Watch: Connected factories, predictable futures
By AMS2022-05-25T17:42:00
This AMS livestream explores how Ford, Fraunhofer IPA and other OEMs are advancing smart factories to optimise assembly lines, improve quality and reduce errors, leveraging connected data for digital twins and AI-driven manufacturing planning.
Updated on June 30, 2022 with on-demand video.
Connected technologies are unlocking a new era of digital production, with better planning capabilities, greater flexibility and focus on improving quality and reducing errors. Automotive manufacturers are investing in greater connectivity of equipment, facilities and production schedules, with the aim to gain more control, visibility and predictability across the complex ecosystems in which they operate.
In this AMS livestream, Ford’s Balakrishnan Adhi, who leads MP&L plant operations for the company’s International Group, shares insights on how manufacturers are increasingly gaining a competitive edge by analysing data at the edge and in the cloud to improve product quality, operations and implement predictive maintenance, for example. Alexander Neb, an automation specialist from the Fraunhofer Institute for Manufacturing Engineering and Automation (IPA), discusses how manufacturers can use AI to automate processes such as assembly planning, which is typically done manually. Slides from these expert speakers are available for download.
Learn more about how manufacturers are using connected technologies to advance their digital maturity by analysing data and optimising production, whether it’s a machine on the assembly line, materials, or the workforce operating the plant. The connectivity and digital transformation of automotive manufacturing methods are creating new opportunities in automation, robotics, machine learning and software solutions.
Speakers
-
Dr. Balakrishnan Adhi, Vice-President of MP&L Plant Operations, Material Flow and Packaging Engineering, International Markets Group, Ford Motor Company
-
Alexander Neb, Project Manager, Production and Automation Technology, Department of Robots and Assistive Systems, Fraunhofer IPA