Augmented reality (AR) refers to a class of tools and technologies that overlay virtual objects and information onto the user’s view of the physical world that become a part of the real-world. AR is taking the world by storm. From the explosion of interest in games like Pokemon Go in 2016, to the growing number of use cases we see today, with each passing day, new AR tools and capabilities are being introduced.

Although the term “enterprise-grade AR” is common, no objective and rigorous standards have been developed to define AR solutions along a continuum of excellence
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Although the term “enterprise-grade AR” is common, no objective and rigorous standards have been developed to define AR solutions along a continuum of excellence. This report represents a first step toward developing an objective, rigorous standard for defining enterprise-grade AR that is grounded in the neuroscience of learning and performance. Regardless of the application, it is the same brain that learns and drives performance. Thus, a deep understanding of “Your Brain on Augmented Reality” is the key to building the highest quality enterprise-grade AR solution.

This is an insightful quote from Albert Einstein that is supported by the neuroscience of learning and performance. But why? What is it about experience that is so rich that it is fundamental to learning, and why is information so much less effective?

The Neuroscience of Learning and Performance
“Learning is an experience. Everything else is just information”  Albert Einstein

The human brain is comprised of at least three distinct learning and performance systems (see Figure). As Einstein so eloquently stated, experience is at the heart of learning. Importantly, it is also at the foundation of enterprise-grade AR. AR provides augmented information co-located on the users’ current reality or experience.

The experiential system has evolved to represent the sensory aspects of an experience, whether visual, auditory, tactile or olfactory. Every experience is unique, adds rich context to learning and is immersive. The critical brain regions associated with experiential learning are the occipital lobes (sight), temporal lobes (sound), and parietal lobes (touch).

The cognitive system is the information system. It processes and stores knowledge and facts. Cognitive information comes in the form of text, graphics, sound, or video and is limited by the learner’s working memory and attention span. Critically, these are limited resources and often form the bottleneck that slows learning with more information coming in and available to the learner (the green arrows) than can be processed (the red arrow). This system encompasses the prefrontal cortex and hippocampus.

The cognitive system is the information system. It processes and stores knowledge and facts. Information comes in the form of text, graphics, sound, or video and is limited by the learner’s working memory and attention span
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The behavioral system in the brain has evolved to learn motor skills. The critical brain structure is the striatum. It is one thing to know what to do, but it is completely different (and mediated by different systems in the brain) to know how to do it. Processing in this system is optimized when behavior is interactive and is followed in real-time (literally within milliseconds) by corrective feedback. Behaviors that are rewarded lead to dopamine release that incrementally increases the likelihood of eliciting that behavior again in the same context. Behaviors that are punished do not lead to dopamine release thus incrementally decreasing the likelihood of eliciting that behavior again in the same context. Real-time feedback is critical because the brain’s response fades quickly (within a few 100 milliseconds), meaning that learning and unlearning will not occur.

A Neuroscience-Based Definition of Enterprise-Grade AR

Now that we understand the neuroscience of learning and performance, we can objectively and rigorously define the neuroscience-based enterprise-grade AR standard, and identify the AR capabilities needed to meet this standard.

An enterprise-grade AR tool must engage experiential, cognitive and behavioral learning and performance systems in the brain in synchrony
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– First, and foremost, an enterprise-grade AR tool must engage experiential, cognitive and behavioral learning and performance systems in the brain in synchrony. This can be achieved by engaging the experiential learning system with AR assets overlaid on the real-world that provide information to the cognitive learning system and real-time interactive feedback to the behavioral skills learning system. This builds a cognitive understanding while simultaneously developing a strong behavioral repertoire, all within a real-world setting.

– Second, the AR assets must be presented to the user in a way that minimizes the load on the cognitive system. Recall that the bottleneck in the cognitive system is working memory and attention that are both limited capacity resources. Regardless of whether the AR asset is text, graphics, sound, video, or holographic, it must be presented in a way that minimizes the cognitive load on the user by presenting the user with what they need, where they need it, when they need it. This is not a trivial problem to solve and the type of asset, as well as the timing and location of the asset will be determined by the use case, but the goal must always be to reduce the load on cognitive processing.

