INFORMS Business Analytics Conference 2021
Event Details
DATE:
April 12th 2021 8:00 AM CDT - April 14th 2021 4:00 PM CDT
April 12th 2021 9:00 AM EDT - April 14th 2021 5:00 PM EDT (America/New_York)
HOW TO REGISTER:
Registration for this event has closed.
About INFORMS Business Analytics Conference
INFORMS Business Analytics Conference is an annual event connecting hundreds of leading analytics professionals and industry leaders. This year, the conference will be virtual, from April 12-14, and will bring together over 800 analytics experts to explore best practices and share insights into groundbreaking applications, including healthcare, robotics and AI, data ethics, and the role of data science in the media and workplace.
As a leader in the digital transformation of the industrial space, Engineering Group is committed to delivering technology solutions that help our customers harness the power of data in order to optimize their processes, monetize the data coming off their production floors and drive continuous improvements in their supply chain, manufacturing operations and business processes. Engineering Industries eXcellence will be sponsoring INFORMS Business Analytics 2021, and a number of our Digital Twin, Simulation, Machine Learning and Data Science experts will be speaking at the event. Join us!
Join Engineering Industries eXcellence & Pathmind Online
With one of the few technology practices in North America dedicated to industrial simulation and some of the top Industry 4.0 experts in the world leading it, Engineering Industries eXcellence has something valuable to offer in terms of knowledge and experience in this space. Make sure to join Engineering Industries eXcellence and partner Pathmind’s sessions at INFORMS Business Analytics 2021.
Session 1:
Deep Reinforcement Training and Machine Learning Applications for Industry 4.0
Type: Professional Presentation
Speaker: Luigi Manca
Track: Machine Learning
Date/Time: Tuesday, April 13, 3:35-4:15pm EDT
Summary: Making the right decision now by considering all possible implications in the future is not an easy task. Digital Twins are useful support tools for exploring the potential impact of findings from a systemic perspective. They leverage simulation modeling techniques and usually rely on heuristics to replicate the behavior and logic of how systems evolve. But when it comes to searching for an optimal solution, especially when the goal is many decision steps in the future, there is a need to explore the solution space. Without an automated approach, this can be nearly impossible; mathematical optimization techniques can be compelling, but they are extremely difficult to implement when dealing with long-term decision-making and an environment rich with uncertainty. In this space, Deep Reinforcement Learning (RL/DRL) is gaining attention. Why? Because it can deliver a policy for sequential decision-making for even the most complex, non-linear environment. The two real cases presented aim to highlight the benefits that a DRL policy can bring with respect to established heuristics. In the first case, we explore the application of DRL for identifying an optimal Operations & Maintenance strategy for a wind farm equipped with Prognostics & Health Management capabilities. In the second case, we explore how the application of DRL methodologies enables a Food & Beverage distributor to make smarter decisions about production order sequencing, reducing processing time by 16%. Click here to learn more about this session.
Session 2:
Solving Complex Business Problems with Simulation and Pathmind AI
Type: Technology Showcase
Speakers: Luigi Manca, Sahar Esmaeilzadeh
Date/Time: Monday, April 12, 10-10:40am
Summary: Engineering Industries eXcellence presents technology partner Pathmind. Businesses using simulation modeling to solve problems need an optimization method capable of handling the complexities and variability of real-world operations. When traditional optimizers and heuristics underperform, Pathmind’s AI can help. Using a branch of AI called reinforcement learning (RL), Pathmind can beat your heuristic and offer new insights into speed and profitability. Pathmind makes it easy to adopt Reinforcement Learning, even for teams without AI experts or experience with neural networks. During this showcase, you will learn key RL terms, examine how Pathmind RL is implemented in a model, see the steps of uploading a model to Pathmind and training an AI policy, and compare how a Pathmind AI policy performs against the heuristic. All attendees will be invited to create a free Pathmind account. Click here to learn more about this technology showcase.
Session 3:
Harnessing Deep Reinforcement Learning to Coordinate Automated Guided Vehicles
Type: Professional Presentation
Speaker: Johnny Davenport
Date/Time: Monday, April 12, 1:45-2:25pm EDT
Summary: Pathmind presents a deep reinforcement learning (DRL) policy that was trained to control a fleet of Automated Guided Vehicles (AGVs). The policy determines the loading and drop off tasks of AGVs as they move products through a factory. The goal of the policy is to maximize product throughput. Notably, the policy shows a 50% improvement in throughput over a shortest-queue heuristic, while lowering the AGV utilization by 15%. We attribute the improvement to the policy’s intelligent management of congestion. Interestingly, the policy chooses to “hide” AGVs away from the center of the factory floor, resulting in lower AGV utilization and lower congestion. This presentation will detail the adaptation of the AGV simulation as a DRL problem, the policy training process and the quantitative results. Additionally, we will discuss how the same workflow can be readily applied to a variety of other use cases. Click here to learn more about this session.
