Physics

Business

International trade

Downtime

Scope (computer science)

Operating system

Risk analysis (engineering)

Computerized maintenance management system

Macroeconomics

Engineering

Heuristic

Operational maintenance

Artificial intelligence

Economics

Power (physics)

Preventive maintenance

Programming language

Reliability engineering

Condition-based maintenance

Safeguard

Production (economics)

Maintenance actions

Computer science

Quantum mechanics

Overall equipment effectiveness

Process (computing)

Reliability (semiconductor)

Predictive maintenance

Advances in Mechanical Engineering

In view of the trend towards Industry 4.0, intelligent predictive monitoring and decision-making processes have become a crucial requirement in today’s manufacturing industries to safeguard data exchange and industrial assets from damage that would thus prevent the achievement of overall company goals. For enhanced reliability and safe operation of machines, frequent maintenance of the process equipment and the linked auxiliaries in a plant is highly desirable. Poor maintenance of assets can add to downtime, which can in turn affect the overall cost-effectiveness of the plant. With traditional maintenance strategies and planned or timed-based maintenance, one replaces the faulty systems when they are found to be damaged or broken. However, an early and proactive prediction of machine or equipment fault and failure state enables the industry to take the necessary action to replace the faulty system well before it stops operating entirely. This paper briefly reviews the available predictive maintenance techniques for different applications from the perspective of Industry 4.0. Furthermore, the associated challenges and opportunities are identified and discussed.

A heuristic approach on predictive maintenance techniques: Limitations and scope