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The purpose of this paper is to study the anodising process of a portable amplifier production process to identify and eliminate the sources of variations, in order to improve the process productivity.

The study employs the define-measure-analyse-improve-control (DMAIC) Six Sigma methodology. Within the DMAIC framework various tools of quality management such as SIPOC analysis, cause and effect diagram, current reality tree, etc., are used in different stages.

High rejection rate was found to be the main problem leading to lower productivity of the process. Four types of defects were identified as main cause of rejections in the baseline process. Pareto analysis resulted in detection of the top defects, which were then analysed in details to find the root cause of the problem. Further study resulted in finding improvement measures that were discussed with the management before implementation. The process is sampled again to check the improvements, and control measures were established.

The study provides a framework for implementation of DMAIC Six Sigma methodology for a manufacturing firm. The results presented are based on the data collected from the shop floor. Results and findings of the study were implemented for quality improvement of the process.

The study is based on an original research conducted with the objective of quality improvement in the anodising process of the production process. Besides presenting an approach to DMAIC Six Sigma methodology, an application of the current reality tree tool for root cause analysis is presented, a tool used limitedly in the Six Sigma studies. The tool finds its uniqueness in its ability to address problems relating multiple factors than isolated factors.

The purpose of present study is to carry out stochastic analysis of some important reliability measures of a three-unit system where there are two types of units called type-I and type-II. In type-II, two identical units work simultaneously to meet the system requirements while in type-I, a single unit is kept in spare and can be used to work whenever required at the failure of either of the units of type-II. The system starts its operation with type-II units and thus priority is given to the operation of type-II units. The type II units are different to type-I unit but can perform the same task. There is a single server who handles repair activities of both type of units and the units are assumed to be in pristine condition after every repair. Failures of both types of units are independent and constant. The system can fail at the failure of either of the type-II units and type-I unit.

Semi-Markov process and regenerative point technique are used to study the behaviour of different reliability measures of the system.

In this paper, a three-unit non-identical repairable system is analysed stochastically and its reliability characteristics such as transition probabilities (TP), mean sojourn time (MST), MTSF, steady state availability, expected number of repairs of units, expected number of visits of the repairman and expected busy period of repairman are derived to carry out profit analysis.

The direct application of the present study can be seen is case of a power distribution system where solar panels may be considered as type-II units and transformer as the type-I unit. Here, the case study is carried out by using approximate data from some old studies; however, a study with accurate data would be more preferable.

This paper is one of the few reliability studies conducted on a system with simultaneous working units. Also, the comparative study of the profit of the present system model has been done with that of the model Kadyan et al. (2020a).