Industry thrives on buzz words and fashion, and maintenance management is no stranger to this world. RCM, RCA, TPM and other 3 -letter acronyms have all been rolled out as the holy grail, yet to find true industry success in the long term is rare. You can ask check this yourself by going back to the glossy power point presentation from 10 years ago and ask the hard questions of the site in the study. You may be surprised.

The Internet of Things

When the breathless commentary began about how the internet of things (IOT 4.0) was going to change computerised maintenance management systems with machine suppliers touting their web connected assets as the next best thing in reliability I asked the big question, “Show me where it is truly making a difference?” I asked the audience of reliability experts at the 2023 VANZ (Vibration Assoc of NZ) conference this question and the replies centred around the machines connecting through the Cloud to advise of machine state.

So ok, you can now get feedback from your plant without leaving your desk.

Sorry team, that is reactive maintenance, no different to me looking at the odometer or warning light on my VW Amarok.

Industry Reality Check

As the providers of the latest Cloud based cmms in the market, our team was intrigued by the topic. Yes, there are magnificent advantages to Cloud applications, but is anyone ACTUALLY using feedback from their machines to directly modify and IMPROVE their reliability and what is the experience? I posed this to the 2024 VANZ conference and could not get a reply. Believe me, these VANZ guys know their stuff and the answer was a resounding “No-one”. Crickets.

The problem is there is more to all this automation than direct or fuzzy logic. This is why we demand that the pilot lands the Airbus. Why the turbine feedback cannot automatically shut down power generation in in the middle of a winter brown out. Why AI can analyse potential melanoma but only advise on diagnosis. IOT 4.0 and AI require a humanising step.

AI

The AI conversation is growing rapidly, and the followers of fashion are thronging to join the rush. Again, don’t trip over your boots in the rush to climb in board. Apply some critical thought about what and how the benefits can improve your outcomes. Our team have embedded AI functionality into sections of the maintenance planners world in our systems, but again, the outputs steer well away from allowing any robotic hands on the steering wheel.

Where to From Here?

There are green shoots of high-level technologies on the fringes and I am sure in due course great advancements will be made. What we must remember, using the smart phone analogy, is that we are at the age of the original 1990’s “brick” cell phone. Everyone wanted one, everyone had excuses why they needed one, but no-one truly understood the true potential that is now everyday life in 2025.

The biggest advancements will be in understanding how to humanise the AI inputs. What is (if any) the human intervention point? How do we keep our hands on the steering wheel? Good luck out there.

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The YWAM Koha was built in 1968 as a buoy tender for the German Government, responsible for the maintenance of marine navigation buoys on the River Elbe before seeing service for the South African Maritime Safety Authority. From 2009 to 2018, she plied the Pacific Islands as the Claymore, providing the essential transport links to Pitcairn Island from New Zealand and French Polynesia.

Youth With A Mission

Donated to the Youth With a Mission (YWAM) program by Stoney Creek Shipping company’s Nigel Jolly, the YWAM Koha now distributes medical care to those in need across the Pacific. The ship has the capacity to carry containers, supplies, crew and volunteers to assist with everything from education to medical and developmental projects. Shipping containers converted into medical and dental clinics are stowed on the Koha’s deck, providing operating theatres and X-ray units, among other functions. However, most of the work the organisation does is in the villages themselves. The ship anchors close to shore, providing primary health care, preventative medicine such as vaccinations, oral health checks and eye examinations to remote communities.

The Pacific Islands are one of the most geographically challenging islands on planet Earth with many villages located on the more isolated outer islands and desperately in need of New Zealand’s help. The vast majority have no airstrips and no bridges connecting them, so the only way to reach them is via ship.

Solving a Problem

Staffed entirely by volunteers, a major operational issue for the ship is retaining the detailed institutionalised knowledge required to keep her in good trim and compliant with marine requirements. Historical information was either paper based or stored in people’s heads. Now, the information is digitised into an upwardly driven management information system and available onboard or ashore for future crews thanks to Maintenance Transformation’s Craig Carlyle and the MainTrak maintenance management system.

Answering a call from ABD Groups’ John Clynes, Carlyle not only provided the MainTrak system free of charge, but even mapped the ships assets while she was docked in Tauranga, while Clynes conducted a stocktake of the spares inventory. The ship now has a complete maintenance management system, able to manage its maintenance schedule, technical documentation and spares as well as storing its intellectual knowledge, ready for any future engineers to tap into.

The system is Cloud based, with full Starlink coverage across the Pacific meaning that YWAM Technical director Tony Fish can stay in touch from around the Globe and ensure any replacement parts are ready and waiting anywhere the ship docks.

