Predictive maintenance is the most recent technique in maintenance engineering. Machine operational parameters are used to assess the health of equipment and decide on maintenance schedule. In Aviation, aircraft engine manufacturers continuously monitor their engine parameters in flight to evaluate performance and deviations from normal.

Application of AI in this field enables measurement of behavior that is not observable using traditional means. AI based monitoring provides the edge required to operate in Industry 4.0 where connected machines do away with buffers in between processes and any unscheduled downtime of one machine effects the entire production chain.

This demonstration will walk you through the development of AI models using IoT data for one of the largest metal manufacturing company in India. It will help you master different types of AI models to answer questions like

• When do I plan the maintenance of a given equipment?
• Will a component last till the next maintenance cycle or do I replace it during the current maintenance?
• How to identify faulty equipment in the long production line?

Reinforcement learning helped Google's "AlphaGo" beat the world's best Go player. Have you wondered if you too can train a program to play a simple game?

Reinforcement learning is a simple yet powerful technique that is driving many applications, from recommender systems to autonomous vehicles. It is best suited to handle situations where the behavior of the system cannot be described in simple rules. For example, a trained reinforcement learning agent can understand the scene on the road and drive the car like a human. In supply chain management, RL agents can make decisions on inventory ordering.

In this talk, I will demonstrate how to train a RL agent to a) cross a maze and b) play a game of Tic-Tac-Toe against an intelligent opponent c) act as a warehouse manager and learn inventory ordering; with the help of plain python code. As you participate in this talk, you will master the basics of reinforcement learning and acquire the skills to train your own dragon.

Early warning systems play a key role in multiple business contexts – they could help prevent injuries/deaths at construction sites, predict equipment failure in advance, or determine when a customer is likely to churn. While traditional data analytics approaches to building early warning systems have relied on structured data, new techniques are emerging that use artificial intelligence algorithms on unstructured data – which could be in the form of text, speech, audio, video, etc.

As you participate, you will learn how existing infrastructure can be coupled with AI algorithms to deliver improved safety & performance in different business scenarios.