Investigating the effect of scale and scheduling strategies on the productivity of 3D managed print services

Abstract

Sales of extrusion 3D printers have seen a rapid growth and the market value is expected to triple over the next decade. This rapid growth can be attributed to a step change in capability and an increase in demand for 3D printed parts within mechanical, industrial and civil engineering processes. Correspondingly, a new technical prototyping platform – commonly referred to as Fabrication Laboratories – has emerged to provide a stimulus for local education, entrepreneurship, innovation and invention through the provision of on-demand 3D printing and prototyping services. Central to the effectiveness of the on-demand 3D printing and prototyping services – hereby referred to as 3D managed print services – is their ability to handle multiple users with varying knowledge and understanding of the manufacturing processes and scaling numbers of 3D printers in order to maximise productivity of the service. It is this challenge of productivity and more specifically the scalability and scheduling of prints that is considered in this article. The effect of scale and scheduling strategies on productivity is investigated through the modelling of four scheduling strategies for 3D managed print service of varying scales by altering the number of available printers and level of user demand. The two most common approaches (first-come first-serve and on-line continuous queue) and two alternatives based on bed space optimisation (first-fit decreasing height and first-fit decreasing height with a genetic algorithm) have been considered. Through Monte-Carlo simulation and comparison of the strategies, it is shown that increasing the scale of 3D managed print service improves the peak productivity and range of user demands at which the 3D managed print service remain productive. In addition, the alternative strategies are able to double the peak productivity of 3D managed print service as well as increase the user demand range where the 3D managed print service remains productive.