cpi intel toc lean six sigma may 2008

31
CUSTOMER FULFILLMENT Planning and Logistics Group Using TOC, Lean, and Six Sigma Using TOC, Lean, and Six Sigma to Improve Supply Chain to Improve Supply Chain Operations Operations C. Grant Lindsay, CSCP, Jonah C. Grant Lindsay, CSCP, Jonah Scott Edwards, Jonah Scott Edwards, Jonah

Upload: shahzadhasan

Post on 02-Apr-2015

114 views

Category:

Documents


1 download

TRANSCRIPT

Page 1: CPI Intel TOC Lean Six Sigma May 2008

CUSTOMER FULFILLMENTPlanning and Logistics Group

Using TOC, Lean, and Six SigmaUsing TOC, Lean, and Six Sigmato Improve Supply Chain to Improve Supply Chain

Operations Operations

C. Grant Lindsay, CSCP, JonahC. Grant Lindsay, CSCP, Jonah

Scott Edwards, JonahScott Edwards, Jonah

Page 2: CPI Intel TOC Lean Six Sigma May 2008

2 CUSTOMER FULFILLMENTPlanning and Logistics Group

ObjectiveObjective

Demonstrate how using TOC, Lean, and Six Sigma together can deliver fast measurable results in distribution operations

THIS PRESENTATION CONTAINS THE GENERAL INSIGHTS AND OPINIONS OF INTEL CORPORATION (INTEL). THE INFORMATION IN THIS PRESENTATION IS PROVIDED FOR INFORMATION ONLY AND IS NOT TO BE RELIED UPON FOR ANY OTHER PURPOSE THAN EDUCATIONAL. USE AT YOUR OWN RISK! INTEL MAKES NO REPRESENTATIONS OR WARRANTIES REGARDING THE ACCURACY OR COMPLETENESS OF THE INFORMATION IN THIS PRESENTATION. INTEL ACCEPTS NO DUTY TO UPDATE THIS PRESENTATION BASED ON MORE CURRENT INFORMATION. INTEL IS NOT LIABLE FOR ANY DAMAGES, DIRECT OR INDIRECT, CONSEQUENTIAL OR OTHERWISE, THAT MAY ARISE, DIRECTLY OR INDIRECTLY, FROM THE USE OR MISUSE OF THE INFORMATION IN THIS PRESENTATION.

Page 3: CPI Intel TOC Lean Six Sigma May 2008

3 CUSTOMER FULFILLMENTPlanning and Logistics Group

40 Years of Experience 40 Years of Experience

From our founding in 1968, we’ve grown into the world’s leading silicon innovator with around 86,000 employees, approximately 300 facilities in 50 countries, and over $38 billion in revenues.

Page 4: CPI Intel TOC Lean Six Sigma May 2008

4 CUSTOMER FULFILLMENTPlanning and Logistics Group

IntelIntel’’s Supply Chains Supply Chain

SupplierSupplier

FabFab

FactoryFactory

WarehouseWarehouseOperationsOperations

ShipmentShipmentDeliveryDelivery

CustomerCustomer

Page 5: CPI Intel TOC Lean Six Sigma May 2008

5 CUSTOMER FULFILLMENTPlanning and Logistics Group

Worldwide Manufacturing Worldwide Manufacturing OperationOperationWarehouse NetworkWarehouse Network

Amsterdam

Page 6: CPI Intel TOC Lean Six Sigma May 2008

6 CUSTOMER FULFILLMENTPlanning and Logistics Group

Warehouse and distribution operations have to ship the right orders to the right place at the right time

Page 7: CPI Intel TOC Lean Six Sigma May 2008

7 CUSTOMER FULFILLMENTPlanning and Logistics Group

This is our journey using TOC, Lean, and Six Sigmato improve distribution operations

Page 8: CPI Intel TOC Lean Six Sigma May 2008

8 CUSTOMER FULFILLMENTPlanning and Logistics Group

Understanding the SystemUnderstanding the System

Current Reality Tree

Value Stream Map

Page 9: CPI Intel TOC Lean Six Sigma May 2008

9 CUSTOMER FULFILLMENTPlanning and Logistics Group

Planning the change

““In the long run you In the long run you only hit what you only hit what you aim at.aim at.”” -- ThoreauThoreau

We started here

Identify thecorrect

organizationalgoals

Maintain astable

predictable operation

Page 10: CPI Intel TOC Lean Six Sigma May 2008

10 CUSTOMER FULFILLMENTPlanning and Logistics Group

Warehouse OperationWarehouse Operation

Receiving

WH OrderCreation Order Pick

OrderOrderProcessingProcessing

((WOrPWOrP)QA Order

Packing

OrderStaging

FACTORYFACTORY

InventoryStorage

ProcessingLines

ShipmentShipmentDeliveryDelivery

Page 11: CPI Intel TOC Lean Six Sigma May 2008

11 CUSTOMER FULFILLMENTPlanning and Logistics Group

Before we startedBefore we started……

• High WIP levels

• High Cycle Time at each site

• High Cycle Time Variability from site to site

• Difficult to determine site Output capability

• Balance capacity policy & staffing model

• Safety risks (due to high WIP levels)

Page 12: CPI Intel TOC Lean Six Sigma May 2008

12 CUSTOMER FULFILLMENTPlanning and Logistics Group

Improving Production Operations

DBROld Process New Process

Unbalance CapacityBalance Capacity

Balance FlowUnbalance Flow

It's not about keeping people busy; it's about keeping orders busy.

