-3.png?width=600&height=300&name=Untitled%20design%20(4)-3.png "Untitled design (4)-3")
Intelligent Factory Framework for Optimizing Processes with IoT
The Intelligent Factory Framework integrates OT and IT on a unified, cloud-based platform using AWS services, enabling real-time data acquisition from IoT devices like PLCs, SCADA systems, and sensors. It supports advanced analytics and ML models to predict maintenance, detect anomalies, and optimize workflows, with real-time dashboards helping stakeholders identify inefficiencies and respond proactively. AWS’s scalable infrastructure ensures seamless growth, automated data pipelines, and high-quality data for analysis. By combining IoT and cloud analytics, the framework enhances process visibility, supports remote collaboration, modernizes legacy systems, and helps manufacturers improve efficiency, quality, and align with Industry 4.0 goals.
.png?width=500&height=400&name=Agentic%20AI%20for%20Smart%20Maintenance%20Workflows%20%20(1).png)
- Data scattered across multiple systems like PLCs and SCADA prevented a unified view of operations.
- Lack of real-time monitoring and adjustments led to variations in product quality.
- High energy consumption due to inefficient processes and resource utilization.
- Reactive maintenance practices resulted in frequent equipment failures and production delays.
- IoT Integration: Deployed IoT sensors and AWS services for real-time data and insights.
- Process Optimization: Improved workflows, quality, and energy efficiency using ML and monitoring.
- Scalability: AWS cloud enabled seamless growth and remote collaboration.
- Reduced batch cycle times by 20% and improved equipment utilization by 25%.
- Achieved a 30% reduction in unplanned downtime through predictive maintenance.
- Improved product quality consistency by 15% with real-time adjustments.
- Optimized energy usage, reducing energy costs and waste by 12%.
Industries
Industry domain know - How with technology (digital) expertise.
Has delivered more than 50 projects globally, >50 Digital transformation workshops, and others. Has the capacity to deliver bespoke solutions over multiple platforms - Cognite, Seeq, Kelvin, Databricks, AWS, Azure, Litmus Edge, and others.
Dinesh Makked is a Principal Value Architect, leading the development and delivery of cutting-edge digital solutions for industrial customers across North America. Based in Roanoke, USA, he is focused on expanding Tridiagonal.ai’s footprint in strategic industries like Oil & Gas, Chemicals, and Forestry.
Dinesh brings over 12 years of experience in industrial AI, Cognite Data Fusion (CDF) implementations, and asset performance management. Prior to joining Tridiagonal.ai, he served as the Head of Data Engineering at Pinnacle Reliability, where he led high-impact projects involving AI-driven reliability and performance solutions.
He holds a Post Graduate degree in Computer Science and is recognized for his hands-on expertise in solving complex industrial problems through data-driven, scalable architectures.
