Six Sigma is a data-driven leadership approach using specific tools and methodologies that lead to fact-based decision making. This paper deals with the application of the Six Sigma methodology in reducing defects in a fine grinding process of an automotive company in India. The DMAIC (Define–Measure–Analyse–Improve–Control) approach has been followed here to solve the underlying problem of reducing process variation and improving the process yield. This paper explores how a manufacturing process can use a systematic methodology to move towards world-class quality level. The application of the Six Sigma methodology resulted in reduction of defects in the fine grinding process from 16.6 to 1.19%. The DMAIC methodology has had a significant financial impact on the profitability of the company in terms of reduction in scrap cost, man-hour saving on rework and increased output. A saving of approximately US$2.4 million per annum was reported from this project

Six Sigma as a powerful business strategy has been around for almost a decade and has grown exponentially in healthcare industry during the past five years. During the last five years or so, many leading healthcare institutions have implemented Lean and Six Sigma methodologies with remarkable results in terms of reducing ER cycle time, increasing timely completion of medical records, increasing bed availability, improving patient flow, enhancing patient safety, increasing capacity of the theatres, reducing medication errors and so on and so forth. The purpose of this paper is to reduce patient waiting time in a pathology department of a super-specialty hospital attached to a manufacturing company. The average waiting time for patients was estimated to be around 24 minutes with a standard deviation of 17.5 minutes. This was not acceptable in the eyes of patients, and hence, it was highly desirable to understand the reasons for excessive waiting times as well as the root causes of variation in the waiting times. The Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) methodology was adopted for reducing the average waiting time and variation in waiting times. During the execution of this case study, a number of non-value added activities were identified within the process and actions were initiated to systematically eliminate different forms of waste using the principles of Lean thinking. Cause-and-effect analysis was carried out to identify the potential causes for unacceptable waiting times and data were collected to validate these causes. The tools such as hypothesis test, box plot, dot plot etc. were used to analyse the data through Minitab statistical software and conclusions were made. As a result of this project, the average waiting time reduced from 24 minutes to 11 minutes (i.e. over 50 per cent reduction), the standard deviation reduced from 17.5 minutes to 10.04 minutes(over 40 per cent reduction). This paper highlights the use of data driven and scientific problem solving methodology such as Six Sigma with the involvement of hospital staff members like nurses, clinicians and technicians. The results of the case study have provided greater stimulus among the senior management team for deploying the use of DMAIC methodology for tackling process and patient care related problems in the hospital

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In the present paper the distribution theory of concomitants of order statistics from the Morgenstern family of distribution is investigated. An application of the results in providing some quick estimates of the parameters in the Gumbel's bivariate exponential distribution is also discussed.