AI-Enhanced Production Manager
AI-enhanced management training from DU&T Consulting.
Course overview
This course equips production managers to use artificial intelligence to improve production planning, throughput, quality, resource coordination and decision preparation. It connects practical AI use with lean thinking, safe operations and disciplined performance management.
Participants learn how to evaluate data and recommendations, involve frontline expertise and retain accountability for production decisions. No programming experience is required.
Learning objectives
- Identify suitable AI uses within production management.
- Support production planning, sequencing and capacity analysis.
- Analyse downtime, defects, waste and constraints more efficiently.
- Improve work instructions, shift handovers and production reporting.
- Use AI-assisted scenarios to support labour and material decisions.
- Evaluate predictive and automated solutions before investment.
- Apply safety, quality, security and governance controls.
- Build a practical production AI improvement plan.
Who should attend
Production Managers; Manufacturing Managers; Plant Managers; Shift Managers; Production Supervisors; Industrial and Process Improvement professionals; Quality Managers; and operations leaders responsible for output and efficiency.
Course modules
Module 1: AI Fundamentals in Production
Relevant AI capabilities, limitations, data needs and the production manager's role in oversight and safe adoption.
Module 2: Production Planning and Scheduling
Using AI assistance to compare demand, capacity, sequence, labour and material scenarios while validating constraints.
Module 3: Process Flow Throughput and Bottlenecks
Mapping production flow, analysing cycle time and work in progress, and testing improvement hypotheses.
Module 4: Quality Defects and Waste Reduction
Categorising defects, examining patterns, supporting root-cause analysis and drafting corrective actions for expert review.
Module 5: Workforce Instructions and Shift Management
Improving standard work, skills matrices, shift briefs, handovers and training materials with frontline validation.
Module 6: Production Data KPIs and Decision Support
Interpreting output, downtime, yield and efficiency measures; checking data integrity and communicating performance clearly.
Module 7: Predictive Systems Safety and Governance
Evaluating predictive quality and maintenance tools; addressing safety, cybersecurity, integration, supplier and accountability risks.
Module 8: Pilot Design and Scaled Improvement
Choosing a production use case, setting a baseline, assigning owners, managing change and reviewing measurable results.
Training methodology
The course uses facilitator-led learning, demonstrations, production case studies, process exercises and improvement workshops.
Participants work with fictional or authorised production data to assess schedules, investigate losses and prepare improvement actions. All recommendations are tested against safety, quality and operating requirements.
The course concludes with a production AI pilot charter covering the problem, baseline, intervention, safeguards, responsibilities and success measures.