Curriculum
- 10 Sections
- 73 Lessons
- 2 Days
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- The New Operations Landscape - AI as an Enabler7
- 1.1Evolution of operations: Manual → Digital → Predictive → Autonomous
- 1.2What AI means for Ops leaders: ML, GenAI, Process Mining, Digital Twins
- 1.3Where AI fits in operations: production, maintenance, quality, safety, compliance, reporting
- 1.4Role of Ops teams in enterprise-wide AI enablement
- 1.5AI readiness model for Operations functions
- 1.6Exercise: Identify top 10 time-consuming operational processes suitable for AI
- 1.7Demo: AI summarizing operations logs or plant reports
- AI for Daily Operations Automation8
- 2.1Objective: Reduce operational workload through intelligent automation.
- 2.2AI for SOP automation, shift planning & resource allocation
- 2.3AI-based checklists, inspections & compliance workflows
- 2.4Automating repetitive admin tasks: reports, emails, approval notes
- 2.5AI-enhanced communication between shop floor & leadership
- 2.6RPA + AI for end-to-end workflow automation
- 2.7Exercise: Convert a manual SOP/inspection checklist → AI-automated version
- 2.8Auto-generate daily operations reports using AI
- AI for Operational Data, Dashboards & Reporting7
- 3.1AI for KPI reporting (OEE, downtime, output, yields, cycle time)
- 3.2AI-driven insights from production logs, shift books, QC data, and incident records
- 3.3Control tower capabilities: visibility, alerts, anomaly detection
- 3.4AI for RCA (Root Cause Analysis) from production issues
- 3.5Automated stakeholder updates & executive summaries
- 3.6Exercise: AI-generated “Operations Performance Summary”
- 3.7Transform messy logs into automated insights
- AI in Maintenance, Reliability & Asset Management7
- 4.1AI for predictive maintenance — sensors, algorithms, patterns
- 4.2Predicting failure patterns through ML models
- 4.3Spare parts forecasting & maintenance scheduling
- 4.4AI for lubrication analysis, vibration monitoring & equipment diagnostics
- 4.5Digital twins for asset health & scenario testing
- 4.6Exercise: Predictive maintenance simulation using sample asset data
- 4.7AI recommending preventive tasks & spare part needs
- AI for Quality Control & Process Optimization7
- 5.1AI for defect detection — image analytics & pattern recognition
- 5.2Process optimization using AI-driven parameter adjustments
- 5.3Quality prediction & preventive alerts
- 5.4Reducing rework, scrap & yield losses
- 5.5AI for process variance & capability analysis
- 5.6Exercise: AI-based RCA of a sample quality issue
- 5.7Exercise: Generate an AI-driven process improvement plan
- AI for Resource, Manpower & Capacity Planning7
- 6.1AI-generated shift planning & manpower optimization
- 6.2Dynamic scheduling based on demand, maintenance, & capacity
- 6.3AI for material requirement & resource forecasting
- 6.4Smart allocation for bottleneck operations
- 6.5Linking AI planning tools to ERP/MES
- 6.6Exercise: Create an AI-assisted manpower or shift plan
- 6.7AI-generated capacity plan considering constraints
- AI for Safety, Compliance & Risk Management7
- 7.1AI-based incident prediction (near misses, unsafe acts)
- 7.2Vision AI for PPE, safety violations & hazard identification
- 7.3Predictive risk scoring for plant operations
- 7.4AI for regulatory documentation, safety manuals, audits
- 7.5AI-generated compliance reports & SOP updates
- 7.6Exercise: AI-generated safety audit report
- 7.7Exercise: Analyze a simulated incident using AI for preventive actions
- AI for Supply Chain & Cross-Functional Operations7
- 8.1AI-driven synchronization of production & material planning
- 8.2AI for procurement demand (RM, PM, indirect materials)
- 8.3AI for dispatch scheduling, loading & logistics visibility
- 8.4Linking Ops dashboards with SCM, finance & quality KPIs
- 8.5Multi-functional decision loops with AI support
- 8.6Exercise: Create an AI-enabled cross-functional dashboard
- 8.7Exercise: Simulate a production bottleneck & AI-powered resolution plan
- GenAI for Documentation, SOPs, Trainings & Internal Communication7
- 9.1Auto-generating SOPs, WI (Work Instructions), job aids
- 9.2Automated training content for new operators
- 9.3Meeting notes, reports, escalation templates using AI
- 9.4Digital knowledge base creation & retrieval
- 9.5AI for daily review meetings and production summaries
- 9.6Exercise: Convert a process description → AI-generated SOP
- 9.7Exercise: Create a training-ready “How-To” guide using AI
- Responsible AI, Governance & Implementation Roadmap for Operations9
- 10.1Data governance & security for sensitive operational data
- 10.2AI safety: model accuracy, human oversight, error prevention
- 10.3IT–Ops integration for AI deployments
- 10.4How to pilot, deploy & scale AI in plant operations
- 10.5Building an internal Ops AI COE (Center of Excellence)
- 10.6KPIs to track AI-enabled performance
- 10.7Exercise: Define a governance checklist for Ops
- 10.8Exercise: Build an AI Roadmap for Operations
- 10.9Exercise: Choose 3 high-impact use cases to pilot immediately