AI for Parts & BOM Management
How to tell a part search which limits are hard and which are negotiable, so it returns a ranked shortlist instead of an empty or overlong list.
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8 min read
Michelle Ben-David
Michelle Ben-David is a mechanical engineer and Technion graduate. She served in an IDF elite technology and intelligence unit, where she developed multidisciplinary systems integrating mechanics, electronics, and advanced algorithms. Her engineering background spans robotics, medical devices, and automotive systems.
BOTTOM LINE
A part search works best when it knows which of your requirements are walls and which are slopes. Hard limits are the ones that make the design fail if broken, and they should be stated with a value and a direction. Preferences are the ones you would trade, and they should be ranked so ties break the way you would break them. Given both, a search can return a ranked shortlist instead of a pass or fail list, keeping near misses that would work and ordering them by what you need. Start by writing down what cannot move, then say what you would give up first, and check the top result against your own standards before relying on it.
Every part search starts with a set of requirements that are not equal. The bore has to be 12 mm because the shaft is 12 mm. The material should be stainless, but a coated carbon steel would do. The supplier ought to be one you already buy from, though nobody would stop a project over it. When all of that is typed into a search box, it arrives as one flat string of words, and the search cannot tell which words you would never bend and which ones you would.
This post is about saying the difference out loud. It covers what separates a hard limit from a negotiable preference, why a search that knows the difference can return a ranked shortlist instead of a pass or fail list, and how to word a request so the ranking matches what you actually need. The idea is simple, but it changes how many searches end in either zero results or a long list of near misses.
Why a Flat List of Requirements Misleads
A requirement list in an engineer's head has a structure that a typed query loses. Some items are walls and some are slopes. A wall is a limit the design cannot cross. A slope is something you would like more or less of, and you would trade it against other things. Written as keywords, both look identical: a number, a material, a standard, a supplier.
That flattening produces two common failures. If you treat every requirement as a wall, the search returns nothing, or it quietly drops a part that misses one soft item by a small margin and would have worked perfectly well. If you treat every requirement as a slope, you get a pile of similar parts, and a good share of them break a limit you cared about. Neither result is a bad search. Both are the result of a search that was never told which requirements were which.
Take a retaining clip for a 12 mm shaft in a housing that leaves 18 mm of space. The shaft diameter and the available envelope are walls. Stainless steel, a black finish, and a supplier already on your approved list are slopes. A search that sees five equal keywords cannot rank a stainless clip that is 20 mm tall below a carbon steel clip that fits. A human would do that without thinking.
Showing a physical property beside each result is one way to bring a wall back into view, which is why a size shown next to the relevance score lets you strike impossible candidates before opening anything. Stating the wall up front goes a step further, because it keeps the impossible candidates out of the list to begin with.
IN PRACTICE
The geometry search has been invaluable, helping me find standard parts instead of designing new ones, saving a huge amount of time and effort. The search system is smart and CAD-aware.
- eytan s., R&D Engineer
What Makes a Limit Hard
A useful test is to ask what happens if a candidate violates the requirement. If the design fails, the limit is hard. If the design merely gets a little worse, the requirement is a preference. A part that is too tall for the pocket does not work at any price. A part that costs ten percent more still works.
Hard limits tend to come from three places. The first is physical interfaces: shaft diameters, thread sizes, hole patterns, mating faces, and the envelope left by neighboring components. The second is operating conditions: temperature range, rated load, pressure, and exposure to fluids or radiation. The third is rules that sit outside the design, such as a material a customer specification requires, a standard your industry applies, or a certification a regulator expects.
Notice that a hard limit is a property of the design context, not of the part. The same clip has a hard height limit in one housing and no height limit at all in another. That is why a limit is worth stating with its number and its direction, such as no more than 40 mm tall or at least 80 N rated, instead of a vague word like small or strong. A direction and a value let a search apply the limit exactly. A vague word forces it to guess.
