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The concept of agile manufacturing is becoming critically important to manufacturing industry due to rapid industrialization, fluctuating customer demand, and turbulent business environment. The aim of this study is to prioritize the attributes for successful implementation of agile manufacturing using a combined analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach in Indian manufacturing industry.

The current study identifies eight agile manufacturing attributes through literature review and discussion with subject experts. The experts from different manufacturing industry have been asked to provide data for pairwise comparison of attributes. Afterward, an integrated AHP and TOPSIS approach is employed. The AHP is used to drive the priority weights of the attributes, and TOPSIS is used for prioritizing the attributes for successful implementation of agile manufacturing.

“Information technology,” “human resource management-related issues,” “customer-related issues,” “leadership support,” and “organizationalc related-issues” have been ranked as the top five significant and contributing attributes, which can pave the path for top management to concentrate on the critical areas and allocate significant resources to ensure successful implementation of agile manufacturing.

This research integrates AHP and TOPSIS to prioritize the attributes for successful implementation of agile manufacturing, which are further validated by comparing the ranks obtained through respective approach and sensitivity analysis.

The aim of this paper is to analyze international and national research and development (R&D) programs and roadmaps for the manufacturing sector, presenting how agile and lean manufacturing models are addressed in these programs.

In this review, several manufacturing research and development programs and roadmaps – national programs from the USA and Canada, and international programs from the European Union and from one international organization – are reviewed.

The major finding of this review is that the main concerns in agile manufacturing, as highlighted in these programs, are networks, supply chain and product/service customization, and lean manufacturing's inclination towards achieving better cost efficiency. Although the lean manufacturing approach has been considered in many past and present programs, analysis of the most recent programs shows a greater priority is given to the agile manufacturing approach. The path towards sustainable manufacturing is delineated by pro‐active attitude and action towards customers.

The study analyzes two national R&D programs from the USA, one international program from the European Union, three international roadmaps from the European Union, one business plan from Canada and one international roadmap from the global organization Intelligent Manufacturing Systems.

The findings of this paper are intended to help managers, researchers and practitioners from the manufacturing sector to enhance their understanding and define suitable strategy for their organizations' sustainability and identify suitable manufacturing path with respect to agile and lean philosophies. This study could also help academics in defining course curricula for students more coherent with the R&D policies and/or requirements towards sustainable manufacturing with respect to agile and lean philosophies.

There are reviews comparing agile and lean manufacturing paradigms, but there are no reviews about how the two manufacturing concepts are addressed in manufacturing R&D programs and roadmaps.

This empirical study aims to explore the link between lean manufacturing practices (total quality management, just-in-time production, just-in-time purchasing, total productive/preventive maintenance), agile manufacturing, and operational and financial performance.

Data were collected from 205 Tunisian manufacturing firms, and the results were analyzed using structural equation modeling.

The results indicate that (1) lean manufacturing practices have a direct positive relationship with agile manufacturing except for just-in-time production, (2) agile manufacturing has a positive impact on operational performance and (3) lean manufacturing practices did not seem to contribute directly to operational performance. However, this relationship is significant when it is mediated through agile manufacturing.

This paper shows practitioners the importance of lean manufacturing practices to support agile manufacturing and the key role of agile manufacturing to ensure operational performance.

This paper presents an innovative approach since it studies simultaneously the three dimensions of lean manufacturing and their relationship with agile manufacturing and organizational performance.

The purpose of this paper is to investigate how manufacturing strategies could affect the supplier selection criteria used by business firms.

Survey strategy was used to empirically understand the research argument. First, principal component factor analysis was employed to validate the underlying structure of the supplier selection criteria. Then, simple regression analysis was employed to test the research hypotheses.

Organizations pursuing lean strategies will emphasize factors that improve their efficiency when selecting their suppliers, while organizations pursuing agile strategies will assert factors that improve their ability to respond to customer unique requirements when selecting their suppliers.

