Push Pull Scm

Company

LOGO

Push-Pull: Strategic Thinking for Operational Excellence

Push-Pull: Strategic Thinking for Operational Excellence

Yang Sun

[email protected]

GWC 521Department of Industrial Engineering

Arizona State University

IE@ASU 2

Teaching Philosophy

• Basics • Basics

• Intuition • Intuition

• Synthesis • Synthesis

Know HowKnow How Know WhyKnow Why

Major Source: Wally Hopp and Mark Spearman, Factory Physics, 2nd Ed., 2000

Company

LOGO Basics

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Essential Context

The IDIB Portfolio• Information

• Decision

• Implementation

• Buffer

Sources: Lee Schwarz, Lecture Notes, 2003Lee Schwarz, "A New Teaching Paradigm: The Information/Control/Buffer

Portfolio", Production and Operations Management 7:2, pp. 125-131, 1998Dan Shunk, “Knowledge Management”, Lecturer Notes.

Data

Information

Knowledge

Org. Learning

Wisdom

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Variability Basics

• Variability is a fact of life. Increasing variability (always) degrades system performance.

• Demand Variability• The Bullwhip Effect (Volatility Amplification Law)• Forecasting Laws

• Process Variability• Think about Little’s Law!

• Technology/Organization Variability• Fruit Flies (Clockspeed Amplification Law)

• Variability will be buffered by some combination of inventory, capacity, and time.

Additional Sources: Hau Lee et al., Information distortion in a Supply Chain: The Bullwhip Effect, Management Science, 43(4), 1997; or The

Bullwhip Effect in Supply Chains, Sloan Management Review 38(3), Spring1997Charley Fine, CLOCKSPEED: Winning Industry Control in the Age of Temporary Advantage, 1998

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Buffer Basics

» Inventory» Capacity» Time

• Buffer Strategy• Buffer Flexibility/Pooling• Buffer Location

• Definition: Lean = Minimal Buffer CostTOYOTA Lean Phases:

[Eliminate Direct Waste] (Value-Add)[Substitute Capacity for Inventory Buffers] (Push -> Pull) [Reduce Variability] [Reduce Capacity Buffers] (Cont. Improv.)

Sources: Wally Hopp, Supply Chain Sciences, 2005

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Lessons from History

• A history of buzzwords

EOQ; MRP; MPR-II; ERP;BPR; MES; APS; Kanban; JIT; TQM; CIM; FMS;

……

• What went wrong?

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Lessons from History (cont’d)

• Problems with traditional approaches:– Scientific Management has stressed math over

realism– MRP is fundamentally flawed, in the basics, not the

details– JIT is a collection of methods and slogans, not

systems

• Bottom lines:– Supply Chain/Manufacturing systems are large scale,

complex, and varied. – No “technological silver bullet” can save us.– Continuous improvement is essential.

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Definition: Supply Network

• A value-oriented network of processes and stockpoints that

deliveries goods and services to customers.

Sources: Wally Hopp, Supply Chain Sciences, 2005

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Definition: Push/Pull Production System

• Push Systems: schedule work releases based on demand.

• Pull Systems: authorize work releases based on system status.

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So, pull is not…

• Kanban– Kanban is a special case of pull– ConWIP is a generalized pull concept

• Make-to-Order: – MRP with firm orders on MPS is make-to-order.– But it does not limit WIP and is therefore a push system.

• Make-to-Stock:– Pull systems do replenish inventory voids.– But jobs can be associated with customer orders.

• Forecast Free: – Toyota’s classic system made cars to forecasts.– Use of tact times or production smoothing often involves

production without firm orders (and hence forecasts).

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The magic of pull…

• Cycle Time (Δt) ↓• Variability ↓• Cost ↓• Service ↑• Quality ↑• Flexibility ↑

You don’t never make nothin’ and send it no place. Somebody has to come get it.– Hall 1983

• I dislike this definition.

• The key is the WIP cap.• Why control the WIP?

• ConWIP• Observability, Efficiency, and Robustness• Overcoming rigidity of pull

WIP

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Exercise

• Are the following systems push or pull?– Kinko’s copy shop– Soda vending machine– “Pure” MRP system– Doctor’s office– Supermarket (goods on shelves)– Tandem line with finite interstation buffers– Runway at O’Hare during peak periods– Order entry server at Amazon.com

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Definition: Push/Pull Supply Chain

• A push supply chain makes production and distribution decisions based on forecasts (Build-to-stock)

• A pull supply chain drives production and distribution by customer orders (Build/Assembly-to-Order)

• Key concept: Location of the push/pull boundary (PPB) (strategic inventory point, inventory/order (I/O) interface)

