Abstract

Additive manufacturing (AM) has widely demonstrated its ability to economically produce parts at low volumes. Attention is now shifting to higher volume applications, such as mass customization and the manufacture of standard parts. In these contexts, production losses due to process variability and inefficient machine use are common concerns for the application of AM. The Overall Equipment Effectiveness (OEE) metric is a tool widely used in traditional manufacturing to assess the effective use of production capacity. Previous studies seeking to apply OEE to AM are limited in scope and have neglected the above sources of inefficiency. This article seeks to address this gap in two ways. First, we present a framework for measuring OEE within AM operations; and systematically map the ‘six production losses’ to the AM workflow to codify our understanding of the main sources of inefficiency. Second, we conduct a simulation study investigating how the AM operations approach, product variety and lead time requirements affect the OEE of an AM process. Our findings demonstrate that – with some conceptual adaptation – the OEE metric can indeed be used in the context of AM. Furthermore, we identify the approach to AM operation as a major determinant of performance in terms of the OEE achieved. We conclude with a set of managerial insights on how to apply the OEE metric to AM processes in practice. • Novel framework for ‘what’ and ‘how’ to measure OEE in AM operations. • Systematic mapping of the ‘six production losses’ in OEE to the AM workflow. • Simulation highlights that OEE in AM depends on the operations approach. • Simulation also investigates how product variety and lead-time affect OEE in AM. • Results show that the OEE metric is useful for AM with some conceptual adaptation.

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