– Third, the AR solution must be interactive in the sense that AR assets must guide the users’ behavior, and react to the users’ behavior in real-time. AR assets that guide users’ behavior must be temporally linked to the users’ behavior. In other words, as a user completes a step, AR assets that guide the next step must be presented in real-time. In addition, these assets must react to the specific behavior elicited by the user. If a correct behavior is elicited by the user, then the next asset in the chain should be presented. On the other hand, if an incorrect behavior is elicited by the user, the AR solution must provide some form of real-time corrective feedback to the user. This is where a combination of AR and the Internet of Things (IoT) would be advantageous. Information from IoT will be shared with the AR solution in real-time that will drive the spatial and temporal presentation of AR assets. This real-time interactivity will effectively engage the behavioral learning system and quickly build a strong behavioral repertoire.

Any AR solution must be interactive in the sense that AR assets must guide the users’ behavior, and react to the users’ behavior in real-time
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Enterprise-Grade AR in Manufacturing – A Use Case

The Problem: A major threat to the manufacturing and industrial sector is the increasing workforce skills gap. Research from the Manufacturing Institute suggests that nearly 10 million manufacturing jobs will be needed in the next decade with millions of these going unfilled. To make matters worse, new workers will not have the expertise of seasoned veterans, leaving the manufacturing sector with a less productive, and potentially more error-prone, workforce.

Research from the Manufacturing Institute suggests that nearly 10 million manufacturing jobs will be needed in the next decade with millions of these going unfilled
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What is needed are methods for training the new workforce that quickly and efficiently instill the subject matter expertise and behavioral skills needed on the factory floor. For example, when training a new worker to operate and maintain a piece of equipment, the ideal approach is to train the vocabulary to describe and label each part while simultaneously training the behavioral repertoire needed to effectively operate and repair the equipment. This coordinated training approach reduces the cognitive load on the user while simultaneously providing the opportunity for limitless cognitive learning and behavioral practice. Taken together this speeds learning and retention, quickly builds behavioral mastery, and streamlines performance. Ultimately this will lead to fewer errors and reduced time to completion by minimizing unscheduled downtime.

The Solution: Consider the problem of equipment operation and maintenance. In this case, a worker might don a Microsoft Hololens or some other hands-free AR device. Let’s examine the capabilities of this solution to determine whether it meets the enterprise-grade standards outlined above.

The AR assets must be presented to the user in a way that minimizes the load on the cognitive system
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1. An enterprise-grade AR tool must engage the cognitive, behavioral and experiential learning systems in the brain in synchrony. With the Hololens (or any other hands-free AR device) cognitive information can be provided in the form of a virtual dashboard that includes numeric data and step-by-step instructions that guide the worker’s behavior. The AR solution is wearable and hands-free, thus allowing the worker full range of motion to complete behavioral tasks, and to build a behavioral repertoire in a naturalistic setting.

2. The AR assets must be presented to the user in a way that minimizes the load on the cognitive system. Recall that the critical factor here is to present the user with what they need, where they need it, when they need it. What asset is needed (whether text, graphics, sound, video, or hologram) will depend upon the specific use case. In a typical manufacturing setting text and graphics are the dominant AR assets. Where assets need to be presented to minimize cognitive load is with a co-located, contextualized overlay so that the worker never has to shift gaze or attention away from the task at hand. Every gaze or attention switch slows the process and increases the likelihood of error. Finally, when the asset is needed is just-in-time. As soon as the asset is needed it must be presented to the worker. Every second delay, or need to search long-term memory increases the cognitive load slowing the process and increasing the likelihood of an error.

3. The AR solution must be interactive in the sense that AR assets must guide the users’ behavior, and react to the users’ behavior in real-time. Let’s assume that the information in the virtual dashboard is providing the worker with step-by-step guidance while monitoring the correctness of the workers’ actions. Most likely an IoT solution is working in tandem with the AR system to determine what assets to present and to determine when and where they should be presented. Once a step is completed successfully, the next instruction is presented immediately because the IoT solution knows in real-time that the step was completed successfully. If a step is not completed successfully the worker is immediately presented with corrective feedback and a chance to complete the step successfully, again because the IoT solution knows in real-time that the step was not completed successfully.

