- Principal Sponsor
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Theme: Atmanirbhar Bharat - Artificial Intelligence – A unique Synergy between IT and Defense
CSI-BC has been pioneering to bring the various DRDO labs and the defence services together over the years by organizing
the Conference on Information Technology in Defence (ITD) annually. The last one was held in December 2020 on the
theme IT in Defense Manufacturing. In this edition, the theme chosen is Atmanirbhar Bharat - Artificial Intelligence – A
unique Synergy between IT and Defense.
Speakers Profile Conference on IT in Defence – 2022 (ITD-2022)
Topic: Digital Manufacturing Transformation Approach for Defence Industry
THE MANUFACTURER OF THE FUTURE WITH INDUSTRY 4.0
- Today design and engineer with a variety of isolated systems. In future that's going to be an integrated system engineering across the entire product lifecycle for faster optimum new product introductions.
- Today rigidly sequenced the manufacturing on a production line. In future that's going to be an integrated manufacturing systems capable of producing lot-size-one.
- Today remotely service the aftermarket product. In future that's going to be a service marketplace and circular economy for product as a service business model.
To transform the manufacturers towards Industry 4.0, as a Chief Executive Officer I drive Maxbyte as the technology partner for life for the Manufacturers with whom we jointly define the future, successfully deliver solutions, systematically transform and ensure incremental business value along the journey.
Qualification: ME - Product Design & Commerce,
PSG College of Technology
Specialities: Industry 4.0, Entrepreneurship
Engineering, Manufacturing, Aerospace, Defence, Industrial, Production Jobs Network
Ramshankar has 14 honors 14 Honors & Awards
- BEST START-UP in Manufacturing Sector - CII STARTUPRENEURS 2017
- Young Alumni Award - YAM
- Best Trainer Award for Effective Training to the PLM/CAD Users
- Night on the Town Award - 2009 for building good rapport between the users, for driving team to improve knowledgebase on design & analysis process, for identifying the gaps & needs on the existing process/practices
- Night on the Town Award from GE Aviation Quality Leader for coordinating & conducting ISO QMS internal audits and creating ISO awareness across 150 tools projects
- Night on the Town Award – 2009 for the best Volunteer on Engineer’s Engineer initiative
- Process Excellence Award - 2008 for the strong contribution in design, development and deployment on time by close interaction with the global and local end users and for the positive feedback on the process from the end-users and functional owners
- PProcess Excellence Award - 2009 for executing the “NX-ANSYS custom load extraction process on configuration hardware interfaces”
- Process Excellence Award - 2009 for the NX custom tool development which produces increased annual productivity saving for GE Rail Engine sheet metal manufacturing process
- Process Excellence Award - 2010 for executing the “Proposed, lead & transform ideas to action: in NX-ANSYS integration projects
- Process Improvement Award for the Windchill-CAD Process Efficiency Improvement through Six Sigma DMAIC
- Rock star Innovator an ERW2010 Engineering Excellence Nominee award in the GE Aviation Recognition Event at JFWTC Bangalore
- Say Thanks Award – 2010 for the new tools release newsletter implementation. Received a SHOT (Show n Tell Micro Innovation) Award – 2010 for the new process release newsletter idea and being leverage across all the teams
- Young Achiever Nominee in ERW2010 - GE Aviation Recognition Event at JFWTC Bangalore
Ramshankar has 12 publications 12 Publications
- Intelligent Analytics for Factory Energy Efficiency
- Digital Twin of an Automotive Brake Pad for Predictive Maintenance
- Industry 4.0 Transformation Approach
- Digital Manufacturing Adoption Strategy for Faster IIoT ROI
- Digital Transformation Journey Methodology for Industry 4.0 Implementation
- Best Practices in Multi to Single MCAD Transition
- Pre-requisites for Interactive Electronic Technical Manual (IETM) Technology Implementation
- Proof of concept of Industrial Internet of Things (IIoT) in Corrugated Cardboard Packaging Industry
- Design & Analysis of Aircraft Engine Configuration System by CAD-CAE Integration
- Dynamic Characteristics of Drop-substrate Interactions in Direct Ceramic Ink-jet Printing using High Speed Imaging System
- Automated Machine Shop Monitoring System
- Machine Shop Monitoring System - Virtual Instrumentation & Microcontroller Based Approach
Prof. Bharat Jayaraman
University at Buffalo (SUNY), NY
Topic: Formal Methods in Artificial Intelligence – a Brief Overview
Formal Methods are concerned with logic and mathematical specifications as well as automated (or semi-automated) methods of verification, and are especially important for safety-critical applications, such as avionics. As Artificial Intelligence (AI) and Machine Learning (ML) are being increasingly used in such applications, there is a corresponding need for rigorous guarantees on their correctness. AI- and especially ML-based software are developed in a very different way from conventional software, and pose new challenges in proving their correctness. This talk will give an overview of this subject including the current state-of-the-art and future directions.
