Predictive maintenance (sometimes abbreviated as PdM) is a pre-emptive approach to the maintenance of machinery, plants, vehicles, devices, and other equipment.
Closely linked to IoT (Internet of Things) technology — particularly the use of sensors and smart devices within industrial and manufacturing processes — predictive maintenance involves capturing and analyzing machine data to detect patterns and anomalies and predict when equipment failures are likely to occur.
Predictive maintenance allows you to anticipate failures, measure the rate of performance degradation over time, plan maintenance schedules and budgets in advance, minimize unexpected outages, and potentially extend the lifetime of your assets.
IoT sensors are embedded into equipment to gather important data on asset performance and condition. A few examples include accelerometers, temperature detectors, current transformers, flow meters, viscometers, and strain gauges.
These IoT sensors are connected to a network and transmit data to a centralized, usually cloud-based location. The data needs to be preprocessed to filter out irrelevant information and extract the specific information required for maintenance-based predictive analysis.
Using a range of machine learning algorithms (e.g., regression analysis and time series analysis), models are trained on a combination of historical and real-time data. Based on this, they’re able to predict the likelihood and timing of future failure and the need for maintenance.
Building on this analysis, you get a much clearer picture of pending and future maintenance needs. For instance, on a particular piece of machinery, the analysis indicates that thresholds linked to component fatigue will be reached by X date. You can use this information to schedule component replacement and maintenance accordingly.
On average, large companies lose the equivalent of 11% of revenue each year due to downtime. When a critical asset fails unexpectedly, the financial hit can be both immediate and severe. Predictive maintenance gives you a valuable heads-up, enabling you to intervene before a problem triggers a costly outage.
An effective predictive maintenance system means technicians spend less time in firefighting mode, reacting to failures at short notice. Schedules can be planned, with a lower likelihood that those schedules will need to be reworked as a result of unplanned emergency repairs.
A proactive approach to maintenance gives you greater scope for scheduling activities during planned downtimes, quiet periods, or outside of normal working hours, meaning less disruption for equipment users. Especially if you deliver maintenance as part of a managed service agreement, this can help boost user-focused metrics such as user-impacted downtime and user satisfaction.
Predictive maintenance incorporates regular monitoring of assets’ state of health. This helps you step in with timely maintenance and prevent excessive wear and tear. Equipment tends to stay in good working condition for longer, reducing the need for replacements.
With a diverse portfolio of plant and equipment to oversee, a sizable chunk of your budget can easily be tied up in stockpiling spare parts “just in case”. With a predictive maintenance system, you can predict when parts will be needed, allowing for a more targeted and less wasteful approach to inventory management.
Predictive maintenance can and should perform an integral role in helping you meet sustainability targets. Water leaks, depleted lubricant or coolant levels, excessive waste, increased fuel or power consumption: your predictive maintenance system can be configured to track these variables. That means smarter maintenance management, and sustainability can go hand-in-hand.
Embedded IoT technologies and advanced analytics combine to help build effective predictive maintenance processes across a range of sectors.
Covering remote control, maintenance, and support, along with a cloud-based solution for managing even the most complex IoT projects, TeamViewer’s flexible range of products are trusted the world over.
Predictive maintenance only becomes a reality if you can seamlessly connect all your assets and ensure the right data is analyzed and shared at the right time. With TeamViewer, this is easy.
TeamViewer offers a 360° remote connectivity platform for all kinds of devices, including any IoT elements deployed throughout your business.
With comprehensive remote device monitoring capabilities, the platform ensures early recognition of problems across your entire technical infrastructure and warns you immediately when an issue arises. The result is 24/7 visibility of all assets and an enhanced ability to forecast issues before they turn into major business problems.
No two businesses are the same in their predictive maintenance needs. Exact requirements depend on a range of factors, including the equipment or machinery in question, safety requirements, operating conditions, and organizational goals.
This is where TeamViewer’s expertise comes in. Working in partnership with your team, we can help you implement and configure a solution as an exact match for your predictive maintenance needs, taking into account the variables you need to track, the thresholds for intervention, appropriate connectivity and data transmission methods, and the cadence required for data transmission.
Through this partnership approach, we can help you harness all relevant machine-level performance data, translate it into insights, and use it as a foundation for an effective predictive maintenance strategy.
TeamViewer is fully cross-compatible across operating systems and devices. This means you can rely on a single solution to connect to, monitor, and use predictive maintenance for your entire inventory of machinery and equipment. That includes everything from frontline manufacturing components to back office computers and peripherals.
You’ve predicted a pending need for maintenance. So what happens next? Full remote access and remote control capabilities mean that maintenance teams can remotely access and control any connected machine to perform diagnostics, troubleshooting, and reconfiguration. So, TeamViewer doesn’t just enable you to reduce unplanned maintenance; it also helps reduce reliance on physical intervention.
Depending on the policies and workflows your organization intends to integrate into its predictive maintenance strategy, TeamViewer’s flexibility ensures this. Whether this is the categories of data you need to analyze or the machine-level patterns you intend to track, you can configure TeamViewer’s predictive maintenance strategy precisely according to your needs.
TeamViewer enhances and integrates with your existing software investments, including IoT platforms, cloud storage and data warehousing, predictive analytics tools, enterprise resource planning (ERP), and corporate performance management (CPM) solutions. This facilitates seamless integration of predictive maintenance workflows into existing business processes.
With TeamViewer, your core business processes — and business-critical data — are in trusted hands. Safeguards such as 256-bit AES encryption, fine-grained conditional access controls, and multi-factor authentication ensure that your connections and IoT data transfers remain secure.
Yes. Predictive maintenance helps you pre-empt maintenance requirements, reducing the need for emergency interventions, and giving you more control over maintenance schedules. This improves the asset management process.
The benefits of predictive maintenance include less unplanned machinery downtime, more efficient maintenance activity scheduling, less user disruption, easy management of spare parts, and extended asset lifespans.