Research Article A Decision-Making Model for Selection of the Suitable FDM Machine Using Fuzzy TOPSIS S. Raja and A. John Rajan School of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India Correspondence should be addressed to A. John Rajan; ajohnrajan@gmail.com Received 19 April 2022; Revised 16 May 2022; Accepted 21 May 2022; Published 30 June 2022 Academic Editor: Punit Gupta Copyright © 2022 S. Raja and A. John Rajan. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Additive manufacturing (AM) or 3D printing has been playing a very important role in the manufacturing sector in recent decades. e AM basic process is meant to produce an object layer by layer and has many advantages that include the occurrence of only minimal production waste during production and easy manufacture of even the most geometrically complex materials. However, there are many challenging decision-making situations in the production of AM for its users, for example, the build chamber, material specification, technology types, and application requirements. is includes the choice of the best AM machine (AMM) from many AMM with slightly different features that are identical on the market, especially on a real-time basis. is research explored ways that AMM is to be selected using multi-criteria decision-making (MCDM) on a real-time basis. is includes the use of the MCDM fussy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to help select the most suitable fusion deposition modeling (FDM) for an Indian nongovernment organization (NGO) from nine different machines based on contemporary. Practice in this research paper, an Indian NGO is considered as a decision-maker in the choice of the best FDM machine based on nine common criteria because an NGO has prescribed nine different FDM machines and the NGO needs the help for the purchase of the suitable FDM to produce different fields of prototypes. e outcome of this research is to recommend a suitable FDM machine from the nine similar to slightly different features of FDM machines by the suggestion of the field experts (AM machine users). e contribution of this research is not only to enable the purchase of the suitable AM machine but also to reveal the various contemporary FDM machines and the general criteria to be considered in choosing them. 1. Introduction Conventional manufacturing (CM) or subtractive manufacturing methods have been used in the manufacturing industry for the past several years. Alter- natively, for the past 3.5 decades, AM has been one of the leading technologies in the manufacturing sector, wherever the product is converted from digital format to standard triangle language (STL) file and can be easily produced a product directly layer by layer [1–3]. According to a previous research report, AM is found in the manufacturing industry under many names. is AM production method has been divided into seven types based on the report of the American Society for Testing and Materials (ASTM), and the previous literature on each method has its own unique features. ese seven methods are stereolithography, material jetting, ma- terial extrusion, binder jetting, powder bed fusion, sheet lamination, and direct energy deposition [4]. What re- searchers consider to be the hallmark of AM is such sim- plicity that helps the production of products with accuracy, freedom in design, low inventory, low lead time, and very rigorous production design [5–8]. Many of the challenges in AM are related to product quality, mechanical property, supply chain-related requirements, shrinkage, printing underutilization, etc. [9–12]. Choice of the suitable AM machine, in particular, is also a challenge. is is due to the continuous increase in the number of machinery suppliers and in the number of machinery with slightly different features, which makes the selection of suitable machine challenging. AM executes its shares in a number of key Hindawi Mathematical Problems in Engineering Volume 2022, Article ID 7653292, 15 pages https://doi.org/10.1155/2022/7653292