RT info:eu-repo/semantics/article
T1 An iterative price-based combinatorial double auction for additive manufacturing markets
A1 Antón Heredero, Juan de
A1 Villafáñez Cardeñoso, Félix Antonio
A1 Poza Garcia, David Jesús
A1 López Paredes, Adolfo
K1 Additive manufacturing
K1 Combinatorial auctions
K1 Electronic platforms
K1 E-procurement
K1 Iterative bidding
AB The increasing adoption of additive manufacturing (AM) in the industrial sector is leading to an imbalance between supply and demand of additively manufactured subcomponents: companies demanding AM services require very specific products and AM suppliers differ widely in their capabilities. Some existing proposals aim to help match supply and demand by merely making customer–supplier allocations. Only a few recent works go beyond allocation issues and propose market mechanisms to also address pricing aspects. However, we observe that these mechanisms do not fully exploit the potential of additive manufacturing techniques. The aim of this paper is to design a market mechanism that considers the particularity of AM techniques, wherein suppliers can benefit from manufacturing multiple heterogeneous parts from multiple customers in the same build area to increase production throughput. This market mechanism has been implemented as an iterative combinatorial double auction that adapts to this feature of the AM market: customers will bid to get their orders produced and suppliers will submit asking quotes to win the production of combinations of those orders. The mechanism solves the allocation and pricing of AM orders while seeking the maximization of social welfare. The procedure is simulated in a theoretical environment to evaluate its performance and to identify the most appropriate conditions for its implementation in a real environment. Unlike other existing proposals for client-supplier allocation mechanisms in additive manufacturing, the proposed mechanism allows a single supplier to produce a combination of orders from different clients, leading to a pricing system that maximizes social welfare without participants disclosing sensitive information.
PB Elsevier
SN 0360-8352
YR 2024
FD 2024
LK https://uvadoc.uva.es/handle/10324/70220
UL https://uvadoc.uva.es/handle/10324/70220
LA spa
NO Computers & Industrial Engineering, Noviembre 2024, vol. 197
DS UVaDOC
RD 27-sep-2024