Madlene Leißau, Christoph Laroque • Winter Simulation Conference 2023, San Antonio (USA)

Researchers are investigating innovative techniques and tools to improve operational production planning, as manufacturing processes are increasingly influenced by new product demands, innovation, and cost-effectiveness. Backward-oriented discrete event simulation (SimBack) is one such tool that has shown great promise in this area. However, conducting multiple simulation runs for backward simulation can be time and resource-intensive, hampering its efficiency. To address this issue, this paper proposes an automated approach for executing and evaluating simulation experiments within the framework of backward-oriented discrete event simulation for scheduling and capacity planning. The authors illustrate their approach by applying it to a simulation model of the Semiconductor Manufacturing Testbed 2020 (SMT2020).

ResearchGate

Wolfgang Scholl, Patrick Preuß, Madlene Leißau, Christoph Laroque • Winter Simulation Conference 2023, San Antonio (USA)

In modern manufacturing environments, the digital transformation to smart factories cannot be achieved without data-driven methods like discrete, event-driven simulation. This paper provides an overview of existing current simulation applications at Infineon Dresden in this area, especially on short-term simulation for production control and long-term simulations to forecast process flows in the wafer fabrication facilities. Furthermore, it illustrates the current status of research activities in the area of backward simulation for operational decision support for order scheduling by some latest research results.

ResearchGate

Alp Akcay, Stephan Biller, Boon Ping Gan, Christoph Laroque, Guodong Shao • Winter Simulation Conference 2023, San Antonio (USA)

Digital twins have become an important element in smart manufacturing. As any other product, digital twins also have a lifecycle, starting from specifying the requirements of the digital twins until their decommissioning. As part of the Manufacturing and Industry 4.0 track of the Winter Simulation Conference (WSC), the purpose of this panel is to discuss the state of the art in digital twins with a special emphasis on the operations and maintenance of manufacturing digital twins during their lifecycles. The panelists come from academia, industry, and government with experience in the digital-twin landscape of the manufacturing industry in the United States, Europe, and Asia. This paper provides a collection of the statements from each panelist with the objective of initiating a deeper discussion during the panel session and inspiring researchers in the simulation community with their perspectives on the use of digital twins for smart manufacturing.

ResearchGate

Deike Gliem, Sigrid Wenzel, Wibke Kusturica, Christoph Laroque • Industry 4.0 Science 1(1)

The planning of logistics processes and their efficient implementation are decisive competitive factors for customized plant construction. On the construction site, however, the collection of logistics data is often neglected, preventing the project planner from building a reliable database. Related information gaps can be closed with the help of a digital shadow that collects logistics-relevant data (partially) automatically, stores them in a consistent manner and makes them available to project management. This article describes the first important results of a research project on information and communication processes in construction site logistics and explains their vital role in the development and use of a digital shadow.

ResearchGate

Anna-Maria Nitsche, Christian-Andreas Schumann, Christoph Laroque, Olga Matthias • Apply Data Science

This chapter deals with the changes caused by digital transformation that confront companies with more intense competition, performance pressure and growing customer demands. The quest for increased competitiveness and efficiency is expressed above all in the implementation of (innovative) technological solutions and the increasingly automated and data-driven decision-making processes. The presented tool, the TOCI model (Technological and Organizational Coherence Implementation model), was developed specifically for the implementation of innovative technologies in business practice. The method takes into account the coherence of various factors, including the required changes to the organizational decision support processes. The TOCI model was developed based on well-known models from the academic literature, such as the technology acceptance model, the agile process management method Scrum, the CRISP-DM process model and the Stage-Gate model. In addition, socio-technical system methods and insights from the theory of situational leadership are integrated.

ResearchGate