A Replacement Model for Multi-Tool Transfer Lines

Abstract

Transfer lines have long been used for machining a single product at high production rates. This study deals with the transfer line, in particular, estimating the production time per part and the effect of using probability models in describing tool and machine lives. The production time is estimated using three major causes of line stoppage. An aspiration level criterion is used to establish a scheduled tool replacement interval. The aspiration decision parameter is system reliability. It is shown how a scheduled tool replacement interval could be established to obtain this reliability level. A methodology for selecting the replacement interval for a group of tools is developed and the impact of changing this interval on tool changing costs and tool failure costs is discussed. In this study, only a single premature tool failure is assumed to occur; however, the results are compared with multiple tool failures using the renewal function. It is shown that this single premature failure analysis is equivalent to the renewal function approach for machining systems having a reliability greater than 50 percent and tool failure variabilities having a coefficient of variation less than 1.0. Using the model developed in this paper, an example problem is presented. For this problem, electromechanical equipment failure and tool wear failures are modeled using the exponential and the Weibull probability distributions, respectively. Scheduled tool replacement intervals are developed for a range of target reliabilities. The part cycle time and operating cost for the transfer line based on these reliabilities are computed. These results are compared to the minimum cost reliability level. The minimum cost operating condition is dependent on the ratio of the scheduled replacement costs over the failure replacement costs. For the example presented, the reliability level at minimum cost is much lower than the desired target value of .9. This result illustrates the importance of conducting a careful analysis and using the results to help guide operating practices toward more efficient tool change practices and maintenance policies.