Smart Manufacturing Takes Flight at Collins Aerospace with Cantier MES X.0
Cantier MES X.0 redefined manufacturing at Collins Aerospace by automating data collection, improving OEE computation, and introducing predictive analytics for enhanced operational efficiency and quality control
Challenges
Overcoming Barriers to Smart Manufacturing in Aerospace
Collins Aerospace faced inefficiencies due to manual data collection for Overall Equipment Effectiveness (OEE) computation, a labor-intensive process prone to inaccuracies. The company required a centralized data system to visualize and manage plant performance effectively.
They also sought a solution to enable real-time machine communication, minimize downtime, and enhance quality control using advanced technologies such as SPC and predictive analytics. Addressing these challenges was vital to improving operational efficiency and maintaining a competitive edge in the aerospace sector
Solutions
Tailored Technologies Pioneering Change at Collins Aerospace
Cantier MES X.0 delivered a transformative solution for Collins Aerospace, automating operations, enhancing data accuracy, and integrating advanced technologies to optimize efficiency, quality, and predictive capabilities across manufacturing processes.
Key actions include:
Automating Real-Time Machine Communication
Cantier MES X.0 established seamless connectivity across multiple machines, automating data collection and enabling real-time communication. This eliminated manual processes, improved OEE computation accuracy, and accelerated decision-making
Enhanced Track and Trace with WIP Module
The WIP module offered complete traceability with error-proofing functionalities, ensuring visibility into every production stage. Dashboards with drill-down capabilities allowed proactive identification and resolution of inefficiencies.
Maintenance Optimization Through CMMS Module
The CMMS module tracked key maintenance KPIs like MTTR, MTBF, and MTBA, enabling proactive maintenance
scheduling. This approach minimized equipment downtime, improved reliability, and extended asset longevity.
Advanced Quality Control With SPC
Cantier integrated an SPC module to monitor in-process quality parameters with closed-loop control. This ensured consistent quality adherence, significantly reducing defects and maintaining production standards.
Predictive Analytics with Machine Learning
Machine learning capabilities enabled predictive maintenance and quality analysis by detecting potential issues early. This proactive approach reduced risks, minimized downtime, and ensured consistent product reliability.
Impact
Cantier’s Transformative Results Redefining Aerospace Manufacturing Standards
Cantier MES X.0 introduced advanced automation and data-driven insights, transforming Collins Aerospace’s
manufacturing operations, influencing
- Automated real-time machine communication improved OEE computation and reduced manual workloads.
- WIP tracking and dashboards enhanced production visibility and proactive issue resolution.
- Advanced maintenance KPIs minimized downtime, improved asset reliability, and boosted overall equipment effectiveness.
- SPC ensured consistent quality control, reducing defects and maintaining production standards.
- Predictive maintenance with machine learning reduced risks, improved operational agility, and optimized resource allocation.