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Predictive maintenance: The holy grail in a pre-engineered cleanroom environment

Cleanroom sensor technology, the Internet of Things and big data: these developments are the enablers for modern-day predictive maintenance in pre-engineered cleanroom design. Industries have been exposed to digital disruption during the whole industry 4.0 decade, even though they have different levels of innovation. Maintenance has not changed, and the function of maintenance has been under the spotlight to be reinvented and increase performance by using all the enabling technologies such as AI, IoT, big data, machine learning etc.

In order to ensure constant performances and make our industrial assets more robust and resilient, it is essential to use all available resources. Therefore, we make use of the latest technologies to collect the right data from our cleanrooms and translate it into useful information. Our business model is based on industry 4.0, where machine learning and predictive modelling ensures that our cleanroom uptime is at the heart of our performance strategy. 

R&D Engineers, product developers, business leaders and operators all agree: predictive maintenance results in lighter workloads, reduced maintenance budgets and improved efficiency. By leveraging existing cleanroom and equipment data, predictive maintenance results in improved decision-making, better planning and increased profits. In other words: predicting the future state of a system has a long-lasting impact on its performance. In this connected industrial world, maintenance has found new opportunities arising from unexpected connections between assets within an industry. Failure forecasting capabilities have increased dramatically thanks to the availability of huge amounts of disparate data being able to be fused and merged so predictions do not depend on one-dimension datasets anymore. 

Design for standardization as enabler for predictive maintenance

Design for standardisation and legolisation are important enablers for our predictive maintenance approach. The pre-engineered building blocks that are related to Industry4.0 make it possible to gather data about various cleanroom projects, resulting in extremely reliable information. Going beyond design & installation of a cleanroom, in other words, choosing for a performance-based approach ensures that the customer only pays for a cleanroom that works. New maintenance models are emerging all the time in different sectors, with digital transformation as a key underlying factor. Digital transformation means going beyond digitization so it is not simply about applying new technologies to old maintenance processes. 

For a long time now, we have been integrating industry4.0 into our cleanroom approach. By equipping our cleanrooms with CleanConnect and GMPconnect, our CFR21 Part 11 compliant cloud platform, we can collect and process all sorts of data and insights on our cleanrooms. This data allows us to maintain our risk-based management vision. By collecting and comparing these sets of data, we get a profound insight into the cleanroom on which we define our maintenance strategy. Just like the design for standardisation and legolisation, our predictive maintenance approach acts as a building block within our pre-engineered cleanroom approach. 

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1. Off-site production, on-site assembling

Legolisation means standardisation. Standardisation causes a shift in production. Work is carried out in conditioned spaces such as factory halls. our cleanrooms are manufactured partly or entirely off-site, which means huge savings on transport costs and reduction of inconvenience on-site