The paper presents the application of the newly developed method of the solution of nonlinear equations to the adaptive modelling and computer simulation. The approach is suitable when the system of equations can be arranged in such a way that it consists of a large number of linear equations and a smaller number of nonlinear equations. This situation occurs in the case of adaptive modelling of mechanical systems using finite elements or finite differences techniques. In this case the classical least square method becomes very effective. The paper presents several examples of the application of the method. A solution to the, so called, “black box” problem is also presented.
Aluminium metal matrix composites (AMMCs) are the fastest developing materials for structural applications. Friction Stir Processing (FSP) has evolved as a promising surface composite fabrication technique mainly because it is an eco-friendly and solid-state process. A spurt in the interest of research community and a resulting huge research output makes it difficult to find relevant information to further the research with objectivity. To facilitate this, the present article addresses the current state of the art and development in surface metal matrix fabrication through FSP with a specific focus on ex-situ routes. The available literature has been carefully read and categorized to present effects of particle size, morphology and elemental composition. The effect of various reinforcements on development of different functional characteristics is also discussed. Effect of main FSP parameters on various responses is presented with objectivity. Based on the studied literature concluding summary is presented in a manner in which the literature becomes useful to the researchers working on this important technology.
The focus of this paper is to propose a method for prioritizing knowledge and technology factor in companies’ business strategy. The data has been gathered and analyzed from Malaysian-owned company of medium size type industry, employing around 250 employees and listed in the Malaysian Bourse Stock of Exchange, since 2000. Sense and respond model is used to determine competitive priorities of the firms. Then knowledge and technology part of sense and respond questionnaire is used to calculate the variability coefficient i.e. the uncertainty caused by technology and knowledge factor. The results show that the company is not leading in term of technology (spear head technology share is around 33%). Therefore, the enhancement of technology and knowledge to SCA values is not significantly seen in this study. The usage of the core technologies is around 41% and it might seem relatively enough. In terms of basic technology, while its share is the lowest (around 25%), it has the highest source of uncertainties among technology types. In this case, the proposed model helped to have a clear and precise improvement plan towards prioritizing technology and knowledge focus.