Machine learning (ML) and artificial intelligence (AI) are rising stars in many scientific
disciplines and industries, and high hopes are being pinned upon them. Likewise, ML and …

The evolutionary optimisation algorithms appeared as an effective alternative to
conventional statistical methods that have certain limitations in optimising complex …

The effective optimization of machining process parameters affects dramatically the cost and
production time of machined components as well as the quality of the final products. This …

The optimum selection of process parameters is essential for advanced machining
processes, as these processes incur high initial investment, tooling cost, and operating and …

Manufacturing factories, having continuous pursuit of productivity and quality, often meet
challenges in coping with high production complexities and uncertainties. These are the …

This paper presents an effect of friction welding parameters on the tensile strength and
microstructural properties of dissimilar AISI 1020-ASTM A536 joints. A hybrid response …

In this paper, an integrated optimization approach using an artificial neural network and a
bidirectional particle swarm is proposed. The artificial neural network is used to obtain the …

In the last few years, an increasing attention has been paid to the issues of saving energy
and reducing the manufacturing costs in the transport industry which necessitates further …

In submerged arc welding (SAW), weld quality is greatly affected by the weld parameters
such as welding current, welding speed; arc voltage and electrode stickout since they are …

This papers describes a search technique to optimize the fabrication process conditions of
the high wear resistance Al alloy matrix composites reinforced with different volume …