OpsSuite_OEE
Overall Equipment Effectiveness (OEE)

Overall Equipment Effectiveness (OEE) meticulously monitors and analyzes the performance, availability, and quality of equipment in real-time, providing actionable insights to maximize operational efficiency and drive continuous improvement in manufacturing processes.

Time Model
OEE_TimeModels

Time Model configuration that structures production time into categories such as total, operating, scheduled, and productive time. It defines losses like breakdowns, setup, and idle time, enabling standardized OEE calculations and detailed performance analysis across operations.

Reason Trees
OEE_ReasonTree

Reason Tree configuration used to define and structure loss categories for OEE analysis. It organizes downtime and performance losses into hierarchical categories (e.g., breakdowns, utilities, maintenance), enabling standardized root cause tracking, detailed analysis, and continuous improvement.

Metrics
OEE_Metrics

Metrics configuration where key production and OEE-related data points (e.g., cycle time, speed, quantities, scrap) are defined. It enables standardized data modeling, ensuring consistent measurement, analysis, and reporting across operations.

Algorithms
OEE_Algorithms

Algorithms configuration where key performance formulas (e.g., Availability, OEE, Performance, Quality, Scrap Rate) are defined. It enables standardized calculation of KPIs using configurable logic, ensuring consistent performance measurement and analysis across operations.

Assets
OEE_STT

Assets configuration where production assets are defined and linked to OEE models. It includes state translations that map machine states to time and loss categories, enabling accurate data collection, classification, and performance analysis.

OEE Dashboard
OEE_Dashboard

The OEE Dashboard provides real-time visibility into production performance by tracking key metrics such as OEE, Availability, Performance, and Quality. It enables monitoring of trends, analysis of losses, and identification of root causes to support data-driven decisions and continuous improvement.