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On the Exploitation of Automated Planning for Reducing Machine Tools Energy Consumption Between Manufacturing Operations

Parkinson, Simon, Longstaff, Andrew P., Fletcher, Simon, Vallati, Mauro and Chrpa, Lukáš (2017) On the Exploitation of Automated Planning for Reducing Machine Tools Energy Consumption Between Manufacturing Operations. In: Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling (ICAPS 2017). Association for the Advancement of Artificial Intelligence AAAI, pp. 400-408.

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Abstract

There has recently been an increased emphasis on reducing energy consumption in manufacturing, driven by the fluctuations in energy costs and the growing importance given to environmental impact of manufactured goods. Lots of attention has been given to the reduction of machine tools energy consumption, as they require large amounts of energy to perform manufacturing tasks.

One area that has received relatively little interest, yet could harness great potential, is reducing energy consumption by planning machine activities between manufacturing operations, while the machine is not in use. The intuitive option --which is currently exploited in manufacturing-- is to leave the machine in a normal operating state in anticipation of the next manufacturing job. However, this is far from optimal due to the thermal deformation phenomenon, which usually require an energy-intensive warm-up cycle in order to bring all the components (e.g. spindle motor) into a suitable (stable) state for actual machining. Evidently, the use of this strategy comes with the associated commercial and environmental repercussions.

In this paper, we investigate the exploitability of automated planning techniques for planning machine activities between manufacturing operations. We present a PDDL 2.2 formulation of the task that considers energy consumption, thermal deformation, and accuracy. We then demonstrate the effectiveness of the proposed approach using a case study which considers real-world data.

Item Type: Book Chapter
Subjects: Q Science > QA Mathematics > QA76 Computer software
Schools: School of Computing and Engineering
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
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Depositing User: Simon Parkinson
Date Deposited: 30 Mar 2017 10:52
Last Modified: 10 Aug 2017 07:39
URI: http://eprints.hud.ac.uk/id/eprint/31661

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