Signal Integrity Engineering requires Engineering Judgment.
The same thing that makes
SI
require Creativity causes it to also require above average Judgment; namely
that “you will consistently be asked to craft clear answers from insufficient
data based on ill-defined measures of success”.
There’s no way around it, Engineering Judgment Required.
So we’ll address this topic here in our
mini-series on the
soft
skills required for Signal Integrity Engineering.
While you may have been born with a certain
Intelligence
Quotient (IQ), there are things you can do to improve your
Judgment Quotient® (
JQ®).
As such, this article
will provide both a process for exercising Judgment in your daily tasks as well
as methods for improving your Judgment.
No
doubt your
JQ® naturally increases
over time, yet it’s worth our time to step back and think about how we can hone
our Engineering Judgment and decision-making skills.
I’ll start by detailing a process for exercising Engineering
Judgment using the 3-steps shown in Figure 1:
Gather Ye Data, Hit a Crescendo, and Find Your Way Out.
Figure 1: A 3-step Process for Exercising Engineering
Judgment
Gather Ye Data
While it may seem self-evident that Engineering Judgment
requires data, it is surprising how many times I watch engineers try to skip
this step. Indeed, it is “data” that
changes “Judgment” into “Engineering Judgment”.
As Engineers, we need to gather data to exercise Judgment. SI data comes from a variety of sources such
as simulators, measurements,
field solvers, published works,
and past projects. Well into my 4th
decade of doing SI, I still catch myself deciding things without data. Becoming data-driven is an important
discipline because intuition and data don’t always agree. And, particularly in SI, data has a way of
surprising you; it often shows you things you did not expect. This is the value of the tools we use; they
exist because the interconnects we work with are often unpredictable.
One reason some propose skipping this step is because it
seems data cannot be obtained. Maybe
“there isn’t a model” or “I can’t get a probe on that” or “there’s no time in
the schedule”. As these are all real
problems, we must become skilled at the concepts of “close” and/or “some data is
better than none”. Not having a model or
not getting one in time are everyday problems for SI Engineers, so many times
we have to use something “close”. Judgment
has now entered the process. Substitute
a similar connector, use the generic “spec” model included with your simulator,
or focus your analysis on refining only the passive connection. Learn how to remove (de-embed) whatever is
not ideal in your measurement setup. SI
Engineers do these things all the time.
Once the intellectual and logistical barriers are overcome
and you’ve begun to “Gather Ye Data”, you may encounter the opposite
problem: too much data. Compute farms, simulators that sweep
variables, and measurement automation have the potential to quickly create
Gigabytes of raw data. While some of
this data may arrive pre-processed, the practice of SI typically involves
spreadsheets, scripts, and graphing utilities that help us find what we’re
looking for. Judgment helps us sort the
data between relevant and irrelevant, enabling us to dive deeper into the
things that matter.
There’s nothing like good solid data. I love it when simulators and measurements
are working reliably, piling up data I sense can be trusted. This in itself is a substantial Engineering
achievement, one that might trick us into thinking we have achieved our end
result. Many an SI Engineer has arrived
at review meetings with piles of credible data but little sense of what it all means. So learn how to connect the dots. Think about it, how would you feel if your Layout
Engineer sent you a PCB with colorful traces on dozens of layers yet none
of them connected to the devices? Data
guides Judgment, but it does not make decisions. Engineers make decisions.
While good data is imperative, to help us keep in mind it is
the means to an end and not an end in
itself, we need to learn to Hit a Crescendo.
Hit a Crescendo
In music a “crescendo” is a gradual increase in volume, as
well as the term for the peak volume at the end. A crescendo is stunning when done
correctly. And so it is when gathering
data; you need to sense when you now have enough data and are “there”. If you drag it out you have too much data
and, just as in music, the result is nauseating and suffocating. Get there too fast and there’s no effect at
all. So the skill is timing; enough, but
not too much.
As I work through projects, I plan and allow time to gather
data; this is an important and valid phase.
