{"title":"Design for assembly approach for additive manufacturing products: a decision support system for large-size AM products","authors":"Muhammad Umer Shan, Salman Hussain","doi":"10.22581/muet1982.2301.05","DOIUrl":null,"url":null,"abstract":"In a contemporary era, Additive Manufacturing (AM), 3D printing or rapid prototyping has evolved as a distinctive method when compared with the traditional manufacturing. By addressing the topic of Design for Additive Manufacturing (DFAM), it is observed that the basic principles of DFAM and Design for Assembly (DFA) are well established and usually applicable on small-size AM parts. To address this critical manufacturing decision, our research work presents a new decision support system (DSS) for a large-size AM part which is based on compiling the existing DFAM methodologies. Before presenting the new DSS, the previous DFAM approaches are reviewed and investigated the research trends in part decomposition (PD), part consolidation (PC), and topology optimization (TO). The literature is categorized into six distinctive categories and among them the first phase is the information phase. Following this information requisite step, the next phase is parameter assessment phase and so on. The new DSS starts with the clarification of the design goal while in previous approaches this step was usually done at the later stages. Similarly, the remaining steps are efficiently integrated into the framework structure. The developed system is also guiding the post-decomposition assembly process. The developed DSS is validated using the case study of a 6-axis robotic arm. Moreover, a comprehensive concept for using the developed DSS framework is also presented in the research work.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mehran University Research Journal of Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22581/muet1982.2301.05","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In a contemporary era, Additive Manufacturing (AM), 3D printing or rapid prototyping has evolved as a distinctive method when compared with the traditional manufacturing. By addressing the topic of Design for Additive Manufacturing (DFAM), it is observed that the basic principles of DFAM and Design for Assembly (DFA) are well established and usually applicable on small-size AM parts. To address this critical manufacturing decision, our research work presents a new decision support system (DSS) for a large-size AM part which is based on compiling the existing DFAM methodologies. Before presenting the new DSS, the previous DFAM approaches are reviewed and investigated the research trends in part decomposition (PD), part consolidation (PC), and topology optimization (TO). The literature is categorized into six distinctive categories and among them the first phase is the information phase. Following this information requisite step, the next phase is parameter assessment phase and so on. The new DSS starts with the clarification of the design goal while in previous approaches this step was usually done at the later stages. Similarly, the remaining steps are efficiently integrated into the framework structure. The developed system is also guiding the post-decomposition assembly process. The developed DSS is validated using the case study of a 6-axis robotic arm. Moreover, a comprehensive concept for using the developed DSS framework is also presented in the research work.