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Aluminium alloys can be used as lightweight and high-strength materials in combination with the technology of laser beam welding, an efficient joining method, in the manufacturing of automotive parts. The purposes of this paper are to conduct laser welding experiments with Al2024 in the lap joint configuration, model the laser welding process parameters of Al2024 alloys and use propounded models to optimize the process parameters.

Laser welding of Al2024 alloy has been conducted in the lap joint configuration. Then, the influences of explanatory variables (laser peak power, scanning speed and frequency) on outcome variables (weld width [WW], throat length [TL] and breaking load [BL]) have been investigated with Poisson regression analysis of the data set derived from experimentation. Thereafter, a multi-objective genetic algorithm (MOGA) has been used using MATLAB to find the optimum solutions. The effects of various input process parameters on the responses have also been analysed using response surface plots.

The promulgated statistical models, derived with Poisson regression analysis, are evinced to be well-fit ones using the analysis of deviance approach. Pareto fronts have been used to demonstrate the optimization results, and the maximized load-bearing capacity is computed to be 1,263 N, whereas the compromised WW and TL are 714 µm and 760 µm, respectively.

This work of conducting laser welding of lap joint of Al2024 alloy incorporating the Taguchi method and optimizing the input process parameters with the promulgated statistical models proffers a neoteric perspective that can be useful to the manufacturing industry.

The purpose of this paper is to present a multi criterion failure mode effect and criticality analysis for coal-fired thermal power plants using uncertain data as well as substituting the traditional risk priority number estimation method.

Grey-complex proportional assessment (COPRAS-G) method, a multi criteria decision making tool is applied to evaluate the criticalities of the failure modes (alternatives). In this model the criteria (criticality factor) against each alternative are expressed in grey number instead of crisp values.

Rupture failure of the straight tube of economizer (ECO) due to erosion is the highest critical failure mode whereas rupture failure of the stub of ECO due to welding defect is the lowest critical failure mode.

This paper incorporates human and environmental factors as additional factors which also influence the failure modes significantly. The COPRAS-G method is modified according this problem. Uncertainty in the scoring of criticality factors against each failure mode by various maintenance personnel is expressed in grey numbers.