Sustainable Personnel Planning in Highly Customized Assembly Lines with Work Sharing
Final Report Abstract
Work sharing refers to an organization of work where the responsibility for some accomplishment is shared between several actors; this requires the work efforts of the actors to be coordinated and properly synchronized. Work sharing promises several advantages for companies. For instance, work sharing may reduce the variance in station loads and increase the cost efficiency by allowing actors (e.g., workers or machines) from stations with relatively small workload to assist finishing jobs at bottleneck stations. However, the (algorithm supported) planning of systems with 3 work sharing poses multiple challenges. Hence, the aim of this project was to develop methodological quantitative planning instruments for an effective management of systems with work sharing. We approached this goal along three main lines, which resulted in six scientific articles. Quantitative planning approaches for basic work sharing systems. In a very basic setting, actors, each with a different set of competences, have to support each other to fulfill the assigned work. Their efforts need to be temporally and spatially coordinated. This basic setting frequently arises, for instance, in systems with autonomous vehicles (AVs) such as drones. In this context, we studied work sharing between various AVs in logistics and production applications and in disaster relief. We focused on settings with full and incomplete information, performed advanced analysis, and developed customized solution algorithms. In a case study, for example, we reduced the duration of a search mission for missing persons in case of a disaster by 20%. Human aspects in work sharing systems. We investigated selected human aspects that play a pivotal role in work sharing systems. Müller and Kress (2022) studied workforce constraints in the context of flexible job shops. Hosseini et al. (2023) studied the specificity of workforce, machine and product mobility in manufacturing in an extended literature review. We also performed a case study in the final assembly of an aerospace manufacturer, which features aspects of responsibility in work sharing. Optimization of data collection. Planning of work sharing usually requires explicit data on precedence relations – precedences – between tasks. This data has to be highly accurate and complete: If a precedence between a certain pair of tasks is missing, the resulting manufacturing plan may turn out infeasible. In practice, naïve approaches to the collection of data on precedences are prohibitively expensive, especially for the assemblies of large and complex products. We formalize the problem of data collection via targeted and adjustable expert interviews, perform advanced analysis of the resulting problem and develop a customized AI algorithm.
Publications
- Filter-and-fan approaches for scheduling flexible job shops under workforce constraints. International Journal of Production Research, 60(15), 4743–4765.
Müller, D., & Kress, D.
(See online at https://doi.org/10.1080/00207543.2021.1937745) - The Piggyback Transportation Problem: Transporting drones launched from a flying warehouse. European Journal of Operational Research, 296(2), 504–519.
Wang, K., Pesch, E., Kress, D., Fridman, I., & Boysen, N.
(See online at https://doi.org/10.1016/j.ejor.2021.03.064) - On delivery policies for a truck-and-drone tandem in disaster relief. Working Paper Series of the Chair of Man-agement Science/Operations and Supply Chain Management of the University of Passau.
Otto, A., Golden, B., Lorenz, C., Luo, Y., Pesch, E., & Poikonen, S.
- Resolving the curse of poor data quality: Optimization perspective on data collection and validation. Working Paper Series of the Chair of Man-agement Science/Operations and Supply Chain Management of the University of Passau.
Finnah, B., Gönsch, J., & Otto, A.
- Scheduling in manufacturing with transportation: Classification and solution techniques. Working Paper Series of the Chair of Management Science/Operations and Supply Chain Management of the University of Passau.
Hosseini, A., Otto, A., & Pesch, E.
- Very large-scale neighborhood search for drone routing with energy replenishment. Working Paper Series of the Chair of Manage-ment Science/Operations and Supply Chain Management of the University of Passau.
Lorenz, C., Mimmo, N., Otto, A., & Vigo, D.
