Neo Arithmetic and Ranking Techniques for Trapezoidal Generalized Interval Valued Fuzzy Numbers: Their Applications in Decision Making for Medical Investigation

Neural Processing Letters - The uncertainty caused mainly by the deficiency of precision and data, artificial/human-made errors, information accessed from expert opinions or very miniature size of...     

Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Transport phenomena in laser surface alloying

A three dimensional, transient model is developed for studying heat transfer, fluid flow and mass transfer for the case of a single-pass laser surface alloying process. The numerical study is performed in a co-ordinate system fixed to the laser which moves with a constant scanning speed. The coupled momentum, energy and species conservation equations are solved using a finite volume technique. Phase change processes are modelled using a fixed-grid enthalpy-porosity technique, which is capable of predicting the continuously evolving solid-liquid interface. The three-dimensional model is able to predict the species concentration distribution inside the molten pool during alloying, as well as in the entire cross section of the solidified alloy. Corresponding experimental results show a good qualitative agreement with the numerical predictions with regard to pool shape and final composition distribution.     

Lean philosophy: implementation in a forging company

This research addresses the implementation of lean philosophy in a forging company with a focus on radial forging production flow lines. Here, the prime motive is to evolve and test several strategies to eliminate waste on the shop floor. In this research, a systematic approach is suggested for the implementation of lean principles. This paper describes an application of value stream mapping (VSM). Consequently, the present and future states of value stream maps are constructed to improve the production process by identifying waste and its sources. Furthermore, Taguchi’s method of design of experiments is pursued here to minimize the forging defects produced due to imperfect operating conditions. A noticeable reduction in set-up time and work-in-process (WIP) inventory level is substantiated. Finally, we conclude with a discussion of managerial implications and the future scope of research.     

Design of a wideband microstrip antenna and the use of artificial neural networks in parameter calculation

This paper deals with the design of a multi-slot hole-coupled microstrip antenna on a substrate of 2 mm thickness that gives multi-frequency (wideband) characteristics. The Method of Moments (MoM)-based IE3D software was used to simulate the results for return loss, VSWR, the Smith chart, and the radiation patterns. A tunnel-based artificial neural network (ANN) was also developed to calculate the radiation patterns of the antenna. The radiation patterns were measured experimentally at 10.5 GHz and 12 GHz. The experimental results were in good agreement with the simulated results from IE3D and those of the artificial neural network. A new method of using a genetic algorithm (GA) in an artificial neural network is also discussed. This new method was used to calculate the resonant frequency of a single-shorting-post microstrip antenna. The resonant frequency calculated using the genetic-algorithm-coupled artificial neural network was compared with the analytical and experimental results. The results obtained were in very good agreement with the experimental results.     

Densification and Properties of α-Silicon Carbide

Densification of a-Sic powders with no premixed sintering aids (type 1) and with premixed B and C (type 2) was investigated by sintering them at 2150° to 2200°C for 30 min. Flexure strengths, Weibull moduli, and fracture flaws were characterized for type 2 α-SiC only. The results were compared with those for a state-of-the-art sintered a-Sic material.     

The Design of Discrimination Experiments

Experimentation plays a fundamental role in scientific discovery. Scientists experiment to gather data, investigate phenomena, measure quantities, and test theories. In this article, we address the problem of designing experiments to discriminate between two completing theories. Given an initial situation for which the two theories make the same prediction, the experiment design problem is to determine how to modify the situation such that the two theories make different predictions for the modified situation. The modified situation is called a discrimination experiment. We present a knowledge-intensive method called DEED for designing discrimination experiments. The method analyzes the differences in the two theories' explanations of the prediction for the initial situation. Based on this analysis, it determines modifications to the initial situation that will result in a discrimination experiment. We illustrate the method with the design of experiments to discriminate between several pairs of qualitative theories in the fluids domain.