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Smaller manufacturers can use AR to keep eyes on prize

Kyle Parnell
By Kyle Parnell Research Analyst, Rochester Institute of Technology

As manufacturing becomes ever more complex, tools that assist workers with difficult or unfamiliar tasks are becoming critical to process efficiency and product quality. An explosion in the development of mobile, wearable, and augmented reality (AR) computing technologies has thus created a new world of possibilities for the manufacturing industry.

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Kyle Parnell, Research Analyst, Rochester Institute of Technology

Such technologies can put invaluable information in the palm of one’s hand—or in front of one’s eyes—making it easier than ever to collect data, track process steps, and integrate with business management systems. And with the rapid rise in network connectivity, these tools can even enable on-the-spot consultation with reference materials or live experts, supporting shop-floor problem-solving without taking hands off the work.

These tools can streamline data capture, verification and information management critical to manufactur-ing businesses. For many, these steps remain paper-based or reliant on simple digital text files. In either case, if a technician has a problem, he or she must locate reference materials or subject experts, research their particular situation, and find a best-practice solution—taking their hands and eyes off the present task all the while. This type of ad hoc problem solving is implicitly vulnerable to inconsistent results and incomplete documenta-tion—problems later visible in product quality, process efficiency, and improvement efforts.

Existing technologies that can solve these problems, however, do not fit squarely with the opportunity. Usable solutions from developers like Microsoft and Google are expensive and difficult to integrate into manufacturing operations. So quality and efficiency benefits seem worthwhile only when value, complexity and risk are exceptionally high.

Lockheed Martin, for example, uses AR to build $100 million aircraft with no room for error. But where does that leave the thousands of smaller, high-volume manufacturers? These producers may not experience the same challenges of building multimillion-dollar aircraft, but the potential to benefit from improved accuracy, efficiency, and quality is still clear.

Collaborative research initiatives like the UI Labs-led Digital Manufacturing and Design Innovation Institute (DMDII) work to fill such gaps between technology and opportunity. The Rochester Institute of Technology (RIT), a DMDII partner, recently led a project to develop mobile, wearable and AR technologies that enable the same information management functionality as elite commercial systems, but in a more flexible, cost-effective package—increasing applicability to smaller manufacturers.

RIT leveraged simple hardware platforms and open software standards to develop a program for both authoring and executing manufacturing work instructions. The program connects a responsive-layout user interface to an ERP system through a web application, facilitating integration with existing business tools and keeping the system as simple as possible. A “fillable-form” type authoring function lets manufacturing engineers easily create new job instructions that appear in the same format every time. Users can sign into the web app with a smartphone, tablet or smart glasses and see everything they need to know about a job, including notes left by the previous shift. RIT’s system then lets users verify measurements, inspect assemblies and connect with subject matter experts via live video, consolidating processes and opening new doors for collaboration.

Supporting these features is RIT’s own take on AR. Rather than use highly polished renderings to animate each step, RIT takes raw CAD models from engineering documents and overlays them onto the user’s field of view. The result is a tool that can go from design information to usable work instructions quickly and easily, making it easier to implement for new products and processes and simpler to update those that exist. This also avoids the need for specialized training and software, making it worth using with low- and medium-value products, and not just on fighter jets.

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