From the Plant Floor to OEE Dashboards: How to Harness Your Data

Overall Equipment Effectiveness (OEE) is a widely recognized standard for measuring manufacturing productivity. By combining metrics on availability, performance, and quality, OEE provides a clear snapshot of operational efficiency. It matters deeply because improving OEE directly correlates with higher production output, reduced operational costs, and enhanced product quality.However, despite the abundance of data available from modern industrial equipment, a significant gap persists between the raw plant-floor data and actionable insights. Companies often struggle with vast amounts of fragmented information, hindering effective decision-making. The purpose of this blog is to guide you through a clear pathway—from collecting raw data to creating actionable, insightful OEE dashboards.

Understanding Your Plant-Floor Data

Manufacturing operations generate diverse types of data; production rates, equipment downtime, product rejects, and maintenance logs, among others. These data points originate from various sources, including Programmable Logic Controllers (PLCs), Supervisory Control and Data Acquisition (SCADA) systems, Computerized Maintenance Management Systems (CMMS), and historian/SQL databases.

However, harnessing this data isn't straightforward. Many manufacturers face challenges due to siloed systems, inconsistent data formats, and manual tracking processes. Without integrating these isolated sources, valuable insights can remain hidden, preventing meaningful operational improvements.

The Foundation: Clean, Reliable Data

Quality data is foundational for effective dashboards. Inaccurate or inconsistent data can lead to misleading conclusions, causing managers to distrust their dashboards and revert to intuition-based decisions. Ensuring data quality is non-negotiable.

Here are essential steps to improve your data reliability:

• Standardize Naming Conventions: Adopt uniform labeling across your systems. Consistent nomenclature enables seamless integration and clear data interpretation.
• Sensor Reliability and Calibration: Sensors must be routinely checked and calibrated. Faulty sensors can significantly skew data, leading to incorrect analysis.
• Validating Data Collection Methods: Regularly audit data collection processes and ensure that the methods employed are consistent, reliable, and repeatable.

Building the Data Infrastructure

Establishing a robust data infrastructure is crucial. Modern platforms such as Manufacturing Execution Systems (MES), upgraded SCADA solutions, and historian databases offer substantial advantages. These platforms not only centralize data storage but also facilitate real-time analysis and remote access capabilities.

Integration hurdles include:

• Connecting Legacy Systems: Many plants use older equipment that still performs well operationally but lacks modern data integration capabilities. Employing gateways or protocol converters helps integrate these legacy systems into modern analytical platforms.
• Bridging IT and OT: Operational Technology (OT) and Information Technology (IT) often operate in silos. Effective data integration requires bridging this gap to ensure a seamless flow of information from production equipment to enterprise-level systems. Oftentimes, middleware (pieces of software that connect siloed systems) and security solutions must be added.

Setting up OEE Dashboards

To leverage your data effectively, focus on core OEE metrics:

• Availability: This metric reflects planned and unplanned downtime, capturing periods when equipment is not operational. High availability ensures more uptime and higher potential throughput, directly impacting productivity.
• Performance: Performance measures the speed at which equipment operates compared to its designed maximum speed. It assesses slowdowns and minor stoppages, highlighting opportunities for process optimization and efficiency improvements.
• Quality: Quality quantifies the ratio of acceptable products produced versus the total products started. It addresses yield losses due to defects or rework, directly affecting customer satisfaction and reducing waste.

Best practices for creating impactful dashboards include:

• Real-Time Dashboards: Live data provides immediate feedback, enabling quicker decision-making and problem-solving.
• Mobile-Friendly Views: Dashboards accessible on mobile devices allow stakeholders to access data insights from anywhere, increasing responsiveness.
• Alarm and Notification Integration: Timely alerts for specific thresholds help teams promptly address issues before they escalate.

Tools such as Ignition SCADA, Microsoft SQL Server, and robust PLC integrations form an effective technology stack for building these dashboards. These tools provide flexibility, scalability, and powerful analytics capabilities to support a data-driven operation.

Lessons Learned from Real-World Implementations

Experience from multiple industries highlights key lessons. First, effective stakeholder engagement, from plant operators to executives, is critical. Everyone involved should understand the purpose, usage, and value of OEE dashboards. This collective buy-in ensures successful adoption and consistent use.

Common pitfalls include:

• Overcomplicated Dashboards: Simple, intuitive dashboards that highlight critical metrics are far more effective than overly detailed interfaces that users find overwhelming.
• Lack of Follow-up: Generating insights is only valuable if followed by action. Regular meetings to review insights and track improvements ensure dashboards contribute tangible business value.

Conclusion

Harnessing your data effectively is a journey, starting from plant-floor sensors and culminating in strategic, data-driven actions. It’s a journey built upon the foundation of clean, reliable data and robust infrastructure. To begin, start small, prioritize data quality, and build your dashboards incrementally to deliver scalable and impactful insights. By committing to these principles, manufacturers can dramatically enhance their OEE and drive continuous improvement across their operations.

About the Author

Ian Mogab is the Regional Manager and Senior Project Manager leading Hallam-ICS’s Texas expansion. With over 10 years of experience managing large automation and controls projects, he enjoys helping clients improve their processes and manufacturing systems through automation.

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About Hallam-ICS

Hallam-ICS is an engineering and automation company that designs MEP systems for facilities and plants, engineers control and automation solutions, and ensures safety and regulatory compliance through arc flash studies, commissioning, and validation. Our offices are located in Massachusetts, Connecticut, New York, Vermont and North Carolina, Texas and Florida and our projects take us world-wide.