Modeling and Optimization of IoT Factors to Enhance Agile Manufacturing Strategy-based Production System Using SCM and RSM. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Vates, Umesh Kumar; Sharma, Bhupendra Prakash; Kanu, Nand Jee; Gupta, Eva; Singh, Gyanendra Kumar
• Is Part Of: Smart science. Volume 10:Issue 2(2022)
• Page Start: 158
• Page End: 173
• Publication Date: 2022-04-03
• Subjects: Critical enablers -- JSI data collection approach -- RSM optimization -- SCM analytical tool and validation
• DOI: 10.1080/23080477.2021.2017543
• Languages: English
• ISSNs: 2308-0477

Abstract

ABSTRACT: Agile Manufacturing is a widely accepted strategy by most organizations as a tool to compete in the market. The success of an industrial product or organization depends on their ability to short out the critical and regular factors of agile manufacturing. Identification of suitable implementation of critical enablers could highlight industrial issues to enhance the process performance. The present research aimed to depict the critical enablers of agile manufacturing through the enablers of Internet of things (IoT) to improve the profitability and product quality. The methodologies adopted for the depiction of enablers in the research are similarity coefficient matrix (SCM) and Jaccard's Similarity Index (JSI). The impact of organizational level, technological level, and employee-level enablers on IoT clusters were investigated analytically through SCM and JSI. JSI is applied to acquire data by survey and then a dendrogram is generated on the basis of the calculations done through this index. Response surface methodology (RSM) was also adopted to optimize the critical IoT enablers and it is validated with an analytical result. GRAPHICAL ABSTRACT: uf0001