Purpose Agile manufacturing (AM) has evolved as a revolutionary way of manufacturing the products while managing the uncertainties, product introduction time, responsiveness, innovation, superior quality, etc. along the supply chain to satisfy the ever increasing customer demand and to maximize the profit. The purpose of this paper is to critically analyze the literature related to various dimensions of AM and to report the findings. Design/methodology/approach This paper presents the reviews of 300 scholarly articles from 1993 to 2016 by various researchers and practitioners on AM collected from different sources, i.e. Google Scholar and ResearchGate. The information related to AM is also captured during industrial visits to different Indian manufacturing plants. Findings AM definitions are reported along divergent scopes and objectives in the literature. The researchers have given importance on performance measurement and process analysis through empirical and descriptive analysis whereas its implementation issues are neglected. It is also observed that the effort made on AM is significant for manufacturing industries which is overlooked in service industries. Practical implications This literature review has identified many research gaps in AM which were not paid attention before. Researchers can address these research gaps for strengthening the AM implementation. Originality/value In total, 300 research papers are reviewed and analyzed to capture the various aspects of AM and its related issues but not restricted to research methodologies, author profiles, types of industries, tools/techniques/methodology used, etc.

Purpose – The purpose of this paper is to determine the agility level of a manufacturing system along different timelines. Design/methodology/approach – The fuzzy synthetic extents of agile manufacturing enablers (AMEs), on the basis of their importance, are determined. Then they are integrated with their performance ratings along different timeline for calculating the Fuzzy Agile Manufacturing Index (FAMI). Euclidean distances of FAMI from predetermined agility levels are mapped to determine the agility level of the manufacturing system along different timeline. Findings – The proposed methodology was implemented in an Indian manufacturing organization to determine its agility level. It was concluded from the obtained results that there was significant improvement in the agility level along the timeline. Research limitations/implications – The weights of the AMEs are assumed to be constant along the timeline. Practical implications – The supply chain mangers can easily apply this methodology in their respective manufacturing organizations to assess and determine the agility level. This proposed approach will show the direction to check the performance of agility and evaluate the evolution of agility in their respective manufacturing organizations. Originality/value – The combination of fuzzy synthetic extent of weights and average fuzzy performance ratings of AMEs to calculate the FAMI along the timeline considering judgments of multiple experts is a unique contribution.

Purpose The purpose of this paper is to identify and analyze the agile manufacturing barriers (AMBs) for establishing a cause and effect relationship among them. Design/methodology/approach A methodology is proposed using fuzzy decision-making trial and evaluation laboratory (DEMATEL) to capture multiple experts’ qualitative judgments for mitigating the impact of the AMBs. In order to validate the proposed methodology, it is applied to an Indian automobile manufacturing company. Findings Out of 36 AMBs identified through literature review, 20 AMBs are found to be relevant to the case company. Five AMBs (i.e. lack of resource reconfiguration, inefficient conflicting management styles, imperfect market knowledge, inadequate information handling and improper strategic plan) were identified as significant cause group where the case company has to put efforts and resources. Also the impact relationship matrix for each AMB has been developed to visualize its interactions (i.e. influencing and influenced) among other AMBs. Research limitations/implications The results obtained are specific to the Indian automobile manufacturing company and it cannot be generalized for every manufacturing company or any other sector. However, the proposed approach can be a basis and provide a platform to understand and analyze the interactions between AMBs. Practical implications The proposed methodology will show the appropriate areas for allocating efforts and resources to mitigate the impact of AMBs for successful implementation of agile manufacturing. Originality/value According to the authors’ knowledge, no work is reported in the literature that proposes a framework using fuzzy DEMATEL for the analysis of AMBs in Indian automobile manufacturing company.

Purpose The purpose of this paper is to develop a set of key performance indicators (KPIs) for agile manufacturing (AM) and to propose a methodology for its performance evaluation. Design/methodology/approach The proposed methodology was developed using fuzzy analytic hierarchy process (FAHP) and performance value analysis (PVA) to evaluate and analyze the AM performance. The FAHP is applied to determine the importance of KPIs, and PVA is used to evaluate AM performance. Findings The proposed methodology is applied to an Indian auto component manufacturer, and it is observed that there is an improvement of performance along the timeline. Research limitations/implications The proposed approach is generic in nature and can be applied to different agile business environments for performance evaluation. Practical implications This study provides insights into the AM performance evaluation. The managers can establish the impact of each significant area (SA) on AM and each KPI on its corresponding SA by capturing their manufacturing environments. Originality/value Although many issues related to AM have been widely researched, only a few studies have been carried out to quantify, analyze and evaluate the AM performance in the Indian manufacturing environment. The proposed model has the ability to capture the performance of AM along the KPIs to draw fruitful conclusions.

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