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The CADDi Guide to Spring Cleaning Your Manufacturing Data
Table of Contents
Manufacturing is an industry about fighting fires – sometimes literal ones. Your day-to-day work is often reactive, finding solutions just in time to emerging problems. Outside of very narrow and costly factory shutdown windows, it’s hard to find opportunities to proactively tackle any “extra value” projects. You’re busy enough getting the job done, can you really take the time to improve results beyond that?
As a result, “good enough” but imperfect choices accumulate. A problematic component keeps getting reused in new designs because there’s no time to improve it. You keep ordering from an expensive supplier because there’s no time to find a cheaper one. Incorrect and redundant data piles up in your databases. It’s like a game of Tetris: small mistakes keep accumulating, and you never get the piece (or peace) you need to clean it up.
We’re here to tell you, though, that Spring Cleaning is worth it, and with CADDi, it’s easier than you think. We made our CADDi Spring Cleaning Challenge to make it clear how low the labor costs can go on these exercises. Wouldn’t it be nice if you could click a button to organize your garage instead of needing a whole Saturday? That’s what we can do for your data.
Let’s look at the three challenges in our new page and why they’re worth doing with your own database.
Removing Duplicates and Redundancies
The simplest data cleaning task is getting rid of duplicate and redundant data. Most manufacturing shops end up with tons of it, and it’s more problematic than you might think. Generally, there’ll be slight differences in the content or “metadata” (things like associated labels, timelines, or context). When someone stumbles across one file or another, it could lead to seemingly minor changes in results that can cause “butterfly effects” with major changes.
The issue is that it’s hard to expose these differences when the data is scattered across many systems. If you have a given drawing, what would you do to track down every other drawing that’s obsoleted by that drawing? Most solutions involve opening a ton of files and doing some manual comparisons. But CADDi has a better way. Our AI-driven similarity search understands how drawings are broken down into components and can find meaningful patterns and matches instantaneously.
Check out the difference in our first challenge game.
Bill of Materials Analysis for Problem Parts
A very common issue in manufacturing shops, especially HMLV (high mix low volume) shops, is assemblies ending up with component parts that are overly costly, difficult to assemble, prone to defects, or other bad things. Often, it isn’t so hard to replace or improve the component part in future designs. The real challenge is making sure that the problematic components doesn’t still appear in BOMs that will keep getting used.
Let’s say you’ve identified a problematic component and you want to remove it from all BOMs and future designs going forward. How would you tackle it? Once again, it involves a lot of manual work: looking at assemblies, scanning through their BOMs or looking at the drawing itself, and confirming whether or not the component you’re looking for is there. But once again, this is something we’ve automated with CADDi.
Check out how it can go in our second challenge game.
Finding Better Suppliers
How confident are you that you’re getting the best possible deal for component parts? You probably have someone “good enough”, but good enough can quickly become unprofitable as tariffs, shortages, and demand spikes can drive up costs and disrupt timelines overnight. Spending time on tracking down better suppliers will often yield big savings, but they also cost a lot of time and effort.
The biggest issue is that it’s hard to track down every relevant purchase order, and even when you can, it’s tough to make apples-to-apples comparisons. It’s not impossible with a bit of work, but it’s very hard to do at scale, comparing hundreds of purchase orders for dozens of different parts. CADDi has the ability to gather, organize, and analyze purchase orders en masse.
Try out your supplier finding skills vs. CADDi in our third challenge game.
Get on board with proactive cleaning and CADDi!
We can make this happen for your messes too. Sign up for a demo and see for yourself!
Manufacturing is an industry about fighting fires – sometimes literal ones. Your day-to-day work is often reactive, finding solutions just in time to emerging problems. Outside of very narrow and costly factory shutdown windows, it’s hard to find opportunities to proactively tackle any “extra value” projects. You’re busy enough getting the job done, can you really take the time to improve results beyond that?
As a result, “good enough” but imperfect choices accumulate. A problematic component keeps getting reused in new designs because there’s no time to improve it. You keep ordering from an expensive supplier because there’s no time to find a cheaper one. Incorrect and redundant data piles up in your databases. It’s like a game of Tetris: small mistakes keep accumulating, and you never get the piece (or peace) you need to clean it up.
We’re here to tell you, though, that Spring Cleaning is worth it, and with CADDi, it’s easier than you think. We made our CADDi Spring Cleaning Challenge to make it clear how low the labor costs can go on these exercises. Wouldn’t it be nice if you could click a button to organize your garage instead of needing a whole Saturday? That’s what we can do for your data.
Let’s look at the three challenges in our new page and why they’re worth doing with your own database.
Removing Duplicates and Redundancies
The simplest data cleaning task is getting rid of duplicate and redundant data. Most manufacturing shops end up with tons of it, and it’s more problematic than you might think. Generally, there’ll be slight differences in the content or “metadata” (things like associated labels, timelines, or context). When someone stumbles across one file or another, it could lead to seemingly minor changes in results that can cause “butterfly effects” with major changes.
The issue is that it’s hard to expose these differences when the data is scattered across many systems. If you have a given drawing, what would you do to track down every other drawing that’s obsoleted by that drawing? Most solutions involve opening a ton of files and doing some manual comparisons. But CADDi has a better way. Our AI-driven similarity search understands how drawings are broken down into components and can find meaningful patterns and matches instantaneously.
Check out the difference in our first challenge game.
Bill of Materials Analysis for Problem Parts
A very common issue in manufacturing shops, especially HMLV (high mix low volume) shops, is assemblies ending up with component parts that are overly costly, difficult to assemble, prone to defects, or other bad things. Often, it isn’t so hard to replace or improve the component part in future designs. The real challenge is making sure that the problematic components doesn’t still appear in BOMs that will keep getting used.
Let’s say you’ve identified a problematic component and you want to remove it from all BOMs and future designs going forward. How would you tackle it? Once again, it involves a lot of manual work: looking at assemblies, scanning through their BOMs or looking at the drawing itself, and confirming whether or not the component you’re looking for is there. But once again, this is something we’ve automated with CADDi.
Check out how it can go in our second challenge game.
Finding Better Suppliers
How confident are you that you’re getting the best possible deal for component parts? You probably have someone “good enough”, but good enough can quickly become unprofitable as tariffs, shortages, and demand spikes can drive up costs and disrupt timelines overnight. Spending time on tracking down better suppliers will often yield big savings, but they also cost a lot of time and effort.
The biggest issue is that it’s hard to track down every relevant purchase order, and even when you can, it’s tough to make apples-to-apples comparisons. It’s not impossible with a bit of work, but it’s very hard to do at scale, comparing hundreds of purchase orders for dozens of different parts. CADDi has the ability to gather, organize, and analyze purchase orders en masse.
Try out your supplier finding skills vs. CADDi in our third challenge game.
Get on board with proactive cleaning and CADDi!
We can make this happen for your messes too. Sign up for a demo and see for yourself!
Ready to see CADDi Drawer in action? Get a personalized demo.
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