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Transparency Built‐in
Author(s) -
Baumers Martin,
Tuck Chris,
Wildman Ricky,
Ashcroft Ian,
Rosamond Emma,
Hague Richard
Publication year - 2013
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/j.1530-9290.2012.00512.x
Subject(s) - transparency (behavior) , computer science , production (economics) , energy consumption , process (computing) , resource efficiency , minification , electricity , supply chain , manufacturing engineering , process engineering , industrial engineering , business , economics , engineering , ecology , computer security , marketing , biology , electrical engineering , macroeconomics , programming language , operating system
Summary The supply chains found in modern manufacturing are often complex and long. The resulting opacity poses a significant barrier to the measurement and minimization of energy consumption and therefore to the implementation of sustainable manufacturing. The current article investigates whether the adoption of additive manufacturing (AM) technology can be used to reach transparency in terms of energy and financial inputs to manufacturing operations. AM refers to the use of a group of electricity‐driven technologies capable of combining materials to manufacture geometrically complex products in a single digitally controlled process step, entirely without molds, dies, or other tooling. The single‐step nature affords full measurability with respect to process energy inputs and production costs. However, the parallel character of AM (allowing the contemporaneous production of multiple parts) poses previously unconsidered problems in the estimation of manufacturing resource consumption. This research discusses the implementation of a tool for the estimation of process energy flows and costs occurring in the AM technology variant direct metal laser sintering. It is demonstrated that accurate predictions can be made for the production of a basket of sample parts. Further, it is shown that, unlike conventional processes, the quantity and variety of parts demanded and the resulting ability to fully utilize the available machine capacity have an impact on process efficiency. It is also demonstrated that cost minimization in additive manufacturing may lead to the minimization of process energy consumption, thereby motivating sustainability improvements.