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![Production volume versus cost from the aspects of traditional manufacturing and the 3DP. Source: [6].](publication/273875487/figure/fig2/AS:1088654135037957@1636566780918/Production-volume-versus-cost-from-the-aspects-of-traditional-manufacturing-and-the-3DP.jpg)
Production volume versus cost from the aspects of traditional manufacturing and the 3DP. Source: [6].
Source publication
During the past years, the three-dimensional printing (3DP) has become a dominant rapid prototyping (RP) technology due to its very viable process in terms of cost, speed, and sales of related equipment. Nowadays, numerous 3DP based RP services are available. Because of the capability, service quality, and pricing of the services varies, how to sel...
Citations
... Decision Matrix (Properties of materials)[22][23][24][25][26][27][28] ...
A decision-making methodology for the material selection is presented in this paper. A multi-criteria decision-making (MCDM) based hybrid approach, AHP-TOPSIS, was used to choose the appropriate additive manufacturing (AM) material for aerospace applications. This study evaluated nine polymer-based AM materials for an aerospace application. Experts from both industry and academia carefully finalized the selection criteria. Selected criteria are divided into three main categories: performance, economic and environmental. Firstly, the AHP approach was used to get the weights of criteria chosen via pairwise comparisons. Second, a decision matrix containing the properties of materials was created. The TOPSIS method was then applied using the AHP criteria weights and decision matrix, resulting in the final ranking of materials. ULTEM material ranked number 1 and was selected as the appropriate material for an aerospace application. Additionally, sensitivity analysis was also carried out to check the proposed method’s reliability and robustness.
... The effort of shaping MCDM methods for the sake of applications encouraged scholars to develop the so-called class of hybrid MCDM methods. Hybridisation of MCDM methods has been recognised after the works of Shyur and Shih (2006), Tzeng et al. (2007) and Liao et al. (2014). Following the work of Zavadskas et al. (2016), hybrid approaches to MCDM can be categorised in four groups. ...
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW) are among the most employed approaches for aggregating performances in Multi-Criteria Decision-Making (MCDM). TOPSIS and SAW are two MCDM methods based on the value function approach and are often used in combination with other MCDM methods in order to produce rankings of alternatives. In this paper, first, we analyse some common features of these two MCDM methods with a specific reference to the additive properties of the value function and to the sensitivity of the value function to trade-off weights. Based on such methodological insights, an experimental comparison of the results provided by these two aggregation methods across a computational test is performed. Specifically, similarities in rankings of alternatives produced by TOPSIS and SAW are evaluated under three different Minkowski distances (namely, the Euclidean, Manhattan and Tchebichev ones). Similarities are measured trough a set of statistical indices. Results show that TOPSIS, when used in combination with a Manhattan distance, produces rankings which are extremely similar to the ones resulting from SAW. Similarities are also Experimental results confirm that rankings produced by TOPSIS methods are closer to SAW ones when similar formal properties are satisfied.
... Liao et al. [82] established a hybrid MADM framework for evaluating and enhancing 3D printing service providers. This framework was realised using the DEMATEL-based network process and VIKOR. ...
Multi-attribute decision-making (MADM) refers to making preference decisions via assessing a finite number of pre-specified alternatives under multiple and usually conflicting attributes. Many problems in the field of additive manufacturing (AM) are essentially MADM problems or can be converted into MADM problems. Recently, a variety of MADM methods have been applied to solve MADM problems in AM. This generates a series of interesting questions: What is the general trend of this research topic from the perspective of published articles every year? Which journals published the most articles on the research topic? Which articles on the research topic are the most cited? What MADM methods have been applied to the field of AM? What are the main strengths and weaknesses of each MADM method used? Which MADM method is the most used one in this field? What specific problems in AM have been tackled via using MADM methods? What are the main issues in existing MADM methods for AM that need to be addressed in future studies? To approach these questions, a review of MADM methods in AM is presented in this paper. Firstly, an overview of existing MADM methods in AM was carried out based on the perspective of specific MADM methods. A statistical analysis of these methods is then made from the aspects of published journal articles, applied specific methods, and solved AM problems. After that, the main issues in the application of MADM methods to AM are discussed. Finally, the research findings of this review are summarised.
... Finally, the later defuzzification VIKOR method (LDVIKORM) is employed to order the appropriate alternatives. Liao et al. (2014) intended to resolve the problem of selecting a suitable 3DP-based rapid prototyping service provider by using a HMCDM framework based on the DEMATEL-based network process and VIKOR MCDM technique. Rahman et al. (2020) utilised the fuzzy-VIKOR methodology to determine the substantial barriers to green SC management execution and suggest possible alternatives to alleviate these barriers within the context of the plastic industry of Bangladesh. ...
