Arup Ranjan Mukhopadhyay

Estimation of Cost of Quality in an Indian Textile Industry for Reducing Cost of Non-conformance

This case study reflects the importance of estimating quality-related costs to diagnose and redress quality-related problem areas. It is only possible to eliminate the costs of non-conformance if they can be identified. In todays business environment of global competition, reduction of the cost of non-conformance strengthens ones competitive position by focusing on customer orientation. Quite naturally, this facilitates survival and further growth of the company. And, of course, reduction of cost of non-conformance is much more preferable to increasing the volume of sales turnover, especially in a competitive market or a recession. The distinguishing feature of this study is the simultaneous increase in sales turnover as well as the reduction in cost of poor quality over a span of three years.

Root cause analysis, Lean Six Sigma and test of hypothesis

Purpose – In implementing Six Sigma and/or Lean Six Sigma, a practitioner often faces a dilemma of how to select the subset of root causes from a superset of all possible potential causes, popularly known as root cause analysis (RCA). Generally one resorts to the cause and effect diagram for this purpose. However, the practice adopted for identification of root causes is in many situations quite arbitrary and lacks a systematic, structured approach based on the rigorous data driven statistical analysis. This paper aims at developing a methodology for validation of potential causes to root causes to aid practitioners.Design/methodology/approach – Discussion has been made on various methods for identification and validation of potential causes to root causes with the help of a few real life examples for effective Lean Six Sigma implementation.Findings – The cause and effect diagram is the frequently adopted method for identifying potential causes out of a host of methods available for such identification. T...

Multivariate attribute control chart using Mahalanobis D2 statistic

Abstract Process control involves repeated hypothesis testing based on several samples. However, process control is not exactly hypothesis testing as such since it deals with detection of non-random patterns of variation as well in a fleeting kind of population. Compare this with hypothesis testing which is principally meant for a stagnant population. Dr Walter A. Shewhart introduced a graphic method for doing this testing in a fleeting population in 1924. This graphic method came to be known as control chart and is widely used throughout the world today for process management purposes. Subsequently there was much advancement in process control techniques. In particular, when more than one variable was involved, process control techniques were developed mainly by Hicks (1955), Jackson (1956 and 1959) and Montgomery and Wadsworth (1972) based on the pioneering work of Hotelling in 1931. Most of them have worked in the area of multivariate variable control chart with the underlying distribution as multivariate normal. When more than one attribute variables are involved some works relating to test of hypothesis was done by Mahalanobis (1946). These works were also based on the Hotelling T2 test. This paper expands the concept of ‘Mahalanobis Distance’ in case of a multinomial distribution and thereby proposes a multivariate attribute control chart.

Reduction of Yarn Packing Defects Using Six Sigma Methods: A Case Study

This article originated when an Indian textile company identified packing rejection of yarn cones as its major quality problem and decided to use Six Sigma methods to correct the problem. At the end of its manufacturing process, yarn is wound into conical-shaped packages called cones, and it is shipped to customers in this format. Customers were rejecting cones due to unacceptable weight variation. Pareto charts revealed the major “counts” (a measure of yarn fineness) that were experiencing this problem. Technological deliberations led to identifying variation in yarn length, yarn count, empty yarn container weight, and moisture content of yarn as the critical parameters for this rejection. Statistical hypothesis testing established that the observed weight was significantly more than the set weight of yarn at the assembly winding stage. In addition, a significant difference in gross yarn weight between left and right sides of a machine was found at this stage. This occured despite the attachment of electronic length measuring devices (LMDs) on all assembly winding machines. The gage capability analysis of LMDs, performed on the yarn length at two assembly winding machines, revealed inadequate capability. In addition, for the polyester yarn of count 4/12s, a relation was found between gross yarn weight and length of yarn through regression analysis. This relationship was used to arrive at the optimum parameter level.

Improvement of service quality by reducing waiting time for service

Abstract One of the major concerns of any service organisation is the time customers have to spend waiting for service. As is well known, waiting time depends on a number of quantities, such as the system arrival rate, service rate, type of services, time of the day, and efficiency of the servers. In this paper, we propose a service model appropriate in the Indian banking industry and discuss the effectiveness of various solutions using simulation. The best solution found from the alternatives has been implemented. In this paper, we summarize the efforts and the results thereof.

