Friction welding is one of the foremost welding processes for similar and dissimilar metals. Previously, the process has been modeled utilizing the rudimentary techniques of constant friction and slip-stick friction. The motivation behind this article is to present a new characteristic for temperature profile estimation in modeling of the rotary friction welding process. For the first time, a unified model has been exhibited, with an implementation of the phase transformation of similar and dissimilar materials. The model was generated on COMSOL Multiphysics^® and thermal and structural modules were used to plot the temperature curve. The curve for the welding of dissimilar metals using the model was generated, compared and analyzed with that of practical curves already acquired through experimentation available in the literature, and then the effect of varying the parameters on the welding of similar metals was also studied.

Effective maintenance strategies are of utmost significance for system engineering due to their direct linkage with financial aspects and safety of the plants’ operation. At a point where the state of a system, for instance, level of its deterioration, can be constantly observed, a strategy based on condition‐based maintenance (CBM) may be affected; wherein upkeep of the system is done progressively on the premise of monitored state of the system. In this article, a multicomponent framework is considered that is continuously kept under observation. In order to decide an optimal deterioration stage for the said system, Genetic Algorithm (GA) technique has been utilized that figures out when its preventive maintenance should be carried out. The system is configured into a multiobjective problem that is aimed at optimizing the two desired objectives, namely, profitability and accessibility. For the sake of reality, a prognostic model portraying the advancements of deteriorating system has been employed that will be based on utilization of continuous event simulation techniques. In this regard, Monte Carlo (MC) simulation has been shortlisted as it can take into account a wide range of probable options that can help in reducing uncertainty. The inherent benefits proffered by the said simulation technique are fully utilized to display various elements of a deteriorating system working under stressed environment. The proposed synergic model (GA and MC) is considered to be more effective due to the employment of “drop‐by‐drop approach” that permits successful drive of the related search process with regard to the best optimal solutions.

This research work is aimed at optimizing the availability of a framework comprising of two units linked together in series configuration utilizing Markov Model and Monte Carlo (MC) Simulation techniques. In this article, effort has been made to develop a maintenance model that incorporates three distinct states for each unit, while taking into account their different levels of deterioration. Calculations are carried out using the proposed model for two distinct cases of corrective repair, namely perfect and imperfect repairs, with as well as without opportunistic maintenance. Initially, results are accomplished using an analytical technique i.e., Markov Model. Validation of the results achieved is later carried out with the help of MC Simulation. In addition, MC Simulation based codes also work well for the frameworks that follow non-exponential failure and repair rates, and thus overcome the limitations offered by the Markov Model.