Rockwell Automation and CAR Release Automotive Smart Manufacturing Report

Rockwell Automation and the Center for Automotive Research (CAR) have released a collaborative white paper titled Smart Manufacturing in Automotive: Deployment and Impact. The report analyzes how artificial intelligence (AI), machine learning (ML), and automation are being integrated across the automotive, tire, and battery production sectors.

Expanded Automation and AI Deployment
The research indicates that the adoption of smart manufacturing has entered a new deployment phase across specialized operational areas. While traditional automation is already fully established within body, paint, and welding processes, manufacturers are expanding automated workflows into areas that have historically been more difficult to automate, including electronics assembly, validation, production coordination, and logistics. Concurrently, AI and ML algorithms are applied to existing operations to optimize predictive maintenance frameworks, inspection precision, and overall system performance.

Operational Drivers and Market Impact
The acceleration of smart manufacturing adoption is influenced by several operational factors, including increasingly complex production environments, ongoing warranty pressures, rising operational costs, and growing global competition. Additionally, automated processes support cost-competitive manufacturing within tight labor markets, helping enable onshoring initiatives.

The findings also highlight a widening adoption divide across the supplier network, where variance in technology implementation creates clear gaps in product quality, equipment uptime, and factory floor output with implications for long-term competitiveness.

Performance Metrics and Production Yield
The implementation of real-time production analytics and automation has delivered specific performance breakthroughs for manufacturers:

The analysis combines CAR analytics with proprietary data from Rockwell Automation's 11th annual State of Smart Manufacturing report to evaluate how companies scale these digital capabilities.

Industry Positioning
The integration of data networks and AI is designed to help manufacturing teams manage complexity and identify systemic issues earlier in the product lifecycle.

The full white paper is available here.

Edited by Romila DSilva, Induportals Editor, with AI assistance.