Source: Simchi-Levi et al., Designing and Managing the Supply Chain, 2003

Material ProcessIntermediateInventory

FinishedGoods

Process Deliver

Push

Push Pull

Pull

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Push/pull Boundary Location

• Real World Examples:– IBM PCB Case– GM Case (WSJ Oct. 21, 96, A1)– HP DeskJet Case (See Lee, Billington, and Carter, HP gains control of inventory

and service through design for localization, Interfaces 23(4), 1993; Feitzinger and Lee, Mass

Customization at HP: The Power of Postponement, HBR Jan-Feb, 1997)

• Goal: eliminate entire portion of cycle time seen by customers by building to stock. (Need for responsiveness)

• Basic Tradeoff: Responsiveness vs. Inventory (Time vs. Cost)

• Levels: Product design (postponement) and process design (quick response mfg)

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Basic Takeaways

• Most systems are hybrid

• Push/pull supply chain is a strategic design– Key: where the push/pull boundary is located– Lead time is the primary driving factor. (Δt)

• Push/pull production is a control policy– Push keywords: Ctrl Release Utilization– Pull keywords: Ctrl WIP Cycle Time (Δt)– A pull thinking is always desired

Company

LOGO Intuition

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The problem is choice

• Yes, but not only…

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Fisher’s Matrix

Source: Marshall Fisher, “What is the right supply chain for your product”, Harvard Business Review, March-April 1997

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Hau Lee’s Matrix

Basic Appeals, Grocery, Food, Most Commodities

Fashion Appeals, Computers, Pop Music, Toys

Some Power, Some Food Produce, Precious Metals

M-commerce, Telecom, High-end Servers, Semiconductor

Demand UncertaintyLow

(Functional Product)

High(Innovative Product)

Low(Stable

Process)

Low(Functional

Product)

High(Evolving Process)

Su

pp

ly U

ncertain

ty

Efficiency, Information Integration, Auto-Replenishment, VMI

(Efficient SC)

Build-to-Order, Flexible Mfg, Accurate Response, Postponement

(Flexible SC)

Buffer Inventory, Shared Resources, Multi-Sourcing, Info Sharing

(Risk-Hedging SC)

Supply Network, Postponement, Design Collaboration

(Agile SC)

Demand UncertaintyLow

(Functional Product)

High(Innovative Product)

Low(Stable

Process)

Low(Functional

Product)

High(Evolving Process)

Su

pp

ly U

ncertain

ty

Source: Hau Lee, “Aligning supply chain strategies with product uncertainties”, California Management Review, 44(3), 2002

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Simchi-Levi’s Matrix

Source: David Simchi-Levi et al., Designing and Managing the Supply Chain, 2003

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Where to locate the PPB?

• Auto• Semiconductor/Electronics• Grocery• …• Everything

Material AssemblyPartsInventory

FinishedGoods

Process Deliver

Push

Push Pull

Pull

Push Pull

Push Pull

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Semiconductor Case Study

Fab Probe Assembly TestDieBank

FinalGoods

DeliveryMaterial

Push

Push Pull

Pull

Source: Yang Sun, Comparing Semiconductor Supply Chain Strategies under Demand Uncertainty and Process Variability, Master’s Thesis, ASU

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Forecasting and Demand Uncertainty

• There is a confusion between two kinds of forecasting: ‘what can be sold (WCBS)’ and ‘what will be sold (WWBS)’ (Montgomery et al. Forecasting and Time Series Analysis, 1990). The former represents the possible market trends. The latter always represents the company’s capacity and budget constraint. Since capacity utilization is extremely important in semiconductor manufacturing, it is always the WWBS forecasts that triggers the production plan (push).

• The semiconductor industry is always under stress: either ‘lack-for-sales’ (LFS) (WCBS < WWBS) or ‘lack-for-capacity’ (LFC) (WCBS > WWBS) (Shunk et al. Electronics Industry Drives of Intermediation and Disintermediation, submitted, 2005)

• Note that huge demand uncertainty EXISTS in the semiconductor industry.

WWBS

WCBS

WCBS (LFC)

(LFS)

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Process Variability

• Integrated into a cycle time distribution– Issues that can affect the variance of mfg cycle times: variable

capacity, shortage of material, variable priorities in lot release, scheduling and dispatching, frequent machine breakdowns, operator error, etc.

– Issues that can affect the variance of delivery time: globally distributed destination, regional traffic condition, variable 3PL/4PL, holding in custom


FinalGoods

DeliveryMaterial

Front-end Back-end Delivery

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Performance Metrics: Cost and Service

• On-time delivery service is of critical importance in today’s semiconductor business, but companies are not doing very well today (case: Gateway penalized Intel by shifting business to AMD to blame Intel’s bad delivery service.)

