Gartner estimates that through 2022, decision automation in the form of predictive maintenance will generate the highest business value for organizations with heavy assets. Businesses in asset-intensive industries struggle to maintain a balance between keeping costs down and asset availability up. Effective asset management and maintenance play a key role in ensuring that this balance is maintained – enabling these businesses to comply with regulations, avoid the costs associated with unnecessary maintenance, and avoid unplanned downtime.
Preventive vs. Predictive Maintenance – What’s the Difference?
Preventive maintenance is planned or scheduled maintenance that takes place on a regular basis irrespective of asset conditions, whereas predictive maintenance is performed only when it is necessary, depending on asset conditions i.e. when there is a predicted risk of equipment malfunction or failure. Although the upfront investment for predictive maintenance is comparatively higher than preventive maintenance, operational costs, in the long run, can be reduced by eliminating unnecessary maintenance.
How Does Predictive Maintenance Work?
Predictive maintenance is performed by evaluating the health and performance of equipment through periodic or continuous asset condition monitoring. Data captured by IoT devices connecting different assets and systems enable businesses to predict, plan, and take proactive steps for any events like parts repair or equipment failure before it occurs. Predictive maintenance is mostly performed while the equipment is operating under normal working conditions to avoid any disruption in the business.
What are the Benefits of Predictive Maintenance?
According to a report by PwC, on average, predictive maintenance in factories could:
- Reduce costs by 12%
- Improve uptime by 9%
- Reduce safety, health, environment, and quality risks by 14%
- Extend the lifetime of an aging asset by 20%
1. Reduce maintenance costs
Each asset has multiple associated costs, and unexpected failure cost contributes significantly to the total cost of ownership of any asset. Therefore, companies can save money by being able to predict and avoid equipment failure. In asset-intensive industries, improving maintenance planning can result in huge savings. IoT-based predictive maintenance utilizes historical data from multiple sources including IoT devices and sensors to make accurate predictions about asset health, utilization, and the possibility of failure, enabling you to take action based on this information. IoT-based predictive maintenance allows you to systematically schedule the optimal maintenance and inspection routine to avoid unplanned downtime and unnecessary effort. Avoidable costs can be reduced greatly and you can also reduce the amount of time the machinery or equipment is down for maintenance.
2. Increase asset utilization
Unplanned downtime due to equipment failure, costs incurred due to production delays, and expensive maintenance and repairs drive down profitability. IoT-based predictive maintenance enables more efficient use of existing assets by providing the ability to predict machine failures and reduce maintenance issues. It can help identify the causes of delays, whether they’re internal or external, and help set up processes to address these causes. You can also detect equipment issues before they become operational, and provide early warnings thus improving asset availability, reliability and performance.
3. Extend asset life
IoT-based predictive maintenance enables you to monitor, maintain, and optimize assets for better availability, utilization and performance. You can gain better visibility into assets via real-time monitoring, allowing you to predict machine failure and identify parts that need replacement. You can schedule maintenance and repairs, predict events before they occur, and get real-time notifications that enable you to take quick action, thereby extending the life of your assets.
4. Improve field crew efficiency
IoT-based asset monitoring solutions allow companies to monitor the health of field assets at scheduled intervals. A 360-degree view of asset health can help companies in work planning, prioritization, and scheduling. Unplanned downtime or machine failure often requires reallocation of field service crews from other work locations to address the issue, or hiring of extra personnel, or a complete rescheduling of other planned maintenance activities. This can be avoided with IoT-based predictive maintenance, thus improving the utilization and response times of field service crew and reducing maintenance duration and asset downtime.
5. Improve safety and compliance
Predictive asset maintenance enables companies to anticipate and address possible safety risks and predict potential issues before they impact workers. They can quickly take appropriate action to mitigate safety risks by analyzing data from multiple sources –both internal and external sources along with the data generated from IoT devices and sensors. By analyzing data over long periods of time, you can identify potentially hazardous conditions and estimate its impact on working conditions. By integrating with human capital management (HCM) solutions, you could then trigger instructions to reallocate resources and keep exposure levels below the threshold values, in compliance with regulations.