Why Automated Estimation of Machined Parts is Hard
I was more than a decade into my engineering career before I saw the inside of a modern machine shop. I was there to help crack a problem, which I was told was hard and incredibly valuable: how can we accurately estimate the runtime of a machined part? At first, I didn’t understand at all why it was a hard problem. I just assumed no one had ever approached it rigorously. It seemed simple enough. Given a 3D model, how would a machine tool mill the part and how long would it take? My mental model for CNC machining looked something like this.
How people think CNC machines work
byu/Dr_Madthrust inMachinists
To be fair, for simple enough parts and simple enough processes, it’s quite possible to automate estimation. And there are a number of manufacturers and marketplaces that will sell you instant-quoted CNC parts. Generally, at least one of two things is true about these services. Either the part complexity is significantly restricted, the service doesn’t mind losing money, or both. In fact, the leading public custom part marketplace has many situations where parts are quoted manually and the company still loses millions of dollars each year. That’s not a land grab job shops can afford to participate in.
The mystery at the center of quoting a machined part is runtime. Today’s machines are highly automated, change cutting tools automatically, and operate on 3, 4, or 5 axes. The question for estimators is, for each setup, how much time will the machine spend working on the part.
It’s important to recognize just how many factors influence milling runtime.
The part specification itself, beyond the raw geometry, plays a huge role. What are the general tolerances, specific feature tolerances, required surface finish, and finishes or coatings? Does the dimensionality apply before or after finishing? What features will be measured and how does this affect how the part is cut? Typically, a 3D model describes the geometry and a 2D print describes tolerances and other callouts. A tight tolerance can have a dramatic impact on runtime. Milling may need to be slowed down significantly, special cutting tools may be required, or an entirely different work center or process might be needed. For example, a hole might have a tight positional or diameter tolerance, or a curved surface could have a tight profile tolerance. To mill these features to spec, machines typically slow down their “speeds” (i.e., the spindle speed at which the cutting tool is rotating) and “feeds” (i.e., the speed at which the cutting tool is moved along the part). At slower speeds, tools make more precise cuts because the tools don’t bend and chatter, don’t overheat, and remove a smaller, more precise chip from the workpiece on each revolution. A lot of people (including me!) are working hard on AI to extract and interpret callouts from prints and link them to features in a 3D model. It’s likely going to be years before that technology works reliably on a large fraction of real-life parts. Today, a skilled person needs to make those connections and determine how they impact runtime.
Given identical part specifications, two machine shops — or even two experts in the same shop — may come up with different manufacturing approaches. To start, the choice of stock material clearly impacts runtime. Will you use stock from inventory or order something closer to the part bounding box? Is there a more appropriate starting shape for the process than a bar (i.e., rectangular prism) or rod (i.e., cylinder)? Does it make sense to order precision ground stock to reduce in-house runtime? Estimators must select or assume which machine tool will be used. Different milling centers have different capabilities and will have different runtimes. Shops need some sort of quoting strategy that considers the fact that you can’t finalize a schedule until orders are placed, which means you might not know where the bottlenecks are and what work centers will be involved. Based on your workholding equipment and strategy, how many setups will this part require? What standard cutting tools are available in your milling centers? Based on the complexity and quantity, is it worth it to change out tools for this part? If so, would you use something from your tool crib, or order new tooling, or even get a custom cutting tool made? What CAM package do you use and how much time and attention will the CAM programmer give this part? Do you want them to spend an extra couple hours programming to find a more efficient toolpath? Finally, who will run this part and how experienced are they? What efficiency and uptime will they achieve based on what else they’re working on?
Furthermore, there is no “correct” theoretical runtime for a part. Given the part, work center, cutting tools, and CAM program, there are at least three runtimes you could calculate, and they’ll all likely disagree: the predicted runtime from the estimator, the simulated runtime from your CAM system, and the actual runtime achieved by the machinist. Estimators might use intuition or rules of thumb to determine how long the part should take to run. The CAM system produces a toolpath that can be simulated to calculate a runtime. The actual runtime won’t perfectly match the simulation for a number of reasons including machine dynamics, tool wear and tear, and operator intervention. An experienced machinist might adjust speeds and feeds based on what they’re hearing and seeing from the mill. That means, not only will runtime differ from estimated and simulated runtime, but runtime may differ between runs of the same job!
Over the last few years, I’ve come to appreciate why it’s so hard to accurately and automatically estimate a theoretical runtime for a part. It’s why we’ve had to make Paperless Parts so flexible with configuration, APIs, and our custom pricing language, P3L. There’s simply no one-size-fits-all way to estimate parts, and every shop has to make a lot of decisions about how to quote and make parts. These decisions have big implications on what a part costs and how long it takes to make.
I’ve seen amazing “digital manufacturing” companies emerge, and we’ve been able to help some of them automate most of the quoting and ordering process. Digital manufacturers make major investments to drive down costs, compete globally, and they can be quite successful. Many of these investments are in software and tightly controlling all the variables on the shop floor. If you can’t control the shop floor, you can’t quote quickly and accurately. The challenge for these companies is to stay ahead in capabilities to avoid becoming a fully commoditized service. Automated runtime estimation tends to be part of their secret sauce. For these companies, Paperless Parts provides a platform for building out custom quoting logic, driven by geometry, that also integrates with other software systems and in-house capabilities.
There’s another type of company I’ve seen be really successful, and they’re much more common in American manufacturing. A lot of our job shop customers serve niches in the custom part market by being able to manufacture special types of precision parts better than anyone else. These companies serve industries like aerospace and defense, oil and gas, and semiconductors. They often achieve high margins, assemble highly skilled work forces, and build generational businesses. The challenge for these companies is scaling. Pricing precision parts requires a human touch. Paperless Parts helps these skilled estimators and sales forces do more with less and stay on top of RFQs.
It would be great if an off-the-shelf software tool could fully automate quoting custom machined parts. In the coming years, AI will bring that closer to reality. But today, shops can take pride in the fact that a world where your quoting is hard to automate likely means your business has a competitive moat.
