As the maintenance world has embraced the digital world more, we see more opportunities for efficiency and productivity. Access to the amount of specialized data is the key benefit of this new digital realm. However, with the amount of data available, some of this data needs to be prioritized in order to realize its true value.

This priority data can be classified into three categories:

1. Sensor Data

This is the data that is received from sensors monitoring asset and building activity. The Internet of Things (IoT) is becoming more prevalent as more organizations put in place sensor-enabled devices and intelligent systems that connect things with people and processes to help drive efficiencies and unlock new opportunities. Companies of all sizes are automating processes, streamlining work, boosting productivity, enhancing customer engagement, getting ahead of inventory issues, proactively maintaining assets, and more.

Companies are using predictive sensors to detect when a critical piece of machinery is close to failing. The small wireless sensors directly monitor the machine. Data generated and analytics indicates whether the bearing is about to fail and predicts how long it will last before failure.

Your predictive maintenance might be constrained if the employees must rely on measurements that are not precise, if the batteries in measuring equipment fail or if data communications are limited. New predictive sensors and data analysis software are simplifying condition monitoring and streamlining the process of predictive maintenance.

2. Operational Data

Operational data refers to the data needed by maintenance personnel. This includes asset, location, inventory and technician information, work orders and procedures and some efficiency reporting. This is the data that drives and is produced by a CMMS or EAM program. Technicians use this data to carry out their work while managers and supervisors use this data to allocate resources and organize their responsibilities.

This data involves the planning and recording of important maintenance information from preventive, predictive and emergency maintenance. Operational data can also be generated from sensors, building automation systems and other previously independent areas that can now be integrated to trigger work orders and actionable data in a maintenance program.

3. Management Data

Management data refers to the historical results of operational data. With the work order and maintenance data, management can see history, reports, KPIs, analytics, costs and budgeting information. This data can be used to measure the efficiency of their practices and to evaluate and replace their maintenance decisions.

Whereas the IT (information technology) and OT (operational technology) sectors used to work independently of each other, these days there is much more convergence that benefits both organizations.

To maximize the benefits of this data, it’s important that it is created and produced in a consistent format. You should also ensure that proper data is available from sensors and OT and it is integrated with CMMS, ERP and accounting systems. Doing this will make giant strides towards safeguarding production assets while maximizing their efficiency and performance.