Forthcoming and Online First Articles

International Journal of Six Sigma and Competitive Advantage

International Journal of Six Sigma and Competitive Advantage (IJSSCA)

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International Journal of Six Sigma and Competitive Advantage (4 papers in press)

Regular Issues

  • DMAIC approach to using confidence intervals to assess conformance and reduce variation in net weight for a manufactured product: a case study   Order a copy of this article
    by Kesiena Ezewu, Stephen O. Emumena, Monday E. Amagre 
    Abstract: Markets have become global, and economic conditions are becoming more competitive. To ensure products meet international standards, manufacturers must begin to key into the average quantity system for products released into the market. This paper demonstrates the applicability of deploying confidence intervals within a DMAIC structure to assess conformance in the net weight of a manufactured product. We applied the I-MR chart to investigate stability in the manufacturing process and used the Ishikawa fishbone diagram to improve consistency in net weight, reducing the variability from a standard deviation of 1.5 to 0.39. The percentage out of specification improved from 76.6% to 0.02%. The process capability indices Cp and Cpk improved from 0.2 to 1.32 and -0.21 to 1.25, respectively. Finally, a 97.5% confidence interval affirmed the suitability of lots for the international market in view of AQS standards as demanded by the government and international regulatory agencies.
    Keywords: DMAIC; product net weight; Six Sigma; confidence intervals; process capability.
    DOI: 10.1504/IJSSCA.2023.10059457
     
  • Five whys: a possible path to failure   Order a copy of this article
    by Matthew Barsalou, Beata Starzyńska, Maria Konrad 
    Abstract: This paper investigates the use of five whys in industry. Literature was first reviewed and categorised as describing five whys as a simplified method for asking why without an empirical aspect, empirical when the author or authors clearly indicated that actual investigation was needed, and ambiguous when it is not clear how five whys should be used. A survey was then sent to organisations to assess how five whys is actually used in industry. Authors need to be much clearer when describing five whys. Over half of the literature assessed indicated that five whys is a simplified brainstorming tool, 30.0% of authors were not clear on how five whys should be used, and only 16.7% clearly indicated that investigation and empirical methods are required when using five whys. The results of the survey were more not much more positive, with 41.8% of respondents using five whys as a purely brainstorming tool. Five whys can be applied when investigating problems such as safety incidents and quality failures; however, it is essential to answer each why with an investigation and not just brainstorming.
    Keywords: five whys; problem solving; failure investigation.
    DOI: 10.1504/IJSSCA.2023.10059758
     
  • Integrating DEA, balanced scorecard, and Lean Six Sigma in a total quality model for strategic planning and improving organisation performance: a case study   Order a copy of this article
    by Stelios K. Georganzinos, Evangelia Sakellariou, Alexandra Tseni, Ioannis Giannikos 
    Abstract: This work presents a model of total quality management in which the data envelopment analysis (DEA), balanced scorecard and Lean Six Sigma are combined and are implemented for the improvement of a specific organisation. The general objective of the present study is to provide a framework for improving the industry performance, finding the appropriate strategic directions, providing services at the highest quality level and, of course, and achieving customer satisfaction. The required data and the implementation belong to a modern pharmaceutical industry. The customer service process was chosen as an example of the application of the methodology. Combining balanced scorecard, DEA, and quality principles, the process of response to customer quality complaints is considered as a strategic customer service process. Then, the five phases of Lean Six Sigma are applied to measure and improve the level of process efficiency, in terms of customer satisfaction. The one-sample t-test method is employed to test the hypotheses, ultimately revealing that the model effectively contributes to achieving the outlined objectives. The findings highlight the benefits of implementing an integrated approach, providing valuable insights for organisations aiming to improve their overall strategy and performance while simultaneously increasing customer satisfaction.
    Keywords: total quality management; TQM; data envelopment analysis; DEA; balanced scorecard; BSC; Lean Six Sigma; LSS; strategy; performance improvement; customer satisfaction.
    DOI: 10.1504/IJSSCA.2023.10060955
     
  • A DMAIC framework to improve tumbler index of iron ore sinter at JSW Steel Dolvi a case study   Order a copy of this article
    by Dharmendra Kumar Rajak, Mrigandra Singhai, Dharmendra Patel, M. Vijayakumar, K.Y. Pamali, Amit Bairagi, R.K. Sinha, Sujoy S. Hazra 
    Abstract: In the sintering process, the tumbler index is one of the most important quality parameters which determine the sinters disintegration during the transit. Several attempts have been made to predict and improve the tumbler index of sinter; however, the selection of appropriate variables is a challenging task as the sintering process involves multiple variables. Therefore, in this paper DMAIC framework of Six Sigma has been illustrated through a case study to improve the tumbler index of the sinter. The case study prioritises sinter basicity, sinter machine speed, coke oven gas flow rate and wind box suction pressures as significant causes impacting the tumbler index of the sinter. Implementation of one of the four solutions shows improvement in the tumbler index from 73.5% to 74.7% accruing a reduction in internal fine generation by 1.6% with an annual increase in available sinter by 37,184 tones and saving of 0.3 million USD.
    Keywords: sinter; tumbler index; Six Sigma; DMAIC.
    DOI: 10.1504/IJSSCA.2023.10061660