Manufacturing Boost for AI Talent

Manufacturing Boost for AI Talent

Increasing use of AI and automation during the pandemic has boosted opportunities for human talent too, as manufacturing sector records a 20-year high in job openings

The pandemic has helped artificial intelligence (AI) make significant inroads into the manufacturing sector, with adoption almost increasing by over 25% in the last 24 months. This is remarkable as manufacturing has been a little slow off the mark in leveraging AI. According to 451 Research’s Voice of the Enterprise: AI & Machine Learning, Use Cases survey, 60% of manufacturing respondents have AI in production or proof of concept at their organization – an increase of 25% over the past two years.

This surge in adoption, across the entire value chain of manufacturing, has in part been accelerated by the pandemic, as organizations have invested in automation and computer vision technology to augment remote workers and maintain plant operations with fewer personnel on the floor. Data from the US Bureau of Labor Statistics for May shows that current job openings in the manufacturing sector are at their highest level in more than 20 years.

When the pandemic hit, manufacturers had to act quickly to maintain operations and preserve their bottom line. Despite past scepticism, AI integration has demonstrated immense value in addressing these concerns and is now seen as an investment for the future. According to the survey, 87% of manufacturing respondents indicated that they have or will invest in new AI initiatives in response to COVID-19.

One of the most adopted use cases has been leveraging artificial intelligence in workplace screening and safety, driven primarily by the pandemic. It’s possible to use AI to identify employees, conduct thermal screenings, or to monitor employee interactions for contact tracing and facility sanitization. The same technologies have also led to long-term solutions associated with workplace safety events before they happen or speeding up post-incident root cause analysis (for example, think slips, trips, and falls). These solutions lead to healthier employees, a safer workplace, and continued operations.

With an ever-increasing number of devices and limited cybersecurity resources, we are leveraging artificial intelligence to help tackle the most considerable cybersecurity challenges. Operational technology environments produce massive amounts of security logs and data, along with their respective networks, security appliances, and applications. Artificial intelligence can help sift through the noise and assist by autonomously detecting intrusions, malware, fraud, employee behaviours outside normal baselines, and ultimately elevating threat intelligence.

There is opportunity for AI integration across the entire value chain in the manufacturing process – be that planning a new product, monitoring the production line, or even helping with maintenance and equipment scheduling. According to the survey 43% of respondents in the manufacturing space deploy AI for quality assurance (QA). This was the top use case in 2020 and remains so in 2021. QA is a critical part of the manufacturing process – not only for maintaining consistency in products, but also for catching defects and deficiencies that could have serious safety repercussions.

Predictive maintenance is another common use case for AI in the manufacturing space, and according to our data, is the fastest-growing use case over the next two years. Predictive maintenance is the tracking and monitoring of equipment condition to identify issues early on and predict equipment failure. By doing this, manufacturers can either schedule maintenance to correct issues ahead of time – extending the equipment’s functional life – or order a replacement before it fails to minimize downtime.

© 2024 Praxis. All rights reserved. | Privacy Policy
   Contact Us