Selection of a Solution When Using Axiomatic Design

Slătineanu, Laurenţiu; Dodun, Oana; Coteaţă, Margareta; Dulgheru, Valeriu; Duşa, Petru; Banciu, Felicia Veronica; Beşliu, Irina

doi:10.1051/matecconf/201712701019

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…Some details concerning the stages corresponding to the AHP method used in the case of a device for evaluating the universal lathe university were presented in [7]. In this paper section, a more synthetic presentation of applying the AHP method in the case of selecting a device for ultrasonic machining will be made.…”

Section: Use Of Ahp Methodsmentioning

confidence: 99%

Axiomatic Design in Obtaining a Device for Ultrasonic Machining

et al. 2018

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Ultrasonic abrasive cavitational machining is a nonconventional machining method applied to remove surfaces in workpieces made of brittle, hard, or non-conductive materials that cannot be efficiently machined by other classical or nonconventional machining methods. Among the factors that can affect the values of the parameters of technological interest for the ultrasonic machining process, the relative pressure between the ultrasonic tool and the workpiece surface to be machined could be considered. The main objective of the research presented in this paper was to analyze the possibilities of selecting the most convenient solution among many such available solutions to ensure the tool feed motion, when designing a device for achieving an ultrasonic drilling process. At present, this selection could be achieved by means of an optimal selection method. Taking into consideration some functional requirements of the device, the method of analytic hierarchy process and the axiomatic design theory were used to solve some problems met in the design process.

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Section: Use Of Ahp Methodsmentioning

confidence: 99%

Axiomatic Design in Obtaining a Device for Ultrasonic Machining

et al. 2018

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“…In a real-world problem, it is not always possible to find perfect judgments; therefore, a consistent pairwise comparison matrix 𝐴 is needed after performing pairwise comparisons [36]. The consistency ratio (𝐶𝑅) is an important aspect of AHP, as its value primarily determines optimal decision making in pairwise comparisons [50].…”

Section: Analytical Hierarchy Processmentioning

confidence: 99%

“…However, while AHP has significance in this context, it may not provide a complete assessment of the AM equipment selection process. This limitation can be effectively addressed by integrating axiomatic design (AD) principles, which can stimulate technical creativity and be seamlessly integrated with the AHP [36]. A hierarchical decision-making model using AD, customer requirements, quality, time, and costs makes it possible to not only give weight to qualities but also systematically select the most suited equipment based on the complete assessment of many design possibilities, thus optimizing evaluation indicators [37].…”

Section: Introductionmentioning

confidence: 99%

A Hierarchical Axiomatic Evaluation of Additive Manufacturing Equipment and the 3D Printing Process Based on Sustainability and Human Factors

Mendoza-Muñoz,

Montoya-Reyes,

Maldonado-Macías

et al. 2024

Processes

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As interest in additive manufacturing (AM) continues to increase, it has become more important to have a robust method to help potential users select the AM process that best suits their technological needs while providing the greatest potential benefits in terms of sustainability and its effect on people. This paper presents the development of a framework for selecting the best AM process for a given application by considering both sustainability and human factors through the combination of axiomatic design and the analytic hierarchy process. Thirty-one participants with varying levels of expertise (novice and advanced users) were involved in the study, considering the frequency of 3D printer usage (novice users: never, rarely; expert users: sometimes, almost always, always) for prototyping parts. They employed fused deposition modeling (FDM) and stereolithography (SLA) (both 3D desktop printers) and collected data on five evaluation criteria. The participation of experts helped establish a novel methodology, with material cost deemed most important (49.8%), followed by cycle time (28%), energy consumption (11.7%), error rate (6.6%), and equipment noise (3.9%). The results showed that FDM was the optimal equipment option for advanced users. By examining the information content of the other options, it was found that FDM demanded less information than SLA, regardless of the user’s level of expertise. The proposed method is appropriate to assess the sustainability aspect of FDM and SLA; however, it can be further improved by adding indicators such as environmental impact, recyclability, and ergonomic and occupational health factors.

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