Predictive Maintenance With IoT And Field Service Management Software Integration
For field services that involve the use or installation of equipment, maintenance of the same is a major revenue driver. Good equipment as an asset means your business can complete more jobs and improve workforce productivity. While installing good equipment means gaining customer trust and more maintenance contract revenues.
Equipment maintenance is also important for industries ā especially for manufacturing, energy, and utilities. For them, equipment downtime can lead to significant financial losses, not to mention the potential safety risks.
To achieve and maintain an optimum level of equipment performance for yourself and your customers, a field service business must explore a predictive maintenance strategy. It leverages data to anticipate and address equipment issues before they fail.
In this article, we will learn more about how to implement a predictive maintenance strategy using the āInternet of Thingsā or IoT technology.
How does predictive maintenance strategy work for field service business?
With predictive maintenance, a field service business can foresee potential issues in equipment and address them before they cause disruptions.
Predictive maintenance uses data from various sensors embedded in machinery to monitor the equipment's condition in real time. This can include data across changing temperatures, vibration levels, noise, and more.Ā
A field service management software like Zuper that is equipped with predictive analytics tools will analyze this information. It will share predictions for the businesses when a piece of equipment is likely to fail and schedule maintenance accordingly. This proactive approach helps reduce unplanned downtime, extend the lifespan of equipment, and optimize maintenance costs.
The role of the Internet of Things in implementing predictive maintenance strategy
The technology of IoT is what helps us capture data from the equipment. One places these IoT sensors at relevant parts of the equipment where they are intended to measure the change in key metrics. Then, field service management software will use artificial intelligence and predictive analytics algorithms to analyze this operational data to highlight any issues, suggest maintenance schedules, alert managers, and much more.
For example, in an energy plant, IoT sensors can monitor the temperature and pressure of turbines. If these readings exceed a certain threshold, the system can alert the maintenance team to potential issues.
How to integrate IoT with field service management software?Ā
Field service management software is a specialized tool to streamline operations across field service scheduling, customer management, finances, and more. You can integrate it with IoT to help implement a predictive maintenance strategy as follows:
1. Enable real-time monitoring and alertsĀ
Since IoT sensors constantly collect data from equipment, any trend observed for failure or breakdown gets alerted instantly. These alerts are then sent to the appropriate field service technicians, enabling them to take immediate action.
For example, a field service management app can receive data from an IoT sensor indicating that a critical piece of machinery in a factory is overheating. The software can automatically schedule a technician to inspect the equipment.
2. Optimize field service scheduling
Traditional scheduling methods rely on routine maintenance schedules or reactive service requests. This leads to inefficiencies and delays, especially if one assigns the wrong technician for the wrong job. However, with IoT-enabled predictive maintenance, scheduling becomes more dynamic and efficient.Ā
As FSM software understands which equipment needs maintenance, it can schedule service appointments based on available workers and skills. The time to respond to any potential downtime is reduced, ensuring continuity for the equipment.
3. Improve asset management
When you know the performance and condition of assets like equipment, then a business can better plan any replacement. One can budget their assets accordingly and ensure replacements or spare parts are always ready as per insights from IoT-enabled FSM software.
For example, a company that operates a fleet of delivery trucks can use IoT data to monitor vehicle performance. Based on demand for the delivery service, it will help the manager understand the requirement for additional trucks based on the current truckās schedule and vehicle health.
Whatās next for IoT-enabled field service management software?Ā
IoT and predictive maintenance algorithms will continuously evolve as a technology to make it more accurate and intelligent in terms of its insights. Integration of augmented reality (AR) to assist technicians in the field when they perform maintenance will further ensure accurate resolutions.
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Contributor:
This is Rehan Naeem, a Digital Marketer at Techy Stribe.
Providing Guest Posting and Content Writing Services with 3+ years of experience. For more information, please contact me atĀ rehannaeem705@gmail.com.
