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.
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 language | English |
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Title of host publication | 20th IEEE International Conference on Automation Science and Engineering 2024 |
Publisher | IEEE |
Pages | 296-303 |
Number of pages | 8 |
ISBN (Electronic) | 9798350358513 |
DOIs | |
Publication status | Published - 28 Aug 2024 |
Event | 20th IEEE International Conference on Automation Science and Engineering 2024 - The Nicolaus Hotel, Bari, Puglia, Italy Duration: 28 Aug 2024 → 1 Sept 2024 Conference number: 20 https://2024.ieeecase.org/ |
Conference
Conference | 20th IEEE International Conference on Automation Science and Engineering 2024 |
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Abbreviated title | CASE 2024 |
Country/Territory | Italy |
City | Bari, Puglia |
Period | 28/08/24 → 1/09/24 |
Internet address |