Integrated Smart Warehouse and Manufacturing Management with Demand Forecasting in Small-Scale Cyclical Industries

In the context of global economic slowdown, demand forecasting, and inventory production management have long been important topics to industries. With support smart warehouses, big data analytics, optimization algorithms, enterprises can achieve economies scale, balance supply demand. Smart warehouse manufacturing is considered culmination recently advanced technologies. It enhance scalability extendibility industry. Despite many researchers having developed frameworks for various fields, most these models are mainly focused on logistics product not generalized tackle specific problem facing in cyclical Indeed, industry has a key problem: risk which high sensitivity poses business cycle recession, difficult foresee. approaches being proposed optimize level facilitate management, forecasting technique seldom cyclic On other hand, usually based complex process instead integrating stock, very crucial composing warehouses manufacturing. This research study digital twin framework by with roulette genetic algorithm We also demonstrate how this practically implemented demand, sustaining optimization, achieving optimization. adopted small-scale textile company case results Various scenarios were conducted simulate twin. The help manufacturers companies improve management. theoretical practical significance