  Production planning in 3D printing factories brings new challenges among
which the scheduling of parts to be produced stands out. A main issue is to
increase the efficiency of the plant and 3D printers productivity. Planning,
scheduling, and nesting in 3D printing are recurrent problems in the search for
new techniques to promote the development of this technology. In this work, we
address the problem for the suppliers that have to schedule their daily
production. This problem is part of the LONJA3D model, a managed 3D printing
market where the parts ordered by the customers are reorganized into new
batches so that suppliers can optimize their production capacity. In this
paper, we propose a method derived from the design of combinatorial auctions to
solve the nesting problem in 3D printing. First, we propose the use of a
heuristic to create potential manufacturing batches. Then, we compute the
expected return for each batch. The selected batch should generate the highest
income. Several experiments have been tested to validate the process. This
method is a first approach to the planning problem in 3D printing and further
research is proposed to improve the procedure
