Optimising the laser-welded butt-joints of medium carbon steel using RSM

The optimization capabilities in design-expert software were used to optimise the keyhole parameters (i.e. maximize penetration (P) and minimise the heat input, width of welded zone, (W) and width of heat affected zone (WHAZ)) in CW CO2 laser butt-welding of medium carbon steel. The previous developed mathematical models to predict the keyhole parameters in terms of the process factors namely; laser power (LP), welding speed (S) and focused position (F) were used to optimize the welding process. The goal was to set the process factors at optimum values to reach the desirable weld bead quality and to increase the production rate. Numerical and graphical optimization techniques were used. In fact, two optimization criteria were taken into account. In this investigation optimal solutions were found that would improve the weld quality, increase the productivity and minimize the total operation cost. In addition to that, superimposing the contours for the various response surfaces produced overlay plots

Development of an Ant Colony Optimization Algorithm to improve Maintenance Process Efficiency

Efficient maintenance policies are of fundamental importance because of their fallbacks into the safety and economics of air traffic operations. Usually the optimization of maintenance process is limited to a resource optimization in position and number. But it should be considered that maintenance tasks are performed by man whose excessive workload has negative falls-out not only for workers well-being but also for process safety and efficiency. Thus, in maintenance process optimization it is necessary to take into account also ergonomic aspects of workplace. This gives rise to an optimization of the maintenance process by using an ergonomic approach. In this way, the result of the optimization could allow improvements in the quality of the work of maintenance, but also a greater efficiency of the whole maintenance system. An ant colony optimization algorithm has been developed in order to optimize the system efficiency. This kind of algorithm natively permits to improve man movements into the workplace; furthermore the optimization of the workplace ergonomics has been added. To do this, an objective function of efficiency levels has been determined, linked to any task performed by man. Some protocols have been created on the basis of a literature survey and experimental results. This paper illustrates an applied research in which a method for the optimization of the maintenance process efficiency has been developed in order to show the applicability of a tool offering benefits on both sides: the maintenance process and the related human factors

Designing Algorithms for Optimization of Parameters of Functioning of Intelligent System for Radionuclide Myocardial Diagnostics

The influence of the number of complex components of Fast Fourier transformation in analyzing the polar maps of radionuclide examination of myocardium at rest and stress on the functional efficiency of the system of diagnostics of pathologies of myocardium was explored, and there were defined their optimum values in the information sense, which allows increasing the efficiency of the algorithms of forming the diagnostic decision rules by reducing the capacity of the dictionary of features of recognition.The information-extreme sequential cluster algorithms of the selection of the dictionary of features, which contains both quantitative and category features were developed and the results of their work were compared. The modificatios of the algorithms of the selection of the dictionary were suggested, which allows increasing both the search speed of the optimal in the information sense dictionary and reducing its capacity by 40 %. We managed to get the faultless by the training matrix decision rules, the accuracy of which is in the exam mode asymptotically approaches the limit.It was experimentally confirmed that the implementation of the proposed algorithm of the diagnosing system training has allowed to reduce the minimum representative volume of the training matrix from 300 to 81 vectors-implementations of the classes of recognition of the functional myocardium state

Evolutionary Algorithms for

Many real-world problems involve two types of problem difficulty: i) multiple, conflicting objectives and ii) a highly complex search space. On the one hand, instead of a single optimal solution competing goals give rise to a set of compromise solutions, generally denoted as Pareto-optimal. In the absence of preference information, none of the corresponding trade-offs can be said to be better than the others. On the other hand, the search space can be too large and too complex to be solved by exact methods. Thus, efficient optimization strategies are required that are able to deal with both difficulties. Evolutionary algorithms possess several characteristics that are desirable for this kind of problem and make them preferable to classical optimization methods. In fact, various evolutionary approaches to multiobjective optimization have been proposed since 1985, capable of searching for multiple Paretooptimal solutions concurrently in a single simulation run. However, in spite of this variety, there is a lack of extensive comparative studies in the literature. Therefore, it has remained open up to now

Speed trajectory planning at signalized intersections using sequential convex optimization

An algorithm is developed to optimize vehicle speed trajectory over multiple signalized intersections with known traffic signal information to minimize fuel consumption and travel time, and to meet ride comfort requirements using sequential convex optimization method. A comparison between the proposed method and dynamic programming is carried out to verify its optimality. In addition, vehicle motion during turning is studied because of its significant effect on fuel consumption and travel time.Comment: 2017 American Control Conference, May 24-26, Seattle, WA, US