IMPROVED SHEWHART-TYPE X ̅ CONTROL SCHEMES UNDER NON-NORMALITY ASSUMPTION: A MARKOV CHAIN APPROACH

Journal Title: International Journal for Quality Research - Year 2018, Vol 12, Issue 1

Abstract

In statistical process control and monitoring (SPCM), traditional (or classical) X ̅ control schemes are designed under the assumption of normally distributed data. However, in real-life applications, the normality assumption could easily fail to hold, and the results would no longer be realistic. Therefore, X ̅ control schemes designed under flexible probability distributions are needed. In this paper, we consider to improve the Shewhart-type X ̅ control scheme using supplementary 2-of-(h+1) and 1-of-1 or 2-of-(h+1) runs-rules (where h≥ 1) for non-normal data. The proposed control schemes are designed using the Burr type XII probability distribution function (pdf) because of its properties and suitability for general industrial applications. The performance of the proposed control schemes is investigated using the Markov chain approach. It was found that the proposed schemes outperform the existing standard and improved X ̅ control schemes in many cases. An illustrative real-life example is used to demonstrate the implementation of the proposed schemes.

Authors and Affiliations

Jean-Claude Malela-Majika, Busanga Jerome Kanyam, Maria Rapoo

Keywords

Related Articles

THE SELF-ASSESSMENT PROCESS AND IMPACTS ON PERFORMANCE: A CASE STUDY

The purpose of this paper is to analyze the effectiveness of the European Foundation for Quality Management model self-assessment process and its effects on performance in a private manufacturing firm. A case study is us...

PROVIDING A COMPREHENSIVE MODEL TO MEASURE THE PERFORMANCE DIMENSIONS OF INDUSTRIAL CLUSTERS USING THE HYBRID APPROACH OF Q-FACTOR ANALYSIS AND CLUSTER ANALYSIS

One of the most important development strategies with the emphasis on small and medium industries is the geographical concentration of production units and the formation of cluster. The industrial cluster is a globally e...

SIX SIGMA METHODOLOGIES: IMPLEMENTATION AND IMPACTS ON PORTUGUESE SMALL AND MEDIUM COMPANIES (SMES)

Six Sigma is a disciplined approach for dramatically reducing defects and producing measurable financial results (Anand, 2006; Linderman et al., 2003). It should not be a simple statistical tool, but rather a strategic m...

KNOWLEDGE AND LEARNING IN TERMS OF OPERATIONAL RISK MANAGEMENT IN THE FINANCIAL AND BANKING SYSTEMS

This paper is a part of the author`s wider research that examines the impact of operational risks on the functioning of financial organisations, with particular reference to central banks. The research clearly demonstrat...

REALITY AND EXPECTANCIES OF INDEPENDENT ASSESSMENT AND CERTIFICATION OF QUALIFICATIONS THE RESULTS OF MONITORING, AUTUMN 2014

The monitoring of an independent assessment and certification of qualifications held by the Pastukhov Academy in the framework of the project of Federal Service for Supervision in the Sphere of Science and Education (Ros...

Download PDF file
  • EP ID EP266418
  • DOI 10.18421/IJQR12.01-02
  • Views 83
  • Downloads 0

How To Cite

Jean-Claude Malela-Majika, Busanga Jerome Kanyam, Maria Rapoo (2018). IMPROVED SHEWHART-TYPE X ̅ CONTROL SCHEMES UNDER NON-NORMALITY ASSUMPTION: A MARKOV CHAIN APPROACH. International Journal for Quality Research, 12(1), 17-42. https://europub.co.uk./articles/-A-266418