Predictive Maintenance

The Role of Sensors in Enhancing Predictive Maintenance Capabilities


As the world of manufacturing continues to evolve, the importance of predictive maintenance has become increasingly apparent. This proactive approach to maintenance, powered by advanced technologies like FAT FINGER, is revolutionizing the way businesses operate.

FAT FINGER is a digital workflow procedure builder that empowers front-line teams to do their work correctly every time. It allows you to build checklists, workflows, and digital procedures that unlock operational excellence. With features like Drag & Drop Workflow Builder, Mobile & Desktop Workflows, Dashboards, Integrations, Augmented Reality, Connect IoT Devices, and Artificial Intelligence Coaching, FAT FINGER is a game-changer in the realm of predictive maintenance. Request a demo today to see how FAT FINGER can transform your business operations.

Understanding Predictive Maintenance

Predictive maintenance is an engineer’s best friend and a powerful tool for optimizing platforms in a manufacturing facility. Instead of having scheduled maintenance done on a predetermined timeframe, predictive maintenance uses data and technology to specify when maintenance needs to be completed to prevent costly breakdowns accurately. It works by collecting data from a facility’s various components and then using it to determine when parts need maintenance, as well as use algorithms or Artificial Intelligence (AI), if necessary. Predictive maintenance can help save time and money, improve efficiency in the facility, and help ensure that safety standards are adhered to throughout the lifecycle of all machines.

The Role of Sensors in Predictive Maintenance

Sensors play a crucial role in predictive maintenance. They are the eyes and ears of the system, collecting data on various parameters such as temperature, pressure, vibration, and more. This data is then analyzed to predict potential failures and schedule maintenance accordingly.

  • Temperature Sensors: These sensors monitor the temperature of machinery and alert the system if it exceeds the normal range, indicating a potential problem.
  • Pressure Sensors: Pressure sensors detect changes in pressure within a system, which can be a sign of a malfunction or impending failure.
  • Vibration Sensors: These sensors monitor the vibration levels of machinery. An increase in vibration can indicate a problem such as misalignment or imbalance.

Case Study: The Power of Sensors in Predictive Maintenance

One of the best ways to understand the role of sensors in predictive maintenance is to look at real-world examples. A leading manufacturing company implemented a predictive maintenance program using sensors and saw significant improvements in their operations. The sensors detected anomalies in machine behavior, which were analyzed to predict potential failures. As a result, the company was able to reduce downtime by 30%, increase productivity by 20%, and save millions in repair costs.


The role of sensors in predictive maintenance cannot be overstated. They provide the critical data needed to predict and prevent equipment failures, leading to increased efficiency, reduced downtime, and significant cost savings. With advanced technologies like FAT FINGER, businesses can leverage the power of predictive maintenance to optimize their operations and achieve operational excellence. Create a predictive maintenance workflow for free on FAT FINGER or schedule a demo today to see how you can harness the power of predictive maintenance in your business.

Discover how sensors can enhance your predictive maintenance capabilities. Learn how to optimize your operations, reduce downtime, and save costs. Don’t wait, Schedule a Demo today to see the power of sensor technology in action.