Optimization of machining processes using pattern search algorithm

Optimization of machining processes not only increases machining efficiency and economics, but also the end product quality. In recent years, among the traditional optimization methods, stochastic direct search optimization methods such as meta-heuristic algorithms are being increasingly applied for solving machining optimization problems. Their ability to deal with complex, multi-dimensional and ill-behaved optimization problems made them the preferred optimization tool by most researchers and practitioners. This paper introduces the use of pattern search (PS) algorithm, as a deterministic direct search optimization method, for solving machining optimization problems. To analyze the applicability and performance of the PS algorithm, six case studies of machining optimization problems, both single and multi-objective, were considered. The PS algorithm was employed to determine optimal combinations of machining parameters for different machining processes such as abrasive waterjet machining, turning, turn-milling, drilling, electrical discharge machining and wire electrical discharge machining. In each case study the optimization solutions obtained by the PS algorithm were compared with the optimization solutions that had been determined by past researchers using meta-heuristic algorithms. Analysis of obtained optimization results indicates that the PS algorithm is very applicable for solving machining optimization problems showing good competitive potential against stochastic direct search methods such as meta-heuristic algorithms. Specific features and merits of the PS algorithm were also discussed

Optimization of cutting conditions using an evolutive online procedure

This paper proposes an online evolutive procedure to optimize the Material Removal Rate in a turning process considering a stochastic constraint. The usual industrial approach in finishing operations is to change the tool insert at the end of each machining feature to avoid defective parts. Consequently, all parts are produced at highly conservative conditions (low levels of feed and speed), and therefore, at low productivity. In this work, a framework to estimate the stochastic constraint of tool wear during the production of a batch is proposed. A simulation campaign was carried out to evaluate the performances of the proposed procedure. The results showed that it was possible to improve the Material Removal Rate during the production of the batch and keeping the probability of defective parts under a desired level

OPTIMIZATION OF CUTTING CONDITIONS FOR SUSTAINABLE MACHINING OF SINTERED POWDER METAL STEELS USING PCBN AND CARBIDE TOOLS

Powder metals are becoming a popular choice in the automotive and other manufacturing industries because of their ability to meet wide ranging product functional requirements without compromising the performance of the product. They offer various advantages, including weight reduction, near net-shape processing capability, and their ability to be sintered to achieve desired properties in the end-product. However, in order to satisfy the product design requirements during manufacturing, they need to be machined to the required tolerances. Machining of powder metals is quite different to machining of traditional metals because of their specific properties, including porosity. This thesis work deals with the finish machining of powder metal steels in automotive applications, for increased tool-life/reduced tool-wear. Tool-life is affected by a variety of factors such as tool grade selection, tool coating, cutting conditions and tool geometry including cutting edge geometry. This work involves optimization of cutting conditions for plunge cutting and boring operations of automotive powder metal components using PCBN and carbide tools. The cycle time of the process introduces an additional constraint for the optimization model along with the tool-wear criterion. Optimized cutting conditions are achieved for maximum tool-life

The influence of flute form on drill design and performance

Many modifications have been made in the past to the conventional drill points and references to the better performance of curved lip drills when cutting cast iron can be found. Similar drill points do not seem to be as successful with steel. The objective of this research was set to analyse drill design and to study the effect on drill performance of changing the drill conventional flute form when cutting steel. Changing the conventional flute form has an immediate effect on the shape of the drill lip - it is no longer a straight cutting edge. A new range of problems arises when the drill lip is a curved line as the available expressions in literature for drill cutting angles calculation are not valid except for straight lines. However, to be able to calculate and to predict the cutting angles with a nonconventional flute drill is a matter of necessity, especially if the new flute design is based or specified upon some condition relative to these angles. The drill lip shape is also influenced by the flank surface. Thus the analysis of the drill lip shape and the calculation of the cutting angles cannot be made without studying both the flute and the flank surfaces. Geometric surfaces are better deal with by computing techniques and computers. Thus the shape of a drill lip - the intersection of the flute with the point flank - and the cutting angles, are analysed by means of computer design aids for both varying flute and point flank surfaces. [Continues

Evolutionary optimization of machining processes

The many problems arising in manufacturing have led to the development of a new area of technology which Merchant has called "optimization technology" and has defined as being that area which facilitates operation of a manufacturing system at its minimum cost point, while helping to maximize performance by providing information and control. The most important areas of optimization technology are computer-related technology and variable programme automation. Variable programme automation deals largely with the direct automatic control of manufacturing operations, as in numerical control and adaptive control. This presents the possibility of the eventual realization of a fully automated self-optimizing integrated manufacturing system. [Continues.