The 21st century digital technologies as well as hardware automation tools facilitated the transformation of manufacturing, maintenance as well as digital supply chain to enter the Industry 4.0 era. Since, the increasing use of automation and intelligent networking has seen traditional industrial environments transformed and the advent of the ‘Smart Factory’ model.
The augmentation in use and integration of cyber-physical systems, has gone hand-in-hand with what is a significant element of modern industrial practices – Maintenance 4.0. One of the key drivers of Maintenance 4.0 is the use of digitisation and data exchanges to perform cost effective and efficient maintenance before the equipment actually fails or becomes damaged.
For government-level critical systems, the technology and processes have many proofs of concept and achieving 100 per cent guaranteed availability as a minimum requirement is not simply an ambition for the future – it is available now. With data at the very core of predictive maintenance, the more detailed and accurate information you have, the easier it is to access the full potential of operations.
However, the move to Predictive Maintenance will only happen when trust in the employed technologies, data and processes is guaranteed. This requires a high level of trust in new and disruptive technologies, as well as appropriate digital maintenance strategies, to ensure ultimate availability of critical systems.
Using a combination of Internet of Things (IoT), Big Data related technologies, predictive maintenance is already such a significant component of contemporary industrial processes that a 2015 McKinsey & Company report on IoT suggests it could save manufacturers – worldwide – around $200 billion to $600 billion, by 2025.
While government-level projects focused on critical systems such as electricity and water supply, nuclear power, or transportation and logistics, often receive appropriate state funding, the costs of implementing a predictive maintenance strategy for private industry, as well as smaller manufacturing entities, may seem daunting. But just as you cannot put the roof on a house without foundations and supports, the same logic applies to scaling up your predictive maintenance approach.
Predictive maintenance in the SME segment
For SME to mid-sized entities, small incremental steps can be taken to transition the company towards Industry 4.0 standards. Condition-based maintenance (CBM), integrated across selected priority assets, demonstrate the value of early warnings on potential failures and establish the foundation for a more comprehensive strategy. The learning experience gained from these initial applications will then dictate how the system can be rolled out across your whole operation and facilities.
It can be easy to forget, when talking about complex systems and the technological benefits of predictive maintenance, that the implementation of any new technology always starts with people. Undoubtedly, automated and digitised functions make the human operators’ jobs simpler; however, successfully transitioning to Industry 4.0 standards needs a solid foundation of skilled and well-trained experts to manage the processes and tools safely and securely, to maintain availability.
Three implementation factors
The three core elements to consider when deploying maintenance strategies are: safety, security, and availability. Maintenance 4.0 is increasingly key to contributing towards achieving sovereignty and autonomy. In part inspired by its sustainable approach to 21st century production, to achieve this goal, the UAE has put in place a manufacturing skills strategy that includes cross-domain competencies and vocational training across manufacturing sectors.
In this light, Thales and Tawazun Economic Program launched Thales Emarat Technologies, a local entity 100% owned by Thales in 2019, to support growth, localisation and the industrialisation strategies of the UAE. The company intends to foster its contribution to the UAE’s ambitions to become a global leader, with outstanding civil infrastructure and defence capabilities underpinned by a strong local industrial technology base.
Introducing a Maintenance 4.0 strategy and predictive maintenance cannot simply be achieved through the acquisition of new technology. It must form part of a wider approach of seamless integration between industry, innovation and education. In order to develop new and disruptive technologies for Maintenance 4.0 with the required level of trust and maturity, powerful research and development capabilities, as well as cooperation with local top-notch innovation ecosystems are basic prerequisites.
These will provide the foundation for developing and sustaining a relevant maintenance skills base and a strong dynamic of innovation. That’s how providers of both a disruptive product and its innovative, efficient maintenance will stand apart in a world of giants.