Maintenance 4.0: The Digital Twin of Industrie 4.0

Updated: Aug 31



As the information era continues to progress and technologies rise and fall in prominence, one question persists in the minds of industry leaders and the public at large - what is the next big app that will change and disrupt the market? Like smart phones or the internet before it, what development will disrupt and change for the better the way we live our lives, run our businesses and perceive the world around us? I would suggest that this “next big thing” with such massive potential is Maintenance 4.0, the ‘digital twin’ of Industrie 4.0.

Maintenance 4.0 is the concept of applying Industrie 4.0 philosophies into the area of maintaining systems rather than manufacturing them. We live in a world full of increasingly complex equipment, and maintaining that equipment to its design specifications increases in time and complexity in tandem. Consequently we require a methodology utilising the latest in technology to ensure these increasing maintenance requirements are performed efficiently, in a way that assists technicians and upholds stringent safety parameters.

On the other side, Industrie 4.0 is a term coined by the German government to cover their efforts to bring about the age of what has been called the “fourth industrial revolution.” If you haven’t heard of it, in brief it is a groundbreaking shift in thinking and technology occurring in the area of manufacturing and industrial works. Industrie 4.0 at its core is about increasing ease of access, efficiency and functionality of systems. This is an attractive concept that has gained much interest for obvious reasons, and leads to the question – if it can be done for manufacturing, why not the other half of the equation – maintenance?

This is the question that has led to the development of Maintenance 4.0. Manufacturing is incredibly important to modern society, but the other side of the coin in maintenance is perhaps more so. Time and resources dedicated towards maintaining systems, or worse fixing those systems after they have failed, means less time and resources available to invest in new infrastructure. This is significant because historically, competing companies have largely had the victor decided by who was most efficiently able to deliver their product or service.

The path to increasing this efficiency is Maintenance 4.0, my methodology of applying the tenets of Industrie 4.0 in combination with cutting edge technologies like artificial intelligence to the upkeep of complex systems. Over the last few years, tech commentators and leaders of industry alike have looked to AI - and more specifically machine learning - to be that next great leap forward in our capabilities, like the internet or computing were at their advent. Through these technologies we can put the evolving computational abilities and data analytics of recent years to work for us in ways that would have been inconceivable even a few short years ago, and solve real world problems that have daunted us as a species for millennia.

I believe that Maintenance 4.0 will be central to the achievement of the goals of Industrie 4.0, and furthermore that it will support advances in performance of assets and business across many sectors. Originally developed for airlines, the platform has shown to be strongly transferable across industries – from assisting maintenance on planes to buses and even power plants.

You may be wondering what exactly the 4.0 following Industrie (and thus Maintenance 4.0) signifies. This represents its place in the order of advancements that have lead to “industrial revolutions” in the past, this being the fourth. To provide some perspective on the significance of that, the first three industrial revolutions in this context being:

1st Industrial Revolution: Steam power and mechanisation

2nd Industrial Revolution: Mass Production and the uses of electrically powered assembly lines

3rd Industrial Revolution: Robotic automation and computer chips

4th Industrial Revolution: Industrie 4.0 - IoT and merging of cyber and physical spaces

The significance of this concept is already being assessed by industry thought leaders and analysts as a potential game changer. Gartner estimates that Industrie 4.0 will be increasingly used in manufacturing, and furthermore they project that by 2022 more than half of those utilising these ecosystems will use a virtual or intelligent assistant.

The essence of the idea behind Industry 4.0 is that it represents bringing a greater level of connectivity and intelligence to industrial efforts. The goal is to create a “SMART Factory”, where machinery can be easily controlled and interfaced with, and where data can be accessed and analyzed easily in order to make more informed decisions.

One area today where the benefits of Industrie 4.0 can already be seen in use is the cutting edge and suitably named Audi Smart Factory. Utilizing some of the advantages of having a virtual layout and intelligent machinery to create a highly modular assembly space, moving away from a typical assembly line. Machinery can be adapted and moved throughout the facility, resulting in a much more flexible and efficient system as a whole. Audi are also experimenting with additional technologies to help merge the gap between cyber and physical like virtual reality glasses and 3D metal printing.

In turn, early examples of Maintenance 4.0 along these lines is already being used in ever forwards-thinking Japan, where they are beginning to apply these concepts and machine learning technology to their trains. The Yamanote Line is the world’s busiest train line and thus it’s essential that it is running all the time, or as close to 100% of the time as can be made possible.

In Japan, it is such a serious occasion when a train isn’t running on time that the train line will provide a certificate to present to your work as evidence of their part in making you late. The Japanese government has decided to look to machine learning as the next step in increasing their availability, efficiency and reducing downtime. Sensors on trains and tracks allow them to gather large amounts of real time data on the condition of infrastructure and helps make decisions on when and what to maintenance. This is an example of Condition Based Maintenance and has lead to the Prime Minister of Japan’s office stating that “smart maintenance will trigger a revolution in the world’s transportation infrastructure.”

The above examples of Audi and Japan begin to make clear how huge an advantage improvements in these areas can be. Increased interconnectivity and transparency of data in the facility or train line will allow engineers and technicians to view performance statistics and make informed on the fly adjustments to equipment. The increased modularity of machinery and tools they can achieve as a result of having greater control means they can adapt what type of car or repair they are making at any moment without having to undergo difficult manual adjustments. Technicians can interact easily with the system through IoT features and the most elegant aspect being that it can learn and self-improve as it runs. At the end of the day, the idea of both Industrie and Maintenance 4.0 is about placing greater control over their equipment into the hands of technicians.

I believe at this point it should be evident the potential impact Maintenance 4.0 might have, but there is more to come. Stay posted for more blogs going into detail on individual aspects of the philosophy and technology behind Maintenance 4.0 below, such as:

  • Interconnectivity, using the “Internet of Things” or “IoT” to ensure the ability of machinery, devices and people to communicate.

  • Transparency of information, ensuring that vast quantities of data can be accumulated and analyzed to assist learning and decision making.

  • Technical assistance, forming synergy between computer and technician to best equip and assist them.

  • Decentralised decisions, to automate minutiae and allow systems to make decisions and run as autonomously as possible.


Written by

Anant Sahay

LexX CEO and Founder

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