25 June 2019
Industry 4.0 is the industrial revolution we're currently living through - but instead of steam trains and textiles, we're being powered by artificial intelligence (AI) and the power of machines to analyse, interpret and synthesize data. So how does Predictive Maintenance fit?
When the first industrial revolution hit, we were collectively amazed and irrevocably changed by the introduction of machines, powered by steam engines and hydropower. Now, a different revolution is taking place but machines are once again at the heart of the massive shift that's currently occurring. We're living in and through Industry 4.0 and what we're seeing is that this time, it's predictive technology that's driving us forward.
What is Industry 4.0?
Industry 4.0 is a term that is often mistakenly interchanged with 'fourth industrial revolution'. In actual fact, it's a subset of the fourth revolution, focused more specifically on "the concept of factories in which machines are augmented with wireless connectivity and sensors, connected to a system that can visualise the entire production line, control, and make decisions on its own."
Industry 4.0 is all about data - how it's collected, analysed, synthesized, interpreted and applied. And that's why predictive maintenance and analytics is such a huge part of the Industry 4.0 - because it's all about using data to predict outcomes and improve performance. The AI technology that sits behind this comes with a variety of benefits that include job safety, environmental gains, increased productivity and uptime all of which typically results in supercharged ROI improvements.
How does predictive maintenance fit into Industry 4.0?
Industry 4.0 encompasses the pervasive trend towards automation and data exchange, internet of things (IoT), cloud computing, artificial intelligence and of course, predictive analytics.
Through the lens of industry 4.0, predictive maintenance - which is in essence an extension and improvement of condition-based monitoring - is one of it's many positive outputs. By proactively and pre-emptively managing asset maintenance around predicted failures, uptime is significantly increased and productivity is majorly optimised.
The toolkit for making it possible comes in the form of AI-enabled analysis of big data. Using machine learning (a specific subset of artificial intelligence) it becomes a method of preventing asset failure by analyzing industrial production data to identify patterns and subsequently predict issues, breakages and failures before they happen.
How does IoT Predictive maintenance actually work?
There are several components that must exist for a industrial asset to be predictively maintained and therefore considered Industry 4.0.
The first step in any IoT enabled process is having high quality sensors that are streaming live data. Sensors will ideally be collecting a wide variety of metrics, without bias.
The next critical component is a secure systems by which data can flow between assets and the central data lake.
Central data lake
Creating a data lake that can act as a secure home for all source data is the next important step. It's irrelevant if this is on premise or cloud based, just that it's accessible by the programs that need it - including your predictive analysis software.
Powered by artificial intelligence for profound insight, machine learning algorithms will ingest, aggregate and synthesize data, with the ability to recognize complex patterns and generating detailed insights.
Time to Failure and Root Cause Analysis predictions
Predictions are ideally in the form of a user friendly dashboard that provides time-to-failure and root cause analysis alerts and insights. Operational staff can quickly and easily identify and action preventative maintenance as and when required.
Every company wants to remove the word 'downtime' from their vocabulary and their operations. With predictive maintenance you can eliminate unscheduled maintenance and instead plan for it with optimal material and staff resourcing, increasing productivity and profits.
The future of predictive maintenance in Indsutry 4.0?
Predictive maintenance is already playing a key role in Industry 4.0. As machines get smarter and AI technology and platforms get more advanced, maintenance decisions will be increasingly left up to them to reduce the risk of human error and increase the chances of optimal performance.
Data - the currency of our age - is already and will continue to usher in a new era of industrial operations, smart factories and revolutionised ways of working.
As more and more companies recognize the value of implementing asset management software, we will only see a faster gallop towards the end of Industry 4.0 and the start of whatever comes next.
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