scholarly journals A decision support method for evaluation and process selection of Additive Manufacturing

Procedia CIRP ◽  
2019 ◽  
Vol 81 ◽  
pp. 1107-1112 ◽  
Author(s):  
Harry Bikas ◽  
Sotiris Koutsoukos ◽  
Panagiotis Stavropoulos
2018 ◽  
Vol 24 (9) ◽  
pp. 1544-1553 ◽  
Author(s):  
Yuanbin Wang ◽  
Ray Y. Zhong ◽  
Xun Xu

Purpose Additive manufacturing (AM) has been increasingly used in various applications in recent years. However, it is still challenge when it comes to selecting a suitable AM process. This is because the outcome may vary due to not only different materials and printers but also different parameters and post-processes. This paper aims to develop an efficient method to help users understand trade-offs and make right decisions. Design/methodology/approach A hybrid method is proposed to help users select appropriate options from a large-scale and discrete option space in an interactive way. First, the design-by-shopping approach is applied to allow users exploring and refining the option space. The analytical hierarchical process method is then used to capture customers’ preferences. After analyzing the results of different normalization methods, a modified Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach is proposed to rank solutions and provide suggestions. Findings The usefulness of proposed method is illustrated in a case study. The results show that it can help customers understand performance distributions and find most suitable options accurately. The ranking of the modified TOPSIS method is more reasonable. Originality/value Due to the complexity of AM technologies, the process selection is considered at the parameter level. A new system framework is proposed for decision support. The TOPSIS method is modified to achieve a stable performance.


Tribologia ◽  
2019 ◽  
Vol 285 (3) ◽  
pp. 31-38
Author(s):  
Kasper GÓRNY

The article presents a simple and clear decision support method for use when selecting lubricants for refrigeration compressors on the basis of tribological tests. The Bellinger method has been chosen. Moreover, the article shows the process of decision support for the selection of lubricants for various mechanisms of the mixing lubricating oil with refrigerant. For the mixing mechanism of a simultaneous intermolecular diffusion and natural convection, the mixture of polyester oils and R134a was selected, whereas, for the mixing mechanism of intermolecular diffusion alone, it was the mixture of mineral oils with R290 that was selected. There were simulations of several decision-making situations due to the decision maker’s attitude, such as economic, qualitative, and balanced. In each variant, the importance of particular criteria was subjectively assigned trying to reflect the decision maker’s attitude. The presented analysis indicates that the lubricity properties of oils and refrigeration mixtures must be taken into account; otherwise, disregarding them can have serious operational consequences. The decision on the selection of the proper lubricant for refrigeration compressors should be preceded by tribological tests allowing one to assess lubricity properties of oils and their mixtures with a refrigerant.


2020 ◽  
Vol 27 (3) ◽  
Author(s):  
Douglas Rhoden Calderaro ◽  
Daniel Pacheco Lacerda ◽  
Douglas Rafael Veit

Abstract: Additive Manufacturing (AM) has seen continued growth in adoption by organizations in recent years, changing production processes, supply chain, maintenance, product development and the global economy. There are several Additive Manufacturing technologies and equipment on the market, however, there are no guidelines, benchmarking or decision support tools for proper selection. After a systematic review of the literature, the lack of propositions that act during the development of the product and process was evidenced. This research focuses on the selection of Additive Manufacturing technologies for a production system. The general objective being to propose a decision support model based on the characteristics of additive technologies and competitive criteria, resulting in a choice aligned with the guidelines of organizations and their production systems. For the operationalization of the model, the AHP techniques and conjoint analysis were used together, where the characteristics of the Additive Manufacturing technologies were related to the competitive criteria for the model to indicate the recommended technology to the production system or organization in question. Finally, the artifact recommended the right technology in three distinct situations, from a vendor, user, and expert point of view. Thus, this research contributes to both academia and business by developing a functional artifact of additive manufacturing technology selection. Also, by contributing to the increased availability of information on the nine most commonly used additive technologies in industry.


Author(s):  
Nadine Wortmann ◽  
Christoph Jürgenhake ◽  
Tobias Seidenberg ◽  
Roman Dumitrescu ◽  
Dieter Krause

AbstractIn recent years, rapid technical progress has led to additive manufacturing achieving a high degree of technological maturity that enables a broad range of applications. This is reinforced in particular by the advantages of the technology, such as the production of complex components, smaller quantities and fast reaction times. However, a lack of knowledge of the various process techniques, such as insufficient potential assessment, specific design guidelines or even of process restrictions, often lead to different errors.This paper presents a methodological approach to support designers in the manufacturing process selection of specific parts at an early stage of product development. In a four-stage procedure, potential part candidates are first identified and part classes formed on the basis of characteristics. Building on this, AM thinking is to be stimulated, for example, with the aid of design guidelines. A comparison between conventionally and additively manufactured parts can be made using a simplified cost model. The results are incorporated into a process model that supports companies in the systematic selection of manufacturing processes.


2019 ◽  
Vol 109 (06) ◽  
pp. 413-416
Author(s):  
C. Gläßner ◽  
L. Yi ◽  
J. Aurich

Additive Fertigungsverfahren bieten durch den schichtweisen Aufbau von Bauteilen Vorteile gegenüber konventionellen Fertigungsverfahren. Die Vielzahl verschiedener additiver Fertigungsverfahren ist eine Herausforderung für die Identifikation eines optimalen Verfahrens für Funktionsbauteile. Der Beitrag stellt einen Ansatz zur Bewertung additiver Fertigungsverfahren vor, der zur Entscheidungsunterstützung bei der Auswahl des optimalen Verfahrens dient.   Being manufactured layer by layer, additive manufacturing technologies offer unique advantages compared to established manufacturing technologies. The large number of different additive manufacturing technologies makes it difficult to identify suitable technologies. This paper presents an approach for assessing additive manufacturing technologies, assisting in the selection of suitable additive manufacturing technologies.


2009 ◽  
Vol 60 (7) ◽  
pp. 1757-1770 ◽  
Author(s):  
M. A. Hamouda ◽  
W. B. Anderson ◽  
P. M. Huck

The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.


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