Selection of critical processes for “process improvement”

Purpose – The purpose of this paper is to develop a criterion for selection of critical sub‐processes when all the sub‐processes cannot be taken up simultaneously for improvement. There exist various methods but the practitioners get utterly confused because of the existence of these multiple options. In this paper, the goal is to assist practitioners in the selection of the critical sub‐processes.Design/methodology/approach – The authors discuss various statistical methods such as correlation and regression, simulation, basic statistics such as average, standard deviation, coefficient of variation % (C.V.%), etc. for the selection and identification of the critical sub‐processes. The strengths and weaknesses of these methods have been compared through empirical analysis based on real‐life case examples.Findings – The stepwise regression and simulation have been found to yield identical results. However, from the perspective of application, stepwise regression has been found to be a preferred option.Origi...

Improvement of claim processing cycle time through Lean Six Sigma methodology

Purpose – In the service sector, reduction of cycle time is one of the key issues. Among various approaches, Lean Six Sigma became very popular as it provides the organisation the desired speed with quality. The purpose of this paper is to present a Lean Six Sigma case study for reducing cycle time in the claim settlement process in insurance or financial services.Design/methodology/approach – This paper presents an application of Lean Six Sigma methodology for claim settlement cycle time reduction in the insurance sector.Findings – Lean Six Sigma is found to work very well in the insurance sector for reducing process cycle time by carrying out process changes. Mixing statistical and analytical techniques helps to improve the process speed and is very well demonstrated by Lean Six Sigma approach for service organizations.Originality/value – This paper utilizes Lean and Six Sigma approaches in process improvement and presents an application. The main idea behind this paper is to demonstrate how combining L...

Issues in Pareto analysis and their resolution

Vilfredo Pareto established the ‘Pareto principle’, which is also known as ‘vital few, trivial many’, to help in identifying ‘vital few’ errors for problem-solving. However, in many industrial applications, issues such as (a) the incorrect selection of the ‘vital few’ errors, (b) the interrelationship among errors and (c) the merging-up errors of different processes together need to be addressed. Otherwise, the chances are pretty high that the application of Pareto analysis will fail to correctly identify the ‘vital few’ errors, leading to an incorrect problem-solving approach. In this paper, the authors demonstrate the issues with the help of a real-life case study in a service scenario and suggest the appropriate remedial measures, for effectively separating out the ‘vital few’ causes from the ‘trivial or useful many’ causes to enhance the discriminating power of the Pareto graph.

Developing a model for process improvement using multiple regression technique

Purpose – Practitioners often face challenges in model development when establishing a relationship between the input and output variables and their optimization and control. The purpose of this paper is to demonstrate, with the help of a real life case example, the procedure for model development between a key process output variable, called the multi-stage flash evaporator efficiency, and the associated input process variables and their optimization using appropriate statistical and analytical techniques. Design/methodology/approach – This paper uses a case study approach showing how multiple regression methodology has been put into practice. The case study was executed in a leading Indian viscose fiber plant. Findings – The desired settings of the relevant process parameters for achieving improved efficiency have been established by appropriately using the tools and techniques from the Lean Six Sigma tool kit. The process efficiency, as measured by M3 of water evaporated per ton of steam, has improved ...

An outline of the “Control Phase” for implementing Lean Six Sigma

Purpose – The purpose of this paper is to develop a guideline of the control procedure and tools depending on dominance pattern. In Lean Six Sigma (LSS) implementation, the control phase plays a vital role in sustaining the gains achieved from the improvement phase. The process control schemes should be developed by studying the process dominance pattern as suggested by Juran. Design/methodology/approach – Discussion has been made on identification of various methods with the help of a few real life examples for effective LSS implementation. Findings – The dominance pattern helps in identifying the control mechanism. However, with the advent of new business processes, the dominance pattern needs a little bit of modification. Research limitations/implications – The case studies mainly are from the manufacturing sector and one from the service sector, where authors have studied the control mechanism. There exists scope of future research in service sector for adequate representation. Originality/value – The...