Analytical models for flow time estimation of additive manufacturing machines

Abstract

The use of Additive Manufacturing (AM) technology has largely increased in the last years. Because of its large differences from conventional technologies, the use of AM in production systems might call for new strategies in production planning and control. To this aim, this paper proposes analytical models to predict aggregate performance measures such as flow time, work in process, and production throughput, for production systems characterised by Laser Powder Bed Fusion AM technology. These indicators could be used both in operations strategy development and in technology comparison. The proposed models differentiate for their detail of the analysis and the number of input parameters that need to be estimated. The results show that the level of detail of the model affects the analysis leading to quite different values of the performance measures, especially in the case of highly saturated systems. Also, a discussion about the applicability of the proposed model to other AM technologies show whether and to what extent the proposed models can be applied for modelling other AM technologies.

Keywords:

• Performance measures
• laser powder bed fusion
• additive manufacturing
• production planning
• production control

Mathematics Subject Classifications:

• 90C27
• 90B35
• 90C39
• 90C40

Disclosure statement

The authors have no relevant financial or non-financial interests to disclose. The data that support the findings of this study are available from the corresponding author, A.M., upon reasonable request.

Additional information

Notes on contributors

Erica Pastore

Erica Pastore is an assistant professor at Politecnico di Torino, in Turin, Italy. She graduated in Mathematical Engineering at Politecnico di Torino and got her PhD in Management, Production and Design at Politecnico di Torino in 2018. Her research areas include production planning and control, system simulation-optimisation, production scheduling, and supply chain management.

Arianna Alfieri

Arianna Alfieri is a full professor at Politecnico di Torino at Turin, Italy, where she currently teaches production planning and control, analysis and management of production systems, and system simulation. Her main research area includes scheduling and planning, system simulation, and integrated system simulation-optimisation.

Andrea Matta

Andrea Matta is full professor of Manufacturing and Production Systemsat Department of Mechanical Engineering of Politecnico di Milano. He graduated in Industrial Engineering at Politecnico di Milano where he develops his teaching and research activities since 1998. He was Distinguished Professor at the School of Mechanical Engineering of Shanghai Jiao Tong University from 2014 to 2016 and Guest Professor between 2017 and 2019. He has been visiting professor at Ecole Centrale Paris (France), University of California at Berkeley (USA), and Tongji University (China). His research area includes analysis, design and management of manufacturing and health care systems. He has published 180+ scientific papers on international and national journals/conference proceedings. He is Editor in Chief of Flexible Services and Manufacturing Journal since 2017, past member of editorial board of OR Spectrum journal and IEEE Robotics and Automation Letters journal. He is Chair of the technical committee IEE RAS Sustainable Production Automation. He is member of scientific committee in several international conferences. Member of the Steering Committee of PhD on Mechanical Engineering. Member of the ADA University Advisory Board. He was awarded with the Shanghai One Thousand Talent and Eastern Scholar in 2013.

Barbara Previtali

Barbara Previtali is full professor at Politecnico di Milano, Department of Mechanical Engineering, overseeing SITEC-Laboratory for Laser Applications and co-supervising AddMe_Lab, focussing on metal additive manufacturing. Her research focuses on advanced manufacturing processes, including laser-based techniques like DED, L-PBF and WAAM for high-performance materials. She serves on the Mechanical Engineering PhD Program board, is a member of AITeM, Photonics21, and Laser Institute of America. For 2023–2029, she serves on the jury for Berthold Leibinger Innovationspreis and Zukunftspreis and is part of the international Scientific Advisory Board for MAPP EPSRC project. Her research receives funding from regional, national, and international organisations, resulting in nearly 15 national and international patents through collaboration with leading industrial companies.