Artificial Intelligence Applications for Advancing the Canadian Steel Construction Industry

人工智能应用推动加拿大钢结构行业发展

• 批准号: 566566-2021
• 负责人: Driver, Robert
• 金额: $ 1.46万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=722329
• 关键词: Artificial; Intelligence; Applications; Advancing; Canadian

During the last 20 years, ground-breaking advancements in computer hardware, data science, and artificial intelligence technologies, such as artificial neural networks, genetic algorithms, machine learning, big data and data mining, and optimization algorithms have made possible huge advances for many industries, helping them become more efficient and competitive. In industries like finance, transportation, and logistics, artificial intelligence has revolutionized procedures and allowed these industries to tap into new revenue streams. Artificial intelligence is a key technology used to analyze, understand, and ultimately benefit from data. In the construction industry, it can be used to enhance and accelerate decision-making for stakeholders, making processes more efficient, increasing competitiveness, and furthering sustainability objectives--aiding, rather than replacing, decision makers. Although many of these advanced technologies are now well understood, limited applications exist in the steel construction industry, but there is ample opportunity for fabricators to enhance outcomes by providing them with tools to automate workflows and increase efficiency, quality, cost effectiveness, and safety.The proposed research project aims to incorporate emerging technologies from the fields of computer and data science into structural steel design and fabrication. This project is the first of its kind in the Canadian steel construction industry, implementing artificial intelligence technologies and data science techniques to the design and fabrication of structural steel connections, accounting for inventory management, one- and two-dimensional cutting, and fabrication operations. The project is split into three main themes: (1) steel connection design optimization; (2) cutting and fabrication of structural steel members; and (3) management of inventory during the optimization processes.

在过去的20年里，计算机硬件、数据科学和人工智能技术的突破性进步，如人工神经网络、遗传算法、机器学习、大数据和数据挖掘，以及优化算法，为许多行业带来了巨大的进步，帮助它们变得更有效率和更具竞争力。在金融、运输和物流等行业，人工智能已经彻底改变了流程，并使这些行业获得了新的收入来源。人工智能是用于分析、理解数据并最终从数据中获益的关键技术。在建筑行业，它可以用来加强和加速利益相关者的决策，使流程更有效率，提高竞争力，并进一步实现可持续发展目标——帮助而不是取代决策者。尽管许多这些先进技术现在已经被很好地理解，但在钢结构行业的应用有限，但制造商有充足的机会通过为他们提供自动化工作流程和提高效率、质量、成本效益和安全性的工具来提高结果。拟议的研究项目旨在将计算机和数据科学领域的新兴技术纳入结构钢的设计和制造中。该项目是加拿大钢结构行业的首个此类项目，将人工智能技术和数据科学技术应用于结构钢连接的设计和制造、库存管理、一维和二维切割以及制造操作。本课题主要分为三个主题：(1)钢连接设计优化；(2)结构钢构件的切割加工；(3)优化过程中的库存管理。