Modularity Future-Proofs Your System

By Peter Harris | October 31, 2017
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The use of industrial robots to automate high volume tasks goes back to the 1970s, when the German robot maker Kuka pioneered the first true industrial robot (FAMULUS) with six axes of motion.  Since then, robots have slowly but surely been displacing routine mechanical work in a wide range of industries.  However, until quite recently, the nature of such robotic systems has been pretty monolithic and inflexible, in large measure due to the nature of the robotics themselves.  Standard industrial robots are accurate, reliable, and fast, but also unintelligent and in need of significant guarding.  An industrial robot will not adjust its path of motion if a human is in the way, and given the typical speed and payload, can be reasonably dangerous if not properly guarded.  In addition, historically teaching robots motion paths and locations has been a reasonably cumbersome process, not terribly well-suited to regular adjustment.

Given guarding needs, and the historic complexity of robot teaching, systems have historically been designed for high-volume, repetitive tasks where process changes are few and far between.  Like the typical automotive assembly line, the typical robotic system has historically been a large, complex beast, subject to becoming outdated (or at least in need of major modifications) if the process itself changes very much.  If you really look at robotic systems deployed across industries such as automotive, aerospace, warehousing and logistics, and general industry you will see many designs that solved a specific problem at a specific time, but lacked the flexibility to easily adapt.

The solution to the above problem is fairly straightforward: robotic systems need to be designed with sufficient levels of modularity in order to make them adaptable over time.  We have deployed many, many systems over the years in support of ground-breaking scientific research, and if there is one thing that is inarguable it is that science changes with time.  While it may not seem necessary to design modularity into a system for its immediate intended use, including such features makes the system much more adaptable over time.  The relatively minor incremental costs of including modular elements such as docks, carts, and flexible software can pay for themselves many times over if they enable your system to stay functional longer.

Achieving a future-proof level of modularity requires a thoughtful approach to both hardware and software.  Our approach to design is rooted in modularity.  This approach provides real-time benefits such as the ability to change readers for different assays, the ability to move hundreds of plates from a freezer to a system in seconds, or the ability to pull a failed device out of a system and replace it with a new one in a matter of minutes.  But more importantly, it makes the durability and adaptability of the system that much higher.  While you may or may not need to swap readers on a daily basis, it is likely you may want that ability a few years down the road as new technologies emerge.

Advances in docking technology, collaborative robots, and mobile software controls are making modularity more powerful than ever.  Give us a ring if you want to discuss the future-proofing of your robotic system!