Proactive Over Reactive: IoT’s Role in Redefining Industrial Maintenance

Charlie Green, Senior Research Analyst at Comparesoft

Posted 5/19/2024

The industrial maintenance sector is experiencing a significant shift with the integration of the Internet of Things (IoT) and the advent of Industry 4.0. These innovations are fundamentally altering the way maintenance teams function, introducing a new era of efficiency, predictive maintenance, and real-time data utilisation.

IoT technology is central to this transformation, enabling teams to access and analyse data in real time. This advancement shifts maintenance from a reactive to a proactive and predictive model, significantly reducing downtime and extending equipment life.

Reactive Maintenance: The Traditional Model

Reactive maintenance, a longstanding approach in industrial maintenance, is characterised by its “wait until failure” philosophy. In this model, action is only taken when equipment fails or shows signs of significant deterioration. This approach, while straightforward, comes with substantial drawbacks. 

Unplanned downtime is a frequent consequence, as equipment failures are unpredictable and often occur during critical production periods, leading to disruptions and inefficiencies. Moreover, the cost implications are considerable. Reactive maintenance typically incurs higher expenses due to emergency repairs, expedited part shipments, and overtime labour costs. Additionally, this method can shorten the overall lifespan of machinery, as equipment is frequently pushed to its limits without preventative care, necessitating more frequent replacements and higher capital expenditures. There are also inherent safety risks, as equipment failure can pose immediate dangers to operating personnel.

The Advancement to Proactive Maintenance with IoT

The advent of IoT technology has ushered in a new era for maintenance strategies, particularly in shifting the focus from reactive to preventative maintenance. This approach, powered by IoT, leverages real-time data collection and analysis to anticipate and address potential equipment issues before they escalate into failures.

IoT devices, embedded within industrial machinery, continuously monitor various operational parameters such as temperature, vibration, and pressure. This constant stream of data provides a comprehensive view of equipment health and performance. Advanced analytics then process this data, identifying patterns and anomalies that could indicate impending failures. This predictive capability is a cornerstone of IoT-enabled maintenance, allowing for timely interventions that prevent breakdowns and minimise downtime.

using IoT in maintenance

The Value of Incorporating IoT Powered Proactive Maintenance into Your Maintenance Practices 

Enhanced Real-Time Monitoring and Precision Alerts with IoT Technology

The implementation of IoT-enabled sensors revolutionises the way maintenance teams interact with and manage equipment performance. These advanced sensors deliver precise, real-time data, allowing for an immediate and informed response to any irregularities or potential failures in equipment operation. This level of proactive monitoring is essential for preventing equipment breakdowns and guaranteeing uninterrupted operational continuity.

For example, consider sensors specifically designed to monitor vibration levels. These sensors continuously gather and analyse vibration data, creating a comprehensive time-series dataset. This dataset establishes a baseline or ‘normal’ range of vibration for each piece of equipment. When the vibration levels deviate from this established norm, the IoT system instantly alerts the maintenance team. This alert is not just a simple notification but a detailed signal indicating the onset of potential performance degradation.

Such precise monitoring enables maintenance teams to identify and address issues before they escalate into significant problems. This early detection is crucial in environments where equipment reliability and uptime are paramount. By leveraging the power of IoT for real-time monitoring and precision alerts, organisations can significantly enhance their maintenance strategies, leading to improved equipment longevity, reduced downtime, and overall operational efficiency.

Optimising Maintenance Efficiency 

The integration of IoT devices in maintenance processes significantly enhances operational efficiency, allowing maintenance teams to concentrate on pivotal tasks while automating routine inspections. This strategic approach results in a more effective allocation of resources and time, optimising the overall maintenance workflow.

A key aspect of this efficiency is IoT predictive maintenance, which proactively identifies potential issues in machinery before they manifest.  This predictive capability contrasts with traditional preventive maintenance, which typically addresses damages after they have occurred. By employing IoT predictive maintenance, the lifespan of machines is extended, as maintenance is performed based on actual condition rather than on a predetermined schedule.

A critical piece of research supporting this approach comes from the ARC Advisory Group, which found that only 18% of industrial assets show linear depreciation with age. This insight challenges the traditional belief that machine wear and tear are directly proportional to usage and time. Instead, it underscores the effectiveness of predictive maintenance enabled by IoT, which can identify the actual condition of machinery, leading to more targeted and timely maintenance interventions.

