In
“A
vision system selection case study”
posted back on March 10th
I shared a link to a somewhat unremarkable machine vision case study.
This concerned a company that had decided to go with Omron for its
vision.
Now
Omron make a decent vision sensor, although I wouldn’t describe
them as being “leading edge” in terms of capabilities or
technology. In fact without looking at the spec sheet I’d lump them
in with the low end Keyence and SICK systems, possibly Cognex Checker
too. In short, I didn’t give much thought as to why Omron was the
“answer to a maiden’s prayer,” as some might say.
But
reader David Dechow did, and he commented too. Click the link to read
his whole post, but the gist of it is this: it’s unlikely there was
anything so special about the task or the Omron system that meant no
other system would work.
I
think this is a very important point, and I tend to agree. Within a
product class – say, vision sensors – there’s little to choose
in terms of capabilities. Sure, some might be easier to set up than
others, and some may have a steeper learning curve, but it’s my
experience that with skilled implementation they can all do the job.
And
it follows from this that if a task demands a higher-level set of
tools – advanced pattern matching, for example, then no sensor is
going to do the job and you’ll need to look at high-end smart
cameras or possible go to a PC-based system.
I
could probably turn this in to Brian’s Rule of Vision System
Selection, which would say: define the capabilities needed for the
vision task, then search among that class of products for the one
that best meets your needs. Or something like that.
By
the way, I’m sure most of you already know David Dechow, but if
not, let me give a little shout-out to him and his company, Aptúra
Machine Vision Solutions.
Browse his site and you’ll see David knows his stuff.
No comments:
Post a Comment