Högskolan i Skövde

The Transfer Line Balancing Problem (TLBP) concerns the optimal assignment of tasks to workstations in automated machining lines to improve operational efficiency. This problem is particularly relevant to high-volume manufacturing industries, such as the automotive and aerospace industries, because it directly affects productivity and cost efficiency. This study examines how hierarchical configuration decisions at the operational (task assignment), tactical (joint task–tool assignment), and strategic (joint task–tool–fixture assignment) levels affect cycle time in an existing automotive machining transfer line. Three mixed-integer linear programming (MILP) models are developed to represent these configuration levels while accounting for setup times and industrial constraints, including task–machine accessibility, zoning, and technological restrictions. Because the exact models do not scale effectively to large instances, a constructive heuristic combined with a local search strategy is also developed. The proposed solution methods are evaluated using an industrial case study and 225 benchmark instances generated using a MILP-based benchmark generator. Across the benchmark size groups, operational cycle times are, on average, up to 11.87% and 12.65% higher than those obtained under tactical and strategic configurations, respectively, indicating potential productivity and economic benefits. The findings support managers in selecting an appropriate configuration level. Sensitivity analyses are also conducted to assess the effects of task–machine accessibility and task-time variability on solution performance.