This approach not only extends the life of equipment but also ensures that maintenance efforts are more accurately aligned with the actual needs of the machinery, preventing unnecessary downtime and reducing costs associated with over-maintenance or premature replacement of parts.

Advancing Workplace Safety through IoT-Enabled Predictive Maintenance

The application of IoT technology in maintenance regimes plays a pivotal role in elevating workplace safety standards. By continuously monitoring various conditions that could potentially lead to hazardous working environments, IoT systems proactively safeguard workers against a range of risks.

One of the standout features of IoT in this context is its predictive maintenance capability. This aspect of IoT technology empowers operation managers with foresight into potentially dangerous work conditions. For example, IoT systems can detect and analyse anomalies in machine temperature or voltage fluctuations. Such monitoring is crucial because these anomalies can be precursors to more severe issues, including equipment malfunctions or failures that could pose significant risks to worker safety.

By identifying these early warning signs, IoT predictive maintenance enables operation managers to take preemptive actions to mitigate these hazards. This could involve adjusting operational parameters, scheduling maintenance or repairs before a failure occurs, or even temporarily shutting down equipment to prevent accidents. The ability to anticipate and address these issues before they escalate into serious safety concerns is a key advantage of IoT technology in the maintenance sector.

Maximising Energy Efficiency with IoT-Enabled Monitoring and Optimization

The deployment of IoT devices in energy management represents a significant stride towards achieving greater energy efficiency in various industries. These devices are instrumental in monitoring and optimising energy usage, which not only leads to substantial cost savings but also contributes to a reduced environmental footprint.

IoT technology enables a more nuanced and precise approach to energy management. By continuously monitoring energy consumption patterns of equipment and systems, IoT devices can identify areas where energy usage can be optimised. This involves ensuring that equipment operates at peak efficiency and is activated only when necessary. For instance, IoT systems can detect when a machine is operating under suboptimal conditions that consume excess energy, or when equipment is left running unnecessarily, leading to wasteful energy use.

The ability to fine-tune energy consumption in real-time, based on actual usage data, allows organisations to make informed decisions that significantly lower their energy bills. This optimization is not just about reducing costs; it also plays a crucial role in environmental stewardship. By reducing energy waste, IoT contributes to lowering greenhouse gas emissions and other environmental impacts associated with excessive energy use.

The Future of IoT in Maintenance Teams

As we look towards the future of IoT in maintenance, it’s clear that we are on the cusp of a transformative era. The continuous evolution in sensor technology, data analytics, and machine learning is poised to redefine the landscape of industrial maintenance. These advancements are not just incremental improvements; they represent a fundamental shift towards a more intelligent, efficient, and predictive maintenance paradigm.

The integration of IoT with other Industry 4.0 technologies, particularly AI and robotics, is set to revolutionise maintenance processes. AI-driven systems will provide enhanced decision-making capabilities, automating many of the routine maintenance tasks and optimising maintenance schedules based on real-time data and predictive analytics. Robotics, on the other hand, will play a crucial role in executing maintenance tasks, especially in hazardous or hard-to-reach areas, thereby improving safety and efficiency. A report by the World Economic Forum highlights that AI and robotics could lead to a 10-20% increase in production efficiency.

Machine learning algorithms are expected to become more refined, enabling them to analyse complex data sets with greater accuracy and speed. This will lead to more precise predictive maintenance, where potential issues can be identified and addressed well before they manifest into failures. A study by PwC estimates that the use of advanced analytics in predictive maintenance could reduce costs by up to 12% and increase availability by up to 9%.


IoT and Industry 4.0 are revolutionising maintenance strategies, offering unparalleled benefits in terms of efficiency, cost savings, and predictive capabilities. As these technologies continue to evolve, maintenance teams will be equipped with even more powerful tools to optimise their operations, ensuring maximum productivity and safety in the industrial sector.


Charlie Green

Charlie Green is Senior Research Analyst at Comparesoft. Facilities Management, Smart Buildings, Workplace Management and Fixed Asset Management are his key research areas. Charlie holds a masters degree which allows him to offer data led and empirical research driven reports.

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