Product Development & Management

AI, XR and Data: Manufacturing Technology Predictions for 2024

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This image portrays an article about manufacturing technology predictions in 2024.

Jama Software is always looking for news that would benefit and inform our industry partners. As such, we’ve curated a series of customer and industry spotlight articles that we found insightful. In this blog post, we share an article, sourced from IndustryWeek, titled “AI, XR and Data: Manufacturing Technology Predictions for 2024” – written by Dennis Scimeca and originally published on January 3, 2024.

AI, XR and Data: Manufacturing Technology Predictions for 2024

If we’re finished with the hype cycle, we’re probably talking about a technology that’s here to stay. So, when IndustryWeek asks manufacturers and analysts for their predictions about manufacturing technology in the coming year, we’re looking for the most mature technologies with the widest adoption rates.

This year’s answers demonstrate the point yet again. Of the dozen technologies we asked about, artificial intelligence (AI), augmented/virtual/mixed reality (XR for short) and the use of data and analytics garnered the most response. Manufacturers next year really should keep their eyes on these three technologies in 2024.

AI’s 2024 Prospects

Artificial intelligence took center stage in 2023 with the arrival of generative AI, specifically ChatGPT and Microsoft’s Bing AI, sparking a slew of marketing campaigns and enthusiastic op-eds about what gen AI would do for manufacturers and the world.

Listening to our audiences (and IndustryWeek’s own analyses) the hype bubble for gen AI burst rather quickly but the topic of AI generally still holds great relevance for the manufacturing world.

“The current market zeitgeist around AI has bled significantly into manufacturing markets, but its deployment will be held back by a staunch lack of trust amongst operators and calls for comprehensive and provable use cases. This is particularly the case for functionality associated with quality management processes and QMS software, due to an entrenched resistance to change and concern around giving up control of processes,” says ABI research industry analyst James Prestwood.

“QMS software vendors are and will continue to take a slower approach to developing AI functionality for solutions, engaging in strong and consistent dialogue with key customers to ensure that the technology is meeting real plant floor challenges. … However, even as solutions are released, adoption will be slow, if in 2024 at all, and will most likely be focused on manufacturer’s lighthouse facilities, rather than being deployed organization wide,” Prestwood adds.

Paul Miller, vice president and principal analyst at Forrester, was a bit more blunt in his assessment.

“Generative AI will not transform the business of manufacturing in 2024,” Miller says. “There are clear opportunities to add ChatGPT-like interfaces in front of complex sets of product documentation and operational data, lending a helping hand to experienced engineers. The human remains in charge, and they must still be responsible for the actions that they take: We’re not yet in a position where these generative AI tools can be relied upon to support inexperienced users in situations where mistakes can be both costly and dangerous.”

RELATED: 2024 Predictions for Product and Engineering Teams

Tim Gaus, smart manufacturing leader and principal at Deloitte, is more optimistic in the long term, but sees few applications right now.

“GenAI holds the potential to create closed-loop manufacturing systems that can automatically make real-time adjustments and self-optimize based on data. This can bring new levels of efficiency to the industry – but as the capabilities of GenAI continue to be explored and mature, organizations will be best served to start testing the technology in areas like maintenance and repair.” .

Of the technology leaders and experts we interviewed, Anu Khare , senior vice president and chief information officer at Oshkosh Corp., sounded the most optimistic about AI’s potential.

“We are entering into the most exciting period of technological evolution since the advent of the Internet. The most impactful and broadest application of technology will be AI (artificial intelligence). Every aspect of business will be infused with and augmented by various AI tools,” Khare says.

According to Khare, predictive insight, task automation, human machine engagement and content generation are the four areas that will most benefit from new AI technology.

“All these technological advances and adoption will create a new relationship between humans and AI, where AI becomes an augmentation tool, just like we use industrial tools in our manufacturing plants,” Khare adds.