This study provides new insight for researchers to understand the effect of manufacturing strategies on the classification of supplier selection criteria. However, the small sample size might limit the ability to generalize research findings. Further research is required to confirm the findings using a wider sample.

This research provides practitioners with useful insights into how to select their suppliers based on their manufacturing strategies.

This paper classifies supplier selection criteria into three distinct groups: lean, agile, and common capabilities. Lean capability refers to the list of criteria that are highly relevant in selecting suppliers for lean implementers. Agile capability refers to the list of criteria that are highly relevant in selecting suppliers for agile implementers. Finally, common capability refers to the list of criteria that have comparable relevance in selecting suppliers for both lean and agile implementers.

Lean and agile manufacturing are two initiatives that are used by manufacturing plant managers to improve operations capabilities. The purpose of this paper is to investigate internal and external factors that drive the choice of lean and agile operations capabilities and their respective impact on operational performance.

Lean and agile manufacturing are each conceptualized as a second‐order factor and measured through a bundle of distinct practices. The competitive intensity of industry and the competitive strategy are modeled as potential external and internal drivers, respectively, and the impact on quality, delivery, cost, and flexibility performance is analyzed using structural equations modeling. The model is tested with data from the high performance manufacturing project comprising a total of 211 plants from three industries and seven countries.

The results indicate that lean and agile manufacturing differ in terms of drivers and outcomes. The choice of a cost‐leadership strategy fully mediates the impact of the competitive intensity of industry as a driver of lean manufacturing, while agile manufacturing is directly affected by both internal and external drivers, i.e. a differentiation strategy as well as the competitive intensity of industry. Agile manufacturing is found to be negatively associated with a cost‐leadership strategy, emphasizing the difference between lean and agile manufacturing. The major differences in performance outcomes are related to cost and flexibility, such that lean manufacturing has a significant impact on cost performance (whereas agile manufacturing has not), and that agile manufacturing has a stronger relationship with volume as well as product mix flexibility than does lean manufacturing.

Cross‐sectional data from three industries and seven countries are used, and it would be interesting to test this model for more industries and countries.

The results provide insights into the factors that influence the choice of lean or agile manufacturing for improving operations, and the results that can be obtained.

To the authors' knowledge, this is the first large‐scale empirical survey of leanness and agility simultaneously, using data from manufacturing firms in Europe, Asia, and North America. The model incorporates a wide perspective on factors related to lean and agile manufacturing, to be able to identify similarities and differences.

In the past, the insufficiency of the traditional business practices to meet vibrant customer demands in continuously changing business environment has severely affected organizational competitiveness. The purpose of this paper is to develop and propose a new framework for smoother and effective implementation of agile manufacturing by identifying and integrating a set of significant agility principles and techniques.

The present work proposed a framework for agile manufacturing by deploying the comparative analysis of 17 frameworks published in peer-reviewed journals.

The proposed conceptual framework constitutes of eight pillars for agile manufacturing implementation. The proposed framework relies on a strong foundation of leadership support. The roof of the proposed framework of agile manufacturing is supported by the pillars constituted of seven elements, an industry must deploy for successfully implementing agile manufacturing, namely, human resource-related issues, organizational culture-related issues, supplier-related issues, customer-related issues, innovation, concurrent engineering and information technology.

This work is the first attempt, in the best knowledge of the authors, to employ comparative analysis for critically analyzing a wide range of agile manufacturing frameworks. The findings of this study will assist researchers and managers in agile manufacturing implementation in more a smoother and effective way in manufacturing industries.

The study aims at empirically investigating and prioritizing the critical barriers for the successful implementation of agile manufacturing in the medium- and large-scale Indian manufacturing industries.

A literature review of peer-reviewed journals and discussion with experts is used to identify 17 barriers to the implementation of agile manufacturing. An empirical survey is then conducted to collect data regarding the agile manufacturing barriers and is further analyzed using the factor analysis and vlsekriterijumska optimizacija i kompromisno resenje (VIKOR).

