What is pervasive engineering?
SAP used its ASUG (Americas SAP User Group) Sapphire Now conference held in Orlando, Florida this year to detail a number of ‘telling’ partner initiatives that could suggest new directions of focus for software application developers working in data-driven environments.
First among, well, several, was Ansys (pronounced an-sis) — this SAP partner works with engineering and operations technologies
More specifically, Ansys works in what has been called the Pervasive Engineering Simulation (PES) market, specialising in pervasive simulation software.
The company says that if you’ve ever seen a rocket launch, flown on an airplane, driven a car, used a computer, touched a mobile device, crossed a bridge or put on wearable technology, chances are you’ve used a product where Ansys software played a role in its creation.
What is pervasive engineering?
But what, please, is so-called pervasive engineering and pervasive simulation? The Computer Weekly Developer Network offers you this proposed definition.
Pervasive engineering is physical product (and software) development designed to harness information streams from digitally tracked (typically Internet of Things centric) assets using smart sensors that are connected to an analysis hub of data analytics and management. Pervasive simulation (through the use of digital twins and supporting data analytics) allows (physical product and software) engineers to explore design and product development using real-world conditions. Prototypes can be created to ‘fork’ concepts that skew existing products (or services) while those existing assets remain in working operation, in their core pervasive state. The state of all machine assets is therefore developed continuously, iteratively and pervasively.
You can read more here from Ansys on how it positions its approach to this element of design and it is from these pages that we have drawn the above definition.
The firm’s SAP partnership embeds Ansys’ pervasive simulation software for digital twins into SAP’s digital supply chain, manufacturing and asset management portfolio. The partnership’s first result is called SAP Predictive Engineering Insights enabled by Ansys and has been built to run on the SAP Cloud Platform.
“The technology here is designed to help industrial asset operators to optimise operations and maintenance through real-time engineering insights, to reduce product cycle times and increase profitability,” notes SAP, in a product statement.
Diverse data sets
Ansys says that by linking diverse data sets gathered by sensors on assets, engineers can gain an insight into product behaviour to improve future development. Additionally, they can develop hybrid models that fuse machine learning with ‘deep physics’ simulation models to accurately predict how an asset can fail after it is deployed.
Both companies will now work on connecting this type of information into other asset management solutions from SAP including the following: SAP Enterprise Asset Management, SAP Asset Strategy and Performance Management, SAP Predictive Maintenance and Service and SAP Asset Intelligence Network.
“This solution will help equipment operators and service providers to predict and improve asset performance and reliability with engineering insights. A digital twin that ties together engineering models, manufacturing details and operational insights including financial information is unique in the industry,” said Hala Zeine, president for digital supply chain and manufacturing, SAP
Are we there yet?
There’s a lot of conceptual conceptualising here. Whether all engineering firms of any type are actually ready to start employing these concepts is open to question. One might reasonably suggest that this is indeed the future and the wider impact of the Internet of Things will drive all engineering research and development this way.
SAP has clearly made these moves strategically in order to increase the breadth of its SAP Predictive Engineering Insights brand. The Ansys Twin Builder product for building, validating and deploying digital twins will be key to the progress made here.
The grease and spanners will still pervade on the shop floor, but not without software to control industrial assets with predictive and prescriptive maintenance.
Where there’s muck, there’s digital twins and pervasive engineering.