A simulation-based and flexi-time applying prediction model for resilient roster generation and workforce dimensioning for decentrally controlled production systems

• Applicant: Professor Dr.-Ing. Thorsten Schmidt
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 439188616

While flexible working time models have become standard in office environments, production employees still mostly work in largely rigid shift systems. In the predecessor DFG research project "A simulation-based and flexi-time applying prediction model for scheduling personnel deployment times in the production planning process of cyber-physical systems" (project number 439188616), we already investigated the "Dilemma of workforce rostering for decentrally controlled production systems” including working time flexibilization and desired working times of employees. Building on that research, we focus in our current project "Flexibilization of working hours for production employees" on the following two sub-areas: 1) Resilience of workforce rosters despite stochastic influences, and 2) Requirements for the long-term shape of the workforce (esp. the qualification structure) when applying time-flexible working time models in decentralized controlled production. The generation of resilient workforce rosters includes investigations on the robustness and the regeneration capability in case of disturbances and failures in the daily production routine. The goal is the identification of influences and effects of stochastic parameters. This includes topics such as adaptive planning horizons, rescheduling, decision-making autonomy of the decentralized control and current complexity drivers, such as the shortage of skilled workers. For the long-term dimensioning of the workforce, we analyze the conditions and the required development of workforce structures as well as their effects on the production system. This includes, for example, varying order scenarios, different qualification scenarios, potentials and risks in the integration of part-time employees and the shortage of skilled workers as a complexity driver. For our investigations we use a simulation-based optimization that is based on the methodology of the predecessor project. We will extend this methodology according to the project requirements, so that an inner optimization cycle (roster generation and evaluation of the production runs) and an outer optimization cycle (long-term workforce dimensioning) is created.

• DFG Programme: Research Grants