AI in Manufacturing Sector

8.45 am to 12.30 pm CT,
24 September 2021

AI-driven manufacturing

presents manifold advantage

AI-driven defect detection

improves quality by orders of magnitude

AI-driven assembly line optimization

enables real-time inspection of the finished product

Innovation in design is

facilitated by AI algorithms and Generative Design

AI facilitates deployment of

predictive maintenance to minimize downtimes

AI can fulfill employees by

shifting tedious tasks to machines through automation.

AI drives quality, efficiency, and innovation within manufacturing.

AI-driven technologies are paving the way for the ‘smart’ manufacturing sector of tomorrow.

AI within manufacturing increases precision of defect detection.

AI cuts down on quality control times in manufacturing

AI and IoT together pave the way for a plethora of automations.

AI can facilitate the designing of new products

AI saves manufacturers countless hours by minimizing false positives

AI-driven image processing algorithms facilitate real-time validation of products

AI facilitates assembly line optimization by proactively managing equipment breakdown

Generative design algorithms explores all permutations of a solution and leverages ML to evaluate each iteration.

Amazing Partners & Sponsors


24 September 2021 (8.45 am to 12.30 pm CT)
08:45 am
Aganda 1

Introduction of Speakers

-by Nitin Naveen, Vice president-Innovation Strategy, AICorespot


09:00 am
Aganda 2

Leveraging Data and Analytics to drive profitable growth

-by Deepak Jose, Director, Demand Analytics Mars Digital Technologies

  • Introducing the global digital transformation journey at Mars
  • How does Mars leverage Advanced Analytics to build capabilities?
  • Why is it important to build capabilities to break organizational silos?


09:20 am
Aganda 4

Reducing Inspection Errors, Costs, and Risk with Hybrid AI

-by Jonathan Hou, President, Pleora Technologies​

Manufacturers and brand owners navigating through the complexities of AI are left with a few key questions. How can AI reduce errors and automate manual tasks? Is algorithm training expensive or complicated? Can I keep existing infrastructure and processes?
This session will introduce hybrid AI, a unique approach that merges the best of computer vision and machine learning to address these key concerns and allow manufacturers to deploy advanced end-to-end quality inspection. We will look at how AI addresses critical quality challenges to increase profitability and reduce risk. We will then outline hybrid AI algorithm training and deployment strategies for automated inspection systems, and opportunities to add decision-support to manual tasks. We’ll close the session with a case study on how a consumer brand is deploying hybrid AI today while also preparing for more advanced Industry 4.0 and IIoT automation.


09:40 am
Aganda 4

Artificial Intelligence Toolbox For Industrial Control

by Arthur Gooch, Director of Innovation, Andritz Automation

Optimization of industrial processes requires a broad range of artificial intelligence approaches. With the ultimate objective of having fully autonomous manufacturing, we will look at the different categories of problems and show how a diverse set of approaches is necessary to solve the automation challenges that exist in modern facilities. Successful machine learning applications are focused on specific objectives, rather than being a general AI operator for a facility. Implementation combines existing industry standard techniques with artificial intelligence components. We will show an example of how a machine learning enabled tool can solve a practical automation problem without the user needing any significant data science knowledge.


10:00 am
Aganda 6

Digital Innovation in Supply Chain

by Harshad Kanvinde, Global Practice Head – Supply Chain, Slalom

Supply chain agility is no longer a luxury, rather, it is an imperative to sustainably drive business growth and address disruptions. Digital Innovation done right is necessary to achieve agility i.e. flexibility, responsiveness, speed in supply chain. In this keynote, Harshad Kanvinde, leader of Slalom’s Supply Chain Practice, talks about how Digital Innovation is helping manufacturing companies achieve agility, what are the best practices to get the most out of your digital investments, and the common pitfalls to avoid..
10:20 am
Aganda 8



10:30 am
Aganda 7

What will be the future of AI for Manufacturing

Panel Discussion
Chithrai S Mani, Chief Technology And Innovation Officer, Infovision (Moderator)
-​ Helenio Gilabert, Sr. Director, Edge Solutions Industrial Automation Business, Schneider Electric (Moderator)
– ​Brandi Lafontaine, VP & Chief Data Officer, OvareGroup
– ​Jamie Smith, VP of Products, Aver
– ​Jordan Lapp, Head of Product, Teck Resources Limited


11:30 am
Aganda 6

Optimizing Manufacturing with Artificial Intelligence

by Jim Wilmot, Product Marketing Manager, Siemens

Artificial Intelligence is making huge strides into various industries and applications across the board in the manufacturing environment – enabled by digitalization and specifically driven via powerful tools like edge devices and cloud computing, AI is proving to be an effective solution for maximizing production in a large variety of manufacturing applications. This presentation will highlight several real-life, running applications in the areas of quality control and robotics where AI is currently being used effectively to optimize processes and handle challenging, complex control tasks.


11:50 am
Aganda 6

Fusing Artificial Intelligence with Equipment Monitoring for Manufacturing Optimization

by Dr. Yen Chi Chang, Founder & CEO, Mata Inventive

Dr. Yen Chi Chang will be speaking about how artificial intelligence can revolutionize and improve manufacturing processes, increase productivity and efficiency. A demonstration will be performed to show how Mata Inventive’s technology can monitor profitability, reveal delay reasons and act on future productivity. By installing MATA’s machine monitoring solution, shop floor performance is more transparent. Through the MATA dashboard and user application, supervisors can understand daily/weekly/monthly status while machinists can know their utilization performance and report status. In this talk, Dr. Yen Chi Chang will demonstrate the MATA solution in action and as well as presenting a case study of how big companies benefit from it. In fact, with Glen Air and Mata Inventive’s solution, there is a 40% increase in the utilization of an 8-hour workday, leading to 3.2 hours more in productivity, which means $960K worth of more production per year. Through this talk, Dr. Yen Chi Chang will delve into the goals, problems, and approaches towards these successful results.


12:10 pm
Aganda 7