AI-POWERED PROCESS OPTIMIZATION: REDUCING WASTE AND IMPROVING EFFICIENCY IN THE INDUSTRIAL SECTOR OF UDAIPUR, RAJASTHAN – A SECONDARY DATA ANALYSIS

Abstract

Artificial Intelligence (AI) has emerged as a transformative tool for enhancing operational efficiency, reducing resource wastage, and enabling sustainable industrial growth. In India, while large manufacturing clusters have begun adopting AI-powered technologies, smaller industrial hubs such as Udaipur, Rajasthan remain at an early stage of digital transformation. This study explores the potential of AI-powered process optimization to reduce waste and improve efficiency in Udaipur’s industrial sector through a comprehensive analysis of secondary data. The research draws upon government reports, industry publications, and academic studies to assess existing industrial practices, identify opportunities for AI integration, and examine the challenges that impede adoption. Findings indicate that sectors such as marble processing, mining, and small-scale manufacturing exhibit significant inefficiencies that can be addressed through predictive maintenance, real-time analytics, and AI-enabled quality control systems. The study concludes with strategic recommendations to support AI adoption in Udaipur’s industries through capacity building, policy interventions, and technological partnerships, thereby contributing to sustainable industrial development in the region.