An Exclusive Interview with Dr. Shrikant Bhat, Senior Principal Scientist of ABB Group


An Exclusive Interview with Dr. Shrikant Bhat, Senior Principal Scientist of ABB Group



by Analytics Insight

December 9, 2021

When it comes to technology and robotics, ABB group stands out to be the biggest tech giant in this industry. From process automation, electrification to robotics, ABB has a wide range of services available. Its mission is to provide a high-quality standardization environment that is respected worldwide and is relevant to the market expectations.

Analytics Insight has engaged in an exclusive interview with Dr. Shrikant Bhat, Senior Principal Scientist of ABB Group.

 

1.Kindly brief us about Standards Association (IEEE SA). What mission and objectives of this body?

IEEE Standards Association (IEEE SA) is an organization that is focused on bringing together individuals and organizations to build consensus towards various standardization initiatives. Its focus is on nurturing, developing and advancing global technologies, through its parent body IEEE. Its mission is to provide a high-quality standardization environment that is respected worldwide and is relevant to the market expectations. IEEE SA members provide technical expertise and drive participation towards developing global standards in coordination with global, regional and national organizations from across the world.

In my personal experience, I witnessed a lot of flexibility and a very focused and results-oriented approach in dealing with IEEE SA. For this specific topic on Industrial AI, it took less than a couple of months to have a pre-standardization activity conceptualized and approved. The widespread network of IEEE SA also enabled easy onboarding of relevant industrial AI players to contribute to this initiative.It is only testimony to a very supportive environment within IEEE SA that we could formalize a new standardization project activity even within less than a year of initiation industrial AI pre-standardization project.

 

2.What is the current status of Industrial AI in the country? Please describe the need for standardization and its benefits.

With R&D centers for almost every multinational company having their presence in India and availability of the best of resources, India has a major role to play in this space. Bengaluru is also emerging as an Industrial AI start-up hub in India. There is an Industrial AI consortium that is facilitating interactions and collaborations between Industrial AI start-ups, large industrial giants, venture capitalists/incubators, and industry associations. With such dedicated focus and efforts from all the stakeholders, we do see a future promise of Bengaluru emerging as the global industrial AI start-up hub. As with the adoption of AI, the status in India is no different than the global scenario. Many industrial players are considering and piloting industrial AI applications and a few of them are on a path towards scaling-up such solutions. Here is where standardization has a major role to play.

Standardization helps in two aspects: 1) to baseline the performance and 2) to facilitate easy switchover for customers from one solution provider to another. In an industrial context, with so much hype around AI, it is very difficult to rationally compare and evaluate the impact of AI applications from two different service providers. Also, having identified an application better over the other, there are challenges in switching over. A standard approach will not only help customers, but almost every stakeholder in the AI ecosystem, as the expectations as well as responsibilities of every stakeholder will be rationalized facilitating ease of AI implementation and rapid scale-up. This will help in higher penetration of AI leading to its further evolution.

 

3.How is Industrial AI contributing to manufacturing and other industries?

There are two important areas where industrial AI is picking up rapidly – condition monitoring and logistics. These are areas where there is considerably more value to unlock as relatively higher value is at stake. Traditionally, this is being practiced based on approximations and rules of thumb derived from past experience. This is because it is beyond human comprehension to analyze the vast amount of data available and derive insights from that. AI becomes a natural choice to augment expert decision-making in such cases. However, as condition monitoring gets more commoditized, a new manufacturing value network spanning the entire manufacturing value chain will evolve involving suppliers as well as customers and AI will play an important role in tapping value for all stakeholders in the value chain.This is where the future of industrial AI holds the maximum potential and can create a radical impact

 

4.Tell us how your IEEE SA is working towards the standardization of Industrial AI? Also share insights about your role in the endeavor.

Most of the other ongoing AI-related developments are primarily targeted towards consumer AI. This is based on the maturity of consumer AI applications and considering the fact that big established players are involved in this. In this regard, the ongoing initiative from IEEE is very unique as this is solely focused on industrial AI. The whole idea of having a dedicated focus on Industrial AI was acknowledged by IEEE and this initiative was facilitated as a pre-standardization activity. Further, we approached many established industrial AI corporate players as well as start-ups and saw proactive support towards this initiative. With close collaboration between all relevant stakeholders that involve customers, industrial AI application and infrastructure providers, we are able to identify topics of common interest and conceptualize potential requirements of standardization. As I mentioned earlier, within less than a year of initiation of this project. we already have formalized one project IEEE P2975 focused solely on industrial AI data. There are other initiatives in the pipeline focusing on AI maturity, edge analytics, and explainability of industrial AI.

 

5.What are the key challenges you are facing while setting global standards for Industrial AI? How is the ecosystem addressing these challenges?

The major challenge was to create a separate niche from consumer AI. This initiative is a starting step towards that. Coming to specific challenges involved in Industrial AI standardization, we needed to clearly identify alignment with existing industrial automation standards. Note that analytics and AI have been widely practiced within the industrial automation context and have been around for a long time now. There are already well-established industrial automation standards that are quite mature and in practice. It is very important that we are well aligned with such overarching standards that govern industrial processes. To address this, the focus is on evaluating the existing standards and identifying specific gaps w.r.t. AI application and addressing these gaps through new or incremental standards.

Another important aspect, which is unique to Industrial AI, is the role of domain know how in realizing the benefits of industrial AI. This plays an important role in all lifecycle phases impacting engineering time for industrial AI applications. It is important to identify generic aspects related to domain and standardization targeting such focus areas will definitely bea definite value-add. For example, AI data is such a generic aspect, and as mentioned earlier there is an ongoing project, IEEE P2975, focussed on this.

 

How will a global standard for Industrial AI help the industry?

As explained earlier, standardization will help in rationalizing expectations and responsibilities amongst all stakeholders in the AI value chain. As advanced industrial applications are seamlessly traversing national boundaries solely driven by competitiveness, it is absolutely important to have well-established industry standards to unlock the true potential of industrial AI. There is much more potential of industrial AI to address the value chain aspects in the industrial sector beyond condition monitoring and logistics. We are looking at exponential penetration of industrial AI and standardization will be one of the important vehicles to enable scale-up and further evolution. I will request all stakeholders active in Industrial AI to come forward and contribute to this initiative.

Shrikant Bhat

Senior Principal Scientist, India – Corporate Research Center, ABB Group and Chair of the IEEE SA Pre-Standardization Activities on Industrial AI Industry Connections Program

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