Response of shrink fitted assemblies to the dynamic torsion

Product design is mostly centered around design of different contact pairs. Among contact pairs, interference fit pair is widely used. Design of interference fits, involves not only dimensional interference, but also condition of interface between mating surfaces. Factors such as texture of interface, hardness of interface material and also physical properties of contacting materials influence the functional characteristics of interference shrink fitted assemblies. In actual practice most of such joints are subjected to dynamic loading. Data on torsion response is only limited. So that, detailed investigation on the influence of dimensional interference, contact length and interfacial properties (electroless nickel coating) on torsion capacity of interference fitted assemblies has been carried out. The response of interference fitted assemblies to dynamic torsion load has been evaluated, using L-9 Orthogonal array of experimental conditions to bring down the number of experiments. The results are analysed using analysis of variance (ANOVA) to find out the individual effects of parameter on dynamic loading. The Torque load carrying capacity of the shrink fitted assemblies is improved by electroless nickel coating. This could be attributed to the increase in actual contact area and tenacity of Nickel plating and presence of strong molecular bonds between the mating parts chosen for the assemblies. But the selection of interference, contact length and hardness of mating parts play a vital role in deciding the performance of these joints. The results clearly indicate that the dynamic performance of the assemblies could be improved by suitably selecting the materials keeping in mind the above factors. It is also found from the ANOVA results that the assemblies with (hardness) coated interlayer performed better. Interference and contact length also has influence on the strength but in this case their influence is not very significant. An expression is obtained using regression analysis, which gives relationship between the parameters. A result obtained from regression analysis is closer to the experimental values.