With the size of connected products market estimated to be $519 billion to $685 billion by 2020,
manufacturers are expected to add non-physical skills, such as digital engineering, to their traditional
physical skills base. Through increased computing speed, storage capacity and processing capabilities,
digital engineering has empowered a paradigm shift from the traditional design to build methodology to a
model-analyze-build methodology.
Product-based business models are being disrupted by service-based business model, new skills are needed
in a world of smart products, and innovation success depends on the effectiveness of a company's open
ecosystem.
From drawings to simulations, engineers are increasingly using advanced technologies to capture data and
craft design in a digitized environment. From connected coffee makers, vibration monitoring of industrial
pumps to remote patient monitoring devices, the network of physical objects embedded with software,
sensors and network connectivity is growing by the day. Through progressive applications, the art of
digital engineering enables designers to explore possibilities and develop innovative solutions.
So what makes digital engineering so…'innovative?'
Well, in short, the flow of data and the ability to act on data, fast or in an automated fashion.
Manufacturers often find themselves dealing with a legacy system that isn't pro 'digital
continuity' and as a result, many of the functions operate in silos. There is an inherent need to
streamline data flow and reduce discontinuity throughout the entire product lifecycle, starting from
engineering to manufacturing, to services.
What makes this transformation so complex is not just the availability of the right toolchain needed to
make the data consistent across different silos, but also the scarcity of the expertise needed to engineer
the entire connectivity of the data flow.
With productivity, speed of collaboration and faster time to market as the major goals of most
manufacturers, enabling a system that supports an effective flow of data is increasingly becoming
challenging. As a result, manufacturers are tapping into an ecosystem of service providers that have the
expertise and skillsets needed to digitally engineer a system that can streamline data flow and increase
connectivity.
Assess the minimum amount of
data that is needed by each domain and subdomain of the process
Centralize the data into one
coherent system
Build an execution model that
enables the handshake of data across systems
But it is easier said than done. Companies need partners that are
able to handle the different phases of the product development, not only from the technology point but
also from the change management standpoint. Which truly is where the meat of the digital engineering pie
lies.
Engineering a Sustainable Future – Wind Energy
Challenges and Opportunities of Heavy Engineering Industry
Latest defense technology: Air, land, and water
Automotive Question and Answers
PLM: Yesterday, today and tomorrow
9 Real World Applications of Augmented Reality
Manufacturing IOT trends
Manufacturing Automation through AI
The Smart Factory: A View from the Shop Floor
System Engineering
Advent of Radar Age in India
A Smoother Ride