Decisive applications, such as control systems and aerial navigation, require a standby system to meet stringent safety, availability, and reliability. The paper evaluates the availability, reliability, and other measures of system effectiveness for two stochastic models in a symmetrical way with varying demand: Model 1 (a two-unit cold standby system) and Model 2 (a two-unit hot standby system). In Model 1, the standby unit needs to be activated before it may begin to function; in Model 2, the standby unit is always operational unless it fails. The current study demonstrates that the hot standby system is more expensive than the cold standby system under two circumstances: a decrease in demand or the hot standby unit’s failure rate exceeding a predetermined threshold. The cold standby system’s activation time is at most a certain threshold, and turning both units on at once is necessary to handle the increasing demand. In that case, the hot standby will be more expensive than the cold standby system. The authors used semi-Markov and regenerative point techniques to analyze both models. They collected actual data from a cable manufacturing plant to illustrate the findings. Plotting several graphs and obtaining cut-off points make it easier to choose the standby to employ.

The present paper analyzes a two-unit cold standby system wherein both units may become operative depending upon the demand. Initially, one of the units is operative while the other is kept as cold standby. If the operative unit fails or the demand increases to the extent that one operative unit is not capable of meeting the demand, the standby unit becomes operative instantaneously. Thus, both units may become operative simultaneously to meet the increased demand. Availability in three types of upstates is as follows: (i) when the demand is less than or equal to production manufactured by one unit; (ii) when the demand is greater than whatever produced by one unit but less than or equal to production made by two units; and (iii) when the demand is greater than the produces by two units. Other measures of the system effectiveness have also been obtained in general case as well as for a particular case. Techniques of semi-Markov processes and regenerative processes have been used to obtain various measures of the system effectiveness.

The transition of transportation sector from Internal Combustion Engines (ICE) to Electric Vehicles (EVs) has raised many concerns about their users which mainly include locating a suitable charging station for such vehicles. Presently, human intelligence-based methods are being used for the purpose. However, the development of Smart Station Search Assistance (S$^{3}$A) system is an innovative step in this direction as it provides an optimal solution to locate a charging station as per user requirement subject to vehicle constraints. The use of optimization model in S$^{3}$A for recommending an optimal charging station service has been justified. The main challenges which can affect the performance of the system have also been discussed.

The concerned paper illustrates the comparison of two stochastic models of a cable manufacturing plant with varying demand. Here, it shows the comparison between a single unit system (Model 1) and a two-unit cold standby system (Model 2). In Model 1, the system is either in working state on some demand or put to shut down mode on no demand. In Model 2, at initial stage, one of the units is operative while the other is kept as cold standby. At times when the operative unit stops working due to some breakdown/failure, the standby unit instantaneously becomes operative while the repairman repairs the failed unit. In this working model, only one unit remains operative at a time. However, there may be a state when both the units fail. The comparison of systems is done by means of MTSF (mean time to system failure), steady state availability and profit function using Laplace transforms and software package Code-Blocks 13.12. Different graphs have been plotted to discover which model is superior to the other model under the given conditions. The system is analysed by making use of semi-Markov processes and regenerative point technique.

Fossil fuels constitute nearly 80% of the total energy, which has consumed in our daily domestic chores and industries. Approximately 1% of energy use comes from solar radiations. Unlike conventional sources, solar radiations produce no harmful emission that pollutes the environment. A Solar Shed containing solar panel has designed under the program of Engineering Projects In Community Services (EPICS) in Chitkara University to utilize solar energy. A solar panel is a device which results in the conversion of solar energy to electrical energy which is stored in a battery and can be used to glow LED. Arduino and LDR sensors are used to restrict the supply of energy for glow LED only in the night. The overall aim of the device is to promote the usage of solar energy rather than using fossil fuel energy which pollutes the environment.