TY - JOUR AU - Ram, Mangey AU - Negi, Ganga AU - Goyal, Nupur AU - Kumar, Anuj PY - 2022/07/27 Y2 - 2024/03/29 TI - Analysis of a Stochastic Model with Rework System JF - Journal of Reliability and Statistical Studies JA - JRSS VL - 15 IS - 02 SE - Articles DO - 10.13052/jrss0974-8024.1527 UR - https://journals.riverpublishers.com/index.php/JRSS/article/view/20235 SP - 553-582 AB - <p>The demand in the present global industrial system, requires the challenge to meet the growing consumer capabilities and requirements constantly. So, there is always a need to improve different parameters, one of them being different types of failures involved in the working of different engineering systems related to communication systems, manufacturing goods, nuclear and hydro power plants, automobiles and many others. Human error occurring in the working of various systems has always been the challenge to the researchers and is being constantly worked upon by the researchers in the analysis and improvement of reliability and availability of different complex and multistate systems. In the present paper, there is a three-unit system consisting of the unit A with two subunits in parallel and other units B and C are connected in series with A. The authors have investigated and analysed different reliability measures like availability, MTTF and sensitivity taking into account the human failure and carrying out rework system. This research work aims at the study of reliability and availability measures of a multi-state system incorporating human error so as to increase the efficiency of industrial systems by taking maintenance and rework measures to enhance the availability factors. This would help to understand and estimate the reliability measures of any such systems in the field of telecommunication, any electronic devices like that in small power plants, robot systems and such others. Also, a comparison has been made between the availability and reliability estimates in the presence and in the absence of human error. The techniques used are Markov process, Laplace transformation and supplementary variable technique.</p> ER -