"Dataset for Categorical Analysis of Failure Drivers in Industrial Robots (KUKA KR 6 R900)"

"This dataset consists of a technical time series comprising 10,000 operational cycles captured from a KUKA KR 6 R900 industrial robotic platform. The primary data is presented in a structured tabular format, integrating multimodal physical variables: Ambient and Process Temperature (K), Rotational Speed (rpm), Torque (Nm), and cumulative Tool Wear (min). The records are segmented by asset quality categories (Low, Medium, High) and feature a failure distribution classified into five distinct modes: Tool Wear (DH), Thermal Stress (ET), Power Stress (EP), Mechanical Overload (ISM), and Random Failure (FA).In addition to the raw data, the repository includes a technical pre-processing layer using one-hot encoding for asset categories and an exhaustive statistical validation. This validation includes correlation matrices detailing the interdependence between mechanical and thermal variables, alongside ANOVA test results confirming the statistical significance across groups. For each specific failure mode, dedicated spreadsheets provide the corresponding linear regression models, including coefficients and goodness-of-fit metrics (R2) that characterize the behavior of each failure driver. The dataset is specifically structured to support the reproducibility of reliability analyses and the training of predictive maintenance models within automated manufacturing environments."