It is also worth being honest about how many of your walls are real. Teams often carry habits that feel like limits, such as always using one material or always buying from one source. If a habit would give way to a good enough alternative, it is a preference wearing a limit's clothes. Moving it to the right category is often what turns an empty result list into a useful one.
What Makes a Preference Negotiable
A preference is any requirement where you would accept a worse value in exchange for a better one somewhere else. Cost, weight, finish, supplier, lead time, and material family are the usual examples, as long as an alternative would still qualify. The defining feature is that a preference has a price. You would pay a little more for a part from your approved supplier, and you would not pay a lot more.
Preferences also have an order. If you prefer a standard stainless part and also prefer something already used in other assemblies, you may care more about one than the other. Saying which matters more is useful information, because it tells a ranking how to break ties. Without it, two candidates that each satisfy a different preference look equal, and you are left to sort them by hand.
One preference deserves special mention: reuse. A part that already exists in your vault, has been purchased before, and appears in other bills of materials carries value that never shows up in its geometry. It reduces the number of unique items to stock and qualify. The post on finding parts to reuse instead of designing new ones covers why that value is easy to lose, and it is a natural candidate for a stated preference rather than a limit, since a new part is sometimes the right answer.
The practical point is that negotiable does not mean unimportant. A preference still shapes the outcome. It just does so by moving a candidate up or down the list, not by removing it.
How Leo Treats Constraints and Priorities
Leo is an AI assistant for mechanical engineers that connects to an organization's knowledge base, including PDM and PLM data. Its User Intent Search gathers parts under the constraints you state and prioritises them by what you need. In other words, what you say about your limits shapes which parts are gathered, and what you say about your preferences shapes the order they come back in.
That is the difference between a filter and a ranking. A filter answers yes or no for each part. A ranking says which of the parts that pass are closest to what you want, and it can keep a part that misses a soft item while putting it below one that meets everything. You get a shortlist you can reason about, with the trade-offs visible, instead of a list that is either empty or too long to read.
Leo offers integrations with leading PDM and PLM platforms (SolidWorks PDM, Autodesk Vault, PTC Windchill, Siemens Teamcenter, Arena PLM, and others), and it works as an intelligence layer on top of them rather than a replacement. Your existing records stay where they are, and the search works across them. If you want the background on how that kind of search reaches into a vault, the post on searching PLM data with AI walks through it, and the one on finding parts by shape covers the geometry side.
You do not need special syntax to do this. You describe the requirement the way you would to a colleague, including which parts of it are fixed and which are flexible, and the search takes that into account.
Writing a Request That Ranks the Way You Think
A little structure in how you describe the part goes a long way. This sequence works well for most searches:
List what you know, with numbers. Shaft diameter, available height, load, and temperature are all facts, so write them as values and not as adjectives.
Mark each item as cannot move or can move. Use the test from earlier: if breaking it makes the design fail, it is a limit.
Rank the flexible items. Say which preference you would give up first, so ties are broken the way you would break them.
Read the top results and check the trade-offs each one makes. A candidate that misses a preference is only useful if the miss is one you can accept.
If nothing comes back, relax a preference before touching a limit. If a limit has to go, ask whether it was ever really a limit.
A request written this way might read: the clip must fit a 12 mm shaft and stay under 18 mm tall, stainless is preferred, and a part we already use is better than a new one. That one sentence carries two walls and two ranked slopes, and it is far more useful to a search than a list of four keywords.
A ranked result is a screening step, not a verdict. A candidate that meets every stated limit can still interfere with a neighboring part, carry a superseded revision, or fail a qualification you did not mention. Treat the top result as the first one worth opening, confirm it against your standards and your own checks, and let a person make the final call, especially for anything that carries a structural or safety-relevant load. Teams that find their searches returning stale or inconsistent records often discover the real problem upstream, which the post on the real cost of poor PDM search describes.
FAQ
Say which limits cannot move
State hard limits and preferences, get a ranked shortlist.
Leo's User Intent Search gathers parts under the constraints you state and prioritises them by what you need, across your connected PDM and PLM data.
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