This broad-based and coordinated brain activation that results from enterprise-grade AR solutions reduces the cognitive load while simultaneously providing the opportunity for limitless cognitive learning and behavioral practice
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With an enterprise-grade AR training tool, the training can be repeated as many times as the user would like, and the user can be placed in a broad range of situations. For example, the user can be tested by placing them under time pressure, or they can receive additional training on rare, but potentially dangerous, situations.

This broad-based and coordinated brain activation that results from enterprise-grade AR solutions reduces the cognitive load on the user while simultaneously providing the opportunity for limitless cognitive learning and behavioral practice. Taken together this speeds learning and retention quickly builds behavioral mastery and streamlines performance. Ultimately this will lead to fewer errors and reduced time to completion by minimizing unscheduled downtime.

Recommendations and Closing Remarks:

Whether you are an AR developer or user, it is important to understand which AR solution to use when. The best way to make this determination is to understand “your brain on augmented reality” so that you can select an enterprise-grade AR solution.

Here are some guidelines:

– If the users of your AR solution need to learn critical motor skills along with relevant subject matter, as in healthcare or manufacturing, then an enterprise-grade AR solution that uses a wearable device to keep the hands free to work in recommended. This AR tool should present AR assets, such as text, graphics, sound, video, or holograms, in a co-located fashion where the user needs them, and just-in-time when the user needs them. This will reduce the cognitive load on the user that is an ever-present bottleneck on cognitive processing. These assets must be interactive and temporally linked to the users’ behavior. Most likely this means that an industrial IoT solution is being combined with the AR solution to achieve real-time interactivity. If a correct behavior is elicited by the user, then the next asset in the chain should be presented. On the other hand, if an incorrect behavior is elicited by the user, the AR solution must provide some form of real-time corrective feedback to the user.

This AR tool should present AR assets, such as text, graphics, sound, video, or holograms, in a co-located fashion where the user needs them, and just-in-time when the user needs them
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– If you decide to choose a non-interactive AR solution, consider the use case as you decide between a tablet-based solution and a hands-free wearable solution. If your goal is behavior skills development, then choose a wearable, hands-free device. Allowing workers to generate natural motor movements, instead of holding the tablet with one hand while performing some task with the other, will go a long way toward building muscle memory.

– The specific use case will determine whether location-based assets such as GPS, beacon, or triangulation tools are needed. Similarly, the range of content types available should be determined from the use case. For example, holograms, generated voice and graphics may be critical when a 3-d mental representation of a complex piece of machinery, system in the body, or retail setting is needed to build a cognitive and experiential understanding. The more that the user needs continuous eye fixation on the task at hand, the more you want graphic overlays (perhaps in the form of 3-d holograms) and generated voices. Keep in mind what the brain needs, not what is flashy.

– In this report, we focus on training as the use case, but what if you want an AR tool to enhance performance of a repetitive task such as navigating an automobile or managing inventory? In these cases, the goal is to streamline the performance of a well-understood process, not to impart a detailed cognitive and behavioral understanding. When performance is the goal, the key is to reduce cognitive load by reducing working memory demand and the number of attention shifts. An AR tool that automatically detected the user’s location and directs their focus is ideal. In navigating an automobile, the ideal AR solution would overlay a virtual map on the windshield offering turn by turn instructions through non-distracting video and audio. In the case of inventory management, the ideal AR solution would automate the counting of items, facilitate registering the information, flag cases in which more inventory must be ordered, then direct the user to the next item. In both cases, this significantly reduces the cognitive load which reduces errors and speeds time to completion.

