Indian Journal of Science and Technology

Abstract

Objectives: Prognosis of a tool is essential for assigning a proper Condition-based Maintenance program for it. Therefore the objective of the present study is to investigate the reliability of a tool using a stochastic Markov Model. Methods/ Statistical Analysis: This work proposes a stochastic Markov model for estimating the Remaining Useful Life of the turning tool. In this study, a Mild Steel workpiece was machined to a certain length on a lathe machine using a high-speed steel tool and the Flank Wear Width (FWW) were recorded in every 20 minutes interval. This experiment was conducted for stable feed, stable speed and uniform depth of cut until the failure value of the tool flank wear was achieved, i.e. 0.3 mm. Findings: A state based model is developed considering four different degraded stages of the tool. The degradation rates among the states are obtained from the recorded experimental data. The appropriate equations for the four-state Markov model were derived, which show the possibilities of physical changes in the context of time for each level. The set of equations is solved analytically in MATLAB software using Range-Kutta method. After solving these equations, it was concluded that this system is 43% reliable for a 300-minute period and 41% is reliable for 500 minutes time period. Application/Improvements: It helps in preventing any kind of production loss. The remaining lifespan of a tool can be predicted by carefully analyzing the data gathered from the trend exploration method such as health monitoring with time.

Keywords: Condition based Maintenance, Cutting Tool, Markov Model, Prognosis, Remaining Useful Life