Master Scheduling, MRP, DRP and Network Planning

Introduction

Supply-chain plans become executable only when aggregate intentions are translated into time-phased decisions. The sales and operations plan may state that a product family should produce 10,000 units next month, but production, procurement, and distribution teams need more precise answers: which finished products are required, in which weeks, in what quantities, at which locations, and with what capacity and material commitments?

Master production scheduling (MPS), material requirements planning (MRP), distribution requirements planning (DRP), and network planning provide this translation. Together they connect market demand with production, purchasing, deployment, inventory positioning, and customer promise dates. Their value is not merely computational. They establish a common planning logic across functions and expose conflicts between demand, materials, capacity, and logistics.

A planning system is effective when it creates feasible, synchronized plans rather than large volumes of rescheduled recommendations. The central managerial challenge is to balance responsiveness with stability: excessive change creates nervousness and cost, while excessive stability can cause shortages, obsolete inventory, or missed opportunities.

Learning Objectives

By the end of this chapter, the reader should be able to:

1. Explain the relationships among the sales and operations plan, MPS, MRP, DRP, and detailed execution.
2. Construct and interpret a master production schedule using demand, inventory, safety stock, and available-to-promise logic.
3. Explode a bill of material into time-phased gross and net material requirements.
4. Apply lead-time offsetting, lot-sizing rules, pegging, and time fences.
5. Explain DRP deployment across a multi-echelon distribution network.
6. Evaluate finite-capacity feasibility, allocation rules, and network-wide synchronization.
7. Assess implementation risks, governance requirements, and the role of digital planning technologies.

1. Planning Architecture: From Strategy to Execution

The planning hierarchy normally contains several linked levels:

The S&OP plan is usually expressed in product families, labour hours, or monetary values. The MPS disaggregates it into specific stock-keeping units (SKUs) or end items. MRP translates end-item schedules into component requirements through bills of material (BOMs). DRP translates distribution demand into replenishment requirements at warehouses, regional depots, and other stocking points.

These systems should not be viewed as independent modules. A production shortage affects the MPS; the MPS affects MRP; component shortages constrain production; production constraints affect DRP; and allocation decisions affect customer service. Network planning therefore requires feedback, not a one-way cascade.

2. Master Production Scheduling

2.1 Purpose and content

The MPS is a time-phased statement of planned production for important end items. It specifies quantities and completion periods, normally by week. It is both a demand-response plan and a control boundary: it tells the factory what output is expected while preserving sufficient stability for materials and capacity planning.

An MPS is developed from:

• independent demand, such as customer orders and forecasts;
• customer-service policies and delivery commitments;
• opening inventory and safety-stock requirements;
• confirmed production and purchase receipts;
• lot-sizing rules;
• capacity constraints and alternative resources; and
• time-fence policies.

Independent demand originates outside the planning structure. Dependent demand is calculated from the demand for another item. For example, demand for bicycles creates dependent demand for wheels, frames, and brake assemblies.

2.2 Time buckets and planning horizons

The planning horizon should cover at least the cumulative lead time of the relevant product plus a decision margin. Weekly buckets are common for tactical planning, although daily buckets may be required for short-life products or constrained operations. A frozen period near the current date protects schedules from constant changes; later periods remain more flexible.

Three zones are frequently used:

• Frozen zone: changes require senior approval because materials, labour, and capacity may already be committed.
• Slushy or semi-frozen zone: changes are possible within defined rules.
• Liquid zone: replanning is relatively easy, subject to policy and capacity.

These zones are often called time fences. Their exact duration should reflect supplier lead times, production setup requirements, customer commitments, and the cost of change.

2.3 Projected available balance and available-to-promise

A simplified projected available balance (PAB) for period t is:

Here, PAB_t is projected ending inventory in units, ScheduledReceipts_t are already committed receipts, MPS_t is planned production completed in period t, and Demand_t is forecast or order demand assigned to the period. The expression assumes that all quantities are measured in the same units and that production and demand occur at the bucket level.

