Subject Overview

Master Production Scheduling examines how aggregate production plans are converted into feasible, time-phased schedules for finished goods and critical components. The subject integrates demand, inventory, capacity, materials, customer commitments, analytics, enterprise systems and managerial governance in manufacturing and service-related production environments.

Learning Goal

Students will be able to design, validate, execute and improve master production schedules; balance demand, materials and capacity; make evidence-based customer and operational decisions; use contemporary planning technologies; and manage scheduling risks, ethics, governance and strategic performance.

Syllabus

1. Foundations of Master Production Scheduling

Learning Objective: Explain the purpose, scope, terminology and evolution of MPS; distinguish forecasts, production plans, master schedules, MRP and detailed shop-floor schedules; identify planning horizons, time buckets and manufacturing environments.

Category: foundation

2. Manufacturing Strategy and Planning Architecture

Learning Objective: Position MPS within business strategy, operations strategy, sales and operations planning, integrated business planning and planning hierarchies; relate scheduling choices to make-to-stock, make-to-order, assemble-to-order and engineer-to-order models.

Category: foundation

3. Demand Management and Forecast Integration

Learning Objective: Integrate forecasts, customer orders, promotions, interplant demand and service-part requirements; apply demand consumption, segmentation, aggregation, disaggregation and forecast-error analysis while preventing double counting.

Category: core

4. MPS Data, Records and Schedule Construction

Learning Objective: Construct time-phased MPS records using beginning inventory, scheduled receipts, lot sizes, safety stock, lead times and projected available balances; select master-scheduled items and establish planning calendars and horizons.

Category: core

5. Bills of Material, Product Structures and MRP Linkages

Learning Objective: Interpret bills of material, planning bills, modular bills and low-level coding; explain MPS explosion into material requirements and assess the effects of engineering changes, lead times and data accuracy.

Category: core

6. Inventory Policies and Lot-Sizing Decisions

Learning Objective: Evaluate lot-for-lot, fixed-order quantity, economic order quantity, periodic ordering and dynamic lot-sizing policies; balance setup, holding, obsolescence, shortage and working-capital implications.

Category: core

7. Capacity Planning and Schedule Feasibility

Learning Objective: Apply rough-cut capacity planning using capacity bills, resource profiles and overall factors; identify bottlenecks, compare finite and infinite capacity assumptions, and reconcile material and capacity constraints.

Category: core

8. Time Fences, Schedule Stability and Change Control

Learning Objective: Use frozen, slushy and liquid zones, demand and planning time fences, firm planned orders and schedule-freezing policies; measure nervousness and evaluate cost, service and operational consequences of schedule changes.

Category: application

9. Available-to-Promise and Customer Order Management

Learning Objective: Calculate discrete and cumulative available-to-promise and capable-to-promise quantities; support order promising, allocation, priority setting, backlog management and profitable customer-service decisions.

Category: application

10. Uncertainty, Buffers and Scenario Planning

Learning Objective: Manage variability in demand, supply, quality and lead times through safety stock, safety time, hedging, decoupling and alternative sourcing; conduct sensitivity, what-if, simulation and contingency analyses.

Category: advanced

11. Advanced Scheduling Models and Optimization

Learning Objective: Formulate scheduling decisions using linear and mixed-integer programming, constraint-based planning, theory of constraints and multi-objective models; evaluate trade-offs among cost, service, utilization, setups and stability.

Category: advanced

12. ERP, APS and Digital Planning Systems

Learning Objective: Assess MPS functionality in ERP and advanced planning and scheduling systems; address data integration, master-data governance, system parameters, digital twins, cloud platforms, interoperability and implementation risks.

Category: contemporary

13. Analytics, AI and Intelligent Scheduling

Learning Objective: Use dashboards, predictive analytics, machine learning and optimization for demand sensing, exception detection, parameter tuning and schedule recommendations; evaluate explainability, human oversight, cybersecurity, bias and data limitations.

Category: contemporary

14. Performance, Governance and Strategic Improvement

Learning Objective: Design governance roles, planning routines and KPIs for schedule attainment, stability, service, inventory, capacity and working capital; lead cross-functional reviews, audit decisions, resolve ethical conflicts and build resilient, sustainable and continuously improving planning systems.

Category: strategic

15. Emerging Models and Future of Master Scheduling

Learning Objective: Critically evaluate Industry 4.0, autonomous planning, real-time replanning, additive manufacturing, servitization, circular production, carbon-aware scheduling and resilient supply networks through cases and implementation roadmaps.

Category: contemporary