... Therefore, the barriers identified using literature review and expert inputs are ranked systematically using an AHP approach. Compared to eminent conventional ranking approaches, TOPSIS, which realises an outcome with the lesser interval from the desired solution and the greater interval from the undesired solution, the use of the VIKOR technique will overcome the difficulty of not considering the relative importance of those intervals (Liao et al., 2014). Thus, the weights determined by AHP will be used by VIKOR to rank alternatives with non-commensurable and conflicting criteria (Sayadi et al., 2009). ...
This work concentrates on determining, inspecting, as well as ranking the critical barriers and alternatives to help the adoption of BC-ML practices in additive manufacturing (ADM). AHP-VIKOR methodology was applied to examine 20 identified barriers within the BC-ML adoption in ADM. The findings of the study reveal the rankings of the significant barriers as well as alternatives aimed at the trouble-free adoption of BC-ML practices in the ADM industry. Higher build time and complicated design process of blockchain-based platforms emerge as the most critical barriers, with a higher value of weights by using the AHP approach. The outcome of the alternative evaluation shows that the vat polymerisation process ranks at the topmost position. The findings of this study can be useful to practitioners and policymakers to develop proper understanding, alleviation approaches, and make well-informed decisions.
... Traditional 3DP resource evaluation systems are of a guidance or educational purpose to help users understand 3DP capabilities and their differences. According to Qin et al., 2020), the resource capability evaluation process in these systems is generally performed applying three methods: expert knowledge and experience (Bibb et al., 1999;Braglia and Petroni, 1999;Khrais et al., 2011;Liao et al., 2014;Anand and Vinodh, 2018), benchmarking (Campbell and Bernie, 1996;Mahesh et al., 2005;Venkata Rao and Patel, 2010;Roberson et al., 2013;Zheng et al., 2017) and vendor documents (Chuk and Thomson, 1998;Uz Zaman et al., 2018). Vendor documents usually include basic information and are unclear on the conditions under which the data have been collected (Pham and Gault, 1998). ...
Purpose
This study aims to develop a system framework to organise, manage and evaluate 3D printing (3DP) services in the cloud and help users select the best service according to application requirements.
Design/methodology/approach
Users can personalise their 3DP services based on their application requirements. The user is supplied with the performance capabilities and trust of all possible services. If the user is unable to select a service directly from the list of possible 3DP services, he/she can assign preference values for the application requirements to make a trade-off between the performance capabilities of services provided in terms of response time, manufacturing capabilities, lead time, cost and data integrity. After obtaining the finished product, the performance trust of the selected service are modified based on consumer feedback regarding their satisfaction. The accumulated input of a service's users is used to dynamically update its performance trust and is offered to new customers as a guide.
Findings
An industry case study is applied to verify the proposed methodology. The systematic order of the system framework demonstrated its efficiency in customising production based on trusted 3DP service providers.
Originality/value
The system upgraded the conventional 3DP service evaluation and selection approach. It considers the evaluation criteria of 3DP resources and the trust of service performance in the cloud context. The system favours 3DP cloud service providers. A registry tool is proposed to allow 3DP service providers to comprehensively define their services. By implementing a trust evaluation approach, 3DP service providers' trust are regularly updated based on their historical performances. In addition, a punishment mechanism is designed to motivate service providers to publish their true performance capabilities, therefore promoting a competitive environment and resulting in more reliable services.
... Regarding the type of criteria handled, while most references address geometric, functional, manufacturing and costs aspects, Lokesh and Jain (2010) also considers environmental aspects. Liao et al. (2014) is the first reference including subjective experts' opinions as additional criteria. The contributions on this problem are summarised in Table 4. ...
Additive Manufacturing (AM) is a disruptive production technology that challenges many well-established, conventional practices in Operations and Supply Chain Management decisions. Consequently, new context-specific decision problems have appeared in this area, while existing decision problems must be adapted or extended to this context. In this overview, these decision problems in AM are highlighted and classified, describing the different decision in an unified manner and citing the underlying OR techniques that have been applied to solve them. The aim of the paper is that, by presenting an overview of the AM-related problems in a systematic, OR- or Decision-Making-centred (rather than technology-centred) manner, the OR community can become more aware of this stream of research and thus be more active and contribute with some high-quality work. Open research challenges, as well as avenues for future research are also discussed.
