Implementing Lean practices and hosting Kaizen events prior to implementation help avoid automating bad processes. Benefits of greater efficiency, consistency, quick return on investment and the inherent data available for DDM make automation a must do.

Vision Systems: Whether adding sight to robots or used for visual inspection or sorting, vision has come a long way in the past few years. Updates and new options for high resolution 2D cameras, 3D visual systems, laser line scanners and random robotic bin picking solutions are coming out with increasing velocity. The quality of the systems today not only ease the strain on employees but make robust the application of Zero Defect Manufacturing (ZDM) utilizing No Faults Forward (NFF) approaches.

Augmented Reality (AR): AR takes on many forms from station or warehouse scale projection systems to wearables. This rapidly expanding technology presents additional data and instruction to the user within their view of the real world which creates opportunities like never before. Imagine the time savings for training new operators! Instead of working with a new employee on their assembly tasks for several hours, the new operator starts directly at their workstation and follows the directions presented; parts to pick up are highlighted, how-to videos are run, and their motions are tracked for correctness. This non-intrusive system trains the new employee while not limiting the experienced team member, provides real motion data for DDM and enables NFF on manual operations. In high-mix / low-volume operations, it can dramatically improve output quality by making sure things are done properly every time.

Virtual Reality (VR), The complete immersion in the 3D simulation now allows global engineering teams to collaborate and review designs and systems that exist only in a computer without having to leave their facilities. The teams can interact, walk around, mark up changes and work together as if they were together in the same room around real hardware.

Additive Manufacturing (AM): 3D printing is re-writing the rules of how to design and make things. AM is not only used for prototyping and manufacturing trials (machine interference, CMM teaching, fluid studies…), but additionally for tooling, fixtures and gauges. These are being produced in great numbers. Created in very short time at minimal cost, these items can be iterated and optimized for the parts and application. Production parts are always the desire. Metal and many polymer systems produce parts suitable for end use. Design technologies are catching up with our abilities to “grow” parts. Generative Design / Topology Optimization are technologies where the computer uses loads, torques, envelope and constraints provided by the engineer to evolve the design. It does this through multitudes of iterations and presents functional geometry options at minimal weight that may not have occurred to the user.

Machine Learning / Artificial Intelligence (AI): Many manufacturing challenges still rely on people. Difficult inspection processes, or operations with a great deal of variability of parts require the intelligence of people to make decisions. Optimization of machine cycles and robot motion today may only be taken so far due to human limitations. The capabilities of AI and Machine Learning are expanding at a fast pace and will soon be one more common tool in a Manufacturing Engineer’s toolbox to take on these and other tasks. These technologies are good at finding the anomaly and working through multitudes of trials to find the right solution. As processing power increases, so will the application of these technologies.

This rapidly expanding world of manufacturing technologies and capabilities is truly exciting. Manufacturing Engineers have always found developing new processes and manufacturing systems to be rewarding. With new tools and technologies repeatedly becoming available, how could anyone not become even more enamored with this profession?

Check This Out: The Manufacturing Outlook