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