A simulation-based optimization approach to size manufacturing systems

Der Trend zur Fertigung individualisierter Produkte in kleinen Losgrößen erfordert hochflexible Produktionssysteme. Durch die damit verbundene Systemdynamik wird die Reihenfolgeplanung zu einem komplexen Planungsproblem. Der Beitrag beschreibt ein simulationsbasiertes Optimierungsverfahren, welches Echtzeitinformationen zur adaptiven Selektion geeigneter Prioritätsregeln verwendet. Das Potenzial des Ansatzes wird anhand eines Anwendungsfalls aus der Halbleiterindustrie demonstriert.   The trend to manufacturing individualized products in small-scale series demands highly flexible production systems. Because of the dynamic nature of such production systems, scheduling becomes a complex planning problem with frequent need for rescheduling. This article describes a data-driven simulation-based optimization approach using real-time information for adaptive job shop scheduling. The potential of the approach is demonstrated by a use case from semiconductor industry.

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Simulationsbasierte Optimierung von Fabrikabläufen*/Simulation-based optimization of factory processes

wt Werkstattstechnik online ◽

10.37544/1436-4980-2018-04-27 ◽

2018 ◽

Vol 108 (04) ◽

pp. 221-227

Author(s):

T. Donhauser ◽

L. Baier ◽

T. Ebersbach ◽

J. Franke ◽

P. Schuderer

Keyword(s):

Calcium Silicate ◽

Optimization Approach ◽

Process Technology ◽

High Quality ◽

Decomposition Approach ◽

Planning And Control ◽

Simulation Based ◽

Simulation Based Optimization ◽

And Control

Die Kalksandsteinherstellung weist aufgrund prozesstechnisch und zeitlich divergierender Teilprozesse einen hohen Planungs- sowie Steuerungsaufwand auf. Durch Einsatz eines simulationsgestützten Optimierungsverfahrens kann diese Komplexität bewältigt werden. Um bei hoher Lösungsqualität eine Laufzeit zu erreichen, die einen operativen Einsatz des Verfahrens gestattet, wird auf Basis einer vorangegangenen Studie ein Dekompositionsansatz implementiert und dessen Eignung durch Testläufe validiert.   Calcium silicate masonry production requires a great deal of planning and control due to the fact that subprocesses vary in terms of process technology and time. To overcome this complexity, a simulation-based optimization approach is applied. As a short runtime that allows the method to be used operationally and yet still offers a high quality of solution is crucial, a decomposition approach is implemented on the basis of a previous study and its suitability is validated by means of test runs.

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Simulation-Based Optimization of Electricity Demand Response for Sustainable Manufacturing Systems

Volume 1: Materials; Micro and Nano Technologies; Properties, Applications and Systems; Sustainable Manufacturing ◽

10.1115/msec2014-4006 ◽

2014 ◽

Cited By ~ 1

Author(s):

Leah Cuyler ◽

Zeyi Sun ◽

Lin Li

Keyword(s):

Demand Response ◽

Manufacturing Systems ◽

Manufacturing Sector ◽

Sustainable Manufacturing ◽

Optimization Method ◽

Electricity Demand ◽

System Throughput ◽

Commercial Building ◽

Simulation Based ◽

Simulation Based Optimization

Electricity demand response is considered a promising tool to balance the electricity demand and supply during peak periods. It can effectively reduce the cost of building and operating those peaking power generators that are only run a few hundred hours per year to satisfy the peak demand. The research on the electricity demand response implementation for residential and commercial building sectors has been very mature. Recently, it has also been extended to the manufacturing sector. In this paper, a simulation-based optimization method is developed to identify the optimal demand response decisions for the typical manufacturing systems with multiple machines and buffers. Different objectives, i.e. minimizing the power consumption under the constraint of system throughput, and maximize the overall earnings considering the tradeoff between power demand reduction and potential production loss, are considered. Different energy control decisions are analyzed and compared regarding the potential influence on the throughput of manufacturing system due to the different control actions adopted by throughput bottleneck machine.

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