Engineering: leader della Digital Transformation

Engineering Innovation In

Digital Industry

Predictive maintenance in the digital factory

Predictive maintenance in the digital factory

Reducing processing time and costs, optimising the efficiency of machinery and preventing damage are key elements of the new Industry 4.0-oriented digital maintenance.

Approach & Solution

ind-7-q.jpg

Approach

Our client, one of the world’s eight largest automotive groups by number of vehicles produced, decided to update the processes used at one of its plants and move from scheduled maintenance to a more efficient model based on acquiring data from individual machines. With the help of our experts here at Engineering and the technologies included in our DiVe portal, we responded to the challenge of setting up a predictive maintenance system for the client. This “Maintenance 4.0” model involves a first step, called Early Warning, which for each asset focuses on defining the “signature” (the standard behaviour expected) and spotting any behaviour that diverges from this signature, which might indicate potential faults.

Solution

Through the use of configurable dashboards, with our DiVE portal we monitor the assets and any potential early warnings via an interface developed in line with the customer’s requirements. With the help of detailed reports, we then enable the customer to carry out a thorough analysis of the data acquired.
With the aid of the analytics module, we leverage the potential of machine learning in respect of all the various sets of data collected to identify correlations and perform predictive maintenance in the truest sense of the term. In the process of digital transformation, we can estimate the behaviour of the assets over the medium to long term.
We therefore allow the client to evaluate the potential cost reductions that could be obtained by modifying and optimising its maintenance tasks.

Results

With our Engineering solution based on the DiVE portal, we have enabled the client to move from maintenance based on inspections and interventions at fixed time intervals to predictive maintenance based on information about the current condition of the asset. Thanks to our solution, the customer has increased the efficiency and effectiveness of its interventions and consequently limited the associated costs.

Project Value

Cost cutting
Process performance
Innovation

Enabling Technologies

Cloud
AI & Advanced Analytics
IoT

Our Products & Other Technologies

DIVE

Project Team

Engineering Manufacturing & Automation Business Unit