Lam Research Classification Data Trends
Lam Research Corporation engineers, manufactures, and maintains semiconductor processing equipment used in the creation of integrated circuits.
Overview
We had built a classification system comprised of all of Lam’s commercial off the shelf parts. Now questions were starting to arise as to the effectiveness of the system.
Challenges
- Reports were being written with excel on how many duplicates were being avoided, but there was no connection with this data and the business unit that created the duplicate.
- There was a lack of transparency into how effective the system was and the adoption rate.
- There was no visibility into which business units needed additional training with the system.
Solutions
- I created a data model that incorporated all the different databases and excel sheets for cross information comparisons.
- I constructed visualizations in Qlik Sense to answer questions like trending usage, duplicate owners, and the number of parts per class.
- I automated many of the excel reports.
Results
- With the commercial off the shelf search setup, we were able to identify and prevent 512 duplicate parts in the first twelve months.
- We found across the organization that we’d had 15,880 searches in the first 12 months.
- The duplicates we’d averted so far amounted to more than $1,000,000 in savings.

Duplicate Parts Savings Per Year
Number of Duplicates Prevented in the First 12 months.
Total Searches in the First 12 Months
Part Completion
Tracks the number of parts per class and identifies how completely the attributes were filled out per class in a scatterplot.