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The purpose of this paper is to identify a classification scheme which represents the variation in business and supply chain performance of supply chains in Indian manufacturing industry. Classification is done by presenting an empirical taxonomy of clusters representing supply chains in Indian manufacturing industry based on variation in supply chain excellence index (SCEI) and business performance index (BPI).

The clustering of supply chains in Indian manufacturing industry is done by considering BPI and SCEI as clustering variables, which were found by using survey responses and results of a prior empirical study which was carried out in Indian manufacturing industry. The cluster analysis is performed by using Ward’s agglomerative hierarchical clustering followed by using K-means clustering algorithm to establish final set of clusters.

It was found that supply chains in Indian manufacturing industries can be clustered in four major clusters which are named as strategic, celebrity, capable and undeveloped cluster. The characteristics of these clusters reveal some major characteristics of supply chains in Indian manufacturing industry.

The research work presented in this paper takes a novel way to introduce the clusters of supply chains in Indian manufacturing industry. The researchers who are seeking patterns in large data sets of manufacturing companies of Indian industry will be benefitted by using the proposed clusters. While practitioners who are seeking to move their supply chain one step ahead will also reap the benefits of the paper by seeking the characteristics of particular cluster.

The purpose of this paper is to verify the applicability of proposed lean production system (LPS) framework in the Indian manufacturing industry.

The authors conducted a cross-sectional study to collect responses from five major sectors, namely, automobile, process, machines and equipment, electronics and components and textile. They collected 200 responses to perform empirical validation from Indian manufacturing industry. They performed reliability analysis on the proposed framework of LPS in the Indian manufacturing industry.

The findings revealed that all the elements and sub-elements have a high value in reliability. Subsequently, the study performed principles component analysis on LPS framework. The empirical investigation revealed that the proposed LPS framework has a high level of reliability as well as validity in the Indian manufacturing industry. Hence, the study concluded that the LPS framework is helpful to implement lean principles in a structured manner in any Indian manufacturing industry to achieve excellence in organizational functions.

The authors conducted an empirical survey to verify the applicability of the proposed LPS framework in the Indian manufacturing industry. They observed that many researchers proposed various LPS frameworks, but none of the researchers focused on verifying the proposed frameworks. To overcome, the same limitations, the study verified the proposed framework with the larger sample size.

Lean manufacturing (LM) is prevalent in the manufacturing industry; thus, focusing on fast and accurate lean tool implementation is the new paradigm in manufacturing. Value stream mapping (VSM) is one of the many LM tools. It is understood that combining LM implementation with VSM tools can generate better outcomes. This paper aims to develop an expert system for optimal sequencing of VSM tools for lean implementation.

A proposed artificial neural network (ANN) model is based on the analytic network process (ANP) devised for this study. It will facilitate the selection of VSM tools in an optimal sequence.

Considering different types of wastes and their level of occurrence, organizations need a set of specific tools that will be effective in the elimination of these wastes. The developed ANP model computes a level of interrelation between wastes and VSM tools. The ANN is designed and trained by data obtained from numerous case studies, so it can predict the accurate sequence of VSM tools for any new case data set.

The design and use of the ANN model provide an integrated result of both empirical and practical cases, which is more accurate because all viable aspects are then considered. The proposed modeling approach is validated through implementation in an automobile manufacturing company. It has resulted in benefits, namely, reduction in bias, time required, effort required and complexity of the decision process. More importantly, according to all performance criteria and subcriteria, the main goal of this research was satisfied by increasing the accuracy of selecting the appropriate VSM tools and their optimal sequence for lean implementation.

The purpose of this paper is to investigate, validity and reliability analysis on existing Lean manufacturing (LM) frameworks when applied to Indian organizations. LM is one of the best manufacturing strategies that are used by manufacturing plant managers to improve manufacturing capabilities.

In the present research work, a questionnaire-based survey was used to examine 35 LM frameworks. The study targeted respondents ranging from top- and middle-level management personnel in Indian manufacturing industry. The sample includes organizations in a variety of industries ranging from automobile, electronics, engineering, process and textile industries products. The survey tool was prepared with team of 12 members i.e. six academicians and six professionals from manufacturing industry environment. The study received 186 responses from various sectors of manufacturing industry, 180 surveys were usable resulting in a response rate of 23.90 per cent. Factor analysis was conducted to check unidimentionality of the framework. Cronbach’s alpha is calculated to find reliability of each framework’s. Lastly, frequency analysis was used to recognize familiar constructs of LM on the chosen framework.