... Many researchers have addressed the important decision parameters involved in the AM selection process and facilitated that process by developing some advisory tools based on different multicriteria decision-making methods. These methods include analytic hierarchy process (AHP) (Lokesh and Jain, 2010;Armillotta, 2008;Kadkhoda-Ahmadi et al., 2019;Zaman et al., 2018;Mançanares et al., 2015;Liu et al., 2020), analytic network process framework (ANP) (Vimal, 2016), technique for order preference by similarity to ideal solution (TOPSIS) (Byun and Lee, 2005), VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) (Liao et al., 2014), fuzzy AHP (Zhou and Chen, 2010), fuzzy logic (Khrais et al., 2011), fuzzy TOPSIS (Vahdani et al., 2011), fuzzy VIKOR (Vinodh et al., 2014), fuzzy information aggregation operators (Qin et al., 2020), fuzzy decision (Mahesh et al., 2005), graph theory (Rao and Padmanabhan, 2007), hybrid decision-making tools (Anand, 2018;Borille et al., 2010;Zhang, 2014;Wang, 2018), fuzzy axiomatic design (Zheng et al., 2017) and posteriori articulation of preferences approach (Wang, 2017). ...
Purpose
Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.
Design/methodology/approach
The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.
Findings
To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.
Originality/value
This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.
... MCDM approaches have two essential elements: weighting of ranking criteria and the operation technique that utilizes ranking criteria and their weights to rank different options [9]. In MCDM, users can directly evaluate the relative importance of one criterion over others on a certain scale, or be asked to compare a pair of criteria each time: the AHP approach [19], DEMATEL [25], and best worst method (BWM) [7]. Operation techniques can simply be arithmetic operations [23] or complicated calculations, such as GT&MA [24], TOPSIS [19], and VIKOR [25]. ...
... In MCDM, users can directly evaluate the relative importance of one criterion over others on a certain scale, or be asked to compare a pair of criteria each time: the AHP approach [19], DEMATEL [25], and best worst method (BWM) [7]. Operation techniques can simply be arithmetic operations [23] or complicated calculations, such as GT&MA [24], TOPSIS [19], and VIKOR [25]. MCDM methods are sensitive to user inputs. ...
Additive manufacturing (AM) is a promising manufacturing technology; it has great manufacturing capabilities and large material diversity, making it applicable for many applications. However, the limited information related to AM processes, materials, and rules restricts its potential popularity over traditional manufacturing methods. For a particular application, the choice of available AM process/machine and material is critical to the application’s quality, mechanical properties, and other important factors. Moreover, the large number of AM processes/machines and materials and the overlap among them in terms of capability and functionality further complicate the selection task. AM service selection as a problem has three essential aspects, and all support systems that are built to help users select the optimal AM service must consider these aspects during the system development stage. These aspects are the AM resource capability information source, user intervention, and the methodology suggesting the best AM resources that meet user requirements. These aspects actually represent AM resource definition accuracy and availability, selection system usability, and reliability. This study analyses the essence of these three aspects, reviews the literature, and develops a new AM selection system framework that enhances system functionality regarding these aspects. First, 3D printing service providers in the proposed system are considered the source of AM resource capability information to expand AM service options to users, provide accurate resource definitions, and ensure their availability. Second, the proposed system applied the posteriori-based multicriteria decision-making approach through the integration of decision making trial and evaluation laboratory (DEMATEL), analytic hierarchy process (AHP), and modified Technique for Order Preference by Similarities to Ideal Solution (TOPSIS) techniques. This greatly minimizes user inputs during AM service selection process, fully supports the DFAM (Design for additive manufacturing) concept, and maintains the accuracy of final selection decisions.
... Multi-criteria decision-making (MCDM) tools are computer programs that aid in such decision making under conflicting requirements. The literature review evidenced use of MCDM tools to select general AM systems for manufacturing of 3D objects [13][14][15][16], since bioprinting processes involve a number of parameters like bio-ink viscosity and cell viability, which are not considered for other AM processes, the MCDM tool for selection of bioprinting process needs to incorporate such specific requirements. No existing literature was found that has dealt with the development of MCDM tool for bioprinting processes, and hence, the presented work is an attempt toward addressing that gap. ...
... As a result, we resorted to the DEMATEL method to help clarify and gain more insight into the causality intensity and the influence strengths between the factors of interest. The method can be summarized as follows based on the earlier works by Liao et al. [90], Hwang, Huang, and Wu [85], and Hwang, Huang, and Yang [86]. Refer to Appendix A for the detailed procedures. ...
Air pollution poses serious problems as global industrialization continues to thrive. Since air pollution has grave impacts on human health, industry experts are starting to fathom how to integrate particulate matter (PM) sensors into portable devices; however, traditional micro-electro-mechanical systems (MEMS) gas sensors are too large. To overcome this challenge, experts from industry and academia have recently begun to investigate replacing the traditional etching techniques used on MEMS with semiconductor-based manufacturing processes and materials, such as gallium nitride (GaN), gallium arsenide (GaAs), and silicon. However, studies showing how to systematically evaluate and select suitable materials are rare in the literature. Therefore, this study aims to propose an analytic framework based on multiple criteria decision making (MCDM) to evaluate and select the most suitable materials for fabricating PM sensors. An empirical study based on recent research was conducted to demonstrate the feasibility of our analytic framework. The results provide an invaluable future reference for research institutes and providers.