In Summary:

AR tools have enormous potential in manufacturing and many other sectors including automotive, medical, and retail, to name a few. Although the necessary AR features depend upon the use case the goal is always to reduce cognitive load by broadly engaging experiential, cognitive and behavioral learning centers in the brain. Enterprise-grade AR tools have the potential to engage the learners’ brain with co-located information, just-in-time experiences and behavioral training that provides the users’ brain with what they need, where they need it, and when they need it. This speeds time to productivity while reducing errors and costs.

AR tools have enormous potential in manufacturing and many other sectors including automotive, medical, and retail, to name a few
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The post Report: Your Brain on Augmented Reality appeared first on Tech Trends.

Why extended Reality (xR) is an Effective Tool in Manufacturing: A Brain Science Analysis.

This report focuses on a learning science evaluation of extended reality (xR) technology’s potential as a learning and training tool in the manufacturing sector. xR technologies come in two major forms: augmented reality (AR) – in which the learner is in a real environment where digital information is overlaid onto the learner’s field of view –  and virtual reality (VR) – in which the learner is immersed in a completely new virtual environment separate from their physical surroundings.

This report shows that xR technologies hold great promise in manufacturing because they reduce the cognitive load on the learner, provide the opportunity for limitless practice, and speed learning and retention by broadly engaging multiple learning systems in the brain in synchrony.

The Importance of Learning and Training in Manufacturing

High quality training tools are necessary to enhance accuracy and efficiency in the manufacturing process, where one mistake or small inefficiency can have significant ripple effects that are costly and time-consuming. For example, individuals tasked with supply chain management must quickly and accurately evaluate inventory levels, place necessary orders, and facilitate the movement of supplies and goods. All personnel in manufacturing must be well versed on the environmental health and safety rules, regulations, and emergency action plans. This is critical for compliance purposes, but also to reduce the risk of accidents that can endanger workers and slow or stop the manufacturing process.

Experiential learning is effective because it engages multiple learning systems in the brain in synchrony
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Product development is critical and involves an iterative learning process in which prototypes are developed, evaluated, and ultimately lead to a viable product. Product manufacturing requires highly trained technicians to operate and maintain the manufacturing equipment. When the equipment breaks down operators must troubleshoot and address the problem as quickly, accurately and safely as possible. Field service is also important to keep customers happy and their equipment running smoothly.

This report focuses on a learning science evaluation of extended reality (xR) technology’s potential as a learning and training tool in the manufacturing sector
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Learning Science of Training in Manufacturing

“Learning is an experience. Everything else is just information” Albert Einstein

This is an insightful quote from Albert Einstein that is supported by learning science—the marriage of psychology and brain science. As elaborated below, experiential learning is effective because it facilitates the engagement of multiple learning systems in the brain in synchrony. Experiential learning also provides the foundation for the effectiveness of AR and VR in manufacturing and other sectors.

The human brain is comprised of at least three distinct learning systems
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The human brain is comprised of at least three distinct learning systems; a  schematic of theseis provided in the figure below. The cognitive skills learning system in the brain has evolved to obtain and process knowledge and facts. Whether comparing inventory with a checklist, studying safety rules and regulations, reading equipment training manuals, or vetting product descriptions, the cognitive skills learning system is being recruited.

Experiential learning provides the foundation for the effectiveness of AR and VR in manufacturing
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Cognitive skill learning tends to involve processing text and schematics and is limited by the learner’s working memory and attention span. It requires focus and mental repetition for long-term memory storage. The cognitive skills learning system encompasses the prefrontal cortex, hippocampus and associated medial temporal lobe structures in the brain. The ultimate goal of this system is to transfer knowledge from short term memory in the prefrontal cortex to long term memory in the hippocampus and medial temporal lobes. Processing in this system is adversely affected by stress, pressure, and anxiety. This system is slow to develop, not reaching maturity until individuals are in their 20’s, and begins to decline in middle age.

xR technologies reduce the cognitive load on the learner, providing opportunity for limitless practice and speed learning and retention by engaging multiple learning systems in the brain
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One mistake or small inefficiency can have a ripple effect throughout the manufacturing process that is costly and time-consuming
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The behavioral skills learning system in the brain has evolved to learn behaviors. It is one thing to know what to do, but it is completely different to know how to do it. Knowing the safety rules and regulations is completely different from knowing how to initiate those behaviors in an emergency. Memorizing the operations or repair manual for a piece of machinery is different from knowing how to operate or repair the machine. Behavioral skills are learned by doing.

