Lumber Mill Optimization: A Case Study
Overview
When solving a problem, there were more outcomes to consider than just computation resources and solution quality. Sometimes, the right choice of algorithm hinged on a company’s market differentiators. This session was a case study of an AI-enabled system we built for optimizing the production of dimensional lumber, like 2x4s.
We discussed how our choice of algorithm was heavily influenced by the company’s focus on ecological impact, as well as the constraints of their industrial environment. We also explored how using AI changed how we estimated the software, built our team, and educated our client, a hardware company, on how software is developed.
Meet the Speaker
Jordan Thayer, PhD
Former AI Strategist
Jordan served as AI strategist at SEP from 2019 to 2025, bringing invaluable expertise to client projects across multiple industries, including pharmaceutical and construction. Her work focused on Automated Optimization and Machine Learning with time series data.

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