MathWorks, the leading developer of mathematical computing software for engineers and scientists, successfully concluded the 8th edition of its annual conference, MATLAB EXPO. The EXPO featured presentations and workshops by MathWorks technical professionals and customers on a broad range of topics and applications of MATLAB and Simulink.The Key take away from the expo and conference may be derived as: MATLAB makes AI easy and accessible for engineering science, MATLAB integrates AI with “everything else”, and MATLAB AI deploys to both cloud and embedded.
The panel was headed by Michelle Hirsch, Technical Manager, MathWorks India, and discussed the subject, “Are You Ready for AI? Is AI Ready for You”? While Prashant Rao, Technical Manager, MathWorks, India discussed as ‘What’s New in MATLAB and Simulink R2018a’.
The EXPO brought together engineers, scientists, and researchers to learn more about MATLAB and Simulink. The exhibition area showcased solutions from MathWorks partners.Engineers from Honda, NXP, L&T Technology Services and Tata Steel presented their success stories about how MATLAB and Simulink are helping them innovate and address today’s most difficult engineering challenges.
Michelle Hirsch presented the keynote address entitled ‘Are You Ready for AI? Is AI Ready for You?’She said that, “We are happy about the success of MATLAB EXPO 2018 in all three cities. At the time when companies are preparing for 4th industrial revolution, such events serve as a venue for innovators, scientists and industry experts to come together and explore the latest in technology solutions. This year, more than 2,500 MATLAB and Simulink users gathered at the exhibitionthat signifies the growing customer base in India.”
Hirsch said that the main differentiator of MathWorks products in artificial intelligence is that MATLAB can be used in stages of data analysing, model development and deployment. She said that MathWorks generated $1 billion dollars in revenue in 2017 and around 3 million users globally. Hirsch also informed that MathWorks is currently working with over 5,000 universities and 1000 schools worldwide of which 87 are in India.
Prashant Rao, Technical Manager, MathWorks India, leads a team of customer-facing engineers encompassing the application engineering, pilot engineering, and customer training roles. By applying industry and application expertise across numerous domains, Prashant and his team work with customers to enable the adoption of MATLAB and Simulink products for technical computing and Model-Based Design. PrashantRao said that the long-term vision of all MathWorks products was to make Artificial Intelligence accessible and easy, build products that are simple to integrate with everything else and create easy-to-deploy tools which can be used in both cloud and edge-based computing scenarios.
Sunil Motwani is working as Industry Director, MathWorks India, managing sales related activities for commercial customers in India. Motwani informed that, “Within this community of engineers and scientists, our tools are used by automotive, aerospace &defence industries. We also have industries like industrial automation, communication electronics, semiconductor, finance (our tool are used to build financial models).”Motwani mentioned that the main focus is in the areas of image processing, automated driving, data analysis and predictive maintenance. Motwani also informed that MathWorks caters to the broad range of companies ranging from manufacturing, IT services companies to the banking sector. Researchers and students are growing segment of users who are adopting MathWorks products.
Case Studies: Automotive:
Bosch eBike Systems Develops Electric Bike Controller with Model-Based Design By using Model-Based Design with MATLAB and Simulink to design drive and motor control subsystems, run simulations and tests, and generate prototype and production code in order to develop the control system for an electric bike within a tight schedule.
Delphi Develops Radar Sensor Alignment Algorithm for Automotive Active Safety System by using MATLAB to develop the algorithm and use MATLAB Coder to generate production C code to deliver a production automotive radar sensor alignment algorithm in four weeks.
Toyota Front-Loads Development of Engine Control Systems Using Comprehensive Engine Models and SIL+M by using MATLAB products Toyota developed a comprehensive engine model and combine it with SIL+M testing to front load the development process to Accelerate the development of complex engine control system software.
Industrial Automation:
ASML Develops Virtual Metrology Technology for Semiconductor Manufacturing with Machine Learning using MATLAB to create and train a neural network that predicts overlay metrology from alignment metrology.
Mitsubishi Heavy Industries Develops Robotic Arm for Removing Nuclear Fuel Debris: Mitsubishi solved the challenge to design a multi-axis robot for removing molten fuel debris from the Fukushima Daiichi nuclear power station by using MATLAB and Simulink to perform hardware measurement tests and to model and simulate individual robot axes and controllers.
Clearpath Robotics Accelerates Algorithm Development for Industrial Robots: Their challenge was to shorten development times for laser-based perception, computer vision, fleet management, and control algorithms used in industrial robots, MATLAB gave the solution to analyze and visualize ROS data, prototype algorithms, and apply the latest advances in robotics research. Consequently data analysis time cut by up to 50%, customer communication improved and cutting-edge SDV algorithms quickly incorporated.
Energy Production:
OMRON Develops Solar Inverter Control Algorithm for Anti-Islanding Control: Omron overcome the challenge to develop a control system to ensure the safe operation of solar power generation systems during power outages by using Model-Based Design with MATLAB and Simulink to model electrical power and control systems, run simulations, and analyze the systems’ response to outages.
Shell Geologists Develop and Deploy Software for Predicting Subsurface Geologic Features: Overcome the challenge to reduce oil and gas exploration costs and increase well production by constructing accurate models of the subsurface by using MATLAB to develop and deploy algorithms that use seismic data, known scaling relationships, and a database of geologic metrics to quantitatively characterize subsurface features through a MATLAB application.
Biotech Pharma:
Lund University Develops an Artificial Neural Network for Matching Heart: Transplant Donors with Recipients to address the speed and reliability challenges, Lund University researchers developed their initial ANN model using MATLAB and Neural Network Toolbox. To find the optimal network configuration, they wrote MATLAB scripts that varied the number of hidden nodes used in the network for a range of weight decay (or regularization) values.
