Peoplegeist

The Peoplegeist Text-AI for Manufacturing is a software solution designed to analyze maintenance documentation in manufacturing industries. According to the vendor, it aims to help reduce downtime, improve quality, and facilitate knowledge capture and sharing for small to large manufacturing companies. This solution is utilized by maintenance managers, technicians, production managers, quality assurance professionals, operations managers, and manufacturing engineers in industries such as automotive, food and beverage, pharmaceuticals, chemicals, and electronics.

Key Features

Reduce repeating errors: According to the vendor, this feature allows users to identify recurring issues in maintenance comments and automatically generate pareto charts for analysis, eliminating the need for manual categorization or classification-tree.

Share knowledge: The vendor claims that this feature enables the transformation of maintenance documentation into troubleshooting guides by identifying documented maintenance actions for specific problems, facilitating easy knowledge sharing within the team.

Capture & share knowledge: According to the vendor, this feature accelerates troubleshooting time by converting maintenance comments into guides. It allows users to access troubleshooting knowledge from colleagues without having to read through all reports, with no additional work required for sharing experience.

Use TextAI and NLP to analyze maintenance comments: The vendor states that this feature leverages NLP AI to comprehend manufacturing problems and solutions in maintenance logs, eliminating the need for manual categorization or extensive log reading. The AI creates breakdown analysis charts for downtime analysis, maintenance prediction, and identification of training gaps. Users can query the AI for potential solutions based on past experiences.

Multilingual support: According to the vendor, this feature works across 50 languages, allowing employees to use it in their native language. Cross-lingual analysis helps identify problem patterns across different sites and facilitates knowledge sharing among teams working in various languages.

Unlock knowledge in maintenance comments: The vendor claims that this feature automates the reading and summarizing of shift log, maintenance, and MES log comments. It generates pareto charts of production issues, provides hints for root-cause analysis, and suggests resolution steps to expedite troubleshooting.

Save downtime: According to the vendor, this feature aims to decrease downtime by reducing mean time to repair (MTTR) and minimizing incidents (MTBF). Implementation is fast, with no need for an IT project. The vendor also states that discussions about events not being categorized correctly can be avoided.