Six Steps to Predictive Maintenance

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Six Steps to Predictive Maintenance

The manufacturing sector is facing a myriad of challenges, but they all point in one direction – improving the bottom-line performance. Within the energy sector, one of the most important drivers is to increase operational efficiency. Asset management is key to achieving this. Traditionally assets are large and costly, with long service lives. To achieve high operational efficiency and availability means ensuring that all assets are performing at peak performance with high availability and the lowest possible maintenance costs. This is where predictive maintenance comes in.

Plotting the path to a predictive maintenance future

Step 1: Gain visibility to your data

The first step on the journey is to understand where you are at with your processes and equipment. The old maxim that ‘you cannot measure what you do not know’ has never been more apt. In a typical scenario, a company needs to understand what is the current performance of their assets. This may involve taking data that already exists at the plant level and visualizing that information to support useful decision making.

A company could marry this data with IT and maintenance management system level data to have a better view of maintenance histories paired with plant performance. In this situation, the key is often capturing data that has been previously lost and integrating it into the IT domain safely and securely where it can be manipulated, analyzed, and decisions can be made on that data.

Step 2: Understand the gaps and remediate with added sensing

Once visibility has been established, the next step is to close any gaps where information could be lacking from critical assets in a plant. Here additional data points could be added to gain a deeper understanding of asset conditions. There is a vast array of sensors that can be deployed on electrical equipment, rotating equipment, and other plant assets that can then be part of a condition-based maintenance regime. This could be in the form of an engineered system tied into a control system or completely independent that allows informed decisions based on the condition of assets.

A condition monitoring system enables automatic, wireless monitoring of non-critical electric motors and rotating equipment. It can help detect machine vibration and temperature anomalies that could lead to equipment failure and production downtime. Information provided by the system can be accessed remotely by users. With wireless functionality, the system can easily be installed on existing infrastructures without requiring any extra shutdowns. Additionally, the engineering, planning, materials and installation costs are less than traditional wired solutions.

Condition and remote monitoring solutions are vital tools especially when assets are in remote and inhospitable locations, a common problem for the oil and gas industry.

Read the full post from ABB for the additional 4 steps to predictive maintenance, along with case studies

 

Author

Will Leonard - Predictive MaintenanceThis article was written by Will Leonard. He is the Asset Performance Management Product Manager, Energy Industries and has more than 10 years of experience at ABB, working with Industrial Automation companies, academia, and industrial stakeholders on innovation, skills and business partnerships.

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