Managing Agility via Fuzzy Logic: A Case Study of Machine Tool Industry
Material type: TextDescription: 64-79 pSubject(s): In: CHAKRAVORTY S K (EDITOR) PRODUCTIVITYSummary: Owing to fluctuating market demand, manufacturing with agile philosophy can be very useful to gain profit with less investment. This paper aims to measure agility of a machine tool organization using fuzzy logic method. The agility has been classified as management strategic agility, workforce agility, competence agility, manufacturing and technological agility. These four types of agility have been further sub-divided into their agile ability and capability. The data has been gathered on weight of variables and rate of these variables in the organization. The linguistic term of variables has been assigned fuzzy numbers and then fuzzy agility index and level of agility of organization has been calculated. The main obstacles have been identified and improvement plan for complete extreme agile organization has been suggested. The results of the study are expected to facilitate the firms interested in operating in agile environment. [ABSTRACT FROM AUTHOR]Item type | Current library | Call number | Vol info | Status | Date due | Barcode | Item holds | |
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Journal Article | Main Library | 58, No 1/ 5557362JA6 (Browse shelf(Opens below)) | Available | 5557362JA6 | ||||
Journals and Periodicals | Main Library On Display | JOURNAL/OPERATION/Vol 58, No 1/5557362 (Browse shelf(Opens below)) | Vol 58, No 1 (01/04/2017) | Not for loan | 5557362 |
Owing to fluctuating market demand, manufacturing with agile philosophy can be very useful to gain profit with less investment. This paper aims to measure agility of a machine tool organization using fuzzy logic method. The agility has been classified as management strategic agility, workforce agility, competence agility, manufacturing and technological agility. These four types of agility have been further sub-divided into their agile ability and capability. The data has been gathered on weight of variables and rate of these variables in the organization. The linguistic term of variables has been assigned fuzzy numbers and then fuzzy agility index and level of agility of organization has been calculated. The main obstacles have been identified and improvement plan for complete extreme agile organization has been suggested. The results of the study are expected to facilitate the firms interested in operating in agile environment. [ABSTRACT FROM AUTHOR]
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