Development and validation of resource flexibility measures for manufacturing industry
Chauhan, Gulshan (Creator), Singh, T.P. (Creator)
Purpose: Global competition and ever changing customers demand have made manufacturing organizations to rapidly adjust to complexities, uncertainties, and changes. Therefore, flexibility in manufacturing resources is necessary to respond cost effectively and rapidly to changing production needs and requirements. Ability of manufacturing resources to dynamically reallocate from one stage of a production process to another in response to shifting bottlenecks is recognized as resource flexibility. This paper aims to develop and validate resource flexibility measures for manufacturing industry that could be used by managers/ practitioners in assessing and improving the status of resource flexibility for the optimum utilization of resources. Design/methodology/approach: The study involves survey carried out in Indian manufacturing industry using a questionnaire to assess the status of various aspects of resource flexibility and their relationships. A questionnaire was specially designed covering various parameters of resource flexibility. Its reliability was checked by finding the value of Cronback alpha (0.8417). Relative weightage of various measures was found out by using Analytical Hierarchy Process (AHP). Pearson’s coefficient of correlation analysis was carried out to find out relationships between various parameters. Findings: From detailed review of literature on resource flexibility, 17 measures of resource flexibility and 47 variables were identified. The questionnaire included questions on all these measures and parameters. ‘Ability of machines to perform diverse set of operations’ and ability of workers to work on different machines’ emerged to be important measures with contributing weightage of 20.19% and 17.58% respectively. All the measures were found to be significantly correlated with overall resource flexibility except ‘training of workers’, as shown by Pearson’s coefficient of correlation. This indicates that companies do not want to spend on worker t
Downloadable Archival Material, English, 2014-04
OmniaScience, 2014-04