DPS was looking to share and visualize all of their 3D models, laser scan information, engineering drawings, documents and data. Additionally, they wanted to avoid investing in expensive proprietary systems which they’d found to be inflexible and only address one or two verticals within their portfolio.

With Nextspace, they’ve been able to provide complex data integrations and visualisations which are appropriate to the customer’s needs, and build digital twins which can be accessed in the cloud with a standard Internet connection. No more forcing information into a predetermined structure and visualization format.

DPS had found in their research that other providers would require proprietary data formats, meaning current software, system and documentation usage would likely be side-lined. The advantage of Nextspace for DPS was that the systems which were delivering value and already ingrained in customer processes (such as Maximo and SAP) could be incorporated into Nextspace for connection with all other data. For example, work orders can be sent via Maximo from the exact location they relate to in the digital twin.

DPS found Nextspace user training easy and time-economical. Nextspace Operator training took only a few days, and user training less than a day.

They’ve found they can provide complex data integrations and visualizations quickly, easily and reliably—tailoring them specifically to different customers’ needs.

DPS once relied on multiple personnel flying to a single location for three days to share reports and drawings from multiple different systems and software. Each discipline would share their reports: safety, maintenance, operations and so on.

With the digital twins they’ve built on Nextspace, they can now do this remotely and in a third of the time.

DPS reports that digital twins have made training much more effective for their customers. They can now train large groups multiple times to do specific work on the plant. For example, critical incident escalation training—such as major boiler room shutdowns. Customers can teach this to their teams several times in their digital twin so they learn it safely, rather than relying on the knowledge being retained after doing it just once with a large group in a dangerous plant.

DPS is now planning to expand their business into machine learning and artificial intelligence, in order to extract meaning from legacy data for their customers. With this additional capability the process of linking and capturing critical information from engineering documents and drawings will be streamlined, and will mean they can access and incorporate increasing depths of data.

They see Nextspace as being critically important to all areas of digital engineering, including greenfield handover; as a validation tool for the owner & engineering, procurement and construction; brownfield engineering & design; maintenance optimization; operations streamlining; inspection optimization; health, safety and environment management; and predictive analytics.