Page 13: CPI Intel TOC Lean Six Sigma May 2008

13 CUSTOMER FULFILLMENTPlanning and Logistics Group

Example: Single Site ResultsExample: Single Site Results

0

Dai

ly A

vg C

ycle

Tim

e

0 25 50 75 100 125 150 175 200 225Days

Before DBRDBR

Process

Dai

ly A

vg C

ycle

Tim

e

0Before DBR DBR

Process

UnEqual Variances

EstimateStd ErrorLower 95%Upper 95%

3.26633 0.33190 2.61004 3.92263

Difference 9.841

t Test137.528

DF <.0001Prob > |t|

Page 14: CPI Intel TOC Lean Six Sigma May 2008

14 CUSTOMER FULFILLMENTPlanning and Logistics Group

Pull for Lean & SPCWith an understanding of flow and managing constraints, people began to ask questions…

How do I know when the process is running well vs. when I need to fix it?

When do I need to react?

Are there tools available to help us get more out of the constraint?

Page 15: CPI Intel TOC Lean Six Sigma May 2008

15 CUSTOMER FULFILLMENTPlanning and Logistics Group

SPC and Buffer ReportsSPC and Buffer Reports

Cycle Time Cycle Time Control ChartControl Chart

Buffer ReportBuffer Report

Page 16: CPI Intel TOC Lean Six Sigma May 2008

16 CUSTOMER FULFILLMENTPlanning and Logistics Group

World Wide Cycle Time ResultsWorld Wide Cycle Time ResultsC

ycle

Tim

e

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48Months

Before DBRDBRImplementation

ProcessUCLUCL

LCLLCL

CLCL

UCLUCL

LCLLCLCLCL

75% Reduction across all

sites!

Page 17: CPI Intel TOC Lean Six Sigma May 2008

17 CUSTOMER FULFILLMENTPlanning and Logistics Group

Qualitative Results of DBRQualitative Results of DBR

BEFORE

• Operations metrics were not directly effected by daily activity

• Large unexplainable difference in cycle time from site to site

• Difficult order prioritization• Each operation/station was

focused on only their process

AFTER

• Clear link between operations performance and metrics

• Site to site differences are small and can be explained

• Easy order prioritization

• Increase in site team work

Page 18: CPI Intel TOC Lean Six Sigma May 2008

18 CUSTOMER FULFILLMENTPlanning and Logistics Group

Keeping the Momentum GoingKeeping the Momentum Going

• The fast and stable process drove many follow on projects that enabled increased performance– Next Generation Capacity Model– Boards and Systems warehouse implementations– Reduction to early Order Creation

Page 19: CPI Intel TOC Lean Six Sigma May 2008

19 CUSTOMER FULFILLMENTPlanning and Logistics Group

A New Capacity Model

The Old model

• Balanced capacity (resource efficiency)

• Each operation equal

• Numerous static point estimate inputs (9)

• Did not effectively account for variation

• Incomplete decision making (unable to quantify risk)

• Intensive model maintenance

The New Model

• Balanced flow (time efficiency)

• Prioritizes the constraint operation

• Few distribution inputs (3)

• Considers process variability

• More informed decision making (provides estimate of risk)

• Simplified maintenance

Page 20: CPI Intel TOC Lean Six Sigma May 2008

20 CUSTOMER FULFILLMENTPlanning and Logistics Group

Frequency Comparison

.000

.012

.025

.037

.050

50.00 118.75 187.50 256.25 325.00

5 Line Total Output

Demand

Overlay Chart

Frequency Comparison

.000

.012

.025

.037

.050

50.00 118.75 187.50 256.25 325.00

5 Line Total Output

Demand

Overlay Chart

“Next Generation Capacity Model”

INPUTS Monte Carlo Simulation

Simulation based Equations

=)( xf

OIM Operation Heuristics/Assumptions

Model OutputLine & HC

Recommendations

255075100125

Cou

nt

0 10 20 30

255075100125

Cou

nt

0 10 20 30

DN

s

0

100

200

300

400

500

2 3 4 5 6 7

Day

DN

s

0

100

200

300

400

500

2 3 4 5 6 7

Day

DNs per hour

Daily DN Demand

Page 21: CPI Intel TOC Lean Six Sigma May 2008

21 CUSTOMER FULFILLMENTPlanning and Logistics Group

Warehouse OperationWarehouse Operation

Receiving

FACTORYFACTORY

ProcessingLines

ShipmentShipmentDeliveryDelivery

WH OrderCreation Order Pick

OrderOrderProcessingProcessing

((WOrPWOrP)QA Order

Packing

OrderStaging

InventoryStorage

WH Process

Page 22: CPI Intel TOC Lean Six Sigma May 2008

22 CUSTOMER FULFILLMENTPlanning and Logistics Group

Before Six SigmaN

o st

anda

rd w

ork

Inventory co

nsumed early

Inventory on hold

Customer credit problems

Frequent order cancellations

Page 23: CPI Intel TOC Lean Six Sigma May 2008

23 CUSTOMER FULFILLMENTPlanning and Logistics Group

Identifying the Critical Variables

“Control Point”

