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Open AccessArticle

Simulation-Based Multi-Criteria Optimization of Parallel Heat Treatment Furnaces at a Casting Manufacturer

1
Fraunhofer Austria Research GmbH, 1040 Vienna, Austria
2
Department of Industrial and Systems Engineering, Institute of Management Science, Vienna University of Technology, 1040 Vienna, Austria
3
Research Division of Automation Systems, Institute of Computer Engineering, Vienna University of Technology, 1040 Vienna, Austria
*
Author to whom correspondence should be addressed.
J. Manuf. Mater. Process. 2020, 4(3), 94; https://doi.org/10.3390/jmmp4030094
Received: 10 August 2020 / Revised: 12 September 2020 / Accepted: 14 September 2020 / Published: 17 September 2020
(This article belongs to the Special Issue Cyber Physical Production Systems)
This paper presents the development and evaluation of a digital method for multi-criteria optimized production planning and control of production equipment in a case-study of an Austrian metal casting manufacturer. Increased energy efficiency is a major requirement for production enterprises, especially for energy intensive production sectors such as casting. Despite the significant energy-efficiency potential through optimized planning and the acknowledged application potential for sophisticated simulation-based methods, digital tools for practical planning applications are still lacking. The authors develop a planning method featuring a hybrid (discrete-continuous) simulation-based multi-criteria optimization (a multi-stage hybrid heuristic and metaheuristic method) for a metal casting manufacturer and apply it to a heat treatment process, that requires order batching and sequencing/scheduling on parallel machines, considering complex restrictions. The results show a ~10% global goal optimization potential, including traditional business goals and energy efficiency, with a ~6% energy optimization. A basic feasibility demonstration of applying the method to synchronize energy demand with fluctuating supply by considering flexible energy prices is conducted. The method is designed to be included in the planning loop of metal casting companies: receiving orders, machine availability, temperature data and (optional) current energy market price-data as input and returning an optimized plan to the production-IT systems for implementation. View Full-Text
Keywords: production planning and control; simulation; optimization; genetic algorithm; heuristics; energy efficiency; heat treatment; scheduling; batching; case study production planning and control; simulation; optimization; genetic algorithm; heuristics; energy efficiency; heat treatment; scheduling; batching; case study
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Sobottka, T.; Kamhuber, F.; Heinzl, B. Simulation-Based Multi-Criteria Optimization of Parallel Heat Treatment Furnaces at a Casting Manufacturer. J. Manuf. Mater. Process. 2020, 4, 94.

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