Quality Control and Statistical Process Control (SPC)

 

 Introduction:- 

 

Statistical Process Control (SPC) is not new to the industry. In 1924, a man at Bell Laboratories developed the control chart and the concept that a process could be in statistical control. He eventually published a book titled “Statistical Method from the Viewpoint of Quality Control” (1939). The demand for products had forced them to look for a better and more efficient way to monitor product quality without compromising safety. SPC filled that need.      

It was then picked up by the Japanese manufacturing companies where it is still used today.

 

Statistical Process Control (SPC):-

 

SPC is a method of measuring and controlling quality by monitoring the manufacturing process. Quality data is collected in the form of product or process measurements or readings from various machines or instrumentation. The data is collected and used to evaluate, monitor, and control a process. SPC is an effective method to drive continuous improvement. By monitoring and controlling a process, we can assure that it operates at its fullest potential. One of the most comprehensive and valuable resources of information regarding SPC is the manual published by the Automotive Industry Action Group (AIAG).

 

Use Of Statistical Process Control (SPC):-

 

Before implementing SPC or any new quality system, the manufacturing process should be evaluated to determine the main areas of waste. Some examples of manufacturing process waste are reworked, scrap, and excessive inspection time. It would be most beneficial to apply the SPC tools to these areas first. During SPC, not all dimensions are monitored due to the expense, time, and production delays that would incur. Before SPC implementation the key or critical characteristics of the design or process should be identified by a Cross-Functional Team (CFT) during a print review or Design Failure Mode and Effects Analysis (DFMEA) exercise. Data would then be collected and monitored on these key or critical characteristics.

 

 

 Collecting and Recording Data:-

 

SPC data is collected in the form of measurements of a product dimension/feature or process instrumentation readings. The data is then recorded and tracked on various types of control charts, based on the type of data being collected. The correct type of chart must be used to gain value and obtain useful information. The data can be in the form of continuous variable data or attribute data. The data can also be collected and recorded as individual values or an average of a group of readings. Some general guidelines and examples are listed below. This list is not all-inclusive and is supplied only as a reference.

 

 

 

Control Charts:-

 

One of the most widely used control charts for variable data is the X-bar and R charts. X-bar represents the average or “mean” value of the variable x. The X-bar chart displays the variation in the sample means or averages. The Range chart shows the variation within the subgroup. The range is simply the difference between the highest and lowest value.

 

Analyzing the Data

The data points recorded on a control chart should fall between the control limits, provided that only common causes and no special causes have been identified. Common causes will fall between the control limits whereas special causes are generally outliers or are outside of the control limits. For a process to be deemed in statistical control there should be no special causes in any of the charts. A process in control will have no special causes identified in it and the data should fall between the control limits