For Carlyle, mapping the assets was a labour of love, relishing the opportunity to roll up his sleeves and crawl all over the ship. He found the ship well cared for and pleasingly clean. In his words. “This ship reverberates history and engineering experience. Sadly, most of that learning has walked off the gangplank since 1968, but now we have a method to retain it in the Engine Room for future generations.”

Nigel and Brenda Jolly said their decision to donate the vessel to YWAM was out of a desire to see the boat looked after and do something they can be proud of. The MainTrak maintenance management system has provided the crew with the tool to do just that.

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Maintenance Manuals

For the rest of us, a valuable starting point for creating or managing a maintenance plan is the manufacturers operating manual, (a point referenced in regulations). However, while a great starting point, the maintenance instructions must be taken with a grain of salt. Whilst the manufacturer is perhaps providing the benefit of their global experience, some are ensuring the machine does not break before the cheque clears or have a strategy of selling you 2-3 times the capital value in spares over the asset life.

Planners Diligence

Whatever the source of PM routines, even highly technical industries suffer at the coalface from a plethora of additional PM Tasks that deserve some form of challenge from the Maintenance Planner. These tasks are generally easy to spot; the emphasis on check, check, check, and a lunar (monthly, 6 monthly, yearly) frequency. These are FAT routines, (fear and tradition). Scratch the surface and you will generally find that FAT routines are created as a knee-jerk reaction to an asset failure or similar process embarrassment, opinion, or someone else’s good idea.

While they offer a peace offering at the time of shame and atonement, they leave a legacy of unchallenged work that often chokes the maintenance schedule. There is however a solution available, based on due diligence, operational science and optimisation.

The first step is to study the provenance of the task. Who created the routine, when, and why? What results have been recorded? Has anyone ever found anything to justify the check? Unless the check has traceable roots to a statutory or compliance requirement, the planner should challenge the routine, including making frequency changes (see later). Be prepared to not win 100% of these battles, but you will be surprised how much the decks are cleared when you push back with facts.

Operational Science

Operational science is the art of listening to your plant, using measurements and recorded data to provide a foundation for decision making. As an example, your maintenance plan calls for you to change your gearbox oil every 12 month. However, if due to the realities of the process, environment, and service conditions, the drained oil condition, (through tribology or other) is judged to be near perfect condition. This is operational science. Common sense says you should extend your oil change plan to something more than 12 months.

Optimisation

Optimisation is the lean maintenance science of refining the frequency of the PM task to align with the actual plant conditions, rather than arbitrary lunar statements, (monthly, 3 monthly, 6 monthly, etc). Such stagnant frequency declarations indicate opinion rather than facts. Using optimisation theory, the Planner exercises his mandate to expand or contract the PM task frequency to suit the as found history.

On one site, we checked the safety guards every month for 23 years, only finding 10 faults in that time. An argument could be formed to expand the PM task frequency from 1 month to 4 months, based on this as-found history for the plant. This is a 75% reduction in workload, entirely justifiable by the as-found results. The Planner may declare 4 months as the outer limit of confidence, which is a sensible application of the planning role. As planners, we have the mandate to manage. As long as the reasons for a frequency change are recorded, we are leaving a defendable history of the management decisions.

A more scientific optimisation approach is available, developed by Craig Carlyle and available as an automated toggle option in the MainTrak maintenance management system. The algorithm is based on control loop derivatives and uses simple feedback from the tradesman to nudge the task frequency either sooner or later. The steps are

+ 12%, +10%, 0, -10%, -12% depending on whether the as found condition was:

• A – As new, no sign of wear
• B – Good condition, minor wear (could have lasted longer)
• C – Average condition, expected wear (i.e., bang on target!)
• D – Poor condition, significant wear (maintained too late)
• E – Missing or destroyed

Practical experience shows that the as-found results will arrive at “C” within a maximum of 6 PM task cycles. The value is added at the workface, where the tradesman is the best eyes and ears you could ask for, and the relationship is strengthened by your investment in his/her feedback.

Returning to our example of the gearbox oil, if we had used the optimisation algorithm, the first oil change would have given us feedback of “B” – Good Condition, or a 10% increase in the task frequency (13.2 months). Subsequent task feedback would further increment the task frequency until we are changing the oil at just the right time, (condition C), reducing maintenance cost and resource allocation.

In an added value diary processing plant, this concept was used to reduce the cost for weekend process valve maintenance from $40k to just $1,200. With increased reliability!

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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.

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