovers the signs of systemic factors in time according to feedback information, and adopts measures to eliminate its impact, so that the process is maintained in the control state that is affected by random factors to achieve the purpose of controlling quality. It believes that when the process is only affected by random factors, the process is statistically controlled (referred to as controlling state); when the system is influenced in the process, the process is statistically out of control (referred to as out of control). Because the process fluctuations are statistically regular, when the process is controlled, the process characteristics generally obey the stable random distribution; and the process distribution will change when they are out of control. The SPC uses the statistical regularity of the process to analyze and control the process. Therefore, it emphasizes that the process is running in a state of controlling and capable, so that products and services can stably meet customer requirements. The process of implementing the SPC is generally divided into two steps: first analyze the process with the SPC tool, such as the control drawing of the analysis and analysis; The intervention to reduce the random fluctuations of the process to meet the needs of the process. The second step is to monitor the process with a control chart. The control chart is the most important tool in SPC. At present, a large number of traditional control charts based on the SHEWHART principle are used, but the control chart is not limited to this. In recent years, some advanced control tools have been gradually developed, such as the EWMA and CUSUM control charts monitored by small fluctuations, and the proportional control diagram and target control chart of small batch multi -variety production processes; Control Charts. SPC originated from the 1920s and was marked by Dr. Shewhart’s invention control map. Since its establishment, it has been promoted and applied in industries and services. Since the 1950s of the 1950s, the large amount of promotion and application of SPC in the Japanese industry has played a vital role in the rise of Japanese products; In the future, many large companies in the world have actively promoted the application of SPCs in their own internal, and also made corresponding requirements for suppliers. In ISO9000 and QS9000, the requirements for applying the SPC method in production control are also proposed.
The use and selection of the control diagram
continuous group data: XBAR-R control diagram and XBAR-S control chart.
continuous single-value data: I-MR control diagram.
The number of non -compatible products that comply with the two distribution: (The capacity of the group sample is equal to the NP control diagram, without waiting for the P control diagram)
Number of defects:: (The capacity of the group sample is equal to the C control diagram, without waiting for the U control diagram)
xbar-R control chart
xbar (average control diagram) reflects the variable x over time over time Concentration trends and changes between group samples. Note that each point in the control diagram is the average value of each group, and the central line of the control chart is the average value of the packet. R (Extremely Differential Control Figure) Extremely different control diagram monitoring changes in the internal time of the group sample. The central line of the figure represents the average difference in the long -term packet sample, or R. The R control chart is only suitable for occasions with small sample capacity.
xbar-s control graph
xbar (average control diagram) reflects the variableness between the concentration trend of variable x with the concentration trend and the packet sample. This is the same as XBAR-R control chart. For the S control diagram is the value difference, the standard deviation control diagram monitors the changes in the internal time of the group sample. The central line of the figure represents the average value of the standard deviation of the long -term packet sample. The standard deviation diagram can be applied to any occasion of the group sample capacity (that is, n) greater than 2. (In order to verify whether the process is stable, 10 data values are sampled daily, and a total of 10 days.)
i-mr (Indivials and Moving Range) The single -value data changes over time. The scope of use is small in the process, and only one data can be obtained at each time. The I-MR diagram is more susceptible to interference with the X Bar-R diagram due to individual values. For example, if we want to record whether the time is controlled by the vehicle back and forth, it can record a series of continuous data values for I-MR control graph analysis.
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