Energy consumption and performance optimisation of laser cleaning for coating removal. (May 2022)

• Record Type: Journal Article
• Authors: Ouyang, J.; Mativenga, P.; Goffin, N.; Liu, W.; Liu, Z.; Mirhosseini, N.; Jones, L.; Woolley, E.; Li, L.
• Is Part Of: CIRP journal of manufacturing science and technology. Volume 37(2022)
• Page Start: 245
• Page End: 257
• Publication Date: 2022-05
• Subjects: Laser -- Selective coating removal -- Tools -- Energy consumption -- Cleaning rate -- Cobalt binder; Manufacturing processes -- Periodicals; 670.5
• DOI: 10.1016/j.cirpj.2022.02.001
• Languages: English
• ISSNs: 1755-5817

Abstract

Highlights: Fundamental understanding of input factors for maximising cleaning rate and minimising energy requirements. Compositional surface integrity after laser cleaning. New specific energy consumption and processing rate model. High laser pulse frequency as a key tool for rapid cleaning and low energy consumption in support of low carbon manufacturing. Graphical Abstract: Energy consumption and performance optimisation of laser cleaning for coating removal. ga1 Abstract: Selective removal of coatings by lasers can facilitate the reuse of coated tools in a circular economy. In order to optimise and control the process, it is essential to study the impact of process input variables on process performance. In this paper, coating removal from tooling was carried out using a picosecond a pulsed fibre laser, in order to investigate the effects of laser pulse energy, pulse frequency, galvo scanning speed and scanning track stepover. A fractional factorial design of experiments and analysis of variance was used to optimise the process; considering cleaning rate, specific energy consumption and surface integrity as assessed by changes in surface roughness and composition of the tooling after laser cleaning. The results shows synergy between cleaning rate and specific energy with the laser pulse frequency and galvo scanning speed as the two most significant factors, while the laser pulse energy had the greatest contribution to changes in surface composition. Based on extensive experiments, the relationship between processing rate and system specific energy consumption was mathematically modelled. The paper contributes a new specific energy model for laser cleaning and provides a benchmark of the process energy requirements compared to other manufacturing processes. Additionally, the generic scientific learning from this is that the rate of energy input is a key tool for maximising cleaning rate and minimising specific energy requirements, while the intensity of energy applied, is a key metric that influences surface integrity. More complex factors, influence the surface integrity.