Framework for 2D nesting and scheduling in Additive Manufacturing with alternative orientations and multiple objectives

This paper deals with the assignment of parts to jobs (nesting) in Additive Manufacturing (AM) and the scheduling of jobs in non-identical 3D printing machines. The integrated approach of nesting and scheduling is focus on minimizing three alternative objectives: production costs, total delays and makespan. The problem considers the possibility of incorporating different orientations of parts and 2D rectangular bin packing techniques to be grouped in jobs, increasing the complexity and approaching a real situation in the industry. This extra guidance component allows to reduce total production costs, part delays and makespan, especially in highly complex problems. These problems are solved using a semiparallel construction heuristic framework. This kind of heuristics are currently of great scientific interest but have not been evaluated in this way until now in additive manufacturing problems allowing alternative orientations and 2D nesting. In order to validate the performance of the algorithm, computational experiments were carried out on benchmark instances with one orientation in parts. New sets of benchmark cases adapted from the literature with some alternative orientations in parts are also presented and solved to minimize the three objectives separately. It is observed that the proposed method has a good performance and provides reasonably costs- time- and delay- savings when alternative part orientations are used.