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The recent global market trend is seemed enforcing existing manufacturing organizations (as well as service sectors) to improve existing supply chain systems or to take up/adapt advanced manufacturing strategies for being competitive. The concept of the agile supply chain (ASC) has become increasingly important as a means of achieving a competitive edge in highly turbulent business environments. An ASC is a dynamic alliance of member enterprises, the formation of which is likely to introduce velocity, responsiveness, and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern. Apart from traditional supplier/partner selection criteria; different agility-related criteria/attributes need to be taken under consideration while selecting an appropriate supplier in an ASC. The paper aims to discuss these issues.

Therefore, evaluation and selection of potential supplier in an ASC have become an important multi-criteria decision making problem. Most of the evaluation criteria being subjective in nature; traditional decision-making approaches (mostly dealing with objective data) fail to solve this problem. However, fuzzy set theory appears an important mean to tackle with vague and imprecise data given by the experts. In this work, application potential of the fuzzy multi-level multi-criteria decision making (FMLMCDM) approach proposed by Chu and Velásquez (2009) and Chu and Varma (2012) has been examined and compared to that of Fuzzy-techniques for order preference by similarity to ideal solution (TOPSIS) and Fuzzy-MOORA in the context of supplier selection in ASC.

It has been observed that similar ranking order appears in FMLMCDM as well as Fuzzy-TOPSIS. In Fuzzy-MOORA, the best alternative appears same as in case of FMLMCDM as well as Fuzzy-TOPSIS; but for other alternatives ranking order differs. A comparative analysis has also been made in view of working principles of FMLMCDM, Fuzzy-TOPSIS as well as Fuzzy-MOORA.

Application feasibility of FMLMCDM approach has been verified in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA in the context of agile supplier selection.

In today’s ever-changing global business environment, successful survival of manufacturing firms/production units depends on the extent of fulfillment of dynamic customers’ demands. Appropriate supply chain strategy is of vital concern in this context. Lean principles correspond to zero inventory level; whereas, agile concepts motivate safety inventory to face and withstand in turbulent market conditions. The leagile paradigm is gaining prime importance in the contemporary scenario which includes salient features of both leanness and agility. While lean strategy affords markets with predictable demand, low variety and long product life cycle; agility performs best in a volatile environment with high variety, mass-customization and short product life cycle. Successful implementation of leagile concept requires evaluation of the total performance metric and development of a route map for integrating lean production and agile supply in the total supply chain. To this end, the purpose of this paper is to propose a leagility evaluation framework using fuzzy logic.

A structured framework consisting of leagile capabilities/attributes as well as criterions has been explored to assess an overall leagility index, for a case enterprise and the data, obtained thereof, has been analyzed. Future opportunities toward improving leagility degree have been identified as well. This paper proposes a Fuzzy Overall Performance Index to assess the combined agility and leanness measure (leagility) of the organizational supply chain.

The proposed method has been found fruitful from managerial implication viewpoint.

This paper aimed to present an integrated fuzzy-based performance appraisement module in an organizational leagile supply chain. This evaluation module helps to assess existing organizational leagility degree; it can be considered as a ready reference to compare performance of different leagile organization (running under similar supply chain architecture) and to benchmark candidate leagile enterprises; so that best practices can be transmitted to the less-performing organizations. Moreover, there is scope to identify ill-performing areas (barriers of leagility) which require special managerial attention for future improvement.

The concept of agile supply chain (ASC) has become increasingly important as means of achieving a competitive edge in turbulent business environments. An ASC is a dynamic alliance of member enterprises, the adaptation of which is likely to introduce velocity, responsiveness and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern; influenced by various agility-related criteria/attributes. Therefore, evaluation and selection of potential supplier in an ASC has become an important multi-criteria decision-making problem. The purpose of this paper is to report, a supplier selection procedure (module) in the context of ASC.

