Aerospace Supply Chain Dynamics

• Managing specific metallic alloy in a cyclical market is a

challenge for aerospace industry.

• When demand for new aeroplanes fluctuates, glut and

shortages of raw materials may occur.

• Suppliers think of exit from the industry.

• Boeing has faced raw material shortages which resulted in

expediting costs to increase and in worst cases shutdown.

• This problem has been studied and CPFR is being used.

• It should generate planned demand for components and

raw materials throughout supply chain.

• It should help mills producing raw materials plan their

capacity and dampen oscillations throughout S.C.

Introduction

• Study involves metallic alloy which constitutes 40% of world demand.

• Figures 18.1 and 18.2 show the demand for aeroplane, price and alloy price &

production.

• Fluctuation in demand for alloy causes fluctuation in production capacity.

• Companies are forced to adjust to Fluctuation.

• Boeing had to stop production for 20 days as cos could not supply components.

• Prices increased, LT also increased by factor of 8.

• Study indicated that oscillations were caused by delays in the system.

• Delay include order processing, delivery, production, capacity adjustment. Reduce

delays but use of IT.

Figure 18.1 : The cyclical nature of the commercial airplane market, from all airplane manufacturers, causes fluctuation in the demand, production and price of aerospace metal. Source: Roskill Information Services (1998)

Figure 18.2 : The increase in demand for raw material, hence shipment, creates a dramatic increase in lead-time (baseline 1993).

Boeing Commercial Aeroplanes Supply Chain

• Figure 18.3 supply chain

• Most suppliers follow made to order policy in the chain

which causes aeroplane deliveries to lag.

• The industry is capital intensive.

• Limited safety stocks are held by suppliers.

• Mills fluctuate from under capacity to overcapacity.

• Various options were explored for modeling the S.C.

• The figure 18.4 shows the propagation of demand for

components that begins with the delivery schedule.

• There is no sharing of information between entities.

Simplified Supply Chain Networks for Boeing Commercial Airplanes

SPW

RM

FSTSPW

PM

RM

M I L L

Fastener Suppliers

CBPM

Machine Shops

PM

CM

SAM

A/CModel

SAB

FST

CB

FST

SAB

CM

CB

PM

Subassembly Suppliers

Final Assembly

Processing House

Figure 18.4 : The lag that occurs from raw material production to airplane delivery is due to the production and delivery delay within the supply chain network in which most of the entities adopt the make-to-order policy.

Figure 18.10 : Simulated result of lead-time for various entities within the supply chain. The simulation is for the case in which the process house and mill wait to adjust production capacity.

• Manufacturing dynamics for process hours and machine

shops are shown in figure.

• Carrying inventory is costly for mills and hence they produce

rods, bars & billets.

• Orders are batched to minimize set up cost.

• Dynamic modeling; system dynamics that operates in a

jobshop environment is used.

The dynamics in a ‘cell’ for a manufacturing facility that operates in a

jobshop environmentCell

BeginningInventory

ProcessBeginning Inventory

Forging Machining Assembly

BilletConversion

HammerClosed – Die

Forging

Interaction among the entities in the current environment. Only demand from the immediate

downstream entity is passed along.

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assemble

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BuyerIssue externalPO

Issue internalPO

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Mill ForgingHouse

MachineShop

An AssemblyHouse

Final AssemblyDeliverySchedule

Efforts to Dampen Oscillations

• Bullwhip phenomena is observed. When suppliers adopt make to stock

policy to meet customer demand.

• Bullwhip effect can be reduced if collaboration is done in SC.

• Strategic partnership like relationship.

ModelDemand Fulfillment

Filling From Stock

BacklogCancellation

Demand Release toProduction

CompletionRate

Filling from Stock

Shipment of Demand lessOscillation

PartsConsumption

PartsOn hand

Receiving

Ordering fromsuppliers

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Parts onOrder

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Each mode in the supply chain performs demand fulfillment & parts replenishment funcitons.

MTO, MTS production policies can use this

Model Consists

• Final assembly facilities that produce unique aroplane models; these facilities

also produce subassemblies and components.

• Subassembly manufacturers from whom the equipment manufacturer

purchases the “buy subassemblies.”

• Component manufacturers from whom the subassembly and the original

equipment manufacturers purchase the ‘buy’ component for subassemblies.

• Process houses that manufacturer processed raw materials for making

components.

• Fastener manufacturers that produce fasteners for assembly.

• Speciality wires for fasteners.

• Mills that provide ingots and billets.

Planning for purchase and Manufacturer of parts in an MTO environment

Order promisingAnd configuration

Forecast

Development ofFinal assemblySchedule (FAS)

Master ProductionSchedule (MPS)

Material RequirementPlanning (MRP)

MPSMRPMRP

Raw MaterialPurchase

Componentmanufacturing

Sub-Assemblymanufacturing

Final Assembly

ComponentPurchase

Sub-AssemblyPurchase

POU RawMaterial

POU RawComponents

Point of Use (POU) Subassemblies

Forecast

Customer Order

Demand Management

(1)

(2)

(4)

• PM – Processed material

• SPW – Speciality wire

• FST – Fastener

• CB – Components for Boeing

• CM – Component manufacturer

• SAB – Subassemblies produced for Boeing

• SAM – Major subassemblies

• 800% increase in lead time from the mill caused by approximate 100% increase in OEM production.

• Simulations carried out & observed behaviour is shown in figure 18.10• Figure 18.11 gives simulated response of lead time dynamics when mills and

process houses are 80%. responsive

• When the mill adjusts its production capacity as a response to a doubling in demand, the mill experiences a low percentage increase in its lead time.

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Discrete Event Modelling

• It is used to study the effect of complexity & variation within

the system

• It requires significant amount of data

• Software used was “supply Chain Guru” from crystallize inc.

as the modeling tool. The data required are :

• Products (mill products, processed parts, minor/major

subassemblies etc.

• The BOM for airplane product

• Inventory policies are used to replenish and manage the parts

inventory.

Sourcing policies determine the selection of specific suppliers

to provide certain parts.

Transportation policies determine the time, method and route

of transportation.

End-item demand drives the downstream requirements in the

supply chain.

To completely describe S.C. network, software requires data

on initial inventory levels, cost, price, weight etc.

Data composed of 200 suppliers, 40 material types, tons of

thousands of parts & assemblies and ten years of record.

This enabled researcher to observe the behaviour of SC when

changes are made.

In Practicum

Figure 18.1 is an output from the simulation model.

It can be seen in the figure that processing shops experience ups and downs of

the delivery of planes.

Figure 18.13 shows the result of inventory policies for suppliers of Tiers 1

through 5.

Shortage or surpluses are observed.

Purchasing ordering habits of Boeing’s Global Supply Base are studied.

Due to long lead time nature of industry under study, the supply base must

place its orders far into the future.

Boeing should anticipate problems rather than react to problems, the serious

perturbations in the supply chain can be mitigated.

Figure 18.11 : When the mill adjusts its production capacity as a response to a doubling in demand, the mill experiences a low percentage increase in its lead-time

Figure 18.12 : Raw material shipped to Processing House XYZ and Machine Shop ABC.

Figure 18.13 : Inventory policies using various safety stocks levels for Tiers 1 through 5 in the supply chain.