The robotics projects we've worked on share a common tension: the control engineers want tighter tolerances, the business team wants a lower BOM, and the mechanical engineers are in the middle trying to find the design that satisfies both without compromising either. Here's how we think about it.

Not all precision is equal

The first thing to establish is which dimensions actually drive system performance. In a robotic arm, the repeatability of the end-effector position depends on a chain of mechanical parameters: gearbox backlash, bearing preload, structural stiffness, thermal expansion. But not all of these contribute equally — and not at all operating conditions.

A tolerance stack-up analysis early in design tells you exactly which features are driving your precision budget. Tightening the wrong tolerance costs money without improving performance. Loosening the right one can cut cost without any measurable impact on the application.

"We routinely find tolerances in inherited designs that are tighter than the manufacturing process can reliably achieve — and tighter than the application requires. Both are unnecessary costs."

Actuation choices drive everything

The choice of actuator defines the mechanical design space. Servo gearboxes give high torque density and programmable control but add backlash and cost. Direct drive motors offer near-zero backlash but require more torque and thermal management. Pneumatics are cheap and fast but require an air supply and are harder to control precisely.

Most robotics startups default to the actuator their software team is comfortable with, rather than the one that's right for the application. The mechanical engineer's job is to challenge that assumption early — when the cost of changing it is still low.

Structural stiffness vs. weight

Every gram of mass at the end of a robot arm multiplies the required torque at the joint. But a light structure flexes more, which reduces dynamic accuracy. This tradeoff is typically resolved through FEA — finite element analysis — which lets you optimize the structure topology for stiffness-per-gram before machining a single part.

Without FEA, teams guess. Sometimes they over-engineer (heavy, expensive), sometimes they under-engineer (flexible, inaccurate). FEA at the early design stage is cheap relative to the cost of discovering the structure is wrong after first build.

Manufacturing process selection

Tolerances don't exist in isolation — they're only achievable (or not) relative to a manufacturing process. CNC machining from aluminium billet can achieve ±0.02mm with the right setup. Sheet metal bent parts might be ±0.3mm. 3D-printed structural parts vary widely by process and material.

Designing for maintenance

Robots wear out. Bearings, gears, seals, and cables all have finite lifespans — especially in industrial environments. A robot designed for production should have its wear components accessible without disassembling the entire system. This sounds obvious; it's regularly ignored in first-generation designs because the focus is entirely on getting it to work, not on keeping it working.

We build maintenance access into the design from the architecture phase. Mean time to repair (MTTR) is a spec, not an afterthought.

Building a robotics system and want a mechanical design team that's done this before? Let's talk.