Analyzing the factors in industrial automation using analytic hierarchy process. (October 2018)

• Record Type: Journal Article
• Authors: Acharya, Vikas; Sharma, Somesh Kumar; Kumar Gupta, Sunand
• Is Part Of: Computers & electrical engineering. Volume 71(2018)
• Page Start: 877
• Page End: 886
• Publication Date: 2018-10
• Subjects: Industrial automation (IA) -- Analytic hierarchy process (AHP) -- Sustainable manufacturing -- Manufacturing industry -- Optimization; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.08.015
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Industrial automation (IA) is a major manufacturing strategy which employs modern techniques and practices in manufacturing to achieve sustainable competitive advantage in the manufacturing industry. This research aims to categorize AI factors and examine its relative importance for better implementation in manufacturing industries. The relative importance and ranking of AI factors in manufacturing industry was done through a literature review, discussion with experts, and analytic hierarchy process (AHP) approach. In all, 13 IA factors were identified and further divided into three factor categories. Then their prioritization was done using AHP approach to assign the relative importance of these 13 factors affecting the industrial automation in manufacturing industries. The result will help the manufacturing industry mangers to work upon them based on their relative importance to improve their industrial automation performance. Finally, limitations, managerial implications, and scope of future study are presented at the end of the paper.