The advancement of new technologies has highlighted the need for a more precise assessment of the life of goods and systems before allowing them to serve in the market. Due to time and cost constraints, tests must be able to generate rapid and reliable life information, which is not attainable using conventional life testing methods. As a result, various censorship schemes, along with accelerated life testing, in which goods are subjected to increased stress in order to determine the life characteristics of products and systems in a short period of time, have been deemed significant tools. In addition to reducing product testing time through the use of accelerated life testing and various filtering techniques, understanding the impact of failure reasons is critical. In order to get precise failure information, the observer must distinguish between various failure causes. The current work aims to quantify the amount of information accessible for test item lifetimes by employing step-stress partly accelerated life tests with competing risks (CR) based on an adaptive type-I progressive hybrid censoring scheme (AdTI-PHCS). The Rayleigh distribution is used to explain the distribution of test item lifespans. To get point and interval estimates, the maximum-likelihood estimation (MxLE) approach is implemented. Moreover, to assess the performance of the given model parameters, a Monte Carlo simulation approach is utilized.