Energy and Material Flow Analysis of Binder-jetting Additive Manufacturing Processes

Abstract

Proceeding to 21st CIRP Conference on Life Cycle EngineeringConsidering the potential for new product design possibilities and the reduction of environmental impacts, Additive Manufacturing (AM) processes are considered to possess significant advantages for automotive, aerospace and medical equipment industries. One of the commercial AM techniques is Binder-Jetting (BJ). This technique can be used to process a variety of materials including stainless steel, ceramic, polymer and glass. However, there is very limited research about this AM technology on sustainability aspect. This paper presents a method to build an energy consumption model for printing stage of BJ process. Mathematical analyses are performed to find out the correlation between the energy consumption and geometry of the manufactured part. Based on the analyses, total energy consumption is calculated as a function of part geometry and printing parameters. Finally, test printing is performed to check the accuracy of the model. This process model provides a tool to optimize part geometry design with respect to energy consumption.International audienceConsidering the potential for new product design possibilities and the reduction of environmental impacts, Additive Manufacturing (AM) processes are considered to possess significant advantages for automotive, aerospace and medical equipment industries. One of the commercial AM techniques is Binder-Jetting (BJ). This technique can be used to process a variety of materials including stainless steel, ceramic, polymer and glass. However, there is very limited research about this AM technology on sustainability aspect. This paper presents a method to build an energy consumption model for printing stage of BJ process. Mathematical analyses are performed to find out the correlation between the energy consumption and geometry of the manufactured part. Based on the analyses, total energy consumption is calculated as a function of part geometry and printing parameters. Finally, test printing is performed to check the accuracy of the model. This process model provides a tool to optimize part geometry design with respect to energy consumption

Life Cycle Assessment of 3D Printed Products in a Distributed Manufacturing System

“…Research from Serres and colleagues () compares the environmental impact of AM processes through the application of an LCA against a traditional milling process performed by a CNC machine. Meteyer and colleagues () provide a model to assess the amount of energy and material consumed at a unit process level for a binder‐jetting process. A similar research presents a predictive model to estimate consumption of resources during the printing phase (Le Bourhis et al.…”

Rapid Prototyping across the Spectrum: RF to Optical 3D Electromagnetic Structures

“…Most of these methods can be broadly classified into categories that share processing similarities. The ASTM International defines seven categories in the Standard Terminology for Additive Manufacturing Technologies [61] as following: (i) Binder jetting: liquid bonding agent is selectively deposited to join powder materials [62]; (ii) Directed energy deposition: focused thermal energy (e.g., laser, electron beam, or plasma arc) is used to fuse materials by melting as they are being deposited [63]; (iii) Material extrusion: material is selectively dispensed through a nozzle or orifice [64]; (iv) Material jetting: droplets of build material (e.g. photopolymer and wax) are selectively deposited [65]; (v) Powder bed fusion: thermal energy selectively fuses regions of a powder bed; (vi) Sheet lamination: sheets of material are bonded to form an object [66]; and (vii) Photopolymerization: liquid photopolymer in a vat is selectively cured by light-activated polymerization [61].…”

Simulation and optimization framework for additive manufacturing processes

“…A simulation algorithm is proposed to model the energy consumption and process build time of Binder Jetting technology based on the part geometry and process parameters (Meteyer et al, 2014). The algorithm slices the part design into layers, and calculates the energy consumption base on each layer's shape, plus the operation time and energy consumption.…”