Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume 30, Issue 8, Pages 2871-2884Publisher
SPRINGER
DOI: 10.1007/s10845-018-1423-x
Keywords
Automation; Workforce diversity; Quality; Inclusive manufacturing; Good manufacturing practices (GMP); Bayesian belief network
Funding
- Council of Scientific and Industrial Research (CSIR), New Delhi
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In our technology-intensive world, manufacturing is transforming rapidly and is now driven by personalized demand. To deal with the modern manufacturing challenges, one requires an inclusive approach and therefore, a new paradigm has evolved shifting the manufacturing closer to the customer. This paper highlights the need for inclusive manufacturing along with its important aspects of automation, workforce diversity, and environment-friendly manufacturing operations. Variables pertaining to an inclusive manufacturing system were identified from the literature and were shortlisted based on the opinion of domain specialists. The causal relations among the variables are modeled using Bayesian network. The overall focus of the study lies in evaluating the impact of identified variables affecting product quality through the lens of an inclusive manufacturing system. Cascading effect of variables and the sensitivity analysis further build this study to conclude important observations and managerial insights.
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