SOURCE:

Faculty: Engineering
Department: Industrial And Production Engineering

CONTRIBUTORS:

Ogbodo, I. F.
Ihueze C. C.

ABSTRACT:

The current dynamic and challenging manufacturing environment has forced companies that compete globally to change their traditional methods of conducting business. Recent developments in manufacturing and business operations have led to the adoption of preventive maintenance schedules that are based on systems and processes that support global competitiveness. This research employed Monte Carlo Normal distribution model which interacts with a multi regression model to predict the reliability and maintenance of Injection Moulding system. These models were programmed using Monte Carlo Excel tool package software, showing graphs of reliability and failure rates for each component. The Monte Carlo Normal distribution was used to analyse the reliability and failure rate of the entire system. The result showed that failure rate increased with running time accruing from wear due to poor lubrication systems; while system reliability decreased with increase in time (years). Multi regression model was used to evaluate the variance of failure between system components under preventive maintenance and those outside preventive maintenance. The result also showed that at reliability +0.3 and failure rate -0.02, preventive maintenance should be done. MATLAB time series was used to validate the analysis. Interaction between the Monte Carlo normal distribution and multi regression model showed that the total system reliability was 0.489 when maintained which gave 49% and 0.412 (41%) when not maintained. Also quality of production increased during preventive maintenance while system downtime reduced greatly. Therefore, reliability specialist and engineers should be properly trained in preventive maintenance planning methodology in injection moulding system.