Enhancing Manufacturing Excellence with Digital Transformation

Through cloud-based ERP, AI-powered predictive maintenance, and automated supply chain tools, we optimized operations, reduced costs, and improved productivity across global plants.

The Challenge

A global manufacturing company with 15 production plants across five continents wanted to address

Operational Efficiency Challenges

An analysis of operational inefficiencies and bottlenecks across multiple production plants, leading to suboptimal performance.

Supply Chain Management Issues

Identification of disruptions in the supply chain due to lack of integrated systems, affecting timely production and inventory management.

Predictive Maintenance Shortcomings

A review of maintenance practices, highlighting the lack of predictive maintenance capabilities that resulted in increased downtime and higher costs.

System Integration and Downtime Reduction

Recommendations for integrating systems to streamline operations, improve supply chain visibility, and reduce downtime, aiming for more reliable production and cost-effective maintenance.

The Solution

Synaara Consulting provided a comprehensive digital transformation strategy, focusing on IT infrastructure optimization and systems integration. We implemented cloud-based ERP and AI-powered predictive maintenance solutions across their plants, ensuring real-time monitoring and data-driven decision-making.

Key Initiatives

Cloud-Based ERP Implementation

Implemented a scalable ERP platform across all production plants, centralizing data and improving transparency in supply chain management.

AI-Driven Predictive Maintenance

Deployed AI-powered predictive maintenance tools to monitor equipment health in real-time and reduce unplanned downtime.

Supply Chain Automation

Integrated automated supply chain management tools to streamline procurement, reduce lead times, and optimize stock levels.

The Result

The manufacturing company achieved remarkable results within a year of working with Synaara Consulting

20% reduction in downtime, saving the company approximately $15 million annually in lost production time.

35% improvement in supply chain efficiency, reducing lead times by 25% and stockouts by 30%.

40% reduction in maintenance costs due to the proactive nature of AI-powered predictive maintenance.

25% increase in overall productivity, driving higher throughput across production plants.

20% reduction in downtime, saving the company approximately $15 million annually in lost production time.

35% improvement in supply chain efficiency, reducing lead times by 25% and stockouts by 30%.

40% reduction in maintenance costs due to the proactive nature of AI-powered predictive maintenance.

25% increase in overall productivity, driving higher throughput across production plants.

Conclusion