Robotics plays an important part in lab automation and in automated medical device production. In both, their accuracy, repeatability, and reliability can increase throughput and reduce errors that can be associated with manual work. New robots that utilize parallel kinematics can improve performance while often reducing size and lowering cost.
Conventional robot manipulators are serial in design. A Cartesian robot, for example, is made up of individual axes, each with its own bearings, guides, motors, and controls that are stacked on top of each other. This design is easy to design and control but has limitations:
Loads stack up. The X axis has to be built to support the Y and Z axis in addition to the work piece. This can result in significant added mass, which limits acceleration and other performance factors.
Tolerances stack up as well -- backlash, repeatability, and accuracy all add up as more axes are added up.
The system gets more and more complicated and costly, as each axis adds another motor, cabling, and control axis to the system.
Gantries using parallel kinematics, like the Festo EXCM 30 shown here, are being used to make next-generation lab automation systems smaller, lighter, and faster. (Source: Festo)
While most obvious in a gantry robot, the same stack up and complexity issues exist in SCARA and articulated robot designs commonly used in automation today. While these designs work well, they can often end up larger and more expensive than they need to be for many automation applications.
Parallel systems can solve many of these problems. In a parallel system, more than one actuator can work each axis of movement. Probably the simplest parallel system in use today is the 2-axis H gantry design. In this design, both motors are static, driving a single belt fastened only to the X/Y carriage. This can offer many advantages over a similar serial design:
Component count is greatly reduced. The system shares a common belt, there is no need to fasten the axes together, and moving cables are eliminated.
Much less space is needed, as the system can be designed as a single component. The X and Y axes can operate nearly on the same plane, reducing height. No cable tracks/troughs are needed.
The motors act in parallel on every motion, reducing power needs. This feature can be used in design to improve acceleration, lower mass or size, or lower cost by using smaller motors.
It is certainly true that an unconstrained robot takes up a fair amount of spce. Adding hardware motion constraints can reduce that space, but still, mostly, a robot takes up more space than dedicated automation. So that consideration must certainly be a part of the tradeoff calculations.
A two or three axis automation system dedicated to a particular process will almost always be more effective than a universal robot in that same application. There is no question about that. BUT a robot is a flexible device, while a dedicated system designed for a specific task is not. If the task changes a bit the robot only needs a program change, while the dedicated automation system may need a number of hardware modifications. The tradoff between optimization and flexibility is very real and usually recognized.
There is a company that offers a robotic test systen for automotive seats, and it costs more than any of the machines that could do any one of the 8 or nine different tests that are done on seats. BUT it is far less expensive than the collection of different testing machines needed to do all of those tests separately, and it takes up much less space.
So really, there are many applications where a dedicated automation system with fewer axis is thye only wise choice, while there are other applications where the flexibility of a robot system is the only smart choice available. The two are different and have different applications, similar to steak and athletic shoes. Each may be the best choice for a different application.
I wholeheartedly agree. Parallel systems do have their limitations, but their unique capabilities add a lot of options when designing an automated system. For example, while an Hbot is slightly larger than it's motion envelope it is nearly the same size and shape; if it can be placed over or under the motion envelop it can have the smallest impact on footprint of any system. But an Hbot can't deal with "snaking" or inserting nearly as well as a SCARA robot, or come close to handing the huge number of motion axes of a conventional articulated robot.
The big drawback to parallel-kinematic robots: they generall have to be as big as their motion envelopes. Oh, there are exceptions, but in general, if you want to "snake" something into a tight spot from a distance, an articulated serial-kinematic arm is still the way to go.
I see a lot of people trying to use 6+ axis industrial robots as "CNC" machines these days. The articulated arms are cheaper, and have a much greater motion envelope for a much smaller footprint (and price tag). But they simply can't match a gantrybot or "real" CNC machine for strength, rigidity, or accuracy.
As always, it's less about choosing the "best" robot, and more about choosing the tool appropriate to the task. A small lab with a poor equipment budget might well be better served by an articulated-arm robot that can be easily re- or multi-tasked for only the cost of a new end-of-arm tool.
The number of robots in medical assembly has gone through the roof. At the Medical Design & Manufacturing Show in Chicago today, the number of robotic systems (inlcuding Festo's) was incredible. The makeup of the exhibitors is starting to resmeble the packaging indy show, Pack Expo.
Robots and automation systems are becoming so complex, it's hard to tell one from the other. Where does the robot end and the automation system begin? Sometime sit seems the whole automation operation is one big robot.
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For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.