If safety stock is required, a feasible schedule should normally satisfy:

When a shortage would otherwise occur, the MPS quantity or receipt timing must be revised, provided capacity and material availability permit it.

Available-to-promise (ATP) identifies uncommitted supply that may be promised to customers. For the first ATP period:

For later MPS periods:

The first formula includes usable beginning inventory and subtracts orders until the next MPS receipt. The second applies to subsequent MPS receipts. Forecast demand is generally used to calculate the PAB, while confirmed customer orders are used for ATP, although organizations may adopt different order-allocation rules.

Worked example: MPS and ATP

A product has 100 units of opening inventory. Scheduled receipts are 40 units in week 2 and 30 units in week 4. Forecast demand is 60, 80, 70, and 90 units in weeks 1–4. The proposed MPS is 0, 100, 0, and 120 units.

If safety stock is 20 units, the schedule is feasible under the stated assumptions. Suppose customer orders are 25 and 35 units in weeks 1 and 2, and the next MPS receipt after week 2 occurs in week 4. The first ATP is 100 + 0 − (25 + 35) = 40 units, assuming opening inventory is allocated before the week-2 MPS receipt. The week-2 MPS ATP is 100 − (customer orders in weeks 2 and 3 before week 4); if week-2 orders are 35 and week-3 orders are 20, it is 45 units.

ATP is not a promise to manufacture without constraint. It must be checked against material availability, finite capacity, transportation time, and customer-specific eligibility rules.

3. Bills of Material and Material Requirements Planning

3.1 Bill of material structure

A BOM describes the product structure: parent items, component items, usage quantities, and sometimes scrap, substitutes, effectivity dates, and engineering revisions. A single-level BOM shows only immediate components; a multi-level BOM represents all levels from the finished item to purchased raw materials.

If one bicycle requires one frame, two wheels, and one brake set, and each wheel requires 20 spokes, the demand for spokes is dependent on the number of wheels, not directly on the customer forecast. Correct item numbering and revision control are essential because an incorrect BOM produces systematically incorrect requirements.

A planning BOM may represent a family or option mix, whereas a manufacturing BOM must support actual assembly and issue transactions. Confusing the two can distort both requirements and inventory records.

3.2 MRP logic

MRP uses the MPS, BOM, inventory status, scheduled receipts, lead times, and lot-sizing rules to calculate time-phased planned orders. The basic sequence is:

1. Determine gross requirements from parent planned-order releases.
2. Add scheduled receipts and opening inventory.
3. Calculate projected available balance.
4. Identify net requirements when available supply is insufficient.
5. Apply the lot-sizing rule.
6. Offset planned-order receipts by lead time to obtain planned-order releases.
7. Explode the releases to the next BOM level.

For a simple period, net requirements can be expressed as:

where available supply includes usable projected inventory and scheduled receipts, after considering prior-period balances. The max function prevents negative planned requirements. The formula assumes that inventory records are accurate and that all relevant supply is available in the stated period.

A planned-order receipt is the quantity intended to arrive in a period. A planned-order release is the quantity that must be started or ordered earlier. If lead time is two weeks, a receipt required in week 6 has a release in week 4, subject to calendars and supplier working days.

3.3 Lot sizing

Common lot-sizing policies include:

• Lot-for-lot (L4L): order exactly the net requirement. It minimizes cycle inventory but may increase order, setup, or transaction costs.
• Fixed order quantity: order a predetermined quantity, often based on supplier pack size or setup economics.
• Minimum order quantity: order at least a specified quantity.
• Period order quantity: cover requirements for a fixed number of periods.
• Economic order quantity (EOQ): balance ordering and holding costs under relatively stable assumptions.

For the classical deterministic EOQ model:

where Q is order quantity in units, D is annual demand in units per year, S is ordering or setup cost per order, and H is annual holding cost per unit per year. The model assumes relatively constant demand, instantaneous replenishment, no quantity discounts, no shortages, and a constant unit holding cost. It is not automatically appropriate for dependent-demand MRP, where exact time-phased requirements and setup constraints may dominate.

