K.E.K. Vimal

Implementing lean sigma in an Indian rotary switches manufacturing organisation

The manufacturing organisations have been witnessing a transformation in the manufacturing paradigm. Lean sigma and six sigma are the two business process improvement strategies widely employed by organisations to enhance their manufacturing performance. To achieve dramatic result in cost, quality and time, best strategies need to be applied to enhance the process performance. Lean sigma and six sigma are two powerful and effective strategies, enabling the organisation to overcome their weakness and for retaining their improvement. Lean sigma combines the variability reduction tools and techniques drawn from six sigma with the waste and non-value added elimination tools and techniques from lean manufacturing to achieve savings in the organisations. This study uses an integrated lean sigma framework to reduce the defects occurring in the final product, thereby contributing savings to the organisation. The proposed framework integrates lean tools within six sigma methodology to enhance the bottom-line results and to win customer loyalty. The implementation of the proposed framework shows dramatic improvement in key metrics and substantial financial savings to be generated by the organisation.

Application of artificial neural network for fuzzy logic based leanness assessment

Purpose – The purpose of this paper is to report a case study in which artificial neural network (ANN) has been used for performing fuzzy logic based leanness assessment.Design/methodology/approach – Leanness is the measure of lean manufacturing practice. Fuzzy logic has been used for the calculation of leanness. To improve the effectiveness of computation, ANN tool has been used in this study. The network has been modeled, trained and simulated using the MATLAB software.Findings – The disadvantages associated with the scoring method has been overcome by the deployment of fuzzy logic. The problem associated with manual computation has been overcome by the application of ANN. The simulated model has been validated by measuring the leanness level of the case organization.Research limitations/implications – The case study has been carried out in a single electronic switches manufacturing organization. In the fuzzy logic approach, triangular fuzzy numbers are being used in the present study.Practical implicat...

Development of checklist for evaluating sustainability characteristics of manufacturing processes

In recent times manufacturing organisations have been witnessing stringent regulations from government towards environmental policies. In order to cope with the government rules and regulations, many organisations identified sustainable manufacturing as the principal solution. There exists a need to check the effectiveness of sustainability principles implementation. The effectiveness can be measured either using quantitative or qualitative approaches. In general sustainable manufacturing has been viewed in three perspectives namely: process, product and material. Among three orientations, process orientation gains attention as it forms the major contributor for the performance of sustainable concepts in the organisation. In order to assess the process orientation of manufacturing organisations, in this study we attempt to develop a checklist to measure the process orientation specifically. The checklist was developed based on triple bottom line (TBL) concept proposed by Elkington (1997). The checklist consists of 40 questions which covers all three Es of TBL namely: ecology, equity and economy. In order to check the practical usability of the developed checklist, the process sustainability characteristics were measured in five organisations across various sectors.

An approach for evaluation of process sustainability using multi-grade fuzzy method

The rapidly changing modern marketplace and government policies drive an organization to endeavour sustainable manufacturing. Sustainable manufacturing means the production of products/services in such a way that it utilizes minimum natural resources and produces safer, cleaner and environment-friendly products at an affordable cost. Sustainable development in a manufacturing firm can be achieved using three orientations such as material, product design and manufacturing process. Among the three perspectives, process perspective gains more importance because it directly contributes to emissions, energy and resource consumption. Hence, the process sustainability index (PSI) needs to be quantified. In this study, a comprehensive model for assessing process sustainability has been developed. Then by using multi-grade fuzzy approach, PSI has been quantified as 6.94 and performance importance index was computed which helps in identifying the obstacles to enable sustainability improvement. The results indicate that the developed conceptual model is capable of effectively assessing sustainability of process orientation and has practical relevance.

A framework for VSM integrated with Fuzzy QFD

Purpose – The purpose of this paper is to apply a framework for value stream mapping (VSM) integrated with fuzzy quality function deployment (QFD) for enabling scientific prioritization of improvement proposals to improve leanness. Design/methodology/approach – The literature was reviewed from the perspectives of VSM, QFD and fuzzy logic applications. The current state map was developed for the case component; fuzzy QFD was used for prioritizing improvement proposals and prioritized proposals were incorporated in the future state map. Findings – The approach enabled the scientific mapping of wastes with improvement proposals and thereby enabling systematic implementation of improvement proposals. The conducted pilot study resulted in 4 percent reduction in cycle time. As the lean implementation is a continuous process, furthermore improvements are expected in near future. Research limitations/implications – The study was conducted in an Indian camshaft manufacturing organization. The improvements in terms...

Optimization of process parameters of SMAW process using NN-FGRA from the sustainability view point

Welding process does not possess a good environmental image due to fumes, noise and other health hazards. But, it has been widely applied and is irreplaceable as far as structural industries are concerned. In welding process, many factors are responsible for environmental burdens, of which this study investigates and optimizes process parameters. Based on the pilot study, operating levels for parameters like current, voltage and welding speed, and various responses were identified. Further, the responses considered in the study include spatter, slag, fume generation rate, particulates and power consumption. A full factorial design of three factors at five levels requires 125 experiments for a complete analysis; however the conduct of a full factorial design experiment is expensive and consumes much time. Hence,

Thirty criteria based leanness assessment using fuzzy logic approach

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Leanness evaluation using IF–THEN rules

L27 orthogonal design was adopted for three inputs and five levels and 27 experiments were conducted. Further, five back propagation neural network model with network structure of 3-12-1 was individually developed to predict responses.