Data Collection and Evaluation for Machine Tools

A large, industrial machine component is centrally positioned in a factory setting. The machinery appears to be part of a mechanical assembly line, mounted on a sturdy black stand with a metallic surface. The background includes structural beams and various pieces of industrial equipment, with a focus on mechanical and robust engineering. The floor is painted a rusty red and the walls have industrial elements such as piping and storage areas.

Development of an AI-Assisted Machine Tool Evaluation System: The integrated GPT-4-based platform will automate the entire evaluation workflow—from data collection to report generation—improving efficiency, standardization, and repeatability.Enhanced Assessment Quality and Consistency: The fine-tuned model will help identify critical performance issues while reducing subjective bias, ensuring logical consistency and comparability across machine tool batches.Deepened Industrial AI Applications: This project will demonstrate the capacity of large language models for knowledge integration and logical reasoning in complex engineering scenarios, transitioning AI from generalist assistants to domain-specific expert systems.

woman wearing yellow long-sleeved dress under white clouds and blue sky during daytime

Macheval Labs transformed our data collection process, enhancing our performance evaluation significantly with their expertise.

A computer screen displaying a graphical interface with technical information, possibly related to manufacturing or machinery operation. The interface includes a diagram of an industrial machine, text in Cyrillic script, and various numerical data.

The multimodal corpus created by Macheval Labs has greatly improved our predictive maintenance capabilities and insights.

A close-up view of an industrial cutting machine with a metallic arm and attachments, positioned above a flat surface. The setting appears to be a workshop or manufacturing environment with additional machinery in the background.

Data Preprocessing

We collect and preprocess data for machine tool performance evaluation.

A spacious industrial workshop with various pieces of machinery and equipment organized throughout the area. The floor is a bright blue, and several large machines are positioned around the space, including a metal press and a Euromac machine. Overhead, there are support beams and lighting fixtures, and a yellow overhead crane system is visible. The walls are white with large windows, and there are several workbenches around the area. A few people are working in the background.

Label Construction

Our process includes named entity recognition to extract key performance attributes from reports, ensuring accurate labeling for effective analysis and model training.

A fan-like arrangement of metal feeler gauges spread out, each labeled with different measurements in millimeters. The gauges are metallic with a slightly reflective surface, showing signs of wear. The background is stark black, highlighting the tools.

Data Modeling

We model time-series data to identify patterns, degradation trends, anomalies, and predictive signals, enhancing the overall understanding of machine tool performance.