Dr. Saleeshya P. G.

Due to the highly competitive nature of service industries, lean manufacturing intervened service sector as a methodology to reduce waste and improve productivity. Among various service industries, banking sector was selected for the study due to the highly customer centric nature, product complexity and increased transactional work volume persisting. Study was focused on implementing lean manufacturing practices in banking industries for which different lean enablers existing in banking sector were explored from a detailed field study conducted among various banks. A modified lean implementation model for banking industry was designed from literature survey and field study conducted. Analytic hierarchy process was executed among the different enablers and sub-enablers of lean model to obtain the priority percentage of each. Based on priority percentage from AHP the lean manufacturing model was implemented in one of the branches of a private sector bank. A few performance indicators were identified, observed and analysed from the period of implementation. Various performance indicators including productivity index and customer satisfaction index of the bank was calculated and improvements were achieved, which helped the private banking branch to perform better in the current global competitive market.

Sustainability is one of the most critical issues facing manufacturers today. The industries must develop new and innovative approaches to ensure sustainability in economic, environmental and social aspects. The operational excellence strategies such as Lean and Agile manufacturing can be applied in the industries that add value to the product by eliminating waste and quickly respond to dynamic changes in demand. This paper presents a framework that builds and assesses the sustainability of the manufacturing system with combined lean and agile concepts. Analytical Hierarchy Process and Analytical Network Process are identified as suitable methodologies to analyze the model. The model is validated in an Ayurveda Pharmaceutical industry to identify the most important factors of lean and agile manufacturing that build and enable the sustainability dimensions such as Economic, Environmental, Social, Technological and Ethical. The results show that the industry focuses more on economic aspects of sustainability followed by social, environmental, ethics and technological dimensions of sustainability in the case of a lean perspective. For an agile perspective, the weightage is more for social dimension followed by ethics, economic, technological and environmental dimensions of sustainability. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

The concept of lean is ever-expanding and has continuously been researched upon. But, the question of how lean a system is has been frequently overlooked. In this study, we have researched upon the capability of a multi-level model to calculate the leanness of a system based on studies conducted in various manufacturing industries. The major issue studied and addressed in the problem is the evaluation of wastes in the system through the inhibitors of lean manufacturing in an industry. The different levels of the assessment model deal with the lean dimensions in the first and topmost level, the eight major wastes in lean manufacturing in the second level and the inhibiting factors affecting lean behaviour in the final level. Leanness as a metric is then calculated through the implementation of variability source mapping and data envelopment analysis techniques on the specific data collected through our research instrument. The obtained results have been assessed through plotting all dimensions simultaneously on a radar chart for evaluation. The results have been presented and the model's validity has been assessed. Inferences were drawn from findings of the study.

Companies worldwide have now realised that ‘customer focus’ is what wins the game. As demands of the customer become more and more volatile and unpredictable, they have to stay ahead of their competitors in fulfilling the needs of the customer. The supply chain as a ‘unit’ has to compete against other supply chains for reaching out and delighting the customer. Responding fast to the changing customer needs has been an intangible factor underlying a successful business. Thus, responsiveness of the supply chain has become the differentiator between the competing supply chains. In this paper, the end-to-end supply chain factors influencing responsiveness are identified from extant literature and a model of responsiveness of the supply chain has been developed by conducting a survey of 204 pump manufacturers. The developed model has been validated through confirmatory factor analysis using structural equation modelling. These findings can help to identify the areas of improvement for the supply chain and may lead to a focused improvement in these areas thus improving responsiveness and profitability.

During emergencies, decision making to support relief preparedness and response activities are challenging task requiring quick and effective action from responders under uncertainty conditions. This paper proposes a response planning stochastic model for humanitarian transportation operations. The objective of this proposed model is to minimise total transportation duration during emergency situations. This model aims to maximise satisfaction levels through attaining quick response which can help in making decisions on disaster relief logistics. © Copyright 2016 Inderscience Enterprises Ltd.

In this study, we concentrate on one of the three major areas of the whole transit network design problem that being the frequency setting. The main problem addressed here is the minimisation of losses borne by a public state transport corporation in India. This is achieved by optimally allocating resources to shared routes already in existence. The bus frequency setting problem is solved using a bi-level methodology. In the first level minimum required fleet size for the routes are found out by considering the routes individually. In the second level with the guarantee of load feasibility, allocation of frequencies is done for the fleet size found in the first level. This is done by also taking into consideration the achievement of minimisation of operational cost of the routes under consideration as added objectives. The relation between the operations cost and the maintained frequencies are found out using artificial neural network (ANN), and the second level is solved using a multi objective genetic algorithm (GA). This methodology has been used in optimising two shared routes and the results are thus presented.

