Georgia-Pacific

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Georgia-Pacific has 2 source-linked AI deployments documented in AIUseCaseHub, across 1 industry and 1 country.

Use Cases

2

Industries

1

Countries

1

Hyperscaler mix

See whether Georgia-Pacific's cases are powered by Microsoft, AWS, GCP, or multiple providers.

How Georgia-Pacific builds AI

Build / Buy / Compose across this company's documented cases

BuildBuyComposeMixed

2 of 2 cases classified (100%) · Compare all use-case types

Use case portfolio

Use case types at Georgia-Pacific

AI platform leads with 1 of 2 documented cases; 2 distinct types appear across the visible portfolio.

Technology snapshot

What Georgia-Pacific uses across visible cases

6 named technologies are mentioned across 2 cases, led by Amazon Bedrock.

Capability mix

No capability flags are attached to these cases yet.

All Use Cases (2)

Georgia-Pacific predicts converting line failure and optimizes production with AWS

Georgia-Pacific, owned by Koch Industries, produces paper and tissue parent rolls at manufacturing facilities across North America. The company needed to reduce tears and breaks in converting lines, cut unplanned downtime, and predict equipment failure 60–90 days in advance.To address the challenge, Georgia-Pacific built an AWS-based advanced analytics solution centered on Amazon S3, Amazon EMR, and Amazon SageMaker. Real-time machine data was streamed into a central S3 data lake, transformed with EMR, and used to train ML models that recommend optimum machine speeds and detect risk of failure.The solution also helped Georgia-Pacific consolidate disparate production data and expert knowledge into a centralized analytics approach that more experienced operators and central support teams could use to improve production decisions.

Georgia-Pacific Optimizes Operator Efficiency with Generative AI Using Amazon Bedrock

Georgia-Pacific, a leading global manufacturer of pulp and paper products, faced challenges with scattered knowledge across many facilities, leading to production inefficiencies and risk of knowledge loss from retiring employees.The company partnered with AWS and AWS Professional Services to develop ChatGP, a generative AI chatbot using Amazon Bedrock's Anthropic Claude large language model, integrated with IoT sensor data via Amazon Kinesis.ChatGP provides machine operators centralized, contextualized, and real-time troubleshooting guidance and knowledge access tailored to specific equipment and processes across 140+ facilities.Impact includes improved machine production, reduced quality defects, minimized downtime, accelerated troubleshooting, preservation of expert knowledge, and estimated multimillion-dollar annual savings across operations.

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