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Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized...

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1 Today’s Speaker Carl Lefever, Principal Consultant, Improve & Grow, LLC Certified Lean Six Sigma Master Black Belt Personally completed 100+ projects Mentored 50+ project managers Practical, hands-on approach
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Page 1: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

1

Today’s Speaker

Carl Lefever, Principal Consultant, Improve & Grow, LLC

• Certified Lean Six Sigma Master Black Belt

• Personally completed 100+ projects

• Mentored 50+ project managers

• Practical, hands-on approach

Page 2: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

2

Learning Objectives

• Obtain a working understanding of Lean Six Sigma

• Comprehend daily work as a process-oriented activity

• Understand how your role & process fits within the larger

context of providing value to your customers

• Support & perform process improvement activities

Page 3: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

3

Lean Six Sigma Overview Agenda

• Business Case for Lean Six Sigma

• Origins & Focus of Lean Enterprise

• Origins & Focus of Six Sigma

• Lean Six Sigma Approach

• Lean Six Sigma Methodology & Tools

Page 4: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

4

What is Process Improvement?

Process

• taking anything we do…

Improvement

• and finding ways to do them simpler, faster, better…together

Process

Inp

ut(

s)

Ou

tpu

t(s

)

entering customer orders

manufacturing process

processing claims

creating a forecast

giving feedback to employees

increase order entry accuracy

reduce color variation

reduce lead time

reduce estimate variance

improve feedback effectiveness

Page 5: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

5

Process: “A series of steps leading to a desired outcome”

Process Thinking:

Inputs: Outputs:

Management Control

Prepare

Quote

Approve

Price

Issue quote

& close

Setup

Cust. In DBIssue

PO

Tasks:

Task Thinking:Prepare

Quote

Approve

Price

Setup

Cust. In DB

Issue quote

and close

Issue

POSales Dept.

Accounting Dept.

What is a Process?

Page 6: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

6

The Hidden FactoryWork Arounds

Op i Op i + 1

Analysis ScrapOff-Line

Correction

Correctable

?

Verified

?

NoYes

Quick FixesInspections

Scrap

Rework

Extra EquipmentIncreased Inventory

Increased Cycle Time

Frustration

Defects

Customer Dissatisfaction

Cost

Page 7: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

7

Tangible Quality Costs

Available or easy to measure costs from:

• Inspection

• Rework

• Warranty

• Inventory

Difficult or impossible to measure costs from:

• Lost sales

• Expediting

• Redundancies

• Late payment

• Frustrated

employees

• People & equipment idle time

• Lost customer loyalty

• Long cycle times

• More facilities

• Lost reimbursements

Intangible Quality Costs

• Obsolescence

• Scrap

• Customer complaints

• Legal

Cost of Poor Quality “Iceberg”

Page 8: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

8

Process Improvement Fundamentals The outputs of a process are a function of the process and its’ inputs

This function can be understood by studying inputs, process and outputs

Outputs can be improved by eliminating problems in the process & inputs

Step 1 Step 2 Step 3

Results!

Page 9: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

9

History of Formal Process Improvement Methods

Image courtesy of isixsigma.com

Lean Six Sigma

Formal improvement

methods began in early

1900’s; Lean Six Sigma is

the current expression and

combines thinking and

tools of prior approaches

Page 10: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

10

Lean Six Sigma Approach to Process Improvement

So, what is Lean Six Sigma?

Lean Six Sigma is holistic system for process improvement that

incorporates the waste elimination focus of Lean Enterprise with

the variation reduction techniques of Six Sigma

Lean Enterprise:

The application of principles whose objective is to eliminate WASTE while

improving process flow to achieve SPEED and agility at lower COST

Six Sigma:

The application of principles whose objective is eliminate DEFECTS and

reduce VARIATION to improve process QUALITY

When combined and effectively applied, major improvements are achieved in business performance.

Page 11: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

11

Origins & Focus of Lean

Enterprise

Page 12: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

12

What is Lean Enterprise?

•Lean is a systematic approach to solving daily problems by reducing

or eliminating process waste (non-value-added activities)

•Non-value-added activities are best described as those tasks that add

cost or time to a process without adding value to the customer. Such

activities make up 70-95% of the average workday.

•Examples include reworking defective product, incomplete

information, waiting for materials, excessive motion, unnecessary

inventory, etc.

•Lean is a philosophy whose core goal is continuously minimizing

waste to maximize flow (it is an iterative activity)

Page 13: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

13

Lean Enterprise Approach to Continual Improvement

1. Precisely specify the value of a specific process

2. Identify the value stream for each process

3. Allow value to flow without interruptions

4. Let the customer pull value from the process

5. Continuously pursue perfection

* Womack, J.P, and D.T. Jones, 1996, Lean Thinking, Simon & Schuster

Page 14: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

14

Principle #1 – Specify And Focus On Value

• Any activity or task that the customer is both aware of it and willing to pay for it, is “Value-Added”

• Value added tasks:

• Are meaningful to the customer

• Physically transform the product, process or service

• Are completed correctly the first time

• A good test is “are they willing to pay for it?”

