Quantifying the effects of additive manufacturing on supply networks by means of a facility location-allocation model
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ORIGINAL PAPER
Quantifying the effects of additive manufacturing on supply networks by means of a facility location-allocation model Andreas Barz1
•
Tobias Buer1 • Hans-Dietrich Haasis2
Received: 18 December 2015 / Accepted: 1 July 2016 The Author(s) 2016. This article is published with open access at Springerlink.com
Abstract Additive manufacturing (AM), or popular scientific 3D printing, disseminates in more and more production processes. This changes not only production processes themselves, e.g. by replacing subtractive production technologies, but AM will in all likelihood also impact the configuration of supply networks. Due to a more efficient use of raw materials, transportation relations may change and production sites may be relocated. How this change will look like is part of an ongoing discussion in industry and academia. However, quantitative studies on this question are scarce. In order to quantify the potential impact of AM on a two-stage supply network, we use a facility location model. The impact of AM on the production process is integrated into the model by varying resource efficiency ratios. We create a test data set of 700 instances. Features of this data set are, among others, different geographical clusters of source nodes, production nodes, and customer nodes. By means of a computational study, the impact of AM on the supply network structure is
This article is part of a focus collection on ‘‘Dynamics in Logistics: Digital Technologies and Related Management Methods’’. & Andreas Barz [email protected] & Tobias Buer [email protected] Hans-Dietrich Haasis [email protected] 1
Computational Logistics Junior Research Group, Faculty of Business Studies & Economics, University of Bremen, P.O. Box 33 04 40, 28334 Bremen, Germany
2
Chair in Maritime Business and Logistics, Faculty of Business Studies & Economics, University of Bremen, P.O. Box 33 04 40, 28334 Bremen, Germany
measured by four indicators. In the context of our experimental set-up, AM reduces the overall transportation costs of a supply network compared to subtractive production. However, the share of the transportation costs on the second stage of a supply network in the total costs increases significantly. Therefore, supply networks in which production sites and customer sites are closely spaced improve their cost-effectiveness stronger than other regional configurations of supply networks. Keywords Supply network Additive manufacturing 3D printing Quantitative assessment Two-stage capacitated facility location problem
1 Introduction Due to the technological enhancement of additive manufacturing (AM) over the past years, AM starts to replace subtractive production technologies. In some fields of use, AM is competitive, because it reduces production costs and at the same time improves the range of features of components. But if one production technology is replaced by another, this can change production and logistics processes as well. Still it appears that the focus in research is on improving the actu
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