Control chart for high-quality processes based on Six Sigma quality. Issue 1 (3rd January 2017)

• Record Type: Journal Article
• Authors: Joghee, Ravichandran
• Is Part Of: International journal of quality & reliability management. Volume 34:Issue 1(2017)
• Page Start: 2
• Page End: 17
• Publication Date: 2017-01-03
• Subjects: Statistical process control -- High-quality processes -- Six Sigma quality control chart -- Target range -- Upper and lower quality limits; Quality control -- Periodicals; 658.562
• DOI: 10.1108/IJQRM-05-2015-0080
• Languages: English
• ISSNs: 0265-671X

Abstract

Abstract : Purpose: The purpose of this paper is to develop an innovative and quite new Six Sigma quality control (SSQC) chart for the benefit of Six Sigma practitioners. A step-by-step procedure for the construction of the chart is also given. Design/methodology/approach: Under the assumption of normality, in this paper, the construction of SSQC chart is proposed in which the population mean and standard deviation are drawn from the process specification from the perspective of Six Sigma quality (SSQ). In this chart, the concept of target range is used to restrict the shift in the process within plus or minus 1.5 times of standard deviation. This control chart is useful in monitoring the process to ensure that the process is well maintained within the specification limits with minimum variation (shift). Findings: A step-by-step procedure is given for the construction of the proposed SSQC chart. It can be easily understood and its application is also simple for Six Sigma practitioners. The proposed chart suggests for timely improvements in process mean and variation. The illustrative example shows the improved performance of the proposed new procedure. Research limitations/implications: The proposed approach assumes a normal population described by the known specification of the process/product characteristics though it may not be in all cases. This may call for a thorough study of the population before applying the chart. Practical implications: The proposed SSQC chart is an innovative approach and is quite new for the practitioners. The paper assumes that the population standard deviation is known and is drawn from the specification of the process/product characteristics. The proposed chart helps in fine-tuning the process mean and bringing the process standard deviation to the satisfactory level from the perspective of SSQ. Originality/value: The paper is the first of its kind. It is innovative and quite new to the Six Sigma practitioners who will find its application interesting.