Improving the Planning Quality in Practice with Artificial Intelligence

Czarnetzki, L and Karnok, Dávid and Breitschopf, J and Karner, M and Gashi, M (2023) Improving the Planning Quality in Practice with Artificial Intelligence. In: 19th IMEKO TC10 Conference “MACRO meets NANO in Measurement for Diagnostics, Optimization and Control” Delft, The Netherlands, September 21–22, 2023, Proceedings. IMEKO, Delft, pp. 33-38. ISBN 9789299009048

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Accurate production planning is economic interest of manufacturing companies. Reducing the work-inprogress levels, the lead time or control efforts with the simultaneous increase of utilization and adherence to schedule might lead to instantaneous cost reduction and to increased competitiveness on long-term. In the era of digitization various artificial intelligence-based methods have been investigated by the scientific community to improve these key performance indicators. In this paper the results of a joint research project dealing with planning quality improvement with the help of Machine Learning (ML) are summarized. The results of two use case studies investigating the application and suitability of different planning approaches in the semiconductor and steel industries are presented and considerations regarding the practical application of ML assisted planning approaches are discussed.

Item Type: Book Section
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Research Laboratory on Engineering & Management Intelligence
SWORD Depositor: MTMT Injector
Depositing User: MTMT Injector
Date Deposited: 06 Dec 2023 08:15
Last Modified: 06 Dec 2023 08:15

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