• Energy Research

Due to their high speed and versatility, laser processing systems are now commonplace in many industrial production lines. However, as the need to reduce the environmental impact from the manufacturing industry becomes more urgent, there is the opportunity to evaluate laser processing systems to identify opportunities to improve energy efficiencies and thus reduce their carbon footprint. While other researchers have studied laser processing, the majority of previous work on laser systems has focused on the beam–material interaction, overlooking the whole system viewpoint and the significance of support equipment. In this work, a methodical approach is taken to design a set of energy modelling terminologies and develop a structured power metering system for laser systems. A 300 W fibre laser welding system is used to demonstrate the application of the power characterization system by utilizing a purpose-built power meter. The laser is broken down according to sub-system, with each part analysed separately to give a complete overall power analysis, including all auxiliary units. The results show that the greatest opportunities for efficiency improvements lie in the auxiliary units that support the laser devices as these were responsible for a majority of the electrical draw; 63.1% when the laser was operated at 240 W, and increasing as the beam power reduced. The remaining power draw was largely apportioned to electrical supply inefficiencies. In this work, the laser device delivered a maximum of 6% of the total system power. The implications of these results on laser processing system design are then discussed as is the suitability of the characterization process for use by industry on a range of specific laser processing systems.

AbstractIn an increasingly technological world, energy efficiency in manufacturing is of great importance. While large manufacturing corporations have the resources to commission energy studies with minimal impact on operations, this is not true for small and medium enterprises (SME’s). These businesses will commonly only have a small number of laser processing cells; thus, to carry out an energy study can be extremely disruptive to normal operations. Since rising global energy costs also have the largest impact on small businesses who lack the benefit of economies of scale, they are simultaneously the most in need of improvements to energy efficiency, while also facing the strongest practical barriers to implementing them. In this study, a laser processing energy analysis methodology was designed to run simultaneously with normal operation and applied to a laser shim-cutting cell in a UK-based SME. This paper demonstrates the methodology for identifying operating states in a production environment and Specific Energy Consumption and Scope 2 CO2 emissions results are analysed. The Processing state itself was the most impactful on overall energy performance, at 55% for single sheets of material, increasing to 71% when batch processing. Generating idealised data in this production environment is challenging with restrictions to isolating variables, these “real-world” limitations for conducting system energy analysis simultaneously with live production are also discussed to present recommendations for further analysis.

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.