Energy-aware production scheduling for additive manufacturing

Sajad Karimi, Soongeol Kwon, Fuda Ning

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

In recent years, additive manufacturing (AM), also popularly known as three-dimensional (3D) printing, has received significant attention as an emerging manufacturing technology in various industrial sectors, e.g., automotive, aerospace, and medical devices, due to its unique advantages compared to other conventional manufacturing techniques. As tied to the active application of AM to real-world practice, there have been significant efforts to improve energy efficiency and reduce energy cost in AM. Given this context, this study proposes a systematic approach that is uniquely designed to achieve energy-aware production scheduling for AM while it addresses both process-level and scheduling-level controls in an integrated fashion to ultimately save electricity cost. In particular for the process-level control, we first analyze and extract power demand patterns paired with the various process parameter settings. For the scheduling-level control, we formulate a production scheduling problem to minimize energy cost in response to time-varying electricity price as well as demand charge, which has been a common practice for calculating the electric bills of industrial consumers. Specifically, to realize energy-aware production scheduling, the selection of process parameters will be considered as a part of scheduling decisions so that peak power demand and energy consumption patterns can be flexibly adjusted by changing the process parameter setting. While considering the fused deposition modeling (FDM) as a fabrication method, this study conducts numerical experiments based on real-world data to demonstrate the improvement by the proposed approach.

Original languageEnglish
Article number123183
JournalJournal of Cleaner Production
Volume278
DOIs
Publication statusPublished - 2021 Jan 1

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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