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Development of a framework for the design of expanded metal facades: Using artificial intelligence to streamline pre-production work
Linköping University, Department of Management and Engineering, Product Realisation.
Linköping University, Department of Management and Engineering, Product Realisation.
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The field of design automation aims to automate repetitive tasks in a workflow in order to free up time for more productive work. In this thesis, design automation with the help of AI techniques is investigated to streamline the pre-production work of expanded metal facades. 

Two different problems concerning pre-production work are investigated in this thesis. The first one focuses on how to translate architectural drawings in pdf format to a bill of material. The second problem aims to develop a non-linear method for calculating the free area of the expanded metal facades.

The method used for this project is an adaptation of the product development process with the inspiration of knowledge-based engineering. 

For the first project, the AI method template matching was successfully used. With a script using this method, most of the panels are identified, except for panels where the drawings do not provide clear lines or where lines around the panels do not exist. The line quality in the architectural drawings was shown to impact the size estimation of the panels.

In the second project, a non-linear machine learning model was developed. However, it was not managed within this project to get a good enough accuracy. The main reason for this is that it is suspected that the data is not accurate enough, nor are the 78 data points enough to train the model.

Place, publisher, year, edition, pages
2022. , p. 47
Keywords [en]
Artificial Intelligence, AI, Template Matching, Machine Learning, Neural Networks, Expanded Metal, Design Automation, Product Development
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-185990ISRN: LIU-IEI-TEK-A--22/04324—SEOAI: oai:DiVA.org:liu-185990DiVA, id: diva2:1677745
Subject / course
Mechanical Engineering
Presentation
2022-06-07, A37, A-Huset, 581 83 Linköping, 13:00 (English)
Supervisors
Examiners
Available from: 2022-06-28 Created: 2022-06-28 Last updated: 2022-06-28Bibliographically approved

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CiteExportLink to record
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