The phase begins with assembling models or a measurement setup, and then
the data starts to flow. Your Judgment
helps you perceive when the data is looking relevant and believable, and this
in itself may require time and iteration.
Eric
Bogatin’s Rule #9 is helpful here:
“Never do a measurement or simulation without first anticipating the
results.” Once the data is acceptable
you continue to gather it as you journey towards your crescendo. The musical analogy works for me but you
could also picture data collection like filling the gas tank in your car. At some point it becomes “full” and it’s
fruitless to try to put more in. The purpose
is to empower the car to go somewhere, and so it is with data and your project.
A few ways to know you have enough data are: (a) you are no longer learning anything new, (b)
it all starts to look the same, (c) you cannot process it all, and (d) you have
a headache. But note that different
tasks require different amounts of data.
For example, I’m working on a project now that has endless permutations
and hence requires more data. Other
tasks are more straightforward. On the
current project more time, data, expense and engineering are required, yet I’m
still watching for the crescendo. A
crescendo is typically marked by a discovery and/or a sense the data set is
robust and complete. And truth be told,
sometimes the crescendo is provoked by schedule; either someone needs the
answer or the work is no longer equitable.
Those situations might require an additional dose of Judgment, but I’m
getting ahead of myself.
Working in SI, where compute power can provide more data
than you can absorb, sometimes you’re closer to a crescendo than you think; you
just need to slice the data a different way.
For example, plot variable xy against variable z and discover what is
really happening. As we typically work
with more dimensions than we can plot, try holding some variables constant
while plotting the ones that seem most relevant. Some use 3D graphs, but I prefer scatter
graphs overlaid with colored filters on subsets of the data (pages
7-10). When you discover the
dependencies that dictate performance you have had your “aha” moment. Once there, it’s fun to test and confirm your
theory a couple ways to ensure your conclusions are correct. Indeed, you have Hit a Crescendo and now it’s
time to Find Your Way Out.
Find Your Way Out
A crescendo doesn’t work unless you “find your way out”, or,
in musical terms, finish up the song.
Songs don’t end on the crescendo; instead they resolve the excitement
created with settling and easily absorbed harmonies. Similarly, your crescendo doesn’t do any good
unless you package it up and make it useful for the rest of the design
team. You have shopped for the gift and
selected it, but it’s not wrapped or given yet.
It should seem self-evident we need to find our way
out. But engineers love to engineer, and
hence managers have discovered that at some point they need to “shoot the
engineer and ship the product.” Can we
become skilled enough to find our way out before we get shot? I think so, but this may require improving
our Engineering Judgment. We need to
acquire the ability to sense either that we are
“done”, or should be done. Judgment is
the thing that stands between dawdling and finishing up. You’ve gathered your data, hit your
crescendo, and now you need to decide what it means in terms of the
Project. Do we need to constrain that
length? …swap that dielectric? …use a different connector? …none at all?
Or maybe the system is acceptable as is and we don’t need to (get to?)
change anything, hence our value-add was verification and sign-off. Sleep on it, if you must, but it’s time to
make a decision. And decisions require
Engineering Judgment; the moment has arrived.
“Finding Your Way Out” forces another problem with many
engineers – particularly we techy SI Engineers.
How will you communicate what you have learned? How will you make it simple and
digestible? You resolved the correct
length to be 1.2894 inches, but perhaps you can communicate it to be 1.3”? What’s the best way to show that graph? …enlarge the fonts? …leave out that variable? …not show it at all? Finding your way out and finishing well
requires you to hand-off your work, and simplification and clarity are
essential. Don’t be content just to know
you have finished your task; provide ways for others to know that too.
Engineering is an endless stream of projects and revisions
of projects. Sometimes you might need to
delay that thing you want to do until the next revision. And at times I’ve clung onto projects because
it was a good one and/or I didn’t want to do the next one. Engineering offers a non-compelling reward
for finishing up: more work. So we have to train ourselves to move forward;
that project you just finished will soon be out of date technology. That’s the nature of engineering. You have to learn to enjoy the process
because completion can be underwhelming. Find Your Way Out and everyone wins. Done.