Worked MRP example

A finished product has an MPS receipt of 50 units in week 5. Each finished product requires two units of component A. Therefore, the gross requirement for A is 100 units in week 5. Component A has 20 units of opening inventory, a scheduled receipt of 30 units in week 4, a safety stock of 10 units, and a one-week lead time. Using lot-for-lot:

• Supply available before week 5 = 20 + 30 = 50 units.
• Required supply including safety stock = 100 + 10 = 110 units.
• Net requirement in week 5 = 110 − 50 = 60 units.
• Planned-order receipt = 60 units in week 5.
• Planned-order release = 60 units in week 4.

If component A itself requires a subcomponent B, the release of A creates the gross requirement for B, multiplied by the quantity of B per A and offset according to B’s lead time. This is the essence of multi-level explosion.

Pegging and exception management

Pegging traces a component requirement back to its source: a customer order, MPS receipt, distribution demand, or another parent item. It answers questions such as: “Which customer orders are affected by this shortage?” and “Why does this purchase recommendation exist?”

MRP should be managed by exception rather than by manually reviewing every line. Useful exceptions include late orders, projected shortages, unusually large order changes, invalid dates, excess inventory, and orders outside frozen rules. Exception messages are decision aids; they do not replace professional judgement.

4. Distribution Requirements Planning

DRP applies MRP-style time-phased logic to distribution networks. It begins with demand at stocking locations and calculates replenishment requirements from supplying locations. A distribution structure may contain a central plant, national distribution centre, regional warehouses, and retail or service locations.

At each location, DRP considers:

• forecast and customer demand;
• opening inventory and safety stock;
• in-transit shipments and scheduled receipts;
• transportation and handling lead times;
• order cycles and shipment calendars;
• minimum shipment quantities and vehicle capacity; and
• allocation priorities during constrained supply.

The basic balance relationship is analogous to MRP:

When projected inventory falls below the target level, DRP creates a planned replenishment receipt. That receipt becomes a planned shipment from the supplying node, and the shipment is offset by the transportation lead time. At the supplying node, the requirement becomes demand that must be supported by production, inventory, or an upstream transfer.

Push, pull, and deployment

DRP can operate as a forecast-driven push system, a demand-driven pull system, or a hybrid. Forecast-driven deployment positions inventory in anticipation of demand; pull replenishment responds to consumption or orders. A hybrid is often appropriate: stable base demand may be forecast deployed, while volatile or high-value items are replenished from actual orders.

Deployment is not identical to allocation. Deployment determines where supply should be positioned over time. Allocation determines which customers or locations receive scarce supply when total demand exceeds available supply. Allocation rules may prioritize contractual customers, strategic accounts, emergency requirements, profitability, geographic fairness, or first-come-first-served orders. These rules must be explicit and auditable.

5. Finite Capacity and Network-Wide Synchronization

Traditional MPS and MRP often use infinite-capacity assumptions: they calculate material and production requirements without proving that machines, labour, tooling, docks, suppliers, or transport can perform the work. A plan can therefore be materially complete but operationally impossible.

Finite-capacity planning checks whether required load fits available capacity. For work centre w in period t:

Capacity is feasible when:

Here, quantity is in units, standard time is hours per unit, setup time is hours, and available capacity is effective labour or machine hours after planned downtime, calendars, and efficiency assumptions. The equation is a screening relationship; actual sequencing may create additional constraints such as changeover order, batch precedence, and material availability.

A finite-capacity response may involve moving orders, changing lot sizes, using alternate resources, subcontracting, adjusting priorities, revising the MPS, or negotiating customer dates. The cheapest local solution may be harmful globally. For example, producing a large batch at a plant may reduce setup cost but create regional stock imbalance and transport congestion.

The bullwhip and synchronization problem

Uncoordinated replanning amplifies variability. A small change in retail demand may become a larger change in warehouse replenishment, production orders, and supplier schedules. Time fences, shared forecasts, order visibility, common calendars, and disciplined exception management reduce this amplification.

