In this week's newsletter, Aaron Moncur has a conversation with Rick James, CEO of SimuTech Group, the number one ANSYS partner in North America.
We went in and looked at using Python and just automated it. It took their process down from four days to a couple hours.
In this episode:
How Python automation eliminated manual decision handoffs and reduced aerospace simulation workflows from four days to hours
Why the best engineering teams place simulation at the top of the V-diagram during system architecture rather than treating it as end-stage validation
How multi-physics coupling maps full-field data between structural, thermal, and fluid domains instead of relying on simplified boundary conditions
Why the simulation versus physical testing debate misses the economic optimization angle, using simulation to eliminate worst candidates before million-dollar tests
Bonus Content:
A Framework for Engineers Working with Contract Manufacturers
S6E46 Rick James | ANSYS & Engineering Simulation
Rick James built his first go-kart in seventh grade and constructed a three-story fort with electrical outlets and a fireplace by age 11. Three decades later, he leads SimuTech Group's 220 engineers serving 2,500 active customers across North America. This conversation explores the economics of simulation versus build-and-test, the persistent challenge of companies treating simulation as end-stage validation rather than upfront design exploration, and how Python automation is collapsing workflows that once took days into hours. James discusses multi-physics integration that eliminates boundary condition assumptions, shares his perspective on AI's emerging role in simulation, and explains why he models brisket smokers with CFD to optimize smoke flow. Listen to understand where simulation delivers measurable value and where engineering teams still resist adopting it despite clear economic benefits.
>If YouTube isn’t your thing, check out this episode and all of our past episodes on Apple, Spotify, and all the rest.
Stop. Before you automate that manual process step-by-step, read this.
In the 1890s, inventors tried to ease the transition from horses to automobiles by building "horseless carriages" - mechanical contraptions with articulated metal legs, rein-based steering, and fake horse heads housing lamps. They were solving the wrong problem. The answer wasn't replicating a horse. It was rethinking transportation entirely.
Modern automation projects make the same mistake. Your manual process evolved around human capabilities. Operators compensate for variation, use visual judgment, make micro-adjustments. Automating these workarounds directly creates complex, unreliable systems.
Pipeline Design & Engineering’s focus? Solving for the optimal outcome. Clear, reliable, effective.
Don't automate the workaround. Solve the actual problem.
Evaluating automation? Pipeline has solved this puzzle 100+ times.
Python Automation Eliminates Manual Handoffs in Aerospace Simulation
SimuTech worked with an aerospace customer whose simulation team had strong technical fundamentals - accurate methodologies, proper training, appropriate hardware. The workflow itself created the bottleneck.
The users are really good in terms of the methodologies were sound, they're accurate, they're well trained. They had good hardware,"
James explains. The problem wasn't technical competence.
Their process required four days from analysis start to final results. Python automation collapsed that timeline to a couple of hours by encoding decision-making that previously happened through verbal communication between engineers.
A lot of that was maybe from them, so maybe they're helping us out on our metrics, but it was definitely a lot of individual decisions, and a lot of human handing off to other humans,
James says. The script captured institutional knowledge about when to apply which methods.
The application involved fatigue and fracture analysis requiring cycle counting across multiple load steps and model sources. Engineers needed to accumulate cycles from different scenarios to calculate remaining component life.
I've got a few different models I'm pulling from. I've got to accumulate those cycles to get what's the remaining life of this product? Those are scriptable methods,
The pattern appears across SimuTech's customer base. Python integration into ANSYS products enables engineers to move beyond GUI-based workflows where every step requires manual button clicks and decision points.
A Framework for Engineers Working with Contract Manufacturers
Most engineers approach contract manufacturer selection like a procurement exercise: gather specifications, request quotes, select the lowest bidder. Three months later, they discover their partner lacks capacity, documentation is insufficient, and actual costs bear little resemblance to the quote. Contract manufacturing is a relationship problem disguised as a procurement decision. Engineers who treat it purely as vendor selection encounter the same failures: missed timelines, cost overruns, quality issues, and eventually, expensive mid-production manufacturer switches. Success requires understanding you're entering a partnership where both parties need specific things to work. Working with contract manufacturers requires understanding cost structures, managing technology transfer, and maintaining productive relationships. This guide provides decision frameworks and identifies common pitfalls across partner selection, pricing negotiations, documentation requirements, and ongoing relationship management.
For more, visit the full article on The Wave.
Think your manufacturer keeps screwing up your circuit boards? The problem might be the design itself, setting them up to fail before they even start assembly.
On December 4th, Chris Denney is running a free webinar that walks through the most common PCB design mistakes that frustrate manufacturers and how to prevent them.
Your Manufacturer is Stupid – What's Really Going Wrong in PCB Design
This is a 45-minute session focused on practical DFM issues that create real problems on the manufacturing floor. No vendor pitches, no abstract theory, just specific design decisions that make assembly harder than it needs to be.
📅 Date: Dec 4, 2025 @ 8:00 AM PT / 11:00 EST
📍 Location: Microsoft Teams (link provided upon registration)
💰 Cost: Free
Who should attend:
This webinar is built for mechanical engineers who want to understand how board layout and design choices impact manufacturability, cost, and communication with electrical teams. You'll learn the fundamentals that let you collaborate more effectively with PCB manufacturers and avoid expensive surprises when boards move to production.
Electrical engineers will pick up real-world DFM insights they can apply immediately to improve yield and reduce rework.
You'll learn how to:
Identify design choices that complicate PCB assembly unnecessarily
Communicate more effectively with PCB vendors and electrical teammates
Design in ways that reduce rework, waste, and frustration across the boar