• Cost (per product sold) performance= front-end mfg costs + back-end mfg costs + inventory (holding) costs + penalty costs based on tardiness

• Delivery cost ignored

• (Quality is a given in SC analysis.)

Penalty

L.T.Due

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The Simulation Model


FinalGoods

DeliveryMaterial

Front-end Back-end Delivery

WWBS

Order Generator based on

WCBS

Forecasts

Push Pull(Pull Strategy)

Pull(Push-PullStrategy)

Pull(Push

Strategy)

Performance

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DOE Factors

Factors Level 1 Level 2 Level 3

Strategy Pull Push-Pull Push

Due-Date Lead Time Tight Medium Loose

Penalty Weight Light Heavy

Demand of Product A LFS (Low) LFC (High)

Demand of Product B LFS LFC

Front-end CT Variability Zero High

Back-end CT Variability Zero High

Delivery Time Variability Zero High

Front-end Mfg Cost Low High

Back-end Cost Prod A Low High

Back-end Cost Prod B Low High

5132 fractional factorial design

Assume: two products, same family, assembled from common generic parent die

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A General Case Instance

Due-date Lead Time or Cited Lead Time

Level 1: Tight Level 2: Medium Level 3: Loose

5 days 30 days 55 days

Penalty per delayed hour

Light Penalty $55 $30 $5

Heavy Penalty $275 $150 $25Process Cycle Time

(days)Level 1

Zero VariabilityLevel 2

High Variability

Front-end Constant (45) Triangular (35,45,55)

Back-end Constant (8) Triangular (5,7,12)

Final Product Delivery Constant (4) Triangular (2,3,7)

Mfg Cost ($/wafer) Level 1: Low Cost Level 2: High Cost

Front-end 2400 4000

Back-end for Commodity Goods 2400 4000

Back-end for High-end Goods 4800 8000

And other assumptions

Duarte, 2001

IC Knowledge, 2003

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The ‘Global’ Experiment: Effects

Since in simulation experiments almost all factors have none-zero effects, Sequential Bifurcation Analysis is suggested by Wan et al. 2003 (QSR Winner paper INFORMS Atlanta ‘03)

•Group Screening: Factors are grouped as ‘Important’ and ‘Unimportant’•Step-Down: In each step, a group of factors are tested for importance

Strategy

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Screened Factorial Effects

• Primary Factors: Due-date Lead Time and Penalty Weight (Δt is the game)

• Secondary Factors: Demand Pattern and Mfg Cycle Time Variability

• Unimportant Factor: Final Product Logistics Time Variability

• (Of course “costs” have significant effects, but do we need to analyze them?)

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Due-dates vs. Penalty Weights

0

2000

4000

6000

8000

10000

12000

1 2 3

Pull

Pushpull

Push

5days 30days 55days Due Day

To

tal C

ost p

er w

afe

r sold

in $

Further Step-Down Analysis

√√

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1 2 3

Pull

Pushpull

Push

5days 30days 55daysDue Day

To

tal C

ost p

er w

afe

r sold

in

$

√

Light Penalty

Heavy Penalty

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Demand Pattern vs. Mfg C.T. Variability

7100

7200

7300

7400

7500

7600

7700

7800

7900

8000

8100

Pull

Push-Pull

Push

$ Total Cost per wafer sold – Product A

Low Variability

High Variability

Low Variability

High Variability

Low Variability

High Variability

6300

6400

6500

6600

6700

6800

6900

7000

7100

Pull

Push-Pull

Push

Low Demand Mid Demand High Demand

Low Demand Mid Demand High Demand

$ Total Cost per wafer sold – Product A

High Variability

Low Variability

High Variability

Low Variability

Low Variability

High Variability

High Variability

medium due-dateand light penalty

loose due-dateand heavy penalty

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The analytical results lead to a conceptual decision framework

Due-Date Lead TimeTight Medium

LooseIm

portance of on

-time delivery

service

Less Im

portan

t F

ar More

Imp

ortant

Push

Pull

Step-down to Layer Two Comparison

This is Layer One

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Layer Two: Push-Pull Can be Appropriate

Layer Two Low Demand (Lack-for-sales)

Average Demand High Demand (Lack-for-capacity)

Low Mfg* Variability

Pull Push Push

High Mfg* Variability

Push-Pull Push-Pull Push

* Manufacturing variability contains both front-end and back-end variability

medium due-date + light penaltyor

loose due-date + heavy penalty

Aggregate Demand

Pro

cess

Varia

bility

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What else can be done?