Cognitive skill learning tends to involve processing text and schematics and is limited by the learner’s working memory and attention span
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Processing in this system is optimized when behavior is interactive and is followed in real-time (literally within milliseconds) by corrective feedback. Behaviors that are rewarded will be more likely to occur in the future, and behaviors that are punished will be less likely to occur in the future. Interestingly, this system does not rely on working memory and attention, and “overthinking it” hinders behavioral skills learning. Behavioral skill learning is mediated by the basal ganglia and gradual, incremental dopamine-mediated changes in behavior. The ultimate goal of this system is to train direct neural connections between sensory regions and motor regions in the brain that drive behavior.

As Einstein so eloquently stated, experience is at the heart of all learning. It is also the key ingredient in xR training. The experiential learning system has evolved to represent the sensory aspects of an experience, whether visual, auditory, tactile or olfactory. Every experience is unique, and adds rich context to cognitive and behavioral skills learning. The critical brain regions associated with experiential learning differ as a function of the sensory input. Visual representations are formed in the occipital lobes and auditory representations are formed in the temporal lobes. Tactile representations are formed in the parietal lobes and olfactory information is represented in the piriform cortex and olfactory bulb.

xR Applications in Manufacturing

The key ingredient of xR technology in manufacturing is that experiential learning systems are being recruited in synchrony with cognitive and/or behavioral learning systems. Here I outlined 5 use cases for xR in manufacturing.

The experiential learning system has evolved to represent the sensory aspects of an experience, whether visual, auditory, tactile or olfactory
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Supply Chain: Suppose you are tasked with inventory control. In a typical scenario, you might approach each set of inventory, count it, note this on a clipboard or tablet, and tag inventory that is low and in need of replenishment. In this case, your cognitive system is highly engaged. You must focus on the inventory and count it, then shift attention to the clipboard or tablet, find the appropriate location, write the number down, then repeating the process. The working memory and attention load are high, attention switching is necessary, and thus, the potential for error and reduced efficiency is also very high.

Every experience is unique, and adds rich context to cognitive and behavioral skills learning
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Now consider the same situation but where you don a pair of augmented reality glasses. You scan the inventory room and visual cues on the display direct you to the first set of items to be counted. You scan the items and a built-in algorithm counts the number of items present and the number needed. When the inventory is low a warning is presented and you are asked to tag this item for replenishment. The glasses then direct you to next inventory item to be counted. Once the inventory process is complete the system prompts you to send the inventory needs to the relevant purchasing departments. In this case, your cognitive load is reduced, attention switching is minimized, the experiential and cognitive systems are engaged, and you are guided through the process in the most behaviorally efficient method possible. The process is faster and more accurate and the likelihood of a supply chain error is reduced.

It is one thing to know what to do, but it is completely different to know how to do it
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Environmental Health and Safety: Suppose you work in a manufacturing plant and you need to learn the steps to take to keep the workplace safe. You could read a workplace safety manual that describes the rules and regulations with text and figures. This places a heavy load on working memory and attention to translate the abstract information into a visual representation of the steps you would need to take during a safety incident. Alternatively, you could read the manual and also watch a video that shows actual or simulated safety conditions. This is better because the experiential systems in your brain are being engaged to some degree. However, in both cases, your goal is to store this information in memory for use later during a real-world situation in which your and your co-worker’s safety is in jeopardy.

Behavioral skills are learned by doing
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Alternatively, you could be directed to predefined locations in the workplace while wearing augmented reality glasses. At each location your view of the workplace is augmented with static text overlays or dynamic video that provides specific information on the safety guidelines or usage of safety tools. For specific safety equipment, you could receive step-by-step instructions or visual labels describing exactly how the equipment works. You might then be asked to demonstrate your skill with a specific safety tool, with or without text-based prompting and receive real time feedback. Analogously, you might don a VR headset and be transported into the middle of a workplace emergency. You might scan your virtual environment watching personnel follow or fail to follow the guidelines within this chaotic situation while receiving auditory feedback on the appropriate actions.

