Recently, Additive Manufacturing (AM) has gained wide interest in the manufacturing sector, especially among original equipment manufacturers (OEMs). OEMs are interested in switching from conventional manufacturing (CM) technologies to AM to produce parts of their complex systems. However, this decision is not straightforward since the benefits of AM needs to be weighed against its drawbacks, and this requires OEMs to consider the whole system lifecycle. However, this is currently missing in the literature, and this work aims to fill this gap. Indeed, this work investigates when AM should be preferred over CM considering all the lifecycle phases into a cost objective function to minimize. Moreover, this work considers how changes in electricity prices and raw materials availabilities due to global events (e.g. pandemics, wars, ...) affects the decision on the optimal production technology (AM or CM). To do so, four situations in terms of electricity prices and raw materials availabilities have been considered, and a decision tree has been developed per each of them. The decision tree represents a decision support system that supports the identification of whether producing in AM is economically convenient over CM or not. Finally, the decision trees have then been applied to two case studies.
Additive vs conventional manufacturing for producing complex systems: A decision support system and the impact of electricity prices and raw materials availability
Finco, Serena;
2024
Abstract
Recently, Additive Manufacturing (AM) has gained wide interest in the manufacturing sector, especially among original equipment manufacturers (OEMs). OEMs are interested in switching from conventional manufacturing (CM) technologies to AM to produce parts of their complex systems. However, this decision is not straightforward since the benefits of AM needs to be weighed against its drawbacks, and this requires OEMs to consider the whole system lifecycle. However, this is currently missing in the literature, and this work aims to fill this gap. Indeed, this work investigates when AM should be preferred over CM considering all the lifecycle phases into a cost objective function to minimize. Moreover, this work considers how changes in electricity prices and raw materials availabilities due to global events (e.g. pandemics, wars, ...) affects the decision on the optimal production technology (AM or CM). To do so, four situations in terms of electricity prices and raw materials availabilities have been considered, and a decision tree has been developed per each of them. The decision tree represents a decision support system that supports the identification of whether producing in AM is economically convenient over CM or not. Finally, the decision trees have then been applied to two case studies.Pubblicazioni consigliate
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