Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/317847 
Year of Publication: 
2023
Citation: 
[Journal:] Journal of Scheduling [ISSN:] 1099-1425 [Volume:] 27 [Issue:] 3 [Publisher:] Springer US [Place:] New York [Year:] 2023 [Pages:] 257-275
Publisher: 
Springer US, New York
Abstract: 
Abstract Car mass production commonly involves a moving assembly line that mixes several car models. This requires plenty of material supplies at the line side, but available space is scarce. Thus, material is placed apart from ideal positions. Then, picking it up involves walking along the line. This time is non-productive and can encompass 10–15% of total production time. Thus, it is important to estimate and minimize it during production planning. However, the calculations are difficult because the conveyor continuously moves. Therefore, most literature bounds walking time by a constant, but this discards valuable potential. To better approximate it, we use a time-dependent V-shaped function. A comparison indicates that for a majority of instances, constant walking time estimates of 95% confidence are at least 51% higher. Then, we introduce a model to optimize material positions such that the model-mix walking time is minimized. This poses an NP-hard sequencing problem with a recursive and nonlinear objective function. Our key discovery is a lower bound on the objective of partial solutions, established by a Lagrangian relaxation that can be solved in quadratic time. Resulting branch and bound based algorithms allow to quickly and reliably optimize up to the largest real-world sized instances.
Subjects: 
Scheduling
Moving assembly line
Walking time
Material placement
Mixed-model production
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version
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