Three Approaches to the Automation of Laser System Alignment and Their Resource Implications: A Case Study

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The alignment of optical systems is a critical step in their manufacture. Alignment normally requires considerable knowledge and expertise of skilled operators. The automation of such processes has several potential advantages, but requires additional resource and upfront costs. Through a case study of a simple two mirror system we identify and examine three
different automation approaches. They are: artificial neural networks; practice-led, which mimics manual alignment practices; and design-led, modelling from first principles. We find that these approaches make use of three different types of knowledge 1) basic system knowledge (of controls, measurements and goals); 2) behavioural skills and expertise, and 3) fundamental system design knowledge. We demonstrate that the different automation approaches vary significantly in human resources, and measurement sampling budgets. This will have implications for practitioners and management considering the automation of such tasks.
Original languageEnglish
Title of host publication20th IEEE International Conference on Automation Science and Engineering 2024
PublisherIEEE
Pages296-303
Number of pages8
ISBN (Electronic)9798350358513
DOIs
Publication statusPublished - 28 Aug 2024
Event20th IEEE International Conference on Automation Science and Engineering 2024 - The Nicolaus Hotel, Bari, Puglia, Italy
Duration: 28 Aug 20241 Sept 2024
Conference number: 20
https://2024.ieeecase.org/

Conference

Conference20th IEEE International Conference on Automation Science and Engineering 2024
Abbreviated titleCASE 2024
Country/TerritoryItaly
CityBari, Puglia
Period28/08/241/09/24
Internet address

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