Network synchronization requires alignment of:

• demand signals and forecast ownership;
• inventory policies at each echelon;
• production and transportation lead times;
• supply allocation rules;
• capacity decisions; and
• master data such as BOMs, locations, calendars, and item attributes.

A useful managerial principle is to optimize total landed cost and service across the network rather than local utilization alone. Metrics should include customer service, schedule adherence, inventory by echelon, expedite cost, capacity utilization, forecast consumption, and plan stability.

6. Illustrative Case: Alpine Appliances

The following is a fictional illustrative case.

Background

Alpine Appliances assembles two models of countertop mixer. The final assembly plant supplies one national distribution centre and three regional warehouses. The company experiences frequent component shortages even though total inventory is rising. Sales frequently changes requested dates, while production planners release large batches to protect utilization.

Problem

The company’s MPS is based on a monthly family forecast, but MRP is run weekly. The BOM for the premium mixer contains an outdated motor revision. Regional warehouses use independent reorder spreadsheets, and no formal allocation rule exists during shortages. The plant has sufficient monthly capacity but a bottleneck test station in weeks 3 and 4.

Analysis

The cross-functional team first cleans the item master, BOM revisions, lead times, and location calendars. It then creates a weekly MPS for each model. A PAB calculation identifies that the proposed MPS falls below safety stock in week 4. ATP analysis shows that sales has accepted orders exceeding genuinely uncommitted supply.

MRP explosion reveals that the motor shortage is caused by the obsolete BOM and by a supplier lead time that was recorded as two weeks instead of four. Pegging links the shortage to premium customer orders. DRP analysis shows that the national distribution centre is deploying stock to one region based on an obsolete forecast while another region is experiencing actual-order shortages.

Finite-capacity analysis shows that the bottleneck test station is overloaded by 18 hours in week 3. Producing more mixers would not improve service unless testing capacity is added or the schedule is resequenced.

Approach and solution

Alpine introduces a two-week frozen MPS zone, a four-week semi-frozen zone, and a monthly liquid horizon. It adopts lot-for-lot planning for the constrained motor and a fixed economic batch for standard packaging. The premium motor is dual-sourced, but the approved substitute is controlled through engineering effectivity and quality approval.

DRP uses regional demand consumption and a transparent allocation rule: contractual orders first, then oldest confirmed orders, with emergency exceptions approved by a supply committee. The national distribution centre receives a weekly deployment plan, while regional safety stocks are differentiated by demand variability and replenishment lead time.

The test-station overload is addressed by cross-training operators and shifting selected models to an alternate certified station. Planners monitor MPS changes, projected shortages, ATP accuracy, plan adherence, and regional fill rate.

Outcome

Within three planning cycles, component shortages decline and emergency freight is reduced. Inventory does not fall uniformly: some obsolete packaging is liquidated, while strategic safety stock for long-lead motors increases. The principal improvement comes from better synchronization rather than from a single forecasting algorithm.

Learning points

1. MRP cannot compensate for inaccurate BOMs, lead times, or inventory records.
2. A feasible MPS requires both material and capacity validation.
3. DRP must distinguish replenishment logic from allocation policy.
4. Time fences protect execution without eliminating responsiveness.
5. Network performance depends on shared data and decision rights.

7. Technology, Governance, and Contemporary Practice

Enterprise resource planning systems integrate MPS, MRP, purchasing, inventory, and order management. Advanced planning and scheduling systems add finite-capacity optimization, scenario analysis, constraint propagation, and alternative-resource modelling. Control-tower platforms improve visibility across suppliers, carriers, plants, and distribution nodes.

Artificial intelligence and machine learning can support demand sensing, lead-time prediction, anomaly detection, supplier-risk assessment, and recommendation ranking. However, AI-generated recommendations remain dependent on data quality, correct constraints, and explainable decision rules. A model that predicts demand accurately but ignores minimum order quantities or testing capacity can produce an infeasible plan.

