Overseas EV Manufacturing Plant — Custom Manufacturing Information System (MIS)

Scaling Real-Time Intelligence Across a Global EV Manufacturing Operation

Before this Manufacturing Information System (MIS) deployment, this overseas EV manufacturing plant faced a challenge common to fast-scaling battery and electric vehicle production: shop-floor data, order genealogy, quality reporting, and OT/IT systems operated as disconnected functions, limiting real-time visibility into production and battery management performance.

Disconnected OT/IT Systems Slowing Down Decisions

Without a unified platform bridging operational technology (OT) and information technology (IT), plant leadership lacked the real-time production monitoring and OEE visibility needed to manage a high-growth EV manufacturing environment where battery quality, traceability, and supply chain sustainability are business-critical, not optional.

A Market Leader Needs a Custom, Not Off-the-Shelf, Solution

As a market leader in automotive/EV manufacturing, the client needed a fully custom MIS — not a generic package — capable of integrating shop-floor data collection, ERP/Salesforce data, and genealogy tracking into a single manufacturing information system built specifically around their production architecture.

A Custom Manufacturing Information System Built on Ignition

QAS delivered a state-of-the-art custom MIS solution covering Order Information Management System, Kitting Process, Shopfloor Realtime Data, Order Tracking & Genealogy, Quality Reporting, OEE, Salesforce & ERP Data Integration, and OT/IT Integration — unifying every stage from order intake to finished-vehicle traceability.

Real-Time Shop-Floor Visibility via Ignition Vision and Perspective

The solution was built using Ignition Vision and Ignition Perspective for real-time visualization, with MQTT/HTTP/OPC protocols enabling live shop-floor data collection — giving plant teams the same real-time production data used in daily gemba walks and shift reviews, now available digitally across the plant.

A Full-Stack Technology Build for EV-Grade Precision

The implementation combined Python and SQL for data processing, JAVA/J2EE and FTPC (Rockwell) for automation integration, and Kepware OPC Client for device connectivity — a technology stack purpose-built for the precision and traceability demands of EV and battery manufacturing.

A Compact, Specialized Delivery Team

A team of 4 to 6 QAS engineers delivered this solution across onsite and offshore delivery models over a 1+ year engagement, reflecting the specialized nature of EV manufacturing MIS work compared to broader MES rollouts.

From Disconnected Systems to a Single Manufacturing Information System

The MIS deployment gave this EV manufacturing plant a unified view spanning order management, shop-floor execution, quality, and genealogy — closing the gap between OT and IT systems that had previously limited real-time decision-making.

Measurable Gains in Battery Management and Production Efficiency

With battery management and optimization, real-time production monitoring, and energy efficiency and cost reduction built into the platform, the client strengthened both operational efficiency and sustainability metrics — both increasingly central to EV manufacturing competitiveness.

Predictive, Compliant, and Data-Driven at Scale

Predictive maintenance and downtime reduction, combined with regulatory compliance and safety standards and advanced data analytics, moved the plant from reactive operations to a proactive, data-driven manufacturing model — directly supporting supply chain and sustainability goals central to EV industry growth.

A Reference Model for EV and Battery Manufacturing Digitalization

This engagement positions QAS's Ignition-based MIS capability as a proven model for EV, battery, and automotive manufacturers pursuing Industry 4.0 smart manufacturing maturity — demonstrating that custom-built manufacturing information systems can outperform generic MES packages when built around a client's specific production architecture.