Data Analytics for SMT Assembly

FI Analytics

Product Description

Factory Intelligence Analytics by Cogiscan is a specialized data analytics tool tailored for the PCBA industry. This platform provides advanced web-based dashboards for visualizing a wide range of metrics and KPIs related to the Overall Equipment Effectiveness (OEE) model. It focuses on enhancing the quality, availability, and performance of SMT assembly lines. The Drill-Down feature of this tool allows for in-depth analysis of placement issues and defects, enabling users to identify root causes and initiate immediate corrective actions, thereby maximizing factory margins.

Key Features

  • Comprehensive Analytics: Historical reporting and analyses based on the OEE model, focusing on quality, availability, and performance.
  • Drill-Down Capability: Advanced analytics for detailed examination of placement issues and defects.
  • 70+ Predefined KPIs: Extensive range of KPIs related to the OEE model, including cycle time, yield, downtime, and machine states.
  • Mobile-Friendly Interface: Web-based platform accessible on various devices, offering intuitive and quick assessment capabilities.
  • Open Data Access: Allows integration of collected data into third-party business intelligence tools using standard interfaces.
  • Large Interface Library: Compatibility with a wide range of electronic assembly equipment for seamless data integration.

Technical Specification

  • Data Visualization: Web-based dashboards for real-time tracking of SMT assembly line performance.
  • Customizable Metrics: Ability to tailor KPIs and metrics to specific manufacturing needs.
  • Data Formats: Supports various data formats for comprehensive analysis, including DPMO and PPM for inspection and test operations.
  • User-Friendly Design: Intuitive web interface for easy navigation and data assessment.
  • Equipment Compatibility: Quickly connects to a broad spectrum of electronic assembly equipment, including screen printers, placement machines, AOI, and SPI inspection machines.

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