Important governance practices include:

• ownership of item, BOM, routing, location, and calendar master data;
• approval control for engineering revisions and substitutes;
• audit trails for allocation and priority decisions;
• role-based access to change frozen schedules;
• monitoring for systematic service bias among customers or regions;
• cybersecurity and supplier data protection; and
• periodic validation of planning parameters.

Ethically, allocation rules should not conceal arbitrary discrimination or favour customers solely because they generate greater short-term margins when contractual and public-interest obligations suggest otherwise. Sustainability also matters: lot sizes, deployment frequency, expedited freight, and network design affect emissions and waste. Planning quality should therefore be assessed through service, cost, resilience, and environmental indicators together.

8. Implementation Best Practices and Limitations

Successful implementation normally follows a disciplined sequence:

1. Define planning responsibilities, horizons, calendars, and decision rights.
2. Clean and govern BOMs, routings, lead times, inventory balances, and locations.
3. Establish demand, safety-stock, lot-sizing, and allocation policies.
4. Pilot the MPS and MRP process on a manageable product family.
5. Validate both material feasibility and finite capacity.
6. Connect DRP to actual shipment, consumption, and in-transit data.
7. Use exception dashboards rather than overwhelming planners with messages.
8. Measure plan stability as well as service and inventory outcomes.
9. Review parameters after structural changes, not merely on a fixed calendar.

The methods have limitations. MRP assumes that the product structure and records represent reality. Forecast-driven MPS remains vulnerable to demand error. DRP can propagate poor forecasts through the network. Infinite-capacity logic may create infeasible recommendations. Finite-capacity optimization can be computationally demanding and may oversimplify human, quality, or supplier constraints. Finally, a technically correct plan may fail if users distrust it or if incentives reward local utilization over total network performance.

Chapter Summary

Master scheduling translates aggregate plans and demand commitments into time-phased end-item production. Projected available balance tests whether inventory remains adequate, while available-to-promise identifies uncommitted supply that can support customer commitments. Time fences balance schedule stability with responsiveness.

MRP uses the MPS, BOM, inventory records, lead times, scheduled receipts, and lot-sizing rules to calculate gross requirements, net requirements, planned receipts, and planned releases. Pegging provides traceability from a component requirement to its demand source. DRP applies similar logic across distribution echelons, but deployment must be distinguished from allocation when supply is constrained.

Finite-capacity analysis is essential because material feasibility does not guarantee production feasibility. Network-wide synchronization requires accurate master data, common policies, explicit allocation rules, coordinated calendars, and metrics that reward total supply-chain performance. Digital systems and AI can improve visibility and analysis, but governance, explainability, and human judgement remain indispensable.

Key Terms

Master production schedule: A time-phased plan for producing specific end items.

Projected available balance: Expected inventory remaining after receipts and demand.

Available-to-promise: Uncommitted supply available for customer orders.

Time fence: A boundary controlling how freely a plan may be changed.

Independent demand: Demand originating from customers or the external market.

Dependent demand: Demand calculated from the need for a parent item.

Bill of material: A structured representation of components required for a product.

Material requirements planning: Time-phased calculation of component and material requirements.

Gross requirement: Total requirement before considering existing supply.

Net requirement: Requirement remaining after usable supply is considered.

Planned-order receipt: Quantity planned to become available in a period.

Planned-order release: Quantity scheduled to be started or ordered before its receipt date.

Lot-for-lot: A lot-sizing rule that orders the exact net requirement.

Pegging: Tracing a planned requirement to its originating demand.

Distribution requirements planning: Time-phased replenishment planning across distribution locations.

Deployment: Positioning supply at downstream locations.

Allocation: Assigning scarce supply among competing demands.

Finite-capacity planning: Planning that respects available resource capacity.

Nervousness: Instability caused by frequent planning changes.

Master data: Foundational records such as BOMs, lead times, calendars, and item attributes.

