A.Saravanan , Dr. V.Alamelumangai
The Quality has evolved through a number of stages such as inspection, quality control, quality assurance, and total quality control and the results produced by the above stages are used to control and improve the manufacturing process. Statistical process control (SPC) is a powerful collection of problem solving tools useful in achieving process stability and improving capability through the reduction of variability.SPC can be applied to any process. A control chart is a statistical tool used to distinguish between variations in a process resulting from common causes and variation resulting from special causes. One of the basic control charts is p -chart. For the quality related characteristics such as characteristics for appearance, softness, color, taste, etc., attribute control charts such as p-chart, c -chart are used to monitor the production process. The p -chart is used to monitor the process based upon the fraction In classical p -charts, each item classifies as either "nonconforming" or "conforming" to the specification with respect to the quality characteristic. Another attribute chart is CUSUM (cumulative sum) chart which can be used during smaller shifts occur. For many problems control limits could not be so precise .uncertainty comes from the measurement system including operators, environmental conditions etc .In this situation fuzzy set theory is a useful tool to handle this uncertainty Fuzzy control limits provide a more accurate and flexible evaluation. In this paper the attributes charts like p- chart and CUSUM chart and also fuzzy α cut control chart for standard deviation are constructed for the variable data to improve the process
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