Role-Based Programme
RB1303

AI for Production & Manufacturing Operations

Advanced Process Intelligence, Predictive Operations & Smart Factory Excellence

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across production planning, manufacturing execution, capacity, quality, maintenance, material flow, and continuous improvement.
  • Use AI-assisted analysis to identify production bottlenecks, downtime patterns, quality issues, resource constraints, waste, and performance gaps.
  • Apply AI to production scheduling, root-cause analysis, maintenance planning, quality improvement, inventory coordination, and management reporting.
  • Use AI-assisted analytics to improve throughput, OEE, cycle time, quality, equipment reliability, resource utilisation, and cost efficiency.
  • Build responsible AI-enabled manufacturing workflows with strong safety, validation, governance, data security, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchProduction AnalyticsManufacturing KPI AnalysisDemand & Capacity PlanningProduction SchedulingQuality IntelligencePredictive Maintenance ConceptsDowntime AnalysisRoot Cause AnalysisInventory & Material Flow AnalyticsProcess OptimisationWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Production Managers
  • Manufacturing Managers
  • Plant Operations Managers
  • Production Supervisors
  • Manufacturing Engineers
  • Production Engineers
  • Industrial Engineers
  • Operations Excellence Professionals
  • Process Improvement Managers
  • Plant Performance Analysts
  • Maintenance & Reliability Professionals
  • Quality Operations Professionals
  • Production Planning Professionals
  • Factory Operations Leaders
  • Leaders Responsible for Manufacturing Performance

Prerequisites & Participant Readiness

  • Experience in production, manufacturing, plant operations, industrial engineering, process improvement, or operations management
  • Familiarity with production schedules, manufacturing KPIs, quality, downtime, capacity, and shop-floor processes
  • Basic awareness of Generative AI and common business applications
  • Comfort working with operational, production, equipment, and quality information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, industrial analytics, automation, and AI agents
  • Exploring AI applications across production, quality, maintenance, planning, and plant performance
  • Distinguishing AI-assisted manufacturing decisions from autonomous operational control
  • Understanding hallucinations, unsafe recommendations, data-quality risk, and human accountability
Practical activities
  • Mapping AI opportunities across the manufacturing lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Production and Manufacturing teams

Scenarios

Low OEE & Frequent Downtime to Manufacturing Recovery Plan

Production Data → OEE Analysis → Downtime Patterns → Bottleneck Identification → Root Causes → Maintenance Actions → Process Improvements → Performance Metrics

Participants use AI to diagnose low plant performance, identify recurring downtime and process constraints, prioritise corrective actions, and create a measurable production recovery plan.

High Demand & Capacity Constraints to AI-Enabled Production Plan

Demand Forecast → Capacity → Production Schedule → Material Availability → Bottlenecks → Shift Options → Risk Scenarios → Optimised Production Plan

Participants use AI to analyse rising production demand against constrained capacity, compare scheduling and resource options, identify material and equipment risks, and develop a balanced production plan.

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