AR/VR

XR technology, initially pitched as the next, best thing in gaming instead found its home within the manufacturing world. That’s not to say no one uses VR for entertainment, but we cannot deny the utility of manufacturers blowing up product designs in augmented reality to allow operators to see how their parts fit into the final product, or virtually training operators on dangerous equipment to increase safety or collaborating with colleagues across continents.

Somehow this morphed into discussions of the metaverse, a term borrowed from Neal Stephenson’s 1992 dystopian science fiction novel Snow Crash, but according to our experts XR discussion came down to earth again quickly.

“We see a bit of a resurgence of interest in AR and VR in 2024, as everyone moves away from talking about the industrial metaverse. … . Both AR and VR got caught up in broader hype around the metaverse, and they and other enabling technologies like digital twin and even IoT now risk losing credibility (and project funding) as part of the backlash against that deflating hype bubble. Forrester predicts that over 75% of industrial metaverse projects will rebrand to survive the metaverse winter: project teams will go back to talking about the enabling technologies – and the very real problems they address – and quietly hope that everyone forgets any association with the metaverse,” says Miller.

ABI Research director Eric Abbruzzese expects 2024 will be an important year for the AR/VR/MR market because Apple releases its Vision Pro hardware, the company’s first truly new device in a long time. He there expects an influx of mixed reality content to hit the market next year, both for the Pro and its competitors.

“While mixed reality may have a strong 2024, smart glasses will not. OEMs continue to struggle to create a full smart glasses package that delivers quality of experience alongside acceptable design, form factor, and price. Devices have either been too niche and focused—such as glasses specifically targeting cyclists—or too expensive and bulky for broad use (e.g. Magic Leap),” said Abbruzzese.

“Even if smart glasses from major tech names like Samsung and Meta hit the market in 2024 (which is possible, but releases have traditionally been delayed), these will be first generation smart glass devices mostly targeting developers and early adopters,” he adds.

Dale Tutt, vice president of industry strategy at Siemens Digital Industries Software, adds, “The computing and visualization graphics power that are available makes augmented and virtual reality much more accessible and I think in 2024 there is going to be even greater use of AR/VR.” .

“When I think back to the transition from 2-dimensional drawings on the shop floor to when we started printing 3D pictures with colors to help the technicians install equipment, that had a massive impact and reduced the learning curve. AR/VR provides an even more intuitive environment, so the more that companies can present in virtual and augmented reality, the more effective they are going to make technicians and engineers,” Tutt says.

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Data and Digitization

Of all the technologies highlighting this year’s predictions, data digitization and analysis represent the most mature of the trio. Plant-wide lattices of IIoT devices can capture information on vibration, temperature, humidity, quality check results, cycle times, just about anything you can register and quantify with a sensor.

Even the simplest IIoT system, that only tracks products passing in front of photoeyes or logs when and why machines go down can have profound results in increasing OEE and productivity. At the other end of the spectrum, dense IIoT meshes feeding rich data into AI algorithms enable prediction, process tracking and simulation. That’s also a much more complicated proposition.

“In 2024, we’ll continue to see industrial data management evolve and become a priority for organizations if it is not already at the top of the list. Most manufacturers continue to cite industrial data as one of the biggest challenges to innovation due to complexity and accessibility issues,” says Gaus.

Miller adds, “Industrial IoT software platforms do important work, connecting to, managing and extracting data from large fleets of connected devices in production environments. But that’s only part of the picture. Manufacturers need analytics to make sense of the data. They need AI and machine learning to build models and predictions based on the data. They need job scheduling systems and work order management systems, tasking field service engineers to repair machines when machine learning models trained on IoT data spot a problem ahead.”

“IoT platforms are very good at managing and extracting insight from connected devices, but it may not make sense continuing to extend IoT software much further beyond that. Instead, we should be working to effectively surface IoT data inside these more comprehensive enterprise systems,” Miller adds.

Sean Spees, CPG market segment leader for Bosch Rexroth, says in 2024, the emphasis will be “data retrieval and remote assistance. How the data is used and finding a partner with expertise in the digital space to evaluate it to help with predictive maintenance and line conditioning to move towards a lights out factory will be critical.”

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