1. Three Approaches to the Automation of Laser System Alignment and Their Resource Implications: A Case Study
- Author
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Robb, David A., Risbridger, Donald, Mills, Ben, Rakhmatulin, Ildar, Kong, Xianwen, Erden, Mustafa, Esser, M. J. Daniel, Carter, Richard M., and Chantler, Mike J.
- Subjects
Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Machine Learning ,Computer Science - Robotics - 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., Comment: Author Accepted Manuscript- 8 pages, The 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE 2024), Aug28-Sep1st 2024, Bari, Italy. Keywords: Automation, optimisation, regression, behaviour analysis, artificial neural networks, optical systems, mathematical model, human factors, sampling cost, cost benefit analysis
- Published
- 2024