Simio’s RPS was implemented to improve the production scheduling at the John Deere Cast Iron Foundry in Waterloo Iowa. Many industries demand complex sequencing that involves multiple constraints in order to find the most feasible production schedule. This is particularly true for the highly automated and complex John Deere Cast Iron Foundry, which produces several hundred parts with various iron recipes and production constraints. The challenge was to have an integrated production scheduling system that allows for real-time data exchange between the Wonderware MES, and SAP ERP, as well as a system that could create a schedule based on the actual status of the production line with complex production constraints. The solution was implemented using Simio’s RPS, and it has allowed us to consider complex material requirements, equipment resource availability, due dates, and nine different sequencing constraints.
John Deere has not published a case study on this application, but this description is a summary of the presentation abstract, approved by John Deere, for Simulation-Based Scheduling at John Deere, which was given at the 2015 IIE Annual Conference and Expo in Anaheim, California.