A decision support system driven by artificial intelligence for industrial applications

Abstract

Decision-making in industrial settings is a continuous process that drives the organization's overall performance. It implies consistently selecting the optimal alternative, regularly reviewing the effectiveness of the decision, learning from its consequences, and refining the decision-making framework accordingly. in the modern era, characterized by the abundance of data, the ineffectiveness of conventional multi-criteria decision-making methods to process large volumes of data prevails over their ability to manage the multidimensional nature of decision-making in industrial settings, hence to cope with the increasing complexity of process industrials are challenged to explore the potential of artificial intelligence to optimize their decisions. In the current work, a new decision-making approach is introduced, the model combines artificial neural networks with the Analytic Hierarchy Process and the balanced scorecard to provide real-time decision-making recommendations for complex industrial problems.

Key words: Industrial performance, Artificial Neural Network, Analytical Hierarchy Process, Decision support system.

Received Date: April 10, 2024                  Accepted Date: May 10, 2024            

Published Date: June 01, 2024

Available Online at: https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/154

DOI: https://doi.org/10.5281/zenodo.11244054