Case Study 29 of Industrial Engineering ONLINE Course
Industrial Engineering Case Studies Collection
2017
RESULTS
Production supported sales growth target of 18%
Reduced foundry rejects by 50%
Improved labor and inventory management, equipment uptime and maintenance
Improved productivity by 30%
Minimized the completion time to meet due dates
https://www.nist.gov/mep/successstories/2017/scheduling-model-substantially-improves-foundry-productivity
2017
Batesville Products Inc. (BPI) is a job shop operating an aluminum/zinc foundry, polishing, and machine shop. It is Located in Southeast Indiana and currently has 87 employees. As, it was felt that there were problems in scheduling of permanent mold casting operations leading to lower production, BPI invited a Purdue Industrial Engineering graduate student to lead a project to develop a more optimal schedule for the foundry.
After studying and modeling the operations, its processes, and the associated cost, the Purdue engineering student developed a multi-objective heuristic algorithm to produce a scheduling tool for BPI. The technology factored in the routing of material/semi-products, setup times, cycle times, resource utilization, temperature, and gas level to identify the best scheduling method. Implementing the "scheduling model optimizer” and its proposed schedule, resulted in increased pounds poured by worker hours and decreased the time required to meet due dates. The schedule provided time for maintenance and equipment uptime also increased. The stable and feasible schedules also reduced the number of foundry rejects by half. The economic impact of these improvements has been positive.
RESULTS
Production supported sales growth target of 18%
Reduced foundry rejects by 50%
Improved labor and inventory management, equipment uptime and maintenance
Improved productivity by 30%
Minimized the completion time to meet due dates
https://www.nist.gov/mep/successstories/2017/scheduling-model-substantially-improves-foundry-productivity
Scheduling injection molding operations with multiple resource constraints and sequence dependent setup times and costs
Satyaki Ghosh Dastidar, Rakesh Nagi
Department of Industrial Engineering, University at Buffalo (SUNY), 342 Bell Hall, Buffalo, NY 14260, USA
Computers & Operations Research 32 (2005) 2987–3005
A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint
MPE 2017
Accompanies Lesson 29 Harrington Emerson - A Pioneer Industrial Engineer - His Principles and Practices
Ud 27 May 2021
Pub 15 June 2020
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