{"title":"ALDRAW:算法工程表示法","authors":"Abhinav Pandey, Vidit Gaur","doi":"10.1016/j.aei.2025.103362","DOIUrl":null,"url":null,"abstract":"<div><div>Engineering drawings have been the predominant representation of engineering information but have several deficiencies due to their graphical nature. This paper addresses these issues by proposing an algorithmic framework, ALDRAW, to represent engineering information and de-link design option qualification from representation. ALDRAW enhances engineering communication by enabling purposefulness, explainability, information scalability, domain abstraction, active collaboration, version control, knowledge transfer and machine learning in the representations. The framework has been successfully tested on real-world facility layout and other engineering problems, and compared with other proposed approaches in recent literature, demonstrating its potential to improve the engineering process through more effective and efficient information representation. A web application is also developed based on this framework using Django Python for real-world projects. Recommendations towards industry adoption and future research are also highlighted.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"65 ","pages":"Article 103362"},"PeriodicalIF":8.0000,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ALDRAW: Algorithmic engineering representations\",\"authors\":\"Abhinav Pandey, Vidit Gaur\",\"doi\":\"10.1016/j.aei.2025.103362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Engineering drawings have been the predominant representation of engineering information but have several deficiencies due to their graphical nature. This paper addresses these issues by proposing an algorithmic framework, ALDRAW, to represent engineering information and de-link design option qualification from representation. ALDRAW enhances engineering communication by enabling purposefulness, explainability, information scalability, domain abstraction, active collaboration, version control, knowledge transfer and machine learning in the representations. The framework has been successfully tested on real-world facility layout and other engineering problems, and compared with other proposed approaches in recent literature, demonstrating its potential to improve the engineering process through more effective and efficient information representation. A web application is also developed based on this framework using Django Python for real-world projects. Recommendations towards industry adoption and future research are also highlighted.</div></div>\",\"PeriodicalId\":50941,\"journal\":{\"name\":\"Advanced Engineering Informatics\",\"volume\":\"65 \",\"pages\":\"Article 103362\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Engineering Informatics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1474034625002551\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Engineering Informatics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1474034625002551","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Engineering drawings have been the predominant representation of engineering information but have several deficiencies due to their graphical nature. This paper addresses these issues by proposing an algorithmic framework, ALDRAW, to represent engineering information and de-link design option qualification from representation. ALDRAW enhances engineering communication by enabling purposefulness, explainability, information scalability, domain abstraction, active collaboration, version control, knowledge transfer and machine learning in the representations. The framework has been successfully tested on real-world facility layout and other engineering problems, and compared with other proposed approaches in recent literature, demonstrating its potential to improve the engineering process through more effective and efficient information representation. A web application is also developed based on this framework using Django Python for real-world projects. Recommendations towards industry adoption and future research are also highlighted.
期刊介绍:
Advanced Engineering Informatics is an international Journal that solicits research papers with an emphasis on 'knowledge' and 'engineering applications'. The Journal seeks original papers that report progress in applying methods of engineering informatics. These papers should have engineering relevance and help provide a scientific base for more reliable, spontaneous, and creative engineering decision-making. Additionally, papers should demonstrate the science of supporting knowledge-intensive engineering tasks and validate the generality, power, and scalability of new methods through rigorous evaluation, preferably both qualitatively and quantitatively. Abstracting and indexing for Advanced Engineering Informatics include Science Citation Index Expanded, Scopus and INSPEC.