This study has identified that most of the LM frameworks revealed a high level of reliability. When the study has examined further advance about unidimensionality with respect to the construct, i.e. the LM it measures, it confirmed 11 frameworks were revealing unidimensionality. The frequency analysis was evident that a greater part of the constructs has a high mean score and mode. Finally, the research concludes that there is requirement for a novel framework to Indian manufacturing industry to stay in competition with global manufacturing industries.

Cross-sectional data from manufacturing industries and India (only one country) is used with sample size restricted to 180 only, and it would be interesting to test these frameworks for more than one industry sector and country.

The present work tries to find the suitability of the presented LM frameworks to Indian manufacturing industry sector. The authors hoped that the present research would give the information to the management to execute the suitable LM framework in their firm.

The present work tries to find the suitability of the presented LM frameworks to Indian manufacturing industry sector. The authors hoped that the present research would give the information to the management to execute the suitable LM framework in their firm.

Several authors in extant literature have shown concern towards lacuna in availability of standard constructs in supply chain management (SCM). These standard constructs can represent pillars of SCM excellence. However, frameworks on SCM excellence unlike its contemporary fields are very few. Thus the purpose of this paper is to develop a path analysis for proposed framework of SCM excellence in Indian manufacturing industry proposed by Soni and Kodali (2014) using interpretive structural modelling (ISM) and structural equation modelling (SEM).

The ISM is performed on two exemplary cases of supply chain in Indian manufacturing industry. These cases were selected on the consideration of supply chain excellence index (SCEI), based on the results of an empirical study conducted by Soni and Kodali (2014) in Indian manufacturing industry. The focal manufacturing company which exhibited lowest and highest SCEI were selected as contenders for developing ISM. The relationships among pillars and constructs of SCM excellence framework are obtained from ISM, and later are subjected to statistical testing of model fit by using SEM. The input to SEM was the respondent’s data used in previous study.

The major findings revealed that ISM based on focal company having highest SCEI, is statistically fit for SCM excellence framework, and finally the structural models of the constructs for each pillar of SCM excellence are also formed by using path analysis.

The study offers a unique managerial approach for analysing the underlying relationships between pillars of SCM excellence. Researchers can use this study for developing frameworks in various realms of SCM excellence.

Lean manufacturing (LM) principles are one of the alternatives to improve manufacturing productivity, quality and customer satisfaction in Indian manufacturing industry. The purpose of this paper is to find the implementation status of LM principles across Indian manufacturing organizations through the empirical survey methodology.

The survey questionnaire was developed based upon literature review conducted on LM and also considered experts suggestion in the field of LM. The survey questionnaire was sent to 753 manufacturing organization located in India. The respondent organization details have gathered from the list of Confederation of Indian Industries directory for the year 2011.The selected respondents were production managers, quality managers, sales managers, maintenance managers, CEOs of the organization. The empirical survey collected 180 filled survey questionnaires from Indian manufacturing industries.

The study clearly identified that many manufacturing organizations were in initial transition stage and concentrating mostly in-plant operations instead of collaboration in all levels of business with suppliers and customers. The present study found that drivers for implementation of LM were customer satisfaction and organizational continuous improvement program. The present study also found that barriers to implement LM principles were employee resistance, implementing few elements of LM principles instead of the complete package of LM framework, budget constraints and lack of understanding of LM principles to shop floor managers. Finally the study concluded that Indian manufacturing organizations have to conduct continuous learning programmed to improve understanding of LM principles as well as to maintain their motivation level in apex point. The study also suggested that a systematic LM framework is needs to Indian manufacturing organizations, which will act as clear cut guiding torch to the organization managers to implement LM principles across organization.

The sample size of the present study was moderate number than previous studies. However the study only concentrated on manufacturing organizations across India. The results of the present study cannot generalize across all the sectors of Indian organizations.

The concept of LM was very popular among developed and developing countries in the world. Many research studies were performed across world to find the status of LM implementation in their countries. Very few research studies reported the status of LM implementation in Indian manufacturing industries and those studies also with limited focus of the status of LM implementation. Hence the study presented details status of LM principles implementation in Indian manufacturing industries.

The purpose of the article is to identify suitable existing lean product development (LPD) framework that is useful to implement in Indian manufacturing industry. The number of successful products is one of the most deciding factors in any organization revenue. Lean principles can be applied across product development processes to eliminate waste activities. Thus, to fulfill the objective, the present study has performed validity and reliability analysis on the existing LPD frameworks with the help of empirical data collected from Indian manufacturing sector through a survey questionnaire methodology.

