DMDII Announces $12 Million in Applied R&D Awards

The Digital Manufacturing and Design Innovation Institute (DMDII), a UI LABS collaboration, announced that it has issued seven national applied research, development, and demonstration awards. These projects address several digital manufacturing and design topics, including augmented reality for use on manufacturing shop floors and on wearable and mobile devices.

“We are excited to continue to advance applied R&D within our core technology focus areas,” said Dr. Dean Bartles, Chief Manufacturing Officer of UI LABS and Executive Director of DMDII. “With each project call, we bring additional researchers, global industry leaders, and small companies into our consortium and move closer to making technologies related to ‘smart manufacturing’ and ‘brilliant factory’ applicable to manufacturers across the country.”

The projects involving augmented reality (AR), Manufacturing Work Instructions on Wearable and Mobile Devices with Augmented Reality, led by the Rochester Institute of Technology, and Authoring Augmented Reality Work Instructions by Expert Demonstration, led by Iowa State University, reflect the tremendous potential that AR holds as related technologies transition from consumer applications to the industrial sector.

“Our project will enable the creation of instructions for an augmented reality-based training system that mimic the actual part manipulations of an expert,” said Eliot Winer, Associate Professor of Mechanical Engineering at Iowa State University. “This project builds upon successful research from our project team, which we anticipate turning into real-world applications for manufacturers through the perspective provided by our industry partners.”

Embedding visual instructions in an individual’s environment through projection, wearable elements, or handheld devices can reduce training time and errors at multiple stages of the manufacturing process. AR also allows companies to redeploy experts to other tasks rather than time-consuming training sessions.

“A critical element to driving manufacturing competitiveness is delivering work instructions to our skilled workforce,” said Craig Sutton, Manager of Advanced Manufacturing at Deere & Company. “Given the amount of complexity that this workforce manages, written instructions remain a challenging medium. A tool like augmented reality will enable us to improve our productivity and quality measures in our operations.”

DMDII’s projects bring together teams with expertise in a variety of manufacturing disciplines and include major multinational corporations, small- and medium-sized enterprises (SMEs), government entities, and university researchers. Each project is managed by a lead organization that coordinates work among other organizations on the team. For example, Iowa State University is spearheading a project that includes Purdue University, John Deere, Boeing, Daqri, and Design Mill. Facilitating connections among its diverse consortium to create unique solutions is an important aspect of the UI LABS process.

DMDII’s seven new contract awards are as follows:

Manufacturing Work Instructions on Wearable and Mobile Devices with Augmented Reality – 15-04-01
Lead Organization: Rochester Institute of Technology
Other Organizations on the Team: Harbec, Optimax, OptiPro

This project aims to move shop floor instructions off of paper and into interactive, easy-to-use wearable technology. Using augmented reality technology, users will be able to see how to complete a task in real time, with virtual guides showing them what—and what not—to do. At the same time, the system will collect valuable real-time shop floor data that is not typically captured and harness it to improve future manufacturing processes. The system will be based on open standards to achieve another key goal of the project: the creation of technology that is cost-effective for SMEs.

Authoring Augmented Reality Work Instructions by Expert Demonstration – 15-04-03
Lead Organization: Iowa State University
Other Organizations on the Team: Boeing, Daqri, Design Mill, John Deere, Purdue University

This proposal seeks to create work instructions for augmented reality systems by developing the Augmented Reality Expert Demonstration Authoring (AREDA) product. The end product will be a simple and intuitive method to quickly create augmented reality work instructions using 3D cameras with advanced image processing and computer vision algorithms. The cameras will track experts as they manipulate parts to complete a project, capturing minute details and translating them into virtual instructions. AREDA stands to benefit companies like project team partners John Deere and Boeing by making assembly line training more cost-effective through augmented reality. 

FactBoard: Real-Time Data-Driven Visual Decision Support System for the Factory Floor – 15-02-08
Lead: Iowa State University
Other Organizations on the Team: Boeing, Factory Right, John Deere, ProPlanner

This project will develop FactBoard, a shop floor decision support system that will convert thousands of data inputs from logistics and production systems into a collection of visual dashboards—all in real-time. The dashboards will consist of mobile support displays that can be accessed by a variety of users, from plant managers to factory floor foremen. FactBoard will enable manufacturers to make quick adjustments to respond to resource changes, saving them time and money. Many companies are often not in a position to make major upfront investments in shop floor data collection, so FactBoard would ultimately enable manufacturers to use existing data effectively while increasing the quality of information and decision-making as additional data sources become available in the future.

Elastic Cloud-Based Make: Supply Chain Configuration Use Case – 14-09-02
Lead Organization: GE Global Research
Other Organizations on the Team: Rochester Institute of Technology

The initial Elastic Cloud-Based Make (ECBM) project will transition multiple manufacturing tools developed under the Adaptive Vehicle Make (AVM) program to DMDII. It will create a use case report that will be available on the open source manufacturing resource the Digital Manufacturing Commons (DMC) and will function like a road map for SMEs looking to incorporate AVM tools across their supply chains. This project extends the scope of the original project to further demonstrate paths to commercialization for additional AVM tools throughout the supply chain, from SME suppliers through large manufacturers. These commercialization pathways will be demonstrated through supply chain configuration for new products and for remanufactured products.

SPEC-OPS: Standards-based Platform for Enterprise Communication enabling Optimal Production and Self-awareness – 15-03-02
Lead: Palo Alto Research Center (PARC)
Other Organizations on the Team: ITAMCO, MTConnect Institute, System Insights

SPEC-OPS aims to provide a first-of-its-kind platform to tightly integrate machine tools and the multiple systems involved in the total manufacturing process, such as manufacturing execution systems, enterprise resource planning systems, dynamic planning and scheduling and process analytics. The capability to integrate multiple systems to transfer data back and forth does not exist today, and SPEC-OPS is the first major effort to address the challenge. The final platform will result in savings in planning, scheduling, execution, and maintenance time for manufacturers.

Automated Manufacturability Analysis Software “ANA” – 14-01-07
Lead Organization: Iowa State University
Other Organizations on the Team: American Foundry Society, John Deere, The Lucrum Group,, North American Die Casting Association, Pennsylvania State University Applied Research Laboratory, Steel Founders’ Society of America, Tech Soft 3D, University of Alabama at Birmingham

This project will create a manufacturability analysis package that can work on any platform to provide real-time feedback on critical manufacturing issues. The ANA project builds upon work from the AVM project to develop commercially viable software that will provide feedback to designers at the conceptual design phase. The resulting analysis software will enable conceptual designers to receive immediate feedback on their designs early in the manufacturing process, cutting down the often lengthy conceptual design phase of components. The outcomes of this project will enable significant reductions in manufacturing costs, product launch costs, and time to market.

Integrated Manufacturing Variation Management – 14-07-02
Lead: Caterpillar Inc.
Other Organizations on the Team: Missouri University of Science and Technology, University of Illinois Urbana-Champaign

Incoming stock from casting and forging suppliers can vary to the point that standard machine tools cannot adequately respond to the existing material condition in the as-programmed state. The goal of the project is to generate a system by which a manufacturer, in an automated fashion, can compensate for machine tool workspace (machine tool) errors induced due to part, fixture, tooling, or machine tool errors. This should allow for large reductions in setup times for new parts, new fixtures, or parts that see a large variation in the rough condition as delivered to the machining operation while minimizing human interaction in the machining setup process. The innovation over the present state of technology will yield significant improvement in process reliability and efficiency in the entire value stream.

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