Development of Contact Models for Wear Predictions in Mechanical and Mechatronic Systems

Wear behaviour of engineering members is one of the first considerations in the design of machine elements. Hence, contact models for wear prediction is the main focus of this study. The need to design a mechanical and robotic systems that will be insulated from degradation can not be over emphasized. A detailed wear model is key for the design of machine. Hence, to actualize this, the ball-on-disc tribosystem was engaged to generate friction coefficient and wear data that was used to simulate and develop the contact models. The experimental results were modelled using Minitab 17 software to establish a relationship between the input and output variable: wear rate, while load and speed are the input variables. From the regression equations, a rise of one unit of load (W) resulted in a drop of 0.1886 mm3/Nm wear rate (WR) for avocado, and 0.2001 mm3/Nm for mineral oil respectively. The model equations imply that the avocado seed oil can perform better than the mineral oils under high load, temperature and pressure. In all of the analyses, the load has a greater influence than speed. The test findings of the two dependent variables (wear rate) are statistically significant when the P-values for the predictors are less than 0.05. The study affirms that the chosen model fits the data in determining the coefficient of friction and wear rate of the two mating bodies.