The AchieVer Posted February 19, 2019 Share Posted February 19, 2019 Augmented reality, virtual reality, and mixed reality do bring value to industry Extended reality technology—augmented reality, virtual reality, and mixed reality—can be visually stunning but not of much use. However, there are solid use cases where this technology saves time and money, and brings value to industry. Back in August of last year, I asked for good examples of augmented reality, virtual reality, and mixed reality (together known as extended reality). Unsurprisingly, I saw plenty of examples of the type my original post complained about: Visually stunning, but almost entirely useless for anything other than showing off. Then there were the augmented reality glasses, used to recreate a particular workflow that everyone involved eventually agreed was simpler, cheaper, and more effective when done with pen and paper. But there were also solid use cases, where real time and money were saved, and real benefits accrued. And there were examples of advances in hardware and software that decrease cost, increase usability, and begin to make the previously impractical worth a fresh look. Some of these technologies really can be ready for industrial use, today. As I researched my latest report on extended reality, one thing quickly became clear: Too much attention is paid to rich and fully immersive environments. Most of the success, today, is more mundane. It's often just about basic virtual reality training, and video calls back to base. But if you're a global organization looking to save time and money by not flying staff to your training centers, that can be a big driver. Barloworld uses AR to help its service engineers in remote locations across southern Africa and is exploring the potential of video to let customers demonstrate a problem before engineers visit. In Spain Allianz saves 6.3 million kilometres of unnecessary travel each year, letting loss adjusters review claims by video link. At Nokia, factory workers learn new workflows in VR, before relying on AR to nudge and remind them as they start performing the same tasks on the shop floor. For as long as smartphones have had cameras, field service engineers have used them to get a second opinion from more experienced colleagues. Now, companies like Microsoft, OverIT and SightCall productize solutions to that same need in extended reality, reducing the average time to resolve issues in Airbus' A330 assembly line by 60 minutes, and improving field service productivity at Enel by over 100 percent. But the single biggest inhibitor to widespread adoption of extended reality tools is a lack of good data -- and too few of the players in this space either recognize the problem or demonstrate the capability to do something about it. Digitized manuals and plans aren't particularly easy to page through on a pair of smart glasses. Rather than reams of digitized pages, field operatives need contextualized atoms of content directly related to the task at hand, and these take time and money to create. Similar effort is required to create the 3D models that drive VR and MR use cases. CAD and PLM systems from vendors like Dassault, PTC, or Siemens offer one source of data -- but these multi-gigabyte models must be simplified to fit in a headset's limited memory. The computer model must also be ground-truthed to make sure the designer's beautiful digital vision actually got built in reality. Work is just getting started on a follow-up report, in which I will look much more closely at the link between these devices and data generated by the internet of things (IoT). Stay tuned. Source Link to comment Share on other sites More sharing options...
Back in August of last year, I asked for good examples of augmented reality, virtual reality, and mixed reality (together known as extended reality). Unsurprisingly, I saw plenty of examples of the type my original post complained about: Visually stunning, but almost entirely useless for anything other than showing off. Then there were the augmented reality glasses, used to recreate a particular workflow that everyone involved eventually agreed was simpler, cheaper, and more effective when done with pen and paper. But there were also solid use cases, where real time and money were saved, and real benefits accrued. And there were examples of advances in hardware and software that decrease cost, increase usability, and begin to make the previously impractical worth a fresh look. Some of these technologies really can be ready for industrial use, today. As I researched my latest report on extended reality, one thing quickly became clear: Too much attention is paid to rich and fully immersive environments. Most of the success, today, is more mundane. It's often just about basic virtual reality training, and video calls back to base. But if you're a global organization looking to save time and money by not flying staff to your training centers, that can be a big driver. Barloworld uses AR to help its service engineers in remote locations across southern Africa and is exploring the potential of video to let customers demonstrate a problem before engineers visit. In Spain Allianz saves 6.3 million kilometres of unnecessary travel each year, letting loss adjusters review claims by video link. At Nokia, factory workers learn new workflows in VR, before relying on AR to nudge and remind them as they start performing the same tasks on the shop floor. For as long as smartphones have had cameras, field service engineers have used them to get a second opinion from more experienced colleagues. Now, companies like Microsoft, OverIT and SightCall productize solutions to that same need in extended reality, reducing the average time to resolve issues in Airbus' A330 assembly line by 60 minutes, and improving field service productivity at Enel by over 100 percent. But the single biggest inhibitor to widespread adoption of extended reality tools is a lack of good data -- and too few of the players in this space either recognize the problem or demonstrate the capability to do something about it. Digitized manuals and plans aren't particularly easy to page through on a pair of smart glasses. Rather than reams of digitized pages, field operatives need contextualized atoms of content directly related to the task at hand, and these take time and money to create. Similar effort is required to create the 3D models that drive VR and MR use cases. CAD and PLM systems from vendors like Dassault, PTC, or Siemens offer one source of data -- but these multi-gigabyte models must be simplified to fit in a headset's limited memory. The computer model must also be ground-truthed to make sure the designer's beautiful digital vision actually got built in reality. Work is just getting started on a follow-up report, in which I will look much more closely at the link between these devices and data generated by the internet of things (IoT). Stay tuned. Source
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