Certified International Supply Chain Professional - Preparation Course

This DIXONTECH course delivers advanced knowledge and tools for materials planning and forecasting specifically designed for spare parts management. It focuses on balancing service level, cost, and inventory optimization across complex supply networks. Participants will learn how to forecast spare parts demand accurately, manage unpredictable consumption patterns, and implement bestinclass inventory and replenishment strategies that reduce downtime and operational costs.

TRAINING TOPICS

• Fundamentals of spare parts planning and forecasting
• Spare parts demand characteristics and lifecycle analysis
• Forecasting models for intermittent and slowmoving demand
• Material requirements planning (MRP) and spare parts control
• Inventory optimization and service level management
• Datadriven and AIenhanced forecasting techniques
• Supplier coordination and replenishment strategies
• ERP integration and reporting for spare parts logistics
• Global best practices and case studies

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

• Forecast spare parts demand using modern methods
• Implement efficient materials and inventory planning systems
• Reduce obsolescence and improve service level reliability
• Use ERP and MRP tools for spare parts control
• Apply costeffective replenishment and sourcing strategies
• Manage unpredictable and irregular demand patterns
• Enhance decisionmaking with analytical insights
• Align spare parts management with maintenance strategies

TRAINING IS TAILORED TO:

• Maintenance and asset management professionals
• Materials planners and spare parts controllers
• Supply chain and logistics managers
• Procurement and warehouse supervisors
• Operations and production engineers
• MRO (Maintenance, Repair, and Operations) coordinators
• Inventory and data analysis specialists
• ERP and systems integration professionals

TRAINING METHODOLOGY:

The DIXONTECH methodology integrates theory, practical forecasting models, and handson system simulations. Participants work with case studies, realtime ERP demonstrations, and advanced data analytics for spare parts forecasting. Interactive workshops and scenario analysis sessions ensure direct application of methods to real operational challenges.

DAY 1:

INTRODUCTION TO SPARE PARTS MANAGEMENT AND DEMAND CHARACTERISTICS

• Understanding the role of spare parts in operations continuity
• Classification of spare parts: critical, fastmoving, slowmoving
• Challenges in managing spare parts demand variability
• Demand patterns and consumption behavior analysis
• Differentiating between planned and unplanned demand
• Understanding the spare parts lifecycle and obsolescence risk
• Balancing inventory investment with service level
• The relationship between maintenance, supply, and reliability
• Global trends in spare parts logistics and management

DAY 2:

FORECASTING METHODS FOR SPARE PARTS DEMAND

• Fundamentals of forecasting principles and accuracy
• Time series, moving average, and exponential smoothing models
• Handling intermittent and lumpy demand data
• Croston’s method and its modern adaptations
• Using Poisson and Bayesian models for rare demand events
• Demand classification and model selection techniques
• Data cleaning and preprocessing for forecast reliability
• Forecast validation and performance measurement (MAPE, MAD)
• Practical exercise: forecasting irregular spare parts demand

DAY 3:

MATERIALS PLANNING AND INVENTORY STRATEGIES

• Material requirements planning (MRP) structure and functions
• BOM and spare parts hierarchy configuration
• Reorder point, safety stock, and EOQ models for spare parts
• Stock segmentation (ABC/XYZ and criticality analysis)
• Inventory turnover and optimization indicators
• Balancing cost, service level, and availability
• Dynamic inventory policies for uncertain demand
• Integrating supplier lead time and procurement cycles
• Workshop: designing a spare parts planning system

DAY 4:

ERP INTEGRATION, REPLENISHMENT, AND SUPPLIER MANAGEMENT

• Configuring ERP/MRP systems for spare parts planning
• Data mapping between maintenance and materials systems
• Automatic reorder and replenishment models
• Supplier collaboration and VMI (Vendor Managed Inventory)
• Performance metrics for supplier reliability and delivery
• Multilocation spare parts distribution and transfer planning
• Risk mitigation in parts availability and logistics disruptions
• KPI dashboard design for materials and spare parts control
• Case study: optimizing spare parts network with ERP

DAY 5:

AI, DATA ANALYTICS, AND FUTURE TRENDS IN SPARE PARTS FORECASTING

• Machine learning applications in parts forecasting
• Predictive maintenance and datadriven demand sensing
• Integrating IoT data into spare parts planning
• AIbased optimization for multiechelon inventory
• Scenario analysis and digital twins for spare parts logistics
• Blockchain and smart contracts in parts traceability
• Sustainability and circular spare parts management
• Benchmarking leading global practices
• Final workshop: building a predictive spare parts plan