Optimizing ergonomics and productivity in automotive assembly lines: a bi-objective integer linear programming approach

The automotive industry’s operations face a critical dilemma: achieving high productivity while maintaining adequate ergonomic standards. High-volume production amplifies this condition, because the frequency of task execution keeps ergonomic risk ever-present. This work presents a real case from an automotive body parts assembly line. The objectives are to minimize the maximum individual ergonomic risk throughout job-rotation periods along a daily journey, and to optimize productivity by determining the optimal worker-to-workstation assignments. The Occupational Repetitive Action (OCRA) index is used to assess the risk of upper extremity musculoskeletal disorders. To solve this bi-objective problem, two algorithms are proposed: an ε ε -constraint approach and a Tchebychev method. Both are grounded in a novel Integer Linear Programming (ILP) model tailored to integrate ergonomic and productivity considerations. The algorithms generated a complete Pareto front of 16 efficient solutions within a reasonable computational time. Managerial insights are derived, highlighting the inherent trade-off between the makespan and ergonomic risk, providing valuable guidelines for balancing worker well-being and productivity in assembly-line operations.