The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach

Abstract

Background: Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) technology in the manufacturing sector (MS). Methods: Through an inclusive study, we identify 11 factors within the research background that could be seen as holding significance for machine learning in the manufacturing sector. An interpretive structural modeling (ISM) method is used, and inputs from experts are applied to establish the relationships. Results: The findings from the ISM model show the ‘order fulfillment factor as the long-term focus and the ‘market demand’ factor as the short-term focus. The results indicate the critical factors that impact the development of machine learning in the manufacturing sector. Conclusions: Our research contributes to the manufacturing sector which aims to incorporate machine learning. Using the ISM model, industries can directly point out their oddities and improve on them for better performance.

Artificial Intelligence Capabilities for Demand Planning Process

“…Through employing these approaches, intricate and non-linear correlations between sales and the attributes of previously sold products can be established, enabling the prediction of future item sales. Lakra et al [47] argued that predicting the production timing of specific goods and anticipating market demand can be readily achieved by employing machine learning. This technology enables accurate forecasts in logistics and demand, ensuring the creation of high-quality products to satisfy customer preferences.…”