No abstract

Purpose The purpose of this paper is to investigate the possibility of including the cost consequence of failure in the a priori risk assessment methodology known as failure mode and effect analysis (FMEA). Design/methodology/approach A model of the standard costs that are incurred when an electronic control module in an automotive application fails in service was developed. These costs were related to the Design FMEA ranking of the level of severity of the failure mode and the probability of its occurrence. Monte Carlo simulations were conducted to establish the average costs expected for each level of severity at each level of occurrence. The results were aggregated using fuzzy utility sets into a nine-point ordinal scale of cost consequence. The criterion validity of this scale was assessed with warranty cost data derived from a case study. Findings It was found that the model slightly underestimated the warranty costs that accrued, but the fit could be improved with adjustments dictated by actual usage conditions. Research limitations/implications Cost data used in the simulations were derived from government and academic surveys, analyses, and estimates of the manufacturing cost structure; and nominal costs for various quality issues experienced by Tier 2 automotive electronics supplier. Specificity is lacking. The sample size and the type of the failure modes used to validate the model are constrained by the number and type of products which have had demonstrable performance concerns over the past three years, with cost data available to the authors. The power of the validation is limited. The validation is considered a screening assessment. Practical implications This work relates the characterization of risk with its potential cost and develops a scaling instrument to allow the incorporation of cost consequence into an FMEA. Originality/value A ranking scale was developed that related severity and occurrence rank scores to a cost consequence rank that keys to a cost of quality figure (given as percent of sales) that would accompany a realization of the failure mode.

TThe Malcolm Baldrige National Quality Award is the nation's highest quality award. The application and review process is outlined in this work. The objective of this study was to examine the five previous winners in the Manufacturing category and to establish a firm conclusion about the award's impact. The impact of the award was examined in several categories including financial performance, market share, and employee productivity. This study explored the accomplishments of each company and compared the common factors they shared with one another. It was found that all five companies experienced tremendous financial growth on average of 100% in either sales or revenue as a result of their dedication to quality which ultimately led to winning the MBNQA.

No abstract

Lean Six Sigma is a hybrid continuous improvement methodology that has various definitions, from those that are Lean dominant to those that are Six Sigma dominant. Text mining and cluster analysis based research has helped to illuminate the degree to which Lean Six Sigma models, as described in articles published in the International Journal of Lean Six Sigma, are Lean dominant versus Six Sigma dominant. The iterative cluster analysis was used to identify clusters of articles that were interpretable. The research found that some Lean dominant Lean Six Sigma articles ascertain Lean as the dominant philosophy and Six Sigma as a subordinate tool used in achieving the Lean objectives. The findings of this research as well extrapolation of the literature informed a recommended Lean Six Sigma model as described in this article. The recommended model is Lean dominant and consists of two subordinate methods-Six Sigma and statistical process control. The three synergistic approaches not only each serve in their own way to manifest process improvements, they also all contribute to organizational learning, which is considered a chief contributor to competitive advantage.