Prof. Dr. Lars Mönch
Photo: Photo: Hardy Welsch
Contact
Email: lars.moench
Institutional Affiliation
Faculty of Mathematics and Computer Science
Chair of Enterprise-wide Software Systems
Additional information: Profile (faculty page, in German only)
Research Interests
(in the fields covered by the research center)
In the high-tech sector, and in the semiconductor industry in particular, integrated circuits are manufactured using extremely expensive machinery. Traditionally, the main focuses have been on ensuring on-time delivery and high utilization of these machines. In recent years, however, sustainability aspects have also gained importance. This research group is interested in how sustainability aspects can be modeled in the supply chains of the high-tech industry and incorporated into production planning and scheduling problem algorithms as well as simulation models. Embedding the developed methods in information systems is another area that is being researched. In terms of methodology, the group primarily uses linear and mixed-integer optimization, simulation-based optimization, and multi-objective metaheuristics.
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(in the fields covered by the research center)
- Schorn, D.; Mönch, L. (2024): A Genetic Programming Approach to Solve Flexible Flow-shop Scheduling Problems with Batching and Time Constraints , Flexible Services and Manufacturing Journal, eingereicht
- Schorn, D.; Mönch, L. (2024): Learning Priority Indices for Energy-Aware Scheduling of Jobs on Batch Processing Machines, IEEE Transactions on Semiconductor Manufacturing, 37(1), pp. 3-15.
- Rocholl, J.; Mönch, L.; Fowler, J. W. (2018): Electricity Power Cost-aware Scheduling of Jobs on Parallel Batch Processing Machines, Proceedings of the 2018 Winter Simulation Conference, Göteborg.
- Ziarnetzky, T.; Mönch, L.; Kannaian, T.; Jimenez, J. (2017): Incorporating Elements of a Sustainable and Distributed Generation System into a Production Planning Model for a Wafer Fab, Proceedings of the 2017 Winter Simulation Conference, Las Vegas, pp. 3519-3530.
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(in the fields covered by the research center)
Artificial Intelligence in Manufacturing leading to Sustainability and Industry5.0 (AIMS5.0)
Sub-project of the FernUniversität: "Nachhaltige Planungs- und Steuerungsprozesse in Lieferketten der Halbleiterindustrie" ("Sustainable planning and control processes in supply chains of the semiconductor industry")
IMS5.0, a collaborative Innovation Action, aims at strengthening European digital sovereignty in comprehensively sustainable production. The project and its well-balanced consortium with 53 ambitious academic and industry partners intends to boost the economy by adopting, extending and implementing AI-enabled hardware and software components and systems across the whole industrial value chain.
New technologies from IoT and based on Semantic Web ontologies, ML (Machine Learning) and AI (Artificial Intelligence) will help European manufacturers to shift from Industry4.0 to Industry5.0, creating human-centric workplace conditions and a climate-friendly production.
We will see AI enabled fabs way more productive and eco-efficient. This will go hand in hand with shorter supply chains, a better resilience, a higher sustainability and global competitiveness keeping the main production in Europe.
