Preview for Advancing Cutting Table Estimation with the Help of AI

Advancing Cutting Table Estimation with the Help of AI

Dr. Celeste M. Calkins, Calista J. Smith

Illinois State University

Published 2026

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Abstract

Profitability in the printing industry relies heavily on accurate estimation techniques. Estimating cutting table technology is an area that has proven problematic for companies within the print industry, as we are often limited in knowledge about the scope of a project prior to completing the estimate. While some companies utilize an existing method of cutting estimation, that process has proven unreliable and inconsistent, often throwing off pricing and scheduling structures. This study seeks to expand on prior research to develop a system that more accurately calculates time standards for cutting table estimation.

The results of the study prove promising. With the help of a well-developed mathematical equation that accounts for table speeds (acceleration adjustments), total cut distance, and critical corner/node counts (built in stop time), we can much more accurately assess total cut time. To speed up the estimating process, we can build out a simple prompt within an AI and have the math run for us.