Asset Optimization and Predictive Maintenance in Discrete Manufacturing Industry

The current challenging issue in production is to deliver product in more efficient manner by controlling, monitoring and centralizing all intra-logistical processes. With the growing focus on sustainability, complexity grows even further as production managers have to manage energy and material consumption, carbon footprint, and waste output in addition to Key Performance Indicators like process efficiency, asset utilization, quality, scrap rate and costs. The research objective is to ensure the optimized use of available resources for a scheduled product plan with continuous asset monitoring in discrete manufacturing industry. A study of the existing methodologies for asset management and optimization is presented. The outcome of this study will provide a novel approach for asset management and optimization.