How MPS and RCCP improve production planning efficiency

The role of master production scheduling

Master production scheduling (MPS) bridges high-level production planning with detailed execution. It breaks down the aggregated demand forecasts which we have defined in the previous section into precise schedules for specific products (or SKUs) over a mid-term horizon (usually 3–12 months).  

A good introductory article to MPS by Allics: https://www.allics.be/blog/basics-of-the-master-production-schedule/  

Rough-cut capacity planning introduction

Rough cut capacity planning is looking into the capacity requirements and utilization rates that the master production schedule would require. It is essentially a check on whether the MPS is indeed feasible.  

Sometimes, the RCCP is considered as the high-level production plan, as defined here by Arkieva for instance.  

Key components of MPS & RCCP

Inputs into the MPS (mostly the same as in the high-level production planning but with more details):  

• Demand forecasts: at SKU level, directly from the demand plan or after disaggregation rules 

• Production policies: make-to-stock (MTS), make-to-order (MTO), or a hybrid policy 

• Inventory levels: current stock levels and safety stock requirements 

• Capacity data: machine and labor capacities 

• Production constraints: lead times, batch sizes, and setup times of machines 

Outputs of the MPS: 

• Production schedule: SKU-level weekly or monthly production targets 

• RCCP alignment: ensuring that the capacity is sufficient without overloading 

• Prioritization rules: prioritization of products based on demand, profitability, or other business objectives – some rules about what to do in which case 

• Available-to-promise (ATP): insights into available inventory for unconfirmed orders

Key steps in creating an MPS

1. Disaggregating the demand forecasts: Aggregate demand is disaggregated into specific SKUs based on historical sales ratios, customer orders, or priority customers (if the demand isn’t forecasted at the lowest level already).
    
2. Balancing capacity: Validate that the machine and labor capacities can meet the planned production! RCCP involves a rough estimation of required capacity, ensuring no major constraints exist. Unlike before, this should be done at a weekly level here.  
   
   
3. Prioritizing production: Prioritize high-margin or high-demand SKUs while respecting constraints like setup times or production policies.
    
4. Validation and adjustment: Iteratively validate the schedule against capacity constraints and adjust as needed. 

Example for an insulation manufacturing company

The company in our earlier example produced two types of insulation materials: fiberglass sheets and spray foam.  

See the earlier section for the high-level production and resource plan and the assumptions that came with it.

Here, the MPS needs to look into weekly production requirements and capacity availability.  

Inputs into the plan

Suppose the fiberglass sheets have 3 SKUs, each with a different thickness of the sheet. These are the associated weekly demand & safety stock (16% on top of demand) numbers.

Demand assumptions: 

Production inputs: 

Suppose there is no beginning inventory for each SKU and that we’re only looking at 1 location: 

Capacity assumptions: 

Weekly MPS table at SKU-level 

Here below, we’ll outline the MPS at a weekly level for each SKU, including the weekly demand and production target (considering the safety stock requirement) as well as beginning and ending inventory and the ATP.  

Available-to-promise (ATP) represents the quantity of inventory or production that has not yet been allocated to specific customer orders. It shows how much can still be promised to customers without impacting any other commitments. This can be calculated as: 

ATP = inventory + production − cumulative orders

Weekly RCCP table at SKU-level 

Machine days required: 

Machine days = machine rate / planned production   

Labor hours required: 

Labor hours= planned production × labor productivity (hours/unit) 

Utilization and key conclusions 

Both machines and labor are running almost at max capacity. It’s important to make sure that no steps are missed in this planning: if absenteeism or set-up times etc. would not be properly considered, then these production targets cannot be met.  

Material availability isn’t yet looked into at this moment. All in all, this plan is not reasonable at all unless significant capacity for both labor and machines is found. 

As visually shown in this blog article by Allics, the planned workload vs capacity can be shown for each resource during each specific week to get immediate insights into where the bottlenecks or underutilization are.

Rough cut capacity plan visual by Allics