A cloud service platform integrating additive and subtractive manufacturing with high resource efficiency. (20th December 2019)

• Record Type: Journal Article
• Authors: Qian, Cheng; Zhang, Yingfeng; Liu, Yang; Wang, Zhe
• Is Part Of: Journal of cleaner production. Volume 241(2019)
• Publication Date: 2019-12-20
• Subjects: Cloud manufacturing -- Additive manufacturing -- Subtractive manufacturing -- Resource efficiency; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2019.118379
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Cloud manufacturing has been studied for years, yet commercial implementations are still limited. The recent advances in information technology have stimulated the free sharing of additive and subtractive manufacturing (A/SM) resources through cloud services. Currently, due to the lack of a general method to model manufacturing capabilities, as well as the absence of an open platform to integrate business and manufacturing processes, it is difficult to integrate A/SM resources within one platform efficiently and seamlessly. In this research, a service encapsulation model for A/SM resources was described using ontology modeling technique. A collaborative cloud platform integrating A/SM was designed that can provide optimal production plans considering time, cost, quality, and energy waste during manufacturing. The proposed platform and models were demonstrated by a prototype system and tested in a case study, which showed the integrated platform can increase the utilization rate of resources while reducing energy consumption. This research has provided a practical tool for virtualization, integration, and configuration of A/SM resource with high efficiency. Highlights: Additive and subtractive manufacturing resources were equivalently encapsulated for easier access. A Fused Deposition Modeling 3D printer was comprehensively modeled as an example for implementation. Decision variables such as the energy waste during the change of tasks have been considered. The increased utilization rate and the reduced energy waste of machines were observed in a real-life case.