Litcius/Paper detail

Analysis of factors influencing energy consumption of material extrusion-based additive manufacturing using interpretive structural modelling

P. Ramesh, S. Vinodh

2021Rapid Prototyping Journal26 citationsDOI

Abstract

Purpose Material extrusion (MEX) is a class of additive manufacturing (AM) process based on MEX principle. In the viewpoint of Industry 4.0 and sustainable manufacturing, AM technologies are gaining importance than conventional manufacturing route (subtractive manufacturing). Because of the ease of use and lesser operation skills, MEX had wide popularity in industry for product and prototype development. This study aims to analyze energy consumption of MEX-based AM process and its influencing factors. Design/methodology/approach A group of factors were identified pertaining to MEX-based AM process. In this viewpoint, this study presents the configuration of a structural model using interpretive structural modeling (ISM) to depict dominant factors in MEX-based AM process. A total of 18 influencing factors are identified and ranked using ISM methodology for MEX process. The Impact Matrix Cross-reference Multiplication Applied to a Classification analysis was done to categorize influencing factors into four groups for MEX-based AM process. Findings The derivation of structural model would enable AM practitioners to systematically analyze the factors and to derive key factors which enable comprehensive energy modeling and energy assessment studies. Also, it facilitates the development of energy efficient AM system. Originality/value The development of structural model for analysis of factors influencing energy consumption of MEX-based AM is the original contribution of the authors.

Topics & Concepts

Process (computing)Energy consumptionManufacturing engineeringComputer scienceManufacturingIndustrial engineeringNew product developmentEngineeringSystems engineeringProcess managementBusinessMarketingElectrical engineeringOperating systemAdditive Manufacturing and 3D Printing TechnologiesDigital Transformation in IndustryManufacturing Process and Optimization