Lean manufacturing is an emerging concept in the Indian manufacturing scenario. Many small and medium scale enterprises in the country are aiming at becoming lean and thereby improving their productivity. This paper is an outcome of a case study in one such enterprise that deals with the manufacturing and assembly of offset printing machinery in India. Being a vendor-based organisation, part shortage due to delays in the process was a major problem faced. A thorough analysis of the various vendors and processes that the product goes through was done and the process flow was mapped to obtain a clear picture of the entire system, and software modelling helped arrive at quantitative results. Lean tools like Pareto analysis, five-why analysis, source inspection, etc., were used to identify and eliminate the various factors that led to delay. Proper scheduling of jobs is also essential to reduce waiting time, and therefore an algorithm has been developed to help arrive at an optimum scheduling sequence. The results from this case study have proved successful in reducing the lead time of the component under study. Copyright © 2015 Inderscience Enterprises Ltd.

This paper is related to a real life study carried out in Indian manufacturing organisations to assess the extent to which the agile manufacturing paradigm is recognised and deployed, as this paradigm has been a major objective of many companies. A multi-level framework developed by the authors, along with a questionnaire was used to identify various enabling factors of agility in Indian manufacturing industries. This model helps to determine the measure of agility called ‘Effectiveness Index’ (EI) at the various hierarchical levels of an organisation. In this paper we propose an approach to measure the agility of manufacturing systems by combining the analytical hierarchy process (AHP) and the data envelopment analysis (DEA) methodologies. The method of AHP was used to identify important agility enablers by deriving appropriate weights (Importance Index). DEA was used to compare and find out the priorities of various units of organisations by making use of the values of EI and Importance Index for agility.

Lean manufacturing is a philosophy of eliminating waste through continuous improvement. This paper is an outcome of a case study conducted in a textile industry in south India. Though the concept of lean manufacturing has shown good results in continuous process industry, it has not been extensively used as compared to discrete manufacturing industries. Process industries, especially textile industries, have automatic machinery which are highly inflexible and have high volume/low variety products. This nature of the textile industry makes implementing lean manufacturing techniques a challenge; hence implementing lean techniques in a textile industry has been taken up as a challenge. We have chosen a combination of value stream mapping (VSM), 5S, kanban, kaizen, poka-yoke, and visual controls to improve the processes. The achievement potential scores before and after lean implementation has been highlighted using radar diagrams. The findings of this study reveal that a thorough analysis of the process, setup, and changeover time (CO), use of colour coding for identification of volume-mix, use of kaizen and quality circles which empower the workforce, are some of the various keys to a successful lean implementation in a textile industry.

Today's manufacturing companies are measured by how fast they meet the customer and user requirements, how responsive they are to the changing market demands and how capable they are in producing good quality products and supply them at optimal cost. Lean manufacturing is a manufacturing concept which has demonstrated results of successful implementation especially in discrete manufacturing companies. This paper presents a case study of an Indian pharmaceutical firm to outline the scope of a successful lean based manufacturing strategy implementation in this sector. Analytic Network Process (ANP) is applied to measure and rate the present leanness of a pharmaceutical firm. A multi-level model along with the questionnaires developed by the authors was used for the initial assessment. The approach helped to assess the current leanness level. Since inhibitors for lean interventions were identified the authors studied them and established the correlation among different parameters using Interpretive structural modelling (ISM) approach. The model was also validated through MICMAC analysis. The results of ANP, ISM and MICMAC showed the root causes for the unsuccessful implementation of lean in the firm. They were the lack of a responsive supply chain and the excessive Quality regulations and enforcements by the Authorities. This study gives guidelines to companies planning for lean implementation to deploy methods to remove the inhibitors of lean at the initial stages. Identifying the barriers can guide managers in developing strategies to eliminate them at the inception. This paper recommends supplier qualification programmes which managers can use to get the suppliers be part of their extended lean family. Through this supplier's involvement can be improved with an aim of improving the product lead time. © Published under licence by IOP Publishing Ltd.