Inventory HoldsY Y

Cycle Time CancellationsY Y

X

New Tool

Y = f (X)The “Control Point” variable (X) impacts all these metrics (Y)

Page 24: CPI Intel TOC Lean Six Sigma May 2008

24 CUSTOMER FULFILLMENTPlanning and Logistics Group

After Six Sigma…

• Cycle Time – 44% reduction to Mean (41% to St Dev)

• Cancellations – 2 sites tracking– Site 1 - 73% Reduction to Mean (44% St Dev)– Site 2 - 51% Reduction to Mean (70% St Dev)

• Holds– 30% Reduction to Mean (11% St Dev)

• Standardized process • No increase in H/C required• No additional investment required

Page 25: CPI Intel TOC Lean Six Sigma May 2008

25 CUSTOMER FULFILLMENTPlanning and Logistics Group

Bigger SystemBigger System……Bigger ValueBigger Value……

~$15M in inventory savings

Page 26: CPI Intel TOC Lean Six Sigma May 2008

26 CUSTOMER FULFILLMENTPlanning and Logistics Group

Combined Results SummaryCombined Results Summary

• Eight implementations in six countries• Mean cycle time reduction of 75% (over 75% st dev)• Warehouse WIP reduction of over 65%• Fast delivery of operations data (3 weeks to 1 hr)• Next Generation Capacity Modeling• $15M in inventory savings• Increased employee safety• No increase in operating expense• No investment required

Page 27: CPI Intel TOC Lean Six Sigma May 2008

27 CUSTOMER FULFILLMENTPlanning and Logistics Group

Overview of Process

Understand the system – TOC (TP) / Lean (VSM)

Define your scope – TOC (TP) / Lean (VSM)

Ensure proper measures are in place – TOC

Production Improvement

• Remove policy constraints – TOC (TP)

• Improve Production process – TOC (DBR) / Lean / SPC

Exploit the new process

• Next Generation Capacity Model – TOC / Simulation (MC)

• Early Order creation – TOC (TP and CCPM) / Six Sigma

Understanding and usingTOC, Lean, and Six Sigma together is the path to real improvement!

Page 28: CPI Intel TOC Lean Six Sigma May 2008

28 CUSTOMER FULFILLMENTPlanning and Logistics Group

Page 29: CPI Intel TOC Lean Six Sigma May 2008

29 CUSTOMER FULFILLMENTPlanning and Logistics Group

C. Grant Lindsay

C. Grant Lindsay, CSCP, Jonah is a Senior Industrial Engineer in the Supply Chain Strategy and Design department for the Intel Corporation. His professional experience has focused on manufacturing and supply chain process improvement for the semiconductor and aerospace industries. Mr. Lindsay holds a Bachelors Degree in Industrial Engineering from Arizona State University and a Masters Degree in Engineering Management from Washington State University. He is certified in Supply Chain Logistics and the Thinking Process from the Theory of Constraints International Certification Organization (TOC-ICO) and is a member of the TOC-ICO Fundamentals Exam Committee. Mr. Lindsay received his “Jonah” recognition from Washington State University / Avraham Goldratt Institute, is a Certified Six Sigma Black Belt, and an APICS Certified Supply Chain Professional.

[email protected]

480-552-5678

Page 30: CPI Intel TOC Lean Six Sigma May 2008

30 CUSTOMER FULFILLMENTPlanning and Logistics Group

Scott J. Edwards

Scott J. Edwards is an Industrial Engineer in the Supply Chain Industrial Engineering and Statistics department at Intel Corporation. His professional experience includes process improvement, capacity planning and modeling, and network design in logistics/supply chain areas. Scott has a Bachelor of Science degree in Industrial and Management Systems Engineering from Arizona State University and a Masters degree in Business Administration from the University of Phoenix. He is also a certified Six Sigma Black Belt through Arizona State University’s Ira A. Fulton School of Engineering and received his “Jonah” recognition from Washington State University / TOCICO.

[email protected]

480-552-1064

Page 31: CPI Intel TOC Lean Six Sigma May 2008

31 CUSTOMER FULFILLMENTPlanning and Logistics Group

Related Papers

Edwards, Scott and Lindsay, C. Grant “Capacity Modeling with Monte Carlo Simulation for Finished Good Warehouses”. Crystal Ball User Conference, Denver, Colorado May 2006

Lindsay, C. Grant, “TOC in the DC” Institute of Industrial Engineers (IIE), Industrial Engineer magazine, Jun 2005