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Let’s boldly go where no robot has gone before

Glenn S. Daehn  Mars G. Fontana Professor  of Metallurgical Engineering, Department of Materials  Science and Engineering, The Ohio State University
By Glenn S. Daehn Mars G. Fontana Professor of Metallurgical Engineering, Department of Materials Science and Engineering, The Ohio State University

FIELD INTELLIGENCE: Smart Processes, Solutions & Strategies

COVID-19 put a spotlight on the brittleness of the U.S. manufacturing supply chain. Responding to crises of many types requires, at least, the ability to rapidly repair or rebuild the machines that are the foundation of our economy.
The multi-skilled artisan or tool and die maker represents the ideal of where we may want to go in the future.

The tool and die maker can access many processes (machining, forming, welding, heat treating, etc.) and can improvise based on available materials and inevitable surprises.

The downside of human artisans is that they are not nearly as reproducible, precise or strong as machines. Nor can they work lights-out, 24/7.
Many collaborators and I have been forming a vision of the future where autonomous systems can basically act like skilled artisans and use new tools for subtractive, additive, joining and deformation processing to make and inspect assured-quality components.

Two things are needed to reach this future: a shared vision for a pathway to hybrid autonomous manufacturing and new tools to actualize this approach:

The vision part

Inspired by SAE standard J3016, defining levels of driving autonomy, levels of manufacturing autonomy are proposed.

Level 0 represents no automation. Level 1 includes CNC path-following. Level 2 includes closed loop error correction. Level 3 encompasses Industry 4.0 elements of capturing system wide data to make decisions.

Levels 4 and 5 include multiple processes (add, subtract, join, cast, etc.) in an integrated framework. In Level 4, the system can automatically fixture and transfer the component from one process to another.

The highest level—5—mimics a conversation with a skilled artisan where trade-offs between cost, performance and delivery time can be discussed and, once chosen, executed without human intervention while recording critical data that assures component quality and sharing the experience with other manufacturing cells.

New tools and processes

This vision frees us from the very large tools, dies and presses that often set the lead time and capital expenditure.

Instead, we can imagine multiple small tools for adding, deforming and cutting working simultaneously on one part—much like multiple robotic ants doing varied jobs but with precise dimensional control.

While engineering academics have focused on the analysis of highly productive manufacturing processes, there is much opportunity in smaller-scale, highly controlled processes.

Many manufacturing processes based on simple and light tools could be quite powerful in this paradigm.

For example, my group is developing local, high-speed, solid-state, impact-based welding processes that use very light equipment.

Because they do not heat the material, there’s no thermal distortion or degradation of the materials, and they can join very strong and dissimilar metals.

These and similar processes based on light and agile tools will be central to this new automated workshop.

With rapid advancements in sensors, computations, robotics and processes, it seems inevitable that these process innovations will complement our existing very efficient mass production to create complex high-quality products when and where they are needed.

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