In AR and VR, there is minimal need to translate abstract text or figures into a visual representation because this information is being supplemented with experiential learning that is proximal and salient
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In the AR and VR examples, there is minimal need to translate abstract text or figures into a visual representation because this information is being supplemented with experiential learning that is proximal and salient. Because multiple brain systems are active, the memory traces in each system are strong and interconnected. Behavioral learning will also occur when you demonstrate your skill with safety tools and receive feedback either with the AR tool, or in VR with haptic feedback incorporated.

Product Development and Prototyping: Suppose you are part of the product development team. This is an iterative process in which schematics and computer aided design (CAD) tools are utilized and ultimately lead to the development of a prototype. As with reading text and studying static figures, this places a heavy load on the cognitive skills system in the brain to construct a 3D dynamic image from a series of 2D static images. It is difficult to know if this translation is effective for each member of the team and whether all team members “visualize” the same product. This is suboptimal and inefficient.

Instead, imagine donning an AR or VR tool in which a virtual 3D dynamic prototype is presented simultaneously to all members of the product development team early in the development process. The team is either physically present in a single room or are virtually collaborating via VR. Either way, all team members can view the single prototype, can “hold” it in their hands, and can manipulate the prototype –  all while discussing specific design features that they like or dislike. In this case, the cognitive load is minimized because a 3D dynamic prototype is present from the start. In addition, because the prototype can be shared virtually, team members in any location can collaborate.

The key ingredient of xR technology in manufacturing is that experiential learning systems are being recruited in synchrony with cognitive and/or behavioral learning systems
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Equipment Operation and Repair Training: Suppose you are training on the operation and repair of a large, expensive, and rare piece of equipment. Because there are only a few training centers around the world you begin by reading and memorizing the operations and repair manuals. Then you fly to a training center for an intensive 6-week course where you attend classroom training sessions and obtain hands-on equipment training. Once the training is complete you return to work as a certified operator and repair technician. Although certified, there is still much on-the-job learning to obtain to become an expert. In this scenario, you begin the training process with a heavy load on the cognitive system as you attempt to construct 3D dynamic representations of the equipment from 2D static training manuals. With that information in hand you begin the intensive hands-on training that will facilitate behavioral skills learning. Although the practice is intense, it is impossible to obtain enough experience in a 6-week course to attain expertise.

The experiential and cognitive systems are engaged, and you are guided through the process in the most behaviorally efficient method possible
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Now suppose that you begin the training process by exploring the equipment in virtual reality. You can walk around and view the equipment while receiving verbal or written instructions about the specific operations of each part. If you have haptic hardware, you can touch the equipment and manipulate it, again being driven by verbal or written instructions. You might even have a virtual trainer in the same room with you pointing out specific features and answering questions.

Instead of flying elsewhere to a training facility, you might don your VR headset each day for virtual lessons, and your homework might involve troubleshooting an array of equipment malfunctions
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Instead of flying elsewhere to a training facility, you might don your VR headset each day for virtual lessons, and your homework might involve troubleshooting an array of equipment malfunctions. You might even be placed in a virtual emergency situation in which you receive real-time feedback or as part of a test. Once certified, you might continue with more advanced VR training on more complex and rare emergency situations, but ones that can have a major impact on the manufacturing process. In this case, you are receiving cognitive and behavioral training simultaneously with experiential learning. There is no need for physical travel, and the rare and expensive piece of equipment is available, at your fingertips, 24/7. You can train on rare and dangerous situations that would be difficult, if not impossible, to simulate during real-world training. Your confidence and level of expertise will be higher and you will achieve these more quickly.

