This is the first issue of the fifth volume of The IUP Journal of Mechanical Engineering (IUPJME), the peer reviewed academic journal published quarterly. In the past volumes, the coverage of the journal included theoretical and experimental findings in mechanical and closely-related fields. It continues to seek to publish articles that are not only technically competent, but are original and contain information or ideas of fresh interest to our learned readership. I welcome dialogue with the contributors as well as with the readers (rkm.rkm@gmail.com). In the coming year, it is our vision to have IUPJME publish high quality manuscripts from distinguished scholars on recent mechanical and allied engineering issues to further build its reputation.

The five papers in this issue present new applications of well-known techniques, application of software tools and experimental findings of the authors. The first paper is an application of neural networks in the design of gear trains, the next two papers describe applications of software tools, and the last two are on experimental findings. Neural networks have huge potential and are finding newer applications in engineering. Their applications in the area of kinematics are few. The first paper, “A Genetic Algorithm for Structural Comparison in the Fleet of Gear Trains”, by A B Srinivasa Rao, M Sreenivasa Reddy and A M K Prasad, is an extension of application of an algorithm developed for the structural comparison of in-parallel robotic manipulators. The algorithm is applied to gear trains, taking care of the fact that the graphs representing gear trains contain edges of different types unlike linkages in a robot.

To select the best train from the numerous distinct gear trains with the same number of links and degree of freedom, it is desirable to know the characteristics like speed ratio, transmission efficiency, etc., inherent to the structure. The authors have used graph theory-based technique to convert gear train into a graph that can be viewed in terms of half-adjacency, one-adjacency, etc., and have formulated corresponding matrices and applied genetic algorithm to develop quantitative measures. Following the principles of mating, the fitness matrices for adjacency were obtained and the fitness strings, adjacency-wise, were developed for every chain. Fitness strings of two chains reveal isomorphism and fitness value is related to parallelism. Greater value of fitness reflects productive mating of design parameters and more parallelism. Chains with higher fitness are more parallel in structural arrangement of its links and give higher speed ratios, transmission efficiency, more rigid structurally and are less sensitive to accumulation of joint mechanical errors.

The second paper by Kartikeya Tripathi and Vikrant Kulthe gives a method for computation of “Deflection and Stresses in Heavy Propeller Shafts Considering Deformation of Bushed Bearings and Foundation Bolts.” For long marine propeller shafts supported on intermediate bearings transmitting high torque, classical beam theory does not give correct stress and deflection values, as it does not account for the deformation of bearings, supports, bolts used to fix supports to hull and compliance of hull. In this paper, the authors have used finite element method to account for all these factors and compared the results with those obtained using the classical beam theory. The method of analysis and the results should be useful in estimating the deflections and stresses in heavy and long shafts with better accuracy. This approach should also be useful in estimating the possibility of failure due to excessive stresses and deflections during mounting and assembly of such shafts. Their results include shaft deflections, flange-end deflection and stresses for different foundation bolt sizes, rigid and nonrigid bearings.

The third paper, “An Application of Inner Product of Vectors for Selecting Suitable Material”, by Senthil S, examines multiple criteria decision-making problem and the material selection attributes and their relative importance. Material selection is an important step in the process of design as a large variety of available materials are suitable for any desired application, with each material having its own characteristics, applications, advantages and limitations. The proposed method was demonstrated with an example. The author has considered a finite number of attributes and converted qualitative attributes into quantitative value by using a fuzzy conversion scale.

The paper, “Effect of Tool Geometry on Joint Properties of Friction Stir Welded Al/Cu Bimetallic Lap Joints”, by M Satya Narayana Gupta, B Balunaik and K G K Murti, is an experimental exploration of Friction Stir Welding (FSW) technique for joining dissimilar materials like pure Al/Cu. Aluminium and copper are incompatible metals to welding due to a high affinity to each other at a temperature more than 125 °C and produce intermetallic compounds, which are brittle in nature, mechanically and electrically unstable, because they contain a nonmetallic covalence bond. The paper presents information on electromechanical behavior of aluminium to copper bimetallic lap joints fabricated by the FSW technology using tapered and straight fluted tools. The authors claim making use of Design of Experiments (DoE) to reduce the number of trials, and better joint properties were obtained in the joints fabricated using straight fluted tool and the joint resistance was found negligible.

The last paper, “A Study of Semi-Automated Speed Controlling Device for Wood Machining”, by R V Praveena Gowda, A N N Murthy and E Muniraju presents the work on a wood cutting machine with a controller for speed of the cutter, depending on the hardness of the material. The bill of material for the semi-automated speed controlling device for wood cutting machine to vary the speed of the cutter is only given in the paper. By using the developed machine for experiments on the machining of different types of wood, various measurements were done and the results are reported. It is claimed that the power utilization using the designed machine would reduce by about 42% and the tool life would also be increased.

-- R K Mittal
Consulting Editor