The empirical data was collected from 180 manufacturing organizations from Indian manufacturing sector. The study has gathered the empirical data from respondents from top and middle level personnel. Factor analysis was conducted on the collected empirical data to find the unidimensionality of the each framework. Reliability of each individual framework was determined through Cronbach’s alpha value. Finally, the frequency distribution analysis was performed to find familiar constructs in the selected frameworks sorted on the basis of validity and reliability analysis.

The present study found that only eight LPD frameworks have displayed unidimensionality with respect to the construct, i.e. the LPD it measures. The study also found that those eight frameworks have displayed a high level of reliability. Further, the study tried to find the most familiar constructs from the selected eight frameworks by applying frequency distribution analysis. The frequency distribution analysis has identified that most of the constructs have showed a high value in terms of mode and mean. The study also concluded that there is a need to develop a new LPD framework, which is suitable to fulfill the requirements of Indian manufacturing industry, as well as global manufacturing industry.

The study collected empirical data from 180 organizations and all of the respondents were restricted from Indian manufacturing industry. Hence, the study believes that there is a chance some more amplification before being generalizes over across the sectors and countries.

The main objective of the present article is to find out the suitability of the existing LPD frameworks to Indian manufacturing sector. The study also anticipates that the products development managers and executives may collect complete information on the existing LPD frameworks and also a chance to executing proper suitable framework in the respective manufacturing organization.

Decision making in Flexible Manufacturing Systems (FMS) is difficult because of their high complexity level. The operational level of FMS is concerned with the detailed decision making required for real‐time operation. This applies to various control problems such as selection of a transportation path to move parts between stations. Describes a prototype knowledge‐based system for selection of a transport path in real‐time control of FMS. The knowledge‐based system is evaluated with an empirical approach.

The purpose of this paper is to review the existing literature on empirical research in lean manufacturing (LM). It provides a critical assessment of empirical research methodology of 178 research articles published from 1990 to 2009.

The article reviewed a set of 178 empirical research articles in LM research with respect to empirical research design and its related facets. The 236 empirical research articles which are published in 70 journals during 1990-2009 are collected from four major management science publishers, namely, Emerald Online, Science Direct, Springer Link and Taylor & Francis. In total 178 research articles published in 24 journals are selected for critical review of empirical research methodology in LM. The approach for the critical review of 178 empirical research articles in LM is based on empirical research approach given by Flynn et al. (1990). The critical review discusses the current status of empirical research in LM and future directions.

It is concluded from the analysis of the results that: the number of empirical research articles in LM is increasing at a faster pace than ever before; theory building and theory verification articles are equally advanced; the researchers have also unexplored various aspects of empirical research such as importance of triangulation of data, alternate research designs other than survey and case studies; contextual focus is mostly on the manufacturing industry; more focus required on other aspects of empirical research such as collecting the samples from developing and undeveloped countries, larger sample size, longitudinal data collection methods. Finally, it concludes that there is a need of LM frameworks, which gives the stepwise process to remove all kinds of wastes from any organization.

To the knowledge of the authors, it is the first of its kind attempt to critically review the empirical research articles in LM. The review analysis entirely focussed on descriptive statistics of empirical research in LM. The sample size is one of the unique features of this research as the number of shortlisted articles is 178 in 24 journals published over a time span of 20 years (1990-2009).

Manufacturing excellence means to be the best in the field at each competitive priority and to demonstrate industry best practices. Over the years there have been many pioneering efforts in the direction of the assessment and implementation of manufacturing excellence through various frameworks, but none of the existing frameworks was found to be suitable for the Indian scenario, and the completeness of existing Indian manufacturing excellence frameworks was also found to be lacking. Hence this paper aims to focus on the development of a new framework for providing direction and guidance to an organization in achieving manufacturing excellence in Indian industry.

A literature review was carried out to provide a brief overview about the 23 frameworks of manufacturing excellence/world‐class manufacturing as proposed by various researchers, consultants, international agencies and individuals. An attempt is made to propose a new framework for manufacturing excellence using the comparative analysis of the existing frameworks along with the domain knowledge of the concept of manufacturing excellence and through discussion with experts.

The outcome of this research is a framework of manufacturing excellence.

The proposed framework for manufacturing excellence needs to be validated through an empirical approach or by a clinical approach utilizing a case study.

Through comparative analysis, some unique elements/attributes were identified which represent the pillars of manufacturing excellence and through domain knowledge some more elements/attributes have been added. Sub‐attributes/sub‐elements for various pillars have also been identified.