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Development of a Decision Support System for 3D Printing Processes based on Cyber Physical Production Systems

Publication Type : Conference Proceedings

Publisher : Elsevier BV

Source : Procedia CIRP

Url : https://doi.org/10.1016/j.procir.2021.01.115

Keywords : Cyber Physical Production System, Carbon Footprint, Decision Support System, Resource Efficiency

Campus : Chennai

School : School of Engineering

Department : Mechanical Engineering

Year : 2021

Abstract :

3D printing, an additive manufacturing technology, potentially provides sustainability advantages such as less waste generation, lightweight geometries, reduced material and energy consumption, lower inventory waste, etc. This paper proposes a decision support system for the 3D printing process based on Cyber Physical Production System. The user is enabled to dynamically assess the carbon footprint based on the energy and material usage for their 3D printed object. A CPPS framework for the environmental sustainability of the 3D printing process is presented, which supports the derivation of improved strategies for product design and production. A physical world for 3D printing is used with the internet of things (IoT) devices like sensor node, webcam, smart plugs, and raspberry pi to host printer Management Software for real-time monitoring and control of material and energy consumption during the printing process. Experiments have been conducted based on Taguchi L9 orthogonal array with polylactic Acid (PLA) as a filament material to estimate the product-related manufacturing energy consumption with the carbon footprint. The proposed framework can be effectively used by the users to supports the decision-making process for saving resources and energy; and minimizing the effect on the environment.

Cite this Research Publication : Rishi Kumar, Christopher Rogall, Sebastian Thiede, Christoph Herrmann, Kuldip Singh Sangwan, Development of a Decision Support System for 3D Printing Processes based on Cyber Physical Production Systems, Procedia CIRP, Elsevier BV, 2021, https://doi.org/10.1016/j.procir.2021.01.115

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