Master Production Schedule (MPS): A Practical Case Study with Data Analysis

The Master Production Schedule (MPS) is a critical tool in manufacturing that bridges the gap between customer demand, production planning, and inventory management. This article uses a real-life example to illustrate how key metrics—such as Projected Available Balance (PAB), Master Production Schedule Quantity (MPS Quantity), and Available-to-Promise (ATP)—are calculated and applied to maintain an efficient production schedule.

Understanding the Dataset

The MPS example focuses on the production of a single item, with the following assumptions:

• Lot Size: Fixed at 80 units.
• Safety Stock: Set at zero, meaning no additional buffer inventory.
• Forecast: Weekly forecast is 20 units for the first four weeks and 40 units for weeks five to eight.
• Customer Orders: Weekly customer demand varies from 23 units in week 1 to zero units in weeks 5 to 8.
• Initial Inventory (Week 0): Opening inventory of 45 units.

The goal is to ensure demand is met while maintaining an optimal inventory level, scheduling production as necessary, and identifying ATP for new orders.

MPS Data Table

Key Metrics and Their Calculations

1. Projected Available Balance (PAB): The PAB measures the inventory level at the end of each week, ensuring demand is met while avoiding excess stock. It is calculated as: PAB = Previous PAB + MPS Quantity - Max(Forecast, Customer Orders)
2. MPS Quantity: Planned production is triggered only when PAB falls below demand or forecast. MPS quantities are scheduled in fixed lot sizes of 80 units.
3. Available-to-Promise (ATP): ATP indicates the quantity available for new customer orders without disrupting existing commitments. It is calculated as: ATP = MPS Quantity - Sum of Customer Orders until the next MPS release

Insights and Analysis

1. Inventory Control with PAB: The MPS ensures the PAB remains positive across all weeks, reflecting a well-managed inventory strategy that avoids stockouts while minimizing surplus stock.
2. Efficient Production Scheduling: Production (MPS Quantity) is triggered only when necessary to meet future demand, aligning with the fixed lot size of 80 units for operational efficiency.
3. Flexibility with ATP: ATP values provide visibility for accommodating new customer orders without disrupting planned production. For instance, week 5 has an ATP of 80, offering significant flexibility for additional orders.
4. Demand and Forecast Alignment: The example demonstrates how customer orders and forecasted demand are integrated into planning, ensuring production aligns with real-time market needs.

Conclusion

This practical example of an MPS highlights its pivotal role in balancing supply and demand, optimizing inventory, and ensuring production efficiency. By effectively leveraging metrics like PAB and ATP, businesses can streamline operations, meet customer expectations, and maintain high levels of resource utilization. The integration of forecast, customer orders, and production planning underscores the importance of a well-structured MPS in achieving operational excellence.