Improving Your Engineering
Judgment
While your Engineering Judgment will naturally improve over
time, Figure 2 illustrates four things you can do to accelerate the
process: Find a Mentor, Invest in
Learning, Use It, and Close the Loop.
Figure 2: 4 Methods for Increasing Engineering Judgment
1. Find a
Mentor. I’ve been privileged to work
with many excellent engineers, yet three guys standout among them: John, Bob, and Mike. These guys were natural engineers, loved
engineering, and seemed to be born to engineer.
They engineered at work and at home - typically with their ham radio
gear or some other project. They taught me
poise, pace, and new ways of looking at problem solving and the practice of
engineering itself. Find someone like
this and spend time with them. It’s not
intuitive or even scientific, but skill rubs off.
2. Invest in
Learning. I know, you don’t have time to
read books, blogs or go to conferences.
Neither do I. But viewed from
another angle, you don’t have time to be stuck viewing things through the lens
of only what you know. What we know needs to be expanded and honed over
time or it becomes a limitation. It’s
difficult to
cut with a dull ax, so learn to Sharpen the Saw®. SI Engineers should go to DesignCon at least every other year. Find out what other SI Engineers are learning
and leverage their work. Think
critically about what they’re saying and if they have substantiated and
communicated it well. Get in the mix,
and you will discover those you connect with and appreciate learning from. This step is the less organic and
broader-based version of step 1, but is still extremely helpful.
3. Use It. Just as a muscle doesn’t get stronger unless
you exercise it, likely the best way to grow your Engineering Judgment is to
use it. But using it involves risk, and many
SI Engineers hate risk. If your best
data suggests something should work, take the risk and go with it. While I am naturally nervous and conservative,
I’ve been pleasantly surprised by the things I feared might not work yet
did. Taking those risks grew my
Engineering Judgment in ways that wouldn’t have happened otherwise. It’s exhilarating to figure something out and
see it work across millions or billions of units. Taking data-driven risks builds your judgment,
confidence and courage. And when you
muster up the courage to believe your own data, you’ll find others will too and
your credibility will increase.
4. Close the
Loop. In SI this term is typically used
to refer to Measurement
Correlation, but that’s not how I’m applying it here. Because we’ve been successful at migrating SI
to the front of the design cycle, we’re often 3 projects down the road before
our current work gets built, debugged and shipped. Perhaps if there is an SI problem you will be the first to hear about it, but it’s a
rare day when someone finds you to let you know there isn’t an SI problem. So I’ve
learned to ask the question: “Did the
xyz work OK?” I just asked it of a
customer I worked with 2 years ago who replied that “both projects are working
well and in production now. No SI
problems.” Nice. Signal Integrity Engineering forced you to
make decisions about the line between function and failure, and Closing the
Loop provides necessary feedback to your Engineering Judgment. It’s helpful to discover that your Judgment
calls were good ones and that, indeed, your Engineering Judgment is
increasing. So learn to follow-up and
Close the Loop.
In Conclusion
Signal
Integrity, In Practice requires Engineering Judgment; there’s no way around
it. As it’s possibly the skill no one
taught you in college or on the job, we’ve endeavored to examine it here. While Engineering Judgment is intertwined in the
process of gathering data, it is forced by the events I have labeled “Hit a
Crescendo” and “Find Your Way Out”. I
trust these concepts – which are unavoidable moments in the engineering process
– will help you identify when the next step is not more models, measurements or
data but rather Engineering Judgment.
Exercise it effectively.
Notes:
Judgment Quotient®
and JQ® are registered trademarks of
Choiceladder LLC, and are used here with permission.
Sharpen the Saw®
is a registered trademark of FranklinCovey®, is one of The 7 Habits by
Stephen R. Covey, and is used here with permission.