AI in Paper & Forest Products

Georgia-Pacific saved up to $1 million per machine using AWS machine learning for condition-based predictive monitoring of paper mills, predicting equipment failure 60 to 90 days in advance and eliminating 40 percent of parent-roll tears on one converting line with at least 150 lines as future candidates, alongside the GP Chat maintenance assistant built on Amazon Bedrock and Amazon Nova defect detection via natural language prompts.

Georgia-Pacific deployed ChatGP, an industrial AI operator assistant on AWS, using Amazon Bedrock with Anthropic's Claude large language model and Amazon Kinesis for real-time IoT data processing. The solution serves machine operators and maintenance technicians at pulp and paper mills across the Georgia-Pacific network.