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The paper deals with experimental investigations of the influence of laser beam and plasma arc cutting parameters on edge quality of a range of steel grades and thicknesses. Based on the experimental results, a variety of methods have been taken to carry out the analysis of influence of laser beam and plasma arc cutting parameters on the quality and mechanical properties of cut edges of selected high-strength low-alloy (HSLA) strips and plates. In this study, three approaches were investigated corresponding to rank correlation analysis, multidimensional data analysis and decision trees. These techniques were able to elucidate the most relevant cutting parameters as well as the optimal field of values of these parameters to give the required geometrical and mechanical quality levels. As a result of this study, general rules in the form of cutting procedure specifications were established. This was needed to describe the relation between laser beam or plasma arc cutting parameters and the geometrical and mechanical quality factors of cut edges of different medium-and high-strength steel materials. The proposed rules can be also adopted for providing a comparison between the surface qualities achievable by the different combinations of cutting parameters for laser beam and plasma arc cutting processes of medium-and high-strength steels.

The article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. Model-based optimization was used to determine the driving strategy. The numerical model was elaborated in Simulink environment, which includes both the electric vehicle model and the environment, i.e., the race track as well as the vehicle environment and the atmospheric conditions. The vehicle model itself includes vehicle dynamic model, numerical model describing issues concerning resistance of rolling tire, resistance of the propulsion system, aerodynamic phenomena, model of the electric motor, and control system. For the purpose of identifying design and functional features of individual subassemblies and components, numerical and stand tests were carried out. The model itself was tested on the research tracks to tune the model and determine the calculation parameters. The evolutionary algorithms, which are available in the MATLAB Global Optimization Toolbox, were used for optimization. In the race conditions, the model was verified during SEM races in Rotterdam where the race vehicle scored the result consistent with the results of simulation calculations. In the following years, the experience gathered by the team gave us the vice Championship in the SEM 2016 in London.

The paper presents the application of various classification schemes for actuator fault diagnosis in industrial systems. The main objective of this study is to compare either single or meta-classification strategies that can be successfully used as reasoning means in off-line as well as on-line diagnostic expert systems. The applied research was conducted on the assumption that only classic and well-practised classification methods would be adopted. The comparison study was carried out within the DAMADICS benchmark problem which provides a popular framework for confronting different approaches in the development of fault diagnosis systems.

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