Digital Engineering: Convergence of Disruptive Technologies

We constantly talk about next-gen manufacturing, Industrie 4.0, IIoT etc, but I think the underlying nervous system supporting all these is connectivity and convergence. Increased connectivity and computational power have converted hype to reality.  Previously Cloud, IoT, Artificial Intelligence (AI), Big Data and analytics were like nebulous concepts at boardroom discussions; but now they are mature enough and ready to be fully integrated into the design, engineering, and operational environment.   Digitalization is impacting every aspect of our lives because three forces are reinforcing one another: consumer pull; technology push; and economic benefits. This was the theme of the two-day NASSCOM 2017 edition of the Design & Engineering Summit for which ARC Advisory Group was invited. As per NASSCOM, the Engineering & Design industry is currently at $24 billion and is expected to reach $30-32 billion by 2020. Globally, the automotive sector is one of the major drivers of new technology adoption. India’s domestic industry also presents huge opportunities for digitalization in defense, infrastructure, digital, and skilling.

Disruptive Engineering

Due to globalization, design & engineering companies face increasing competition and major disruptions in their core products and business models. Manufacturing is moving from mass production to mass customization.  Many engineering companies are caught in an innovation/efficiency impasse: they have to significantly invest in new technologies while controlling costs.  The Summit addressed the transformation to Digital Engineering in this constrained environment; explaining how the convergence of disruptive technologies helps companies to fully capture the benefits of digitalization.  Digital transformation is happening from both sides: one is external and the second is internal – i.e. people should be quick to accept and adopt. The agenda framework was constructed on three pillars: digital enterprise, mobility, and software defined engineering.

The Technology Trio – Analytics, Automation, and Artificial Intelligence

Integrating disruptive technologies into a well-established engineering company with a proven business model raises significant challenges – a seemingly impossible task. However, many leading players have made the move and are now experiencing the benefits of the technology trio: Analytics, Automation and Artificial Intelligence (AI).  Engaging an audience of about 700+, various topics were discussed: supply chain complexity, the role of robots in powering e-commerce and supply chains, intelligent automation, connected mobility etc. In this context, the speakers highlighted co-robots, soft robots (with flexible hands), and learning robots, on demand fabrication with 3D printing.  ARC found the session on AI – master or servant, particularly interesting. It is necessary to first understand the future role of AI for your organization: What are the main applications of AI? We learned that AI is a product of a number of cognitive technologies: computer vision, machine learning, natural language processing, planning & scheduling, speech recognition, rules based systems, robotics, and optimization. Statistics reveal that cognitive systems and AI will drive revenue from $8 billion in 2016 to $47 billion in 2020.  Some experts found that more than 60 percent of current occupations will see ~30 percent increase of automation in the future; but only 20 percent of the organizations have the necessary skillsets to successfully utilize AI.

I agree with the speaker who said that “In a digital world, one of the biggest risks is not taking risks.” However, the speaker explained that for traditional engineering companies it is not easy to achieve their digital transformation as the main bottleneck is often the lack of a strong and integrated corporate management.  Autonomous vehicles, connected cars, flying cars, connected electric scooters and shared mobility – all of which are clean and smart – are driving innovations in the automotive sector. Today’s car has the computing power of 20 personal computers, features about 100 million lines of programming code, and processes up to 25 gigabytes of data an hour.  Global companies are investing in operating systems for connected vehicles, opening a range of new consumer services and vehicle management features. These companies have the potential to significantly change not just the car itself, but how the entire industry operates.

Continuous Learning Artificial Intelligence

Through continuous learning AI will help address challenges in these sectors:

• Healthcare: Ability to protect the outcome of drug treatment
• Climate change: Predict climatic disaster
• Food security: Optimize water use, improve crop yield, avoid wastage
• Protection of nature: Energy management, reduction of pollution, afforestation

Events such as this one reiterate the fact that all stakeholders – suppliers, users, and competitors have to embrace digitalization or prepare for extinction.