Bharat Jayaraman received his B.Tech and M.Tech degrees from the Indian Institute of Technology, Chennai, and his Ph.D. in Computer Science from the University of Utah (1981). He was on the faculty at the University of North Carolina (Chapel Hill) before joining the University at Buffalo (SUNY) in 1989. Presently he is a Professor Emeritus at the University at Buffalo. Starting this year, he has assumed the position as Dean of a new School of Computing being formed at Amrita University. Dr. Jayaraman has published over 100 scientific articles and has served as Editor for Springer’s Transactions on ICT, the Computer Journal, published by Oxford University, and the Journal of Functional Logic Programming. He has also been active in fostering joint educational partnerships between US and Indian institutions.
Dr. Vinay Jammu
VP-Physical-Digital Technologies, GE
Topic: Digital Twins for Digital Transformation
Over the past few decades, dramatic improvements in communication and computing technologies have driven the growth of consumer internet which has improved efficiencies, increased customer base and created new business models in many industries including retail, banking, hospitality, and transportation. A confluence of these technologies is rapidly changing the landscape of what is possible in industrial internet area as well including power, transportation and healthcare industries by driving new outcomes and efficiencies that were not possible before. For example, 1% fuel saving in airline industry today is worth $30B over the next 15 years in the industry.
This talk will focus on Digital Twin technologies GE is driving for Digital Transformation of industries to improve efficiencies of industrial assets by bringing together sensing, inspection, control, prognostics and optimization. Digital Twins are live personalized learning models of different assets that assist in improved decision making related to operation and maintenance of these assets. For example, Digital Twins models of turbine system in GE90 engine are used to optimize maintenance saving tens of millions of dollars in unnecessary overhauls. In manufacturing, Digital Thread and Digital Twins are being connected to reduce cycle time and improve manufacturing productivity.
Vinay Jammu is the VP-Physical-Digital Technologies at GE Digital based at the John F Welch Technology Organization, Bangalore. He is responsible for strategy and execution of domain-based analytics and software to differentiate GE’s Industrial Internet Solutions. Before this role, Vinay was Technology Director for Software and Analytics in GE Research where he spent 23 years driving physical-digital technologies.
Vinay obtained his doctoral degree from University of Massachusetts, Amherst in 1996 in Mechanical Engineering with specialization in applications of Artificial Intelligence (AI) for machine prognosis. After a brief stint at Mechanical Technology Inc, NY, he joined GE Global Research, Schenectady, NY in 1997 as Diagnostics Engineer where he focused on developing predictive analytics for failure and life prediction of industrial assets. Vinay relocated to Bangalore in 2002 and held multiple roles as Lab Manager, Technology Leader and Technology Director for Aero-Thermal and Mechanical Systems as well as Software and Analytics organizations in GE Global Research. Vinay is a certified master black belt, has 40 patents applications, and 60+ internal and external publications.
Mr. Sagar Verma
Researcher at TCS
Topic: Improve - Optimizing Energy and Comfort in Buildings based on Formal Semantics and Reinforcement Learning
Heating, ventilation, and air-conditioning (HVAC) system’s supervisory control is crucial for energy-efficient thermal comfort in buildings. The control logic is usually specified as ‘if-then-that-else’ rules that capture the domain expertise of HVAC operators, but they often have conflicts that may lead to sub-optimal HVAC performance. We propose EImprove, a reinforcement-learning (RL) based framework that exploits these conflicts to learn a resolution policy. We evaluate EImprove
through a co-simulation strategy involving EnergyPlus simulations of a real-world office setting and a formal requirement specifier. Our experiments show that EImprove learns 75% faster than a pure RL framework.
Sagar Verma is a researcher at TCS-Research, is a member of the Foundations of Computing research area. His research area lies in replicating human-like mental ability to computer programs and algorithm analysis. Currently, he is part of a team that works on AI-driven techniques to learn playing games, involving decision-making and information sharing. He received his Bachelor of Technology from the Indian Institute of Technology, Patna.
Dr. Ramakrishnan Raman
Principal Systems Engineer, Honeywell
Topic: Machine Learning Models for Behavior & Performance Predictions in Complex Airborne Systems