Digitalisation Simplified

Digitalisation Debunked Information

Beyond Just Techology

The Requirement for Tailored Solutions

When digitalisation and Industry 4.0 started to gain traction in industry, they provided a concept around the application of technologies to industrial applications. Now however, the meaning specifically around digitalisation has become clouded, it is now being used as a blanket term to cover anything related to the use of technologies in all areas and not just in industry.

However, there is good reason for this, digitalisation is not a one size fits all, in reality solutions need to be tailored to their application to gain real value from their implementation.

Digitalisation Debunked Overview


The Process of a Digital Evolution

The 'Digital Revolution' is what is spoken about most, however, this is not necessarily the approach we take at Bilfinger UK. To understand what is eventually possible with the technologies available to us is key but we need to set out a roadmap that gets us there. This evolutionary approach to achieve the digital revolution is key to success, step-by-step, gain-by-gain, realising value at all stages of the process.


Steps to Digitalisation

We demonstrate our approach through our defined digitalisation steps shown below:

Steps to Digitalisation


Step 1

Obsolescence management is the first step in this journey but not necessarily using traditional thinking. We need to look at obsolete equipment from the perspective of failure and criticality but also from a capability/functionality perspective. Using new Industry 4.0 technologies, we can look at new ways of augmenting existing equipment to bring new functionality and capability to old equipment. Visit our Digital Enablement page to find out more.

Step 2

Reliability of our equipment must be reviewed, assets, control systems and instrumentation along with maintenance (CMMS) and potentially ERP systems will be relied upon for their data in order for us to realise value. With this in mind, we must ensure that they are running reliably and effectively, which this step focuses on.

Step 3

Understanding assets, this seems obvious but looking at assets and asking the simple questions about their performance and operational functionality is a key element to success. Reviewing the process itself and asset interoperability at both a function and data level can lead to real insights in our operations.

Step 4

The software platforms and systems that form our central data and analytics platforms, and data is the key to achieving what is possible with digitalisation and we need to understand the technologies that allow use to utilise this data successfully. However, this should not be the starting point, choosing a software platform and allowing this to drive what we do with our process is a recipe for disaster. We need to understand our value case alongside our processes, assets and infrastructure and allow the defined targets select which software platforms and tools we use.

Step 5

This is where we realise the full promise of digitalisation, our defined targets and aims for the digital transformation that we are on are here, in this case a predict and prevent model for maintenance.

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