AI-Based Operational Risk Dashboard Concept
Overview
Mayford developed a proof-of-concept design for an AI-enabled Operational Risk Dashboard intended to consolidate real-time safety data, maintenance KPIs, inspection status, and leading risk indicators into a single decision-support platform. The concept was designed for deployment across 5 manufacturing facilities and incorporated 54 operational KPIs sourced from SCADA, CMMS (SAP PM), incident reporting systems, and manual inspection logs. The dashboard design included predictive analytics modules for equipment failure forecasting and anomaly detection, built on historical maintenance records spanning 3 years and over 12,000 work orders.
The Challenge
The client — a multi-site industrial manufacturer — managed safety and operational risk data across disconnected systems. SCADA data was monitored in real-time by control room operators but not trended for long-term risk patterns. Maintenance data lived in SAP PM with no linkage to safety KPIs. Incident reports were filed in a standalone database with limited analytical capability. Safety barrier status (e.g., fire suppression, gas detection, emergency shutdown readiness) was tracked via monthly spreadsheets. As a result, site managers relied on lagging indicators and monthly static reports to make decisions, with no ability to detect emerging risk trends or correlate maintenance backlogs with safety performance degradation.
Our Solution
Mayford designed a dashboard architecture integrating 4 primary data sources: SCADA (process variables and alarms), SAP PM (work orders, equipment history, backlog metrics), the client's incident management system (near-misses, first aids, recordable injuries), and field inspection records. The 54 KPIs were organized into 5 risk domains: Process Safety, Occupational Safety, Asset Integrity, Operational Efficiency, and Regulatory Compliance. The concept included a predictive analytics layer using historical failure data from 12,000+ work orders to forecast equipment degradation curves and flag emerging failure risks 30-60 days in advance. The UI was designed with role-based views for plant managers, HSE leads, and maintenance supervisors, each with customized alert thresholds and drill-down capabilities.
