Author(s)

Wenjing Zhou ¹

Affiliation(s)

¹ Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China

Corresponding Author

Wenjing Zhou

ABSTRACT

Additive manufacturing, also known as 3D printing, has unique process characteristics that not only enable the production of integrated and structurally complex parts but also meet customers' customized requirements. Because the processing times different from those in traditional batch scheduling, the scheduling problems in additive manufacturing face some new challenges. It is important to find a feasible solution for the scheduling problems in additive manufacturing in a reasonable time, to let AM fully display its advantages of cost reduction and efficiency improvement. This paper mainly addresses a parallel-machine scheduling problem in additive manufacturing, with the objective of minimizing the maximum tardiness of all parts. We establish a mixed-integer linear programming (MILP) model for this problem and develop a corresponding algorithm (Algorithm P), in which the greedy allocation stage comprehensively considers the impact of batch membership on the objective function. We conduct a large number of numerical experiments, and the results show that Algorithm P has advantages in terms of computational time and the number of opened batches.

KEYWORDS

Additive manufacturing, Parallel machine scheduling, Heuristic algorithm

CITE THIS PAPER

Wenjing Zhou. Minimizing maximum tardiness for parallel machine scheduling in additive manufacturing. Industrial Engineering and Innovation Management (2025) Vol. 8: 152-162. DOI: http://dx.doi.org/10.23977/ieim.2025.080219.

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