## What is SPC (Statistical Process Control)?

→ SPC (Statistical Process Control) is a method for Quality control by measuring and monitoring the manufacturing process.
→ In this methodology, data is collected in the form of Attribute and Variable.
→ Also, we have to collect readings from the various machines and various product dimensions as per requirement.
→ This data is used for monitoring and controlling the process.
→ It is a tool to improve the Quality of the Product by reducing variation
→ SPC manual is published by the Automotive Industry Action Group (AIAG) which is used by almost all automotive industries for reference.
→ As per Dr. Shewart two sources of variation, (1) Chance variation and (2) Assignable variation or uncontrolled variation.
→ Then Dr. Deming gave a new name to (1) chance variation as Common Cause variation, and (2) assignable variation as Special Cause variation.

### History of SPC:

→ William A. Shewhart developed the control chart and the concept that a process could be in statistical control in 1924 at Bell Laboratories.
→ The SPC was made very famous during World War II and it was very much used by the military.
→ “Statistical Method from the Viewpoint of Quality Control” is a very famous book by William A. Shewhart.
→ After that Japanese manufacturing companies picked up the SPC and they are using it nowadays also.

### Meaning of SPC:

→ It is made from three different words,
1. Statistical
2. Process
3. Control

#### [1] Statistical:

→ The statistical tool used to make a prediction of the operation.
→ Statistics is a science which deals with, a collection, summarization, analysis, and drawing information from the data.
→ There are many and simple methods available for data analysis if these are applied correctly then that can lead to the prediction of the process with a high degree of accuracy.

#### [2] Process:

→ It converts input resources into desired output products & services.
→ It involves a man (People), Machine/Tool, Material, Method, Environment and Management working together to produce desired output (End Product)

#### [3] Control:

→ Controlling process and comparing actual performance against set target then identifying when and what corrective actions are necessary to achieve the target.

### Why we Use SPC?

→ Manufacturing companies today are facing ever-increasing competition.
→ At the same time, raw material costs and processing continue to increase.
→ So, for the industries, it is beneficial if they have good control over their operation.
→ Companies must make an effort for Continuous Improvement in quality, efficiency and cost reduction.
→ Many companies still follow inspection after production for detecting quality-related issues.
→ SPC helps the company to move towards prevention-based quality controls instead of detection based quality controls.
→ By monitoring the graph, we can easily predict the behavior of the process.
→ We can get Good Quality of Product
→ And we can smooth our production and prevent non-conforming output.

### Where to use SPC?

→ It would be most beneficial to apply this tool to that area where unnecessary waste is generated.
→ Some of the examples of manufacturing waste are... rework, scrap and re-inspection time.
→ We can implement SPC for the critical characteristics of the design or operation.
→ Cross-Functional Team (CFT) identifies critical characteristics
→ Critical characteristics are mentioned in DFMEA or in PFMEA.

### Collecting and Recording Data for SPC

→ Data is collected in the form of measurements of a product dimension or product feature.
→ Based on data (Variable or Attribute), it recorded and tracked on various types of graphs.
→ It is important that the correct type of chart is used to gain value and obtain useful information.
→ It can be collected in subgroups or as an individual.

### Selection of Control Chart:

→ The charts are selected based on different two factors
⇢ (1) the data is attribute or variable?
⇢ (2) subgroup size.
→ The X-bar and R chart is one of the most widely used charts for variable type.
→ X-bar represents the average value of the variable x.
→ The X-bar chart displays the variations in the sample averages.
→ A Range chart shows the variations within the subgroup.
→ The difference between the highest and lowest value is called Range.
ðŸ‘‰ Read this article for making an X-bar and R chart in Simple 8 Steps.
→ The chart selection diagram is mentioned in the below picture.

#### [1] Chart related to a variable type

→ The below I-MR, X-bar - R, and X-bar - S charts are related to variable type.
→ I-MR (Individual – Moving Range): used if your data is individual values
→ Xbar – R: used for recording data in subgroups of 9 or less
→ Xbar – S: used for sub-group size is greater than 8

#### [2] Chart related to attribute type

→ The below P, nP, U, and C charts are related to attribute type.
→ P – used for recording the number of defective parts in different subgroup size
→ nP – the number of defective parts in equal subgroup size
→ U – used for the number of defects in different subgroup size
→ C – the number of defects in equal subgroup size

### Analyzing the Data in SPC:

→ If we can see all data points between UCL and LCL then the only common cause is present in the operation.
→ If we can see any points beyond the control limit then the special cause is available in the operation.
→ All points should fall between the UCL & LCL in the graph.
→ Another name of Special cause is an outlier.
→ If there should be no special cause in the chart then we can say that the process is in statistical control and all point should fall between the UCL and LCL.

#### Examples of common cause variation:

→ Wear and tear of machine and tool
→ Variations in properties of the material within specification
→ Seasonal changes in ambient temperature or humidity
→ Variability in operator-controlled settings
→ Normal measurement variations

#### Examples of special cause variation:

→ Special causes generally fall outside of the UCL or LCL.
→ Failed controllers
→ Improper equipment adjustments
→ A change in the measurement system
→ A mean specification shift
→ Machine malfunction
→ Product specifications do not match with the design specifications
→ Punch, drill, cutting tool or any instrument broken.
→ Inexperienced operator not familiar with the operation

#### Instruction During SPC Study

→ When monitoring a process through charts, the inspector should verify that all points should fall between UCL and LCL.
→ If any special causes of variation are identified, then necessary action should be taken to determine the cause and implement corrective actions.
→ Thus the ongoing production can be controlled by implementing the corrective action.
→ Monitor 8 Different Chart Pattern for Special Cause available.

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