AI Production Planning & Quality

Objective

Optimize production schedules and detect quality issues early to cut waste, downtime, and rework across the plant.

Methodology

Agile delivery: process & defect discovery, feature engineering on machine, MES & sensor data, model training, and line validation.

Architecture

Cloud and edge stack unifying MES, IoT sensor & quality data, a feature store, ML scheduling and vision models, and plant dashboards.

Solution

An automated platform delivering optimized schedules, predictive quality alerts, yield analytics, and bottleneck detection on the shop floor.