Ulanbek Auyeskhan, C. Steed, Soohyung Park, Dong-Hyun Kim, Im Doo Jung, Namhun Kim
{"title":"Virtual reality-based assembly-level design for additive manufacturing decision framework involving human aspects of design","authors":"Ulanbek Auyeskhan, C. Steed, Soohyung Park, Dong-Hyun Kim, Im Doo Jung, Namhun Kim","doi":"10.1093/jcde/qwad041","DOIUrl":null,"url":null,"abstract":"\n There is a combinatorial explosion of alternative variants of an assembly design owing to the design freedom provided by Additive Manufacturing. In this regard, a novel Virtual Reality-based decision-support framework is presented herein for extracting the superior assembly design to be fabricated by AM route. It specifically addresses the intersection between human assembly and AM hence combining Design for Assembly, and Design for Additive Manufacturing using Axiomatic Design theory. Several Virtual Reality experiments were carried out to achieve this with human subjects assembling parts. At first, a 2D table is assembled, and the data are used to confirm the independence of nonfunctional requirements such as assembly time and assembly displacement error according to Independence Axiom. Then this approach is demonstrated on an industrial lifeboat hook with three assembly design variations. The data from these experiments are utilized to evaluate the possible combinations of the assembly in terms of probability density based on the Information Axiom. The technique effectively identifies the assembly design most likely to fulfill the nonfunctional requirements. To the authors’ best knowledge, this is the first study that numerically extracts the human aspect of design at an early design stage in the decision process and considers the selection of the superior assembly design in a detailed design stage. Finally, this process is automated using a graphical user interface, which embraces the practicality of the currently integrated framework and enables manufacturers to choose the best assembly design.","PeriodicalId":48611,"journal":{"name":"Journal of Computational Design and Engineering","volume":"6 1","pages":"1126-1142"},"PeriodicalIF":4.8000,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Design and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1093/jcde/qwad041","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 2
Abstract
There is a combinatorial explosion of alternative variants of an assembly design owing to the design freedom provided by Additive Manufacturing. In this regard, a novel Virtual Reality-based decision-support framework is presented herein for extracting the superior assembly design to be fabricated by AM route. It specifically addresses the intersection between human assembly and AM hence combining Design for Assembly, and Design for Additive Manufacturing using Axiomatic Design theory. Several Virtual Reality experiments were carried out to achieve this with human subjects assembling parts. At first, a 2D table is assembled, and the data are used to confirm the independence of nonfunctional requirements such as assembly time and assembly displacement error according to Independence Axiom. Then this approach is demonstrated on an industrial lifeboat hook with three assembly design variations. The data from these experiments are utilized to evaluate the possible combinations of the assembly in terms of probability density based on the Information Axiom. The technique effectively identifies the assembly design most likely to fulfill the nonfunctional requirements. To the authors’ best knowledge, this is the first study that numerically extracts the human aspect of design at an early design stage in the decision process and considers the selection of the superior assembly design in a detailed design stage. Finally, this process is automated using a graphical user interface, which embraces the practicality of the currently integrated framework and enables manufacturers to choose the best assembly design.
期刊介绍:
Journal of Computational Design and Engineering is an international journal that aims to provide academia and industry with a venue for rapid publication of research papers reporting innovative computational methods and applications to achieve a major breakthrough, practical improvements, and bold new research directions within a wide range of design and engineering:
• Theory and its progress in computational advancement for design and engineering
• Development of computational framework to support large scale design and engineering
• Interaction issues among human, designed artifacts, and systems
• Knowledge-intensive technologies for intelligent and sustainable systems
• Emerging technology and convergence of technology fields presented with convincing design examples
• Educational issues for academia, practitioners, and future generation
• Proposal on new research directions as well as survey and retrospectives on mature field.