Condition Based Maintenance

Condition-based maintenance is a maintenance strategy that tells maintenance technicians what condition the equipment is in (such as temperature, humidity, and power), not how it is performing.

The maintenance technician can then determine if the system is in good condition, or in need of repair. In a Condition Monitoring and Maintenance strategy, maintenance is performed when certain indicators indicate that a system is in danger of failure.

When specific indicators show signs of decreasing performance or impending failure, it is in the best interest of the equipment to have maintenance performed before a failure occurs, to avoid shutdowns and downtime.

Condition-based maintenance helps lower the failure rate of a system. It tells us when maintenance will be most useful. When working on a non-mission critical system, such as say a flight simulator, condition-based maintenance will tell us to perform no maintenance on that system for a period of time.

Of course, the failure rate will go up dramatically, but we will be keeping our pilots safe, and we will not be catching flight line workers in the process of dealing with the failure.

The goal of a condition monitoring maintenance framework is to reduce costly disruptions and maintain predictable operational performance of the machines. It helps maximize maintenance resources and reduce the impact of maintenance problems.​

There are several types of condition-based maintenance, each with different objectives, however, not all types are applicable to all machines. These includes, oil analysis, vibration analysis Ultrasound analysis, Electrical analysis, Pressure analysis and Temperature analysis among others.

Performance-based Monitoring

The condition-based maintenance has also moved ahead with technology advancements, thereby incorporating newer techniques such as Performance-based monitoring, which was unheard of earlier.

Performance based condition monitoring is similar to traditional condition-based maintenance, but it also focuses on the actual performance and reliability of the equipment. If a machine is running at less than 80% of its operating potential, then maintenance should be done to keep it in that condition. If a machine is running at 95% of its potential, then it needs no maintenance at all.

Performance based monitoring makes it easier to understand performance data and understand its historical context. A technician can then compare the number of failures of the same type at a different time.Of course, the failure rate will go up dramatically, but we will be keeping our pilots safe, and we will not be catching flight line workers in the process of dealing with the failure.​

Challenges of condition-based maintenance

Condition-based maintenance is a critical strategy for large and complex assets such as electrical power grid and oil & gas pipelines. However, its implementation in industrial operations is limited by its ability to detect process system degradation before it occurs. It also requires a high-level of automation and integration within asset lifecycle management softwares.

Only a few Asset Information Management softwares integrate condition-based maintenance data with their asset health management data. That is where predictive maintenance adds value. It mitigates the challenges associated with traditional condition-based maintenance by offering real-time predictive information about the genuine health and performance of industrial assets.

Future of condition-based maintenance

With newer advancements in technology, condition based maintenance strategies evolve at a much faster pace to accommodate a wide variety of equipment sets across various sectors.

The evolution of Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) systems in manufacturing operations offers a foundation for next-generation maintenance strategies through interconnected network of systems that help monitor, collect and analyze machine health data, thus facilitating real-time performance information of machines.

It enables maintenance and reliability professionals to detect inefficiencies & anomalies earlier than the conventional techniques, which helps manufacturers to take critical business decisions in an accurate & timely fashion, thereby saving time & money.

Integrated predictive maintenance system from Nanoprecise propels condition monitoring & maintenance to the next level, by helping manufacturers lower maintenance costs, reduce downtime, increase productivity and improve equipment reliability.


The biggest challenge that companies face when it comes to maintenance are the costs involved with repairs. Although maintenance can be costly, it’s not all bad. Maintenance can save time & money because it ensures proper functioning of the equipment, and offers real-time machine health data that can help decision makers to make prudent business decisions. Also, it saves equipment from breakdown, which otherwise can cause huge problems for the company as well as their customers.

Nanoprecise offers Automated end-to-end predictive maintenance systems that help customers across sectors such as Chemicals, Pharmaceuticals, Cement and Metals among others, with its state-of-the-art IoT hardware and Artificial Intelligence, to predict faults, prescribe solutions and avoid catastrophic failures by overcoming the downsides of a traditional condition-based maintenance regime. AI-based Predictive Condition Monitoring & Maintenance Solutions from Nanoprecise helps manufacturers significantly improve their equipment’s performance, increase their efficiency and reduce downtime, thereby helping them to stay competitive in the global markets.

Reducing Downtime in Metal Industry

Our IoT driven Predictive maintenance solution helps to reduce downtime, monitor, collect exchange and analyze data from machines to enhance manufacturing processes of the metal industry.

Machine failure in the mines? No worries.

Our solutions can add immense value to your entire mining supply chain by harnessing the power of Industry 4.0. The asset performance will be optimized, costs and machine downtime can be reduced leading to a boost in ROI.

No more unplanned downtime in Cement Industry

Our Industry 4.0 digital solutions can help you tackle the challenges in cement production such as large energy consumption, high costs and complex processes.

Protect your assets with Zone Approved Solution

Our digitization solutions in industrial equipment maintenance can help oil and gas companies streamline maintenance. Our predictive analytics and conditional data monitoring help anticipate failures, reducing unplanned maintenance and unscheduled downtime.

No more Downtime, Keep your Machines Running in Chemical Plants

Our AI driven analytics can propel your chemical business to new heights of reliability by optimizing asset longevity and impacting top-line growth through proactive identification of upcoming machine failures. IoT driven asset maintenance solutions can provide immense flexibility and agility to production.

Request a Call Back

Frequently Asked Questions

Condition-based maintenance strategy identifies the current asset condition to determine the appropriate maintenance activity required.

Condition-based maintenance helps to lower the failure rate of equipment sets and ensures that all machines are operating at the optimum performance levels.

It offers a number of benefits such as reduced unplanned downtime, improved availability of machines and equipment sets, improved worker safety and better productivity as well as lesser time spent on maintenance.

The pre-requisites for the implementation of a condition-based maintenance strategy will vary depending on the program you choose. However, one of the most important factors to consider is to have clear goals and expectations from the program, which will help to make better decisions.