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This is just some announcement which people will want to pay attention to! Learn More

Webinar Recap: AI & Automation in Manufacturing After Covid-19

On June 17th 2020, CrowdANALYTIX CEO Divyabh Mishra and Festo Global Accounts Manager Jeff Hawkins got together online to discuss AI and automation in manufacturing in the wake of the Covid-19 pandemic. Manufacturing has been heavily affected by recent fluctuations in workforce and supply, with nearly 75% of companies reporting disruptions in their supply chains over the past few months. The impact of these disruptions is far-reaching with 16% of affected companies having adjusted their revenue targets downwards as a direct result. 

Although we have only recently begun dealing with Covid-19 and the fallout from its effects, companies must look at how they can adapt to the short-term and long-term changes necessitated by the pandemic, and how they can weather the uncertainty of more potential disruptions. 

Jeff and Divyabh focused on answering the questions:

  • What challenges is the manufacturing industry facing during the pandemic?
  • How could new technologies such as AI and Automation in general help manufacturing corporations to survive?
  • How can we deploy AI and Automation successfully?

Jeff focused on the aforementioned supply chain issues, which will be ongoing, but he also noted that large numbers of people are now working from home and may continue to do so. The dispersion of workforces has highlighted issues with aging infrastructure, especially internet access. Jeff noted that 5G access will likely become crucial as many employees either stay home for work or vacillate between home and their offices as the pandemic ebbs and flows across the globe. New AI technologies and remote technologies will make these sometimes rapid and unexpected changes possible, and help prevent catastrophic losses in productivity.

As far as AI and automation, Jeff sees potential uses for these solutions as manufacturers “re-shore” their production and bring new and changing workforces into their facilities. AI solutions can both take over some manual labor in the face of loss, such as during a rise in Covid-19 infections, and help train new employees to onboard quickly and speed production. Complex automation solutions can be run in advance and implemented remotely. 

He and his colleagues have, out of necessity, opened up new remote means of accessing their customers. They have learned to leverage online technologies in new-to-them ways that are beginning to become the norm. Customers feel secure in the knowledge that their systems can be accessed, updated, and repaired even during lockdowns. 

Jeff concluded that although the pandemic has caused major disruptions in manufacturing, it has also forced the industry to adopt new, better technologies and has uncovered improved solutions that went unnoticed in the past. 

Divyabh began by pointing out that long-term solutions the problems companies are facing now are crucial, because the issues caused by Covid-19 will not be going away any time soon. Recovery and the return to “normalcy” will be long processes stretching over years, not just a few months. Divyabh sees previously hands-on activities like monitoring and quality-testing going remote, but most businesses aren’t sure how to make the change to automated, hands-off versions of these crucial activities. This is why companies must begin the structuring of their data and the implementation of AI basics as soon as possible. Otherwise, their automated solutions won’t be ready before the next stage of the pandemic when they’re needed.

He then gave an example designed to illustrate the importance of automation in the current crisis, as well as the importance of establishing baseline readiness for AI. A CrowdANALYTIX cement manufacturer customer needed to reduce expensive waste by detecting the quality of their cement batches as early as possible. With early detection of low quality, corrections could be made in time to render the batch high-quality and usable. By structuring the raw data from sensors in the manufacturing process, the entire quality detection and correction process could be automated and even managed remotely. If the company had not begun with the process of structuring their data, they never could have reached the point of automated processes.

Divyabh concluded that manufacturers need to begin implementing AI immediately in order to achieve success against the challenges of Covid-19. By remaining open to new technologies and moving forward even in the face of uncertainty, manufacturers can avoid disaster and even grow their businesses in uncertain times.

If you’d like to hear Jeff and Divyabh answer more questions about AI automation in manufacturing, watch the full recording of the 30 minute discussion here

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