Based on the survey of empirical data, the investigated critical barriers were reduced in five critical categories, as follows: Managerial constraints, technological constraints, human resource–related constraints, operational constraints and organizational culture-related constraints, which are further ranked in terms of their severity using VIKOR. This research advocates the development of a strategy for addressing the most critical barriers instead of focusing on all for the successful implementation of agile manufacturing.

This work contributes to agile manufacturing literature by the structured presentation of the barriers to implement agile manufacturing in the Indian manufacturing industry. It also extends the integrated factor analysis and VIKOR method to investigate and rank the barriers.

Agile manufacturing is largely dependent on the capabilities of its people to learn and evolve with change. However, while agile manufacturing uses e‐commerce enabled technology in a decentralized organizational setting, it remains unclear how these individual capabilities should be linked to other organizational resources to create an agile organization. Another important modern management research perspective is the internal resource‐based perspective, resulting in a phenomenon called competence‐based competition with renewed attention for competence management. Competence management comprises the management, building, leveraging and deployment of strategic and operational competencies, the causal relationships and linkages between them, and the way competencies are embedded in organizational and individual resources. In this paper, we explore the relation between agile management and time‐based competence management, and study its adoption in small batch discrete parts manufacturing environments with the help of a coarse fact‐finding survey research.

To provide a modified orthogonal array‐based model for enabling the researchers and practitioners to exploit the technique, “design of experiments” in an agile manufacturing environment.

The characteristics of Taguchi's off‐line models and agile manufacturing were studied. A theoretical model of modified orthogonal array‐based experimentation was designed. This model was subjected to implementation study in an Indian pump‐manufacturing company.

The model contributed in this paper has shown its feasibility in achieving quality in agile manufacturing environment.

The authors are residing in an Indian city where the majority of the companies have not adopted agile manufacturing criteria. Hence, it was not possible to carry out implementation study in an agile manufacturing company. Future researchers should examine the practical validity of the proposed model in agile manufacturing companies.

Since the manufacturing organizations are fast becoming agile, due to the customers' dynamic demands coupled with competition, the traditional quality improvement techniques are becoming obsolete. The model contributed in this paper is found to be useful in achieving continuous quality improvement in AM environment. Hence the model would be a useful technique for today's practitioners whose activities are increasingly focused towards achieving agility in manufacturing.

The literature survey covering articles on agile manufacturing indicates that no researcher or practitioner has contributed a model that would exploit the technique, “design of experiments” in an agile manufacturing environment. Hence the proposed model is expected to be of high value for researchers and practitioners to explore the way of achieving continuous quality improvement in agile manufacturing environment.

Today's businesses are facing a world that is more complex, turbulent and unpredictable than in the past with increasing levels of environmental complexity. Rather than proposing environmental uncertainty as a mediator/moderator of the relationship between agility and performance as others have done, the authors offer an alternative view where supply chain agility is seen as mediating the relationship between environmental uncertainty and supply chain performance.

The authors propose that supply chain agility is a response to the effects of environmental uncertainty and, as such, environmental uncertainty should be seen as a driver of supply chain agility. Few studies test the direct relationship between uncertainty and supply chain performance, and none simultaneously test for agility's mediation and moderation effect between environmental uncertainty and agility.

The model was statistically assessed using partial-least-squares structural equation modeling (PLS/SEM) by analyzing survey data from manufacturing managers in 136 US firms. The study results did not indicate a significant relationship between environmental uncertainty and supply chain performance. However, the authors did find a significant positive relationship between agile manufacturing and supply chain performance using measures that were primarily operations-centered rather than financial. Additionally, the authors found that agile manufacturing fully mediates the relationship between environmental uncertainty and supply chain performance.

The authors’ model, though simple, provides a base for future research for them and other researchers who can incorporate other impacting variables into the model. The study results show that uncertainty can be a force for good and that utilizing agile manufacturing can be a new source of opportunity.