SIX SIGMA-BASED X-BAR CONTROL CHART FOR CONTINUOUS QUALITY IMPROVEMENT
Journal Title: International Journal for Quality Research - Year 2016, Vol 10, Issue 2
Abstract
Introduced by Shewhart, the traditional variable control chart for mean (X-bar Chart) is an effective tool for controlling and monitoring processes. Notwithstanding, the main disadvantage of X-bar chart is that the population standard deviation is unknown though the sample mean is an unbiased estimator of the population mean. There are many approaches to estimating the unknown standard deviation with the expertise available with the researchers and practitioners that may lead to varying conclusions. In this paper, an innovative approach is introduced to estimate the population standard deviation from the perspective of Six Sigma quality for the construction of the proposed control chart for mean called Six Sigma-based X-bar control chart. Under the assumption that the process is normal, in the proposed chart the population mean and standard deviation are drawn from the process specification from the perspective of Six Sigma quality. After discussing the aspects of the traditional X-bar control chart, the procedure for the construction of the proposed new Six Sigma-based X-bar control chart is presented. The new chart is capable of maintaining the process mean close to the target by variance reduction resulting in quality improvement. Also, it may be noted that at a point of time, the process, though under statistical control, may be maintaining a particular sigma quality level only while the goal is Six Sigma quality level of just 3.4 defects per million opportunities. Hence, as a practice of continuous quality improvement, it is suggested to use the proposed control chart every time with improvement till the goal of Six Sigma with 3.4 defects per million opportunities is achieved. An innovative cyclic approach for performing the continuous quality improvement activity is also presented. The construction of the proposed Six Sigma-based X-bar control chart is demonstrated using an illustrative example.
Authors and Affiliations
Joghee Ravichandran
Keywords
Related Articles
- EP ID EP207151
- DOI 10.18421/IJQR10.02-02
- Views 114
- Downloads 0
QUALITY MANAGEMENT OF CLUSTER INSTITUTIONAL DEVELOPMENT: NEW TRENDS AND THE BEST PRACTICES IN REGIONS OF THE WORLD AND RUSSIA
Analysis of the global practice shows versatile innovative tools of the regional cluster institutional development: in the field of functional institutions it's introduction of the cluster ambassador function into its fu...
INTELLIGENT SYSTEMS FOR DECISION-MAKING SUPPORT BASED ON BCM APPROACH
Tis paper represents research of several years which is conducted at the Centre for Quality at The faculty of Mechanical Engineering in Podgorica. The main objective was to obtain performances improvement measures for bu...
INTEGRATED HSEQ MANAGEMENT SYSTEMS: DEVELOPMENTS AND TRENDS
The integration of health and safety, environmental and quality (HSEQ) management systems has become a current topic in the 21st century, as the need for systems thinking has grown along with the number of management sys...
METHODOLOGY FOR REDUCTION OF GHG EMISSIONS FROM MUNICIPAL SOLID WASTE COLLECTION AND TRANSPORT
Collection and transport of municipal solid waste (MSW), as a part of solid waste management, have a great environmental impact due to exhaust emissions from fuel combustion. Distance traveled appears as one of the most...
APPLICATION OF DECISION MAKING WITH UNCERTAINTY TECHNIQUES: A CASE OF PRODUCTION VOLUME OF MAIZE IN ETHIOPIA
Making of an appropriate decision is a challenge that also determines the success of an organization like Adet Agricultural Research Institute. In this agricultural research institute, production volumes of different mai...