Campaign planning and scheduling for multiproduct batch operations with applications to the food-processing industry

We analyze planning and scheduling of multiproduct batch operations in the food-processing industry. Such operations are encountered in many applications including manufacturing of sorbitol, modified starches, and specialty sugars. Unlike discrete manufacturing, batch sizes in these operations cannot be set arbitrarily, but are often determined by equipment size. Multiple batches of the same product are often run sequentially in “campaigns” to minimize setup and quality costs. We consider a multiproduct, single-stage, single-equipment batch-processing scheme and address the problem of determining the timing and duration of product campaigns to minimize average setup, quality, and inventory holding costs over a horizon. We formulate the deterministic, static version of this problem over an infinite horizon. We show that, in general, a feasible, finite, cyclic solution may not exist. We provide sufficient conditions for the existence of a finite cycle, use single-product problems to provide lower bounds on the costs for the multiproduct problem, and use them to test heuristics developed for this problem. Next, we modify this formulation to incorporate fixed cycles that may be necessary due to factors such as product obsolescence, perishability, or contracts with customers. We do this by allowing for disposal of excess stock so that finite cycles are always feasible, though they might not be optimal; we also develop bounds and heuristic solution procedures for this case. These methods are applied to data from a leading food-processing company. Our results suggest that our methods could potentially reduce total annual costs by about 7.7% translating to an annual savings of around $7 million.