In this work, the effect of pulse temporal and spatial overlapping is evaluated in selective laser melting (SLM). An SLM system operating with fiber laser in pulsed wave (PW) emission was employed. The test material was 18Ni300 maraging steel, which shows reduced process stability due to a high amount of vapour and spark generation during the process. The pulsation characteristics of contemporary power-modulated fiber lasers compared to previously employed Q-switched Nd:YAG systems are explained. Processing conditions are studied moving towards continuous wave (CW) by increasing the duty cycle with fixed fluence. The key quality aspects, namely part density and dimensional error, were evaluated and the robustness was assessed. The results demonstrate that with a limited amount of increase in duty cycle by 3%, part density can be improved, while the dimensional error increases. The results show that CW is preferable when fully dense large parts have to be obtained. On the other hand, operating in PW is convenient when thin struts as in lattice structure or micro and precise features are required
Abstract-This paper studies self-mixing interferometry (SMI) for measuring ablation depth during laser percussion drilling of TiAlN ceramic coating. The measurement performance of SMI was investigated in a large processing range producing blind microholes with depths below and beyond the average coating thickness. Signal characteristics of the measurement system were evaluated indicating sources of disturbance. The SMI measurements were compared with a conventional measurement device based on focus variation microscopy to evaluate the measurement error. The measurement error classes were defined, as well as defining the related error sources. The results depict that the measurement error was independent of the processing condition, hence the hole geometry and ablation rate. For 76% of cases, measurement error was below the intrinsic device resolution obtainable by simple fringe counting of half a wavelength (λ/2 = 0.393 μm).
SUMMARYThis work presents the results of a project aimed at verifying the applicability of industrial model predictive control (MPC) to thermal Power Plants. The research is motivated by the need to improve the efficiency of power plants so as to cope with the high levels of competition induced by the deregulation of the energy market. A detailed plant simulator, already used for operators training and controllers tuning, is coupled to an industrial software package implementing the dynamic matrix control algorithm. The achieved results witness the great potentialities of MPC, with respect to classical decentralized schemes, in terms of economical savings, reduction of pollutants, improved flexibility, easier tuning and better documentation.
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