Using Industry 4.0 To Improve Maintenance Management

We have been hearing about Industry 4.0 for some time now, and like any fashion, stories of innovation and success abound.


However, some of us are still left scratching with the concepts and applications. More so, in the rush to adapt tech fashion it is important to understand how the technology fits into your overall systems and processes.

In the maintenance management world, Industry 4.0 offers two powerful advantages – cloud-based maintenance management systems, and integrated machine data. The opportunities are endless, but the application of the technology is where the real learning will take place.

Industry 4.0 (IOT 4.0) is the name for the current trend of automation and data exchange in manufacturing technologies. The term comes from the Fourth Industrial Revolution, (or 4.0) and generally involves putting terrestrial intelligence into the internet (cloud) where it can be integrated, or plugged in, to other systems. It’s like if your vehicle dashboard was weaponised to IOT 4.0, so that when your warning light came on to warn of an issue, that same information would be uploaded to the Cloud. Imagine getting a call from BP in response to your low fuel warning light coming on?

As engineers have evolved from gaining respect for their technical ability to gaining respect for their ability to run a maintenance management process,


computerised maintenance management systems (CMMS) have become the pivotal tool in enhancing efficiency, productivity, and reliability.


CMMSs have evolved from the 1980s paper-based maintenance management systems, to floppy disks, hard drives, LANs, WANs and finally thin clients. Now with the internet delivering bandwidth, Cloud-driven systems are a reality, offering speed, transparency, and transportability as well as the “plugging in” of contiguous systems, either machine- or finance-based. The new breed of Cloud (IOT) based CMMS offer the opportunity to integrate seamlessly into this interconnected ecosystem, ushering in a new era of predictive maintenance, data-driven decision-making, and asset optimisation.

The modern maintenance engineer must bridge between reliability engineering and the operational realities to form a coherent work schedule that avoids reliability embarrassment and financial rabbit holes. Conventionally this would be achieved with strategies including task optimisation (as found results), and condition monitoring (in-service feedback). Direct connection to the plant is a paradigm shift in the role, but it must be understood it is simply another tool in the toolbox. Connected machinery is not in itself a maintenance plan.


The ability to harness real-time data from sensors, devices, and equipment from the production environment leverages the ability to gather, analyse, and interpret vast amounts of operational data, enabling proactive maintenance strategies.


By continuously monitoring equipment performance and health metrics, the CMMS can predict potential issues before they escalate, allowing maintenance teams to intervene pre-emptively and schedule repairs during optimal downtime windows.

Cloud-based CMMS offer a number of benefits:
• Low cost of ownership
• Easy to maintain
• User-friendly interface (web browser)
• Remote system access
• Faster more efficient support from the vendor
• Open architecture and interfaces

Connected CMMS facilitate condition-based maintenance strategies, wherein maintenance activities are triggered based on the real-time condition of assets. By monitoring factors such as temperature, vibration, and performance metrics in real-time, CMMS can dynamically adjust maintenance schedules and prioritise tasks according to the current state of equipment. This dynamic approach not only optimises resource allocation but also minimises unnecessary maintenance interventions, reducing downtime and operational disruptions.

The trap is in managing the flow of data so that you are driving the maintenance management process, not being driven by feedbacks. As an example, a Kiwi dairy company was forced to pare back their IOT 4.0 outputs after a flood of overzealous system alarms threatened to swamp their scheduling.

We can however reap the benefits of the IOT 4.0 era to embrace predictive analytics and machine learning algorithms to unlock actionable insights from historical maintenance data. Through pattern recognition and anomaly detection, trends, patterns, and correlations that may go unnoticed by human operators can be recognised and used to trigger work schedules. This predictive capability enables organisations to transition from reactive and preventive maintenance approaches to a more proactive and data-driven maintenance paradigm, ultimately driving down maintenance costs and extending asset lifespan.

Moreover, CMMS integrated with IoT devices enable remote monitoring and control capabilities, allowing maintenance teams to oversee equipment performance and execute maintenance tasks from anywhere with an internet connection. This remote accessibility enhances operational flexibility, accelerates response times, and empowers maintenance personnel to address issues promptly, regardless of their physical location.


Where to from here? The application of computerised maintenance management systems in the Industry 4.0 world represents an opportunity for a paradigm shift in maintenance practices, leveraging process feedback to drive efficiency, reliability, and cost savings. By integrating these advanced technologies logically into the CMMS, organisations can optimise asset performance, mitigate risks, and stay competitive.


Cloud-based maintenance management systems like MainTrak offer a whole new level of transparency and transportability for the engineer.