• Pooling/Postponement• Hybrid

Strategy Postponement of decision

Inventory at die-bank

Inventory at finished goods

No postponement (Push) X

Partial postponement (Push) X X

Die-bank push-pull X X

Hybrid X X X

Source: Alex Brown et al., Xilinx improves its semiconductor supply chain using product and process postponement, Interfaces, 30(4), 2000

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Technology Involvement

Wafer

ProductionTest

FPGA

Standard IC

ASSP

PLD

GA

Structured ASIC

CBIC

Full- Custom IC

System

Set-up

Assembly

& Packaging

Fabrication

& Probe

Process

Product

Wafer

ProductionTest

FPGA

Standard IC

ASSP

PLD

GA

Structured ASIC

CBIC

Full- Custom IC

System

Set-up

Assembly

& Packaging

Fabrication

& Probe

Process

Product

Push

Pull

Source: Joong-In Kim and Dan Shunk, working paper

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Intuition Takeaways

• Δt is the name of the game. From the semiconductor case, lead time customers require and the perceived importance of on-time delivery are the driving factors.

• We also need to understand not only the nature of the demands but that of the processes.

• Supply Chain Visibility (both Demand Stream and Supply Stream) is important.

• Implementation issues should be addressed.• Transition from push to pull needs tremendous

cultural change and technological support.

Company

LOGOSynthesis -- Push-Pull It All Together

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A Customer-Driven Supply Chain Framework

Semiconductor SC example

Source: Yang Sun, Dan Shunk, John Fowler, Proceedings of INFORMS Annual Meeting, San Francisco, Nov. 2005

Info Flow

Material Flow

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DieBank

Wafer Fabrication (W/F) Assembly & Test (A/T)Configuration& Shipment (C/S)

The Semiconductor Flow

RawMaterial

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Critical Decisions in the Semiconductor Supply Chain


W/F – Build the right stock

•How much raw material inventory to hold?

•What categories of products to release? How many to release?

•What priorities are assigned to wafer lots?

•Which A/T facility to ship to?

A/T – Rough cut, loose allocation

•How much die bank inventory to hold? /How much package material inventory to hold?

•What rough cut allocations of lots to anticipated orders are made?

•What priorities are assigned to anticipated orders or factory released lots?

C/S – Who gets what!

•How much finished goods inventory to hold?

•What is the final priorities for firm orders?

•Which lots are assigned to which order, or Who gets what?

•What quantity and mix of products are shipped from which factory to which customer?

Source: Shunk et al., ASU DBR Survey, 2004

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How are they made?


Optimization .45 .35 .20

Heuristics .33 .27 .29

Tacit Knowledge .22 .38 .51

Decision

Technique

Current

Ideal?

W/F A/T C/SOdds Ratio

≈0.25 2004 Survey Result

Logistic Estimation of Probabilities

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Inventory Management

• Key to Supply Chain Management

• Deterministic model – adjust solution- EOQ to compute order quantity, then add safety stock

– EOQ Assumptions (not realistic)

– Key Insight: There is a tradeoff between lot size and inventory

• Stochastic models- news vendor model

- base stock and (Q,r) models

- (s,S) models

- Multi-echelon and network models

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Prioritizing and Releasing

• There is sometimes confusion between the production planning domain and the shop floor control domain. We need to connect planning and execution.

• The releasing function is key to Push-Pull. It connects supply chain planning and factory operation.– Supply Chain: Release by forecast vs. by order– Factory: MRP Push vs. Kanban/ConWIP Pull

• Allocation is important for determining “who gets what”.

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Logistics

• Key to Supply Chain Management

• Often performed by a 3PL or 4PL

• Begin to contribute large portion to the GDP

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Within The Four Walls

Capacity

Release

Scheduling

Dispatching

$$$$

$$$

$$

$

Recommended reading: John Fowler et al., Workload Control in the Semiconductor Industry, Production Planning & Control, 13(7), 2002

Shop floor ctrl

Workforce planning

Quality ctrl

…

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Synthesis and Implementation

• The Strategic Importance of Details

• The Practice Matter of Implementation– System view– Means-ends analysis– Creative alternative generation– Modeling and optimization– Iteration

• Communication and Teamwork

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Coordination and Collaboration

• Value of Info Sharing/SC Visibility• Coordinated Decision Making• Knowledge Sharing and Communities of

Common Interests• Risk Sharing• Contract Management• VMI and CPFR• Remodeling the Supply Chains to pursue Supply

Network Collaboration

Recommended Reading: Gérard Cochan, Matching Supply with Demand, 2005

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We think in generalities, we live in detail.

–Alfred North Whitehead

Documents

Push Pull Scm