As Einstein stated, experience is at the heart of all learning. It is also the key ingredient in xR training
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The augmented and virtual content must be optimized for human consumption
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Troubleshooting and Field Service: Suppose you are a consumer of a manufactured product (e.g., computer, appliance, DIY furniture, etc.), and you attempt to troubleshoot some problem either with online manual, YouTube videos, or on the phone with a technician. You find yourself trying to convert the abstract information into actionable behaviors to fix the problem. You are constantly switching your attention back and forth from the manual or video to your product, or trying to find the right words to explain the problem on the phone wishing that the technician could “see” what you see. This is frustrating and ineffective.

With these technologies one can quickly obtain subjective ratings of confidence, satisfaction and engagement, or develop objective tests to determine whether learning has actually occurred and to challenge the learner
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When multiple brain systems are active memory traces in each system are strong and interconnected
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Big Data: The Hidden Bonus of xR Training

The focus of this report has been on the psychological and brain-based advantages of xR in manufacturing, but there is another advantage of xR technologies that is equally important and that is the promise of actionable data. With these technologies one can quickly obtain subjective ratings of confidence, satisfaction and engagement, or develop objective tests to determine whether learning has actually occurred and to challenge the learner. These can be combined with eye gaze and heat map patterns that provide a direct window onto attentional processes and engagement, or haptic data to provide real-time behavioral feedback. These data can be used to speed iteration toward optimal solutions and to quantify the ROI associated with xR technologies.

You can train on rare and dangerous situations that would be difficult, if not impossible, to simulate during real-world training
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Quality Content and Optimized User Experiences

AR and VR technologies offer promise as effective tools for manufacturing by facilitating broad engagement of cognitive, behavioral and experiential systems in the brain that are critical in manufacturing. A note of caution though. Although these tools have great potential in manufacturing, the tool in and of itself will not meet this challenge. These tools provide augmented and virtual experiences and information to human users.

Data can be used to speed iteration toward optimal solutions and to quantify the ROI associated with xR technologies
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Thus, the augmented and virtual content and temporal presentation of the content must be optimized for human consumption. Augmented information can reduce the cognitive load, but can also overload the user. Virtual information must be realistic and lead to a veridical sense of “presence”. Optimization follows from good experimental testing and modification. Fortunately, the rich and broad set of real-time data that can be extracted from AR and VR technologies makes this a viable and realistic prospect.

Virtual information must be realistic and lead to a veridical sense of presence
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For companies looking to get into Immersive technologies our VR Consultancy service offers comprehensive support in strategic deployment of Virtual, Augmented and Mixed Reality

Todd Maddox is Science, Sports and Training Correspondent at Tech Trends, and the CEO of Cognitive Design and Statistical Consulting. Follow him on Twitter @wtoddmaddox

The post Report: How XR Works With Your Brain appeared first on Tech Trends.

Tetra Pak is one of the largest companies that most people never heard of. Chances are, however, that you’ve used one of their products very recently, as the Swedish company supplies food processing and packaging solutions to manufacturers in more than 175 countries. Last year alone, they sold 188 billion packages, netting $12.2 billion in sales.

The original Tetra Pak carton changed the milk industry back in the 1950s
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Their original carton changed the milk industry back in the 1950s. At a 1961 press conference in Switzerland, the company presented the first machine for aseptically filled bacteria-free milk, but they haven’t stopped innovating in the decades since, and are now at the forefront of implementing technologies that will enable it to continue to scale its global operations in a much smarter way.

“Over the past few years we’ve invested in new technologies such as artificial intelligence, automation and data exchange to enhance traceability, predict potential machine problems and optimise operational performance for our customers,” explains Johan Nilsson VP, Digitalisation and Industry 4.0 at Tetra Pak. ”By embracing everything that the 4^th Industrial Revolution can offer, we can shape the future, and help customers seize the tremendous opportunities in tomorrow’s connected world.”

Industry 4.0 is essentially the idea of smart manufacturing, achieved through the Industrial Internet of Things (IIoT) which collects and connects data from devices to improve processes and increase efficiency in real-time. Digital technologies such as machine-learning, augmented reality and many others are part of that picture, as they can connect workforces, transform processes, analyse data, and provide greater visibility and flexibility across our supply chains.

