3. Master production scheduling (MPS) & rough-cut capacity planning (RCCP)

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

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).

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.

Prioritizing production: Prioritize high-margin or high-demand SKUs while respecting constraints like setup times or production policies.

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:

SKU	Weekly Demand (Units)	Safety Stock (Units)
FG-10mm	3,125	500
FG-20mm	1,875	300
FG-30mm	1,250	200

Production inputs:

Week	SKU	Planned Production (Units)
Week 1	FG-10mm	3,625
	FG-20mm	2,175
	FG-30mm	1,450

Beginning inventory:

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

SKU	Beginning Inventory
FG-10mm	0
FG-20mm	0
FG-30mm	0

Capacity assumptions:

Capacity Type	Value
Machine Rate	1,500 units/day, operating 5/7 days
Labor Productivity	6 hours/unit
Labor Hours	45,000 / week
Material Requirement	1 kg/unit

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

Week	SKU	Beginning Inventory	Weekly Demand	Safety Stock	Planned Production	Ending Inventory	Available to Promise (ATP)
1	FG-10mm	0	3,125	500	3,625	500	500
1	FG-20mm	0	1,875	300	2,175	300	300
1	FG-30mm	0	1,250	200	1,450	200	200
2	FG-10mm	500	3,125	500	3,625	1,000	1,000
2	FG-20mm	300	1,875	300	2,175	600	600
2	FG-30mm	250	1,250	200	1,450	400	400
3	FG-10mm	1,000	3,125	500	3,625	1,500	1,500
3	FG-20mm	600	1,875	300	2,175	900	900
3	FG-30mm	450	1,250	200	1,450	600	600
4	FG-10mm	1,500	3,125	500	3,625	2,000	2,000
4	FG-20mm	900	1,875	300	2,175	1,200	1,200
4	FG-30mm	650	1,250	200	1,450	800	800

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)

Week	SKU	Planned Production	Machine Days Required	Labor Hours Required
1	FG-10mm	3,625	2.42 days	21,750 hours
1	FG-20mm	2,175	1.45 days	13,050 hours
1	FG-30mm	1,450	0.97 days	8,700 hours
2	FG-10mm	3,625	2.42 days	21,750 hours
2	FG-20mm	2,175	1.45 days	13,050 hours
2	FG-30mm	1,450	0.97 days	8,700 hours
3	FG-10mm	3,625	2.42 days	21,750 hours
3	FG-20mm	2,175	1.45 days	13,050 hours
3	FG-30mm	1,450	0.97 days	8,700 hours
4	FG-10mm	3,625	2.42 days	21,750 hours
4	FG-20mm	2,175	1.45 days	13,050 hours
4	FG-30mm	1,450	0.97 days	8,700 hours

Utilization and key conclusions

Capacity Type	Available	Required (Max)	Utilization
Labor hours	45,000/week	43,500/week	96.67%
Machine days	5 days/week	4.84 days/week	96.8%

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

Master production scheduling: bridging high-level plans with execution