During supplier selection, subjectivity of evaluation information (human judgment) often creates conflict and bears some kind of uncertainty. To overcome this, the present work attempts to explore vague set theory to deal with uncertainties in the supplier selection decision-making process. Since, vague sets can provide more accurate information as compared to fuzzy sets. It considers true membership function as well as false membership function which give more superior results for uncertain information. In this procedure, first, linguistic variables have been used to assess appropriateness rating (performance extent) as well as priority weights for individual quantitative or qualitative criterions. Second, the concept of degree of similarity and probability of vague sets has been used to determine appropriate ranking order of the potential supplier alternatives.

A case empirical example has been provided. It has been proved that the methodology would be fruitful in considering different evaluation criterion (indices); may be contradicting in nature like beneficial and cost criterions. The application of vague set theory has also been proved as a better option to work under uncertain (fuzzy) decision-making environment in comparison to fuzzy set theory.

The application of vague set theory in multi-criteria group decision making has been reported in literature to a limited extent. Application of vague set as a decision-making tool in agile supplier selection appears relative new and unexplored work area. The work has got remarkable managerial implications.

The purpose of this study is to provide an efficient index system for evaluating leanness extent of the organizational supply chain. In today’s competitive global marketplace, the concept of lean manufacturing has gained vital consciousness to all manufacturing sectors, their supply chains and, hence, a logical measurement index system is indeed required in implementing leanness in practice. Such leanness estimation can help the enterprises to assess their existing leanness level and can compare different industries that are adapting this lean concept.

The present work exhibits an efficient fuzzy-based leanness assessment system using trapezoidal fuzzy numbers set.

The methodology described here has been found fruitful while applying for a particular industry, in India, as a case study. Apart from estimating overall lean performance metric, the model presented here can identify ill-performing areas toward lean achievement.

The major contributions of this work have been summarized as follows: development and implementation of an efficient decision-making procedural hierarchy to support leanness extent evaluation; an overall lean performance index evaluation platform has been introduced; concept of generalized trapezoidal fuzzy numbers has been efficiently explored to facilitate this decision-making; and the appraisement index system has been extended with the capability to search ill-performing areas which require future progress.

Lean manufacturing is an operational strategy oriented toward achieving the shortest possible cycle time by eliminating waste. It is derived from the Toyota Production System and its key thrust is to increase the value-added work by eliminating waste and reducing incidental work. In today's competitive global marketplace, the concept of lean manufacturing has gained vital consciousness to all manufacturing sectors, their supply chains, and hence a logical measurement index system is indeed required in implementing leanness in practice. Such leanness estimation can help the enterprises to assess their existing leanness level and can compare different industries who are adapting this lean concept. The paper aims to discuss these issues.

The present work exhibits an efficient fuzzy-based leanness assessment system using generalized interval-valued (IV) trapezoidal fuzzy numbers set. The concept of “degree of similarity” between two IV fuzzy numbers has been explored here to identify ill-performing areas towards lean achievement.

The methodology described here has been found fruitful while applying for a particular industry, in India, as a case study. Apart from estimating overall lean performance metric, the model presented here can identify ill-performing areas towards lean achievement.

The major contributions of this work have been summarized as follows: development and implementation of an efficient decision-making procedural hierarchy to support leanness extent evaluation. An overall lean performance index evaluation platform has been introduced. Concept of generalized IV trapezoidal fuzzy numbers has been efficiently explored to facilitate this decision-making. The appraisement index system has been extended with the capability to search ill-performing areas which require future progress.

Lean manufacturing is a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful, and thus a target for elimination. In today's competitive global marketplace the concept of lean manufacturing has gained vital consciousness to all manufacturing sectors, their supply chains and hence a logical measurement index system is indeed required in implementing leanness in practice. The paper aims to discuss these issues.

The present work exhibits an efficient grey-based leanness assessment system using concept of grey numbers theory.

Such leanness estimation can help the enterprises to assess their existing leanness level; can compare different industries who are adapting this lean concept. The methodology described here has been found fruitful while applying for a particular industry, in India, as a case study.

Lean extent evaluation module (lean index appraisement system) exploring grey numbers theory is quite new and not documented in literature before.