By connecting packaging lines to the Microsoft Azure Cloud, Tetra Pak can collect operational data to help predict informed maintenance timing
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Across all sectors, we’ve seen businesses investing in the equipment and software that allows this information to flow between different platforms, people, and business processes to create new data-based revenue streams and systems. One example of how this works in practice is that Tetra Pak have sensors on more than 5,000 filling machines at customers’ sites, all connected to Microsoft Azure, which feed real-time performance data to the company for monitoring and analysis – nearly 700 million data points each year. As a result, maintenance can be scheduled much more precisely and cost-efficiently.

By connecting packaging lines to the Microsoft Azure Cloud, Tetra Pak can collect operational data to help predict informed maintenance timing. This means they can better foresee machine problems and quickly spot breakdowns – reducing plant downtimes

“When you have plants around the world, the service knowledge we gain from one plant comes to benefit another. This prevents issues from happening,” says Nilsson.

Data that’s gleaned from connected machines gives company technicians an operational snapshot across thousands of packaging machines in use. That information helps service engineers swiftly answer critical questions, such as: When did a specific failure happen and how long did it last? What was that machine’s temperature at the time? What was the pressure? The performance data is aggregated and available on technicians’ mobile devices.

Like many enterprises in various industrial sectors, Tetra Pak is using Mixed Reality technology to optimize its processes and increase efficiency
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When equipment does break down, however, the company has streamlined machine diagnostics and repairs for customers using Microsoft HoloLens devices. Like many enterprises in various industrial sectors, Tetra Pak is using Mixed Reality technology to optimize its processes and increase efficiency.

Back in 2017, Tetra Pak began selling service agreements that incorporated HoloLens to enable the company’s local service representatives to triage diagnoses and repairs in real time with heads-up, hands-free calling. By integrating those capabilities with Microsoft Azure, system specialists were empowered to remotely guide a HoloLens-wearing service engineer – via Microsoft Dynamics 365 Remote Assist – through the steps to fix the machine thousands of miles away.

“This is how we take the global expertise that we have available somewhere in Tetra Pak and bring it to the fingertips of the engineer in the countryside in Chile or Pakistan,” explains Nilsson, adding that this significantly cuts repair time and saves huge amounts of money in reduced downtime, not to mention travel costs.

“Our partnership with Tetra Pak and their investment in the technology is further evidence of the potential of Mixed Reality within automation and manufacturing,” says Lorraine Bardeen, general manager, Mixed Reality Business Applications, Microsoft.

Industry 4.0 has the potential to not only save manufacturers vast amounts of money, but also improve things across the board for businesses, employees and customers
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“In the context of industry 4.0, Mixed Reality is expediting processes such as engineering and maintenance to support the creation of smart factories, and companies like Tetra Pak are reimagining their business by leveraging modern, unified, intelligent and adaptable solutions that bring together the vast amounts of data across their organization to empower their employees with new tools for productivity.

Industry 4.0 has the potential to not only save manufacturers vast amounts of money, but also improve things across the board for businesses, employees and customers through sustainable use of resources, safer maintenance cycles, and empowered employees.

In 2017 Tetra Pak began selling service agreements that incorporated HoloLens to enable the company’s local service representatives to triage diagnoses and repairs in real time
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Industry 4.0 will ultimately enable global industrial operations such as Tetra Pak to function even more efficiently and intuitively
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“A product of mixed reality among other technologies, industry 4.0 will ultimately enable global industrial operations such as Tetra Pak to function even more efficiently and intuitively,” adds Bardeen. “With Mixed Reality, we can understand data in context and simplify workflows to extend human ability. When this happens workers feel more effective, businesses see more progress and everyone has a chance to participate in the modern workplace.”

For companies looking to get into Immersive technologies such as VR/AR/MR/XR our Virtual Reality Consultancy services offer guidance and support on how best to incorporate these into your brand strategy.

Alice Bonasio is a VR and Digital Transformation Consultant and Tech Trends’ Editor in Chief. She also regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. Connect with her on LinkedIn and follow @alicebonasio on Twitter.

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