Purpose

Life-cycle cost optimisation with maintenance planning is considered an important task for manufacturers to maintaining both the performance of the equipment and the quality of the final product. Recently, computer applications are heavily used to help planners and schedulers set up maintenance plan more quickly and efficiently, so that they are able to allocate the appropriate people and resources on the right time.

This tool is designed to provide a Predictive Maintenance method that enables industrial manufacturers to prevent major failures of their equipment from occurring, so that a prediction-based maintenance plan is produced that includes a recommendation to the most cost-effective maintenance action based on sophisticated analysis of the degradation process of the equipment. The tool provides an estimate of the optimised life-cycle cost over the desired period of the planning.

Model Architecture

Degradation Model:

A reliability functions to model the deterioration of a component and predict its future condition.

Repair Impact Model:

Estimates the resulting improvement in the component’s condition after it has been repaired/replaced.

Maintenance Cost Model:

Provides the cost of different types of maintenance strategies applied to a component to extend its useful lifetime.

Core Optimisation Model:

Genetic Algorithm to develop numerous maintenance plans and find the best one that maximise the condition of component and minimise the life-cycle cost.