Review Questions

Short Answer Questions

1. What is the primary purpose of a master production schedule?
2. Distinguish independent demand from dependent demand.
3. What is the difference between a planned-order receipt and a planned-order release?
4. Why is pegging useful in MRP?
5. Distinguish deployment from allocation in distribution planning.

Long Answer Questions

1. Explain how S&OP, MPS, MRP, and DRP form an integrated planning hierarchy.
2. Discuss the purpose and managerial implications of frozen, semi-frozen, and liquid time-fence zones.
3. Explain the principal lot-sizing methods used in MRP and their operational trade-offs.
4. Describe how inaccurate BOMs, lead times, and inventory records affect planning outcomes.
5. Discuss why finite-capacity validation is necessary even when an MRP plan is materially complete.

Analytical / Application Questions

1. Construct a four-period PAB schedule for an item with opening inventory, scheduled receipts, forecast demand, safety stock, and a proposed MPS. Identify any infeasible period and recommend a correction.
2. A parent item requires three units of component X. The parent has a planned-order release of 80 units in week 6. Component X has 50 units available before week 6 and a safety stock of 20 units. Calculate the lot-for-lot net requirement and determine the release period if X has a two-week lead time.
3. Design an allocation policy for a distribution network facing a 30% supply shortage. Justify the priority rules, governance controls, and performance measures you would use.

Multiple Choice Questions with Answers

Question 1

Which planning output specifies quantities of specific end items by time period?

A. Sales and operations plan

B. Master production schedule

C. Supplier scorecard

D. Warehouse layout

Correct Answer: B. Master production schedule

Question 2

A product has 120 units of opening inventory, demand of 70 units, and a scheduled receipt of 30 units in a period. With no production in that period, the projected ending balance is:

A. 20 units

B. 50 units

C. 80 units

D. 220 units

Correct Answer: C. 80 units

Question 3

What does pegging primarily provide in an MRP system?

A. A production sequence based only on machine speed

B. A trace from a component requirement to its demand source

C. A method for calculating annual depreciation

D. A warehouse space-allocation rule

Correct Answer: B. A trace from a component requirement to its demand source

Question 4

A finished item requires 4 units of component A. An MPS receipt of 60 finished items is planned. The gross requirement for A is:

A. 15 units

B. 60 units

C. 64 units

D. 240 units

Correct Answer: D. 240 units

Question 5

Under a one-week lead time, a planned-order receipt for component X in week 7 normally requires its planned-order release in:

A. Week 5

B. Week 6

C. Week 7

D. Week 8

Correct Answer: B. Week 6

Question 6

Which lot-sizing rule orders exactly the calculated net requirement?

A. Fixed order quantity

B. Economic order quantity

C. Lot-for-lot

D. Maximum stock level

Correct Answer: C. Lot-for-lot

Question 7

What is the principal purpose of DRP?

A. To calculate employee salaries

B. To plan time-phased replenishment across distribution locations

C. To replace all customer forecasts with production data

D. To determine product engineering tolerances

Correct Answer: B. To plan time-phased replenishment across distribution locations

Question 8

If a work centre has a calculated load of 460 hours and effective available capacity of 400 hours, the plan is:

A. Feasible with 60 hours of spare capacity

B. Infeasible by 60 hours

C. Feasible because MRP ignores capacity

D. Infeasible by 860 hours

Correct Answer: B. Infeasible by 60 hours

Question 9

Which statement best describes available-to-promise?

A. It is all inventory physically present, regardless of commitments

B. It is uncommitted supply that may support customer promises

C. It is the forecast error for a finished item

D. It is the supplier’s annual production capacity

Correct Answer: B. It is uncommitted supply that may support customer promises

Question 10

Which practice most directly reduces planning nervousness?

A. Changing all orders daily without approval

B. Removing inventory records from the planning system

C. Using time fences and controlled schedule-change rules

D. Ignoring capacity constraints until execution

Correct Answer: C. Using time fences and controlled schedule-change rules