Artificial Intelligence-Driven Integrated Business Planning For Production Optimization In Healthcare Manufacturing Supply Chains

Abstract

Healthcare manufacturing supply chains operate within an environment shaped by demand volatility, layered regulatory obligations, and deep interdependencies across global supplier networks. Static forecasting models and periodic planning cycles are structurally inadequate for managing these conditions, producing capacity imbalances, inventory waste, shelf-life losses, and product shortages during periods of acute demand pressure. This article looks at how AI-based Integrated Business Planning (IBP) frameworks can overcome these structural challenges by creating a unified decision architecture to manage demand signals, production capabilities, and supplier capabilities. Specific areas of focus include demand forecasting, operational constraint mapping, scenario simulation, shelf-life risk mitigation, and executive analytics platforms. The article concludes with a synthesis of these capabilities in the Decision Intelligence Framework and the implications of optimizing production in healthcare manufacturing for society and public health.