Capacity analysis for mixed technology production: evaluating production ramp resource modifications via distributed simulation

This paper describes the design and development of a discrete event simulat ion based, dynamic, capacity analysis tool. Manufacturing capacity analysis , traditionally approached through the prescribed tools of mathematical pro gramming, is presently devoid of a dynamic simulation framework that delive rs multi-period asset evaluations based on a real-time performance estimate . A suggested framework for this class of decisions involves periodic (quar terly), deterministic, constrained evaluation models to specify resource al location decisions. Capacity evaluation models are inherently non-stationar y due to the structural modifications that occur when adding new production resources. Homogeneity is employed here in the uniform description of hete rogeneous resources as general mathematical objects, or discrete event mode ls (DEVS). Each object represents both the individual production resource's dynamic state and static parameters. Exercising these objects via simulati on optimizes resources through Return on Operating Assets (ROOA), a fixed a nd variable cost roll-up metric that results in a balance between capital a ssets (machines) and work-in-process (WIP) allocation for a given demand le vel. Global optimization is achieved through distributed DEVS/CORBA adminis trators that monitor and constrain asset investment in the sequential conca tenation of time periods. While the production model captures the flow beha viour of manufacturing operations and its performance scale, strategic scop e is built into the administrator via alternative rule bases, or specialize d management decision sets. Using System Entity Structure Alternative Evalu ation (SEAE), these specialized alternatives reconfigure the plant model to produce the non-intuitive results for the different production ramp-up sce narios evaluated.