• Based on this (strict) definition of value, we can divide the tasks and activities of any process into three categories:

• Value-Added (VA

• Non-Value-Added (NVA)

• Some add “Business Required” to designate activities that are technically non-value added but are required by the business

Page 15: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

15

Principle #2 – Identify The Value StreamThe Value Stream is the

sequence of steps that lead

from a triggering event

to a final deliverable

C/T = Calendar Time

W/T = Work Time

VA/T = Value-Added Time

Page 16: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

16

Principle #3 – Eliminate Obstacles To Flow Of Value

Value

Wastes are any obstacle

to the continuous flow of value!

Customer

Correction & Repair

Waiting

Wasted Motion

Overproduction

Unnecessary Conveyance

Non-Value Added Processing

Idle Inventory

Page 17: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

17

Principle #4 – Let The Customer Pull Value

Push Production System

• Batch Production

• Based on Forecasts

• Store Inventory

Downstream Effects

• Late Deliveries

• Batches of bad product

• Idle or Obsolete Inventory

Customer Customer

Pull Production System

• Just-in-Time Production

• Make to Order

• Produce When Needed

Downstream Effects

• Faster Delivery Time

• Little to no Inventory

• Lower production costs

Page 18: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

18

Principle #5 – Continuously Pursue PerfectionRaw

Goods

Finished

Product

Sea of Inventory

Inventory allows production to “flow”, but at a tremendous increase in cost

Poor

Scheduling Inspection

& Rework

Setup

Time Communication

Problems

Poor

Service

Redundant

Steps

Raw

Goods

Finished

Product

Poor

Scheduling Inspection

& Rework

Setup

Time Communication

Problems

Poor

Service

Redundant

Steps

To improve the value stream, we must continually find and eliminate problems

Page 19: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

19

Lean Enterprise Tools

Waste Identification Tools

• Value Stream Mapping

• Spaghetti Diagram

Waste Elimination Tools

• 5S’s – Sort, Shine, Set,

Standardize & Sustain

• Visual Workplace

• Quick Change Over (SMED)

• Total Productive Maintenance

(TPM)

Problem Solving Tools

• Kaizen Events

• Fishbone Diagram / 5 Why’s

• Standardized Work

• Mistake Proofing (Poka-Yoke)

Continuous Flow Tools

• Production Signals (Kanban)

• Load Leveling or Balancing

• Cellular Manufacturing

Page 20: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

20

Lean Application Examples

• Used Value Stream Mapping to redesign product

development process for Chemicals company and reduce

cycle time by over 50%

• Applied 5S in Customer Service area, removing over 20

skids of material/equipment and re-organized areas into

work teams for significant workflow improvements

• Implemented Cellular Workflow in electronic document

composition process leading to over 60% reduction in

cycle time & 50% improvement in quality

• Utilized SMED techniques to reduce change over time on

a converting press, reducing setup time from 24 hours to

less than 6 hours for key product line

Page 21: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

21

Origins & Focus of Six Sigma

Page 22: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

22

History of Six Sigma

• Six Sigma developed in 1980’s

• Developed by two Motorola engineers

• Focused on variation to eliminate defects

• Goal was to achieve “six sigma” quality in key processes (99.99996% or 3.4 defects per million opportunities)

• Structured use of existing quality tools

• Relied on data, analysis and statistics to solve problems

• Required rigorous training & certification, like martial arts

• Six Sigma spreads to other large companies in 1990’s

• Allied Signal adopts in 1995 and gains attraction of Wall Street

• General Electric incorporates as overall corporate strategy

• Six Sigma becomes common language in 2000’s

• 1,000’s of companies adopt Six Sigma

• Universities develop formal Six Sigma programs

Page 23: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

23

Corporate Success with Lean Six Sigma

• GE added between $7 to $10 billion in about 5

years

• DuPont added $2.4 billion to its bottom line in the

first 4 years of their Six Sigma program

• Bank of America saved hundreds of millions of

dollars in the first 3 years of their program, cut

cycle times in half and reduced processing errors

by an order of magnitude

• Honeywell achieved record operating margins and

saved more than $2 billion in direct costs

• Motorola saved $2 billion in a 4 year time frame

Page 24: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

24

Six Sigma Core Concepts

Six Sigma is the application of scientific methods to the design and operation of business with the goal of driving improved customer, shareholder and employee value.

