Towards Fair Employee-Job Assignments in Final Assembly Stations

Assigning employees to jobs in a final assembly environment presents a multitude of challenges. Employee competences, preferences, ergonomics, assignment history, and fairness must simultaneously be accounted for, while responding to real-life uncertainties such as illnesses, tardiness, and shifting production demands. To address these needs, this paper presents an integer linear programming approach that calculates fair employee-job assignments by integrating four key elements: a competence matrix, a preference matrix, a record of past assignments, and job ergonomics. This approach enables real-time allocation adjustments when employees are unexpectedly absent and promotes balanced workloads, reduced injury risks, and fair job distribution that incorporates employee preferences. The method is evaluated on synthetic data that closely reflects real-world scenarios. The results suggest that the proposed method can effectively guide decision making, promoting fair job assignments in final assembly stations.