Direct digital manufacture and additive manufacture has expanded from rapid prototyping into rapid
production and has the possibility to produce personalised high quality products with the batch size of
one. Affordable additive manufacturing machines and open source software enables a wide spectrum of
users. With a populace empowered with the possibility of producing their own products, this disruptive
technology will inevitably lead to a change in energy and material consumption. With such an unpredictable
impact on society it is timely to consider the economic and environmental issues of growth in
this sector. This work demonstrates a Design of Experiments approach for part optimisation with a
consideration of scrap weight, part weight, energy consumption and production time. The main
conclusion of this study was that through optimisation of machine build parameters a desired response
is possible and compromises between output responses such as scrap and production time can be
identified. The research also showed that identical build parameters for different designs can yield
different output responses, highlighting the importance of developing design specific models. The scientific
value of the work lies in the contribution of new data sets for models in additive manufacturing.
Together with the optimisation method adopted, the results allow for a more detailed and accurate
assessment of the economic and environmental impact of 3D printed products at the design stage.