Department of Mechanical engineering

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Author: search.filters.author.Digalwar, Abhijeet K.Subject: search.filters.subject.Critical success factors

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    Development and validation of quality management constructs for software industries: an empirical investigation from India
    (Inder Science, 2014-03) Digalwar, Abhijeet K.
    Quality management (QM) is a powerful technique for managing, monitoring, analysing and improving the operational performance. Various studies have been done in the manufacturing and service sectors to find out the relation between quality management practices and operational performance. Very little studies are found from software industries. The aim of this paper is to present results of a survey on QM in the software industries. The focus is on understanding the critical success factors (CSFs) for successful implementation of QM in the software industry. In total, 12 critical success factors (CSFs) with 114 variables were developed from the literature and discussions with software quality professionals. To validate the data obtained from a survey of software industries in India, reliability and validity analysis was carried out. These results provide an increased understanding of how to better implement QM in the software industry, and provide managers with improved guidelines for identifying the most important factors that will lead to success. Indian software companies are leading exporters to Europe and the USA. Considering the growth of the Indian software industry and increased inclination towards acquiring quality certifications and quality improvement techniques, a better understanding of the implementation of QM can provide companies with a stronger competitive advantage.
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    Green manufacturing performance measures: an empirical investigation from Indian manufacturing industries
    (Emerald, 2013-11) Digalwar, Abhijeet K.
    The purpose of the paper is to explore the performance measures for the green manufacturing practices in the Indian manufacturing industries.
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    Evaluation of world-class manufacturing systems: a case of Indian automotive industries
    (Inder Science, 2008-06) Digalwar, Abhijeet K.; Sangwan, Kuldip Singh
    Many industries are implementing World-Class Manufacturing (WCM) systems to compete in the global market. However, the researchers in the area of WCM have not paid much attention to the techniques/methodologies for the evaluation of WCM systems. This paper presents a set of validated critical success factors and their performance variables for WCM industries. The reliability and validity analyses were carried out by using the SPSS? 11.5 statistical tool on the data obtained from the Indian automotive industries. A multiattribute decision model, i.e., Performance Value Analysis (PVA), was developed for the evaluation of WCM systems. The usefulness of the model is demonstrated using a case situation of the Indian automotive industry. By utilising this model, it is expected that managers/decision makers will acquire sufficient confidence in evaluating world-class automotive industries.
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    Development and validation of performance measures for world class manufacturing practices in India
    (World Scientific, 2007) Sangwan, Kuldip Singh; Digalwar, Abhijeet K.
    This paper aims to develop and validate performance measures for world class manufacturing (WCM) in Indian context that could be used by managers/ practitioners in assessing and improving their manufacturing performance. Using a thorough synthesis of the world class manufacturing literature, sixteen performance measures — top management commitment, knowledge management, employee training, innovation and technology, employee empowerment, environmental health and safety, supplier management, production planning and control, quality, flexibility, speed, cost, customer involvement, customer satisfaction, customer services and company growth — of world class manufacturing and their 89 variables have been developed. Using the data obtained from a survey of manufacturing industries in India, the identified performance measures were subjected to appropriate statistical tests to establish reliability and validity. Statistical computing package SPSS 11.5 for Windows was used for reliability and validity analysis. The validated instrument of world class manufacturing measures developed here may be used by manufacturing organizations to prioritise their management efforts to assess and implement WCM. The validated results are in Indian context, however, the instrument developed can be used in global context.