Survey: How to use AI to identify, improve manufacturing production goals

A study of 500 global manufacturers identified top production goals when applying artificial intelligence (AI) and suggests how to better reach those goals. Other topics include challenges, roadblocks, sustainability, workforce, technology among others.

ByMark T. Hoske July 17, 2023
Courtesy: Augury

Learning Objectives

  • Understand data from an Augury survey that explains how artificial intelligence can identify and improve manufacturing production goals. The resulting study also covers manufacturing production topics include challenges, roadblocks, sustainability, workforce, technology among others.
  • See links to 33-page Augury study, “The State of Production Health, 2023” and a related webcast in the article.

AI production goals insights

  • Survey from Augury explains how artificial intelligence can identify and improve manufacturing production goals. The resulting study also covers manufacturing production topics include challenges, roadblocks, sustainability, workforce, technology among others.
  • Article links to 33-page Augury study, “The State of Production Health, 2023” and a related webcast.

Manufacturers’ top production goals in terms of AI usage are improving quality, yield and throughput (33%) and managing cost of materials/energy (31%), according to the 33-pageAugurystudy, “The State of Production Health, 2023,” which had 500 responses.

The study looks at how manufacturers are leveraging machine, process, and operational data to address production challenges, roadblocks to 2023 goals, sustainability efforts, workforce trends and technology implementation issues, among other areas.

The next four manufacturing production goals for AI use were closely grouped:

  • Reducing unplanned production downtime (28%)

  • Optimizing asset care (28%)

  • Empowering data-driven leadership strategy (28%)

  • Upskilling the workforce (27%).

Other responses, see bar chart, were: Streamlining supply chain visibility (25%), meeting production targets (23%), improving capacity (22%), breaking down department silos (21%) and meeting sustainability/ESG/regulatory targets (21%).

Leading manufacturing production goals for using artificial intelligence software are improving quality, yield and throughput (33%) and managing cost of materials/energy (31%), according to the 33-page Augury study, “The State of Production Health, 2023.” Courtesy: Augury

Leading manufacturing production goals for using artificial intelligence software are improving quality, yield and throughput (33%) and managing cost of materials/energy (31%), according to the 33-page Augury study, “The State of Production Health, 2023.” Courtesy: Augury

Ability to use AI to solve manufacturing production challenges

The survey also asked manufacturers to rate their ability to specific production problems using AI. While 35% of respondents said they were advanced, and 52% consider themselves “moderately advanced,” Augury suggested “confidence is at odds with their lack of ability to quantify the business impacts of AI.” While manufacturers “might be embracing AI,” Augury said, “many are getting only a fraction of the full value from their investment. With the top quantifiable capability being optimizing supply chain management (only cited by 25% of companies), a lot of AI capabilities and benefits are being left on the table. Just 21% say that they can quantify their ROI [return on investment] when using AI to improve overall production health.”

Optimism continues, however. A question about the future of the manufacturing industry included AI in the leading reply. 31% said AI and advanced technologies will help create new jobs in the manufacturing industry.

More information about improving manufacturing production

A related webcast on manufacturing production is available for viewing.

How to foster insight-driven, efficient manufacturing with production health

The 33-page Augury study, “The State of Production Health, 2023,” provides more results.

Augury said it provides purpose-built AI, trained by industry experts and the world’s largest data library, to help customers eliminate production downtime, improve process efficiency, maximize yield and reduce waste and emissions. APlant Engineeringarticle covers more of study results, “Survey: How to use upskilling, AI to improve manufacturing production results.”

Mark T. Hoskeis content manager,Control Engineering,CFE Media and Technology,mhoske@cfemedia.com.

KEYWORDS:Manufacturing production health, manufacturing AI use

LEARNING OBJECTIVES

Understand datafrom an Augury survey that explains how artificial intelligence can identify and improve manufacturing production goals. The resulting study also covers manufacturing production topics include challenges, roadblocks, sustainability, workforce, technology among others.

See links to 33-page Augury study, “The State of Production Health, 2023” and a related webcast in the article.

CONSIDER THIS

How are you helping your organization with AI applications?


Author Bio:Mark Hoske has been Control Engineering editor/content manager since 1994 and in a leadership role since 1999, covering all major areas: control systems, networking and information systems, control equipment and energy, and system integration, everything that comprises or facilitates the control loop. He has been writing about technology since 1987, writing professionally since 1982, and has a Bachelor of Science in Journalism degree from UW-Madison.