Six Sigma Management is:

• Customer Focused: Align processes to meet customer needs

• Data Based Decisions: make decisions based on data vs. gut feel

• Process Driven: Focus on the process not the people

• Projectized Approach: Drive improvement, one project at a time

• Root Cause: address root causes not symptoms

• Pareto Principle: Focus on critical few problems vs. trivial many

• Variation Reduction: Variation is the enemy!

Page 25: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

25

Six Sigma Approach to Continual Improvement

1. Understanding and managing customer

requirements (Voice of the Customer)

2. Aligning business processes to meet customer

requirements (Business Process Management)

3. Rigorous analysis to minimize process variation

4. Drive rapid and sustainable improvement

Page 26: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

26

50454035302520

Lower Spec Limit Upper Spec Limit

Process Capability of Output

#1 Understanding & Managing Customer Requirements

• “Voice of Customer” translates to Process Requirements

• “Voice of Process” translates to Process Capability

Voice of Process

Voice of Customer

Defects

Defects

Page 27: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

27

Process Sigma Level As a Measure of Capability

Mean

USL

s, Spread

LSL

Outside of spec. limits All points in spec.

2 Sigma Process 6 Sigma Process

• Standard Deviation or Sigma

(s) is a measure of variation

from the norm (average)

• The number of standard

deviations between the

average & spec limits

equates to the capability

Page 28: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

28

Six Sigma versus 99% Capability

US Postal Service Mail delivery

VISA Credit Card Transactions

99% = $44 Billion in transactional errors / year

6σ = $1.5 Million in transaction errors / year

99% = 20,000 articles lost /hr

6σ = 7 articles lost /hr

Page 29: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

29

How does Quality Affect Business Performance ?

Sigma Levels & Related Reference Statistics

Company Status

Sigma

Level

% Defect

Free

Defects per

Million

Opportunities

Cost of Poor

Quality

(% Sales)

Non-Competitive 2 Sigma 65% 308,537 >40%

3 Sigma 93% 66,807 25%-40%

Industry Average 4 Sigma 99.4% 6,210 15%-25%

5 Sigma 99.976% 233 5%-15%

World Class 6 Sigma 99.9996% 3.4 <1%

Page 30: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

30

#2 Business Process Management

Order Make Pack Ship

I

N

P

U

T

S

O

U

T

P

U

T

S

SUPPLIERS CUSTOMERS

Overall Performance Feedback &

Improvement Opportunities

Process & Customer

Knowledge

Process Monitoring &

Improvement

Process

Owners

Output

“Healthy processes serving

happy customers!”

Page 31: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

31

The Process Transfer Function

People

Materials

Equipment

Methods

Environment

Y = ƒ (X1, X2, X3, X4,…Xn)

Outputs (Y) are a function of Inputs (X’s)

Page 32: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

32

Identify Possible X’s…

Measure Potential X…

Isolate the Probable X’s…

Improve the Critical X’s…

8-10 x’s

30-50 x’s

4-8 x’s

2-4 x’s

#3 Rigorous Analysis of Process Variation

Control the Critical X’s…

Page 33: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

33

DMAIC Problem Solving Methodology

• Define Problem & Establish Project GoalsDefine

• Measure Problem & Potential CausesMeasure

• Analyze to Isolate Critical Few CausesAnalyze

• Improve Critical Few CausesImprove

• Control the Critical Few to Sustain GainsControl

Page 34: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

34

#4 Drive Rapid & Sustainable Improvement

Project

#1

Project

#2

Project

#3

Project

#4

Time

Imp

rov

em

en

t

Page 35: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

35

Six Sigma Tools

Define

• Project Charter

• Stakeholder Analysis

• Project Plan

• Communication Plan

• Process Maps

• Voice of Customer

Measure

• Fishbone Diagram

• Cause & Effect Matrix

• Data Collection Plan

• Measurement System Analysis

• Time Series Charts

• Capability Analysis

Analyze

• Pareto Charts & Pie Charts

• Box Plots & Dot Plots

• Hypothesis Tests

• Regression Analysis

Improve

• Solution Impact Matrix

• Risk Analysis (FMEA)

• Designed Experiments

Control

• Control Plan

• Control Charts

• Mistake Proofing

• Standard Operating Procedures

Page 36: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

36

Six Sigma Application Examples

• Used Voice of Customer analysis to identify critical product need, enabling replication of competitive product at a fraction of cost

• Isolated vendor contributing inordinate number of returns using Pareto analysis, leading to significant reduction in product returns

• Utilized Designed Experiment to identify new approach to kit assembly resulting in over 25% reduction in costs

• Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory by over 50%

• Applied Control Chart techniques to pressroom waste and reduced paper waste by over 10%

• Used Measurement System Analysis to improve color consistency and make dramatic reduction in claims

• Used Process Maps to identify that 26 of 40 process steps were non-value added, many of which were able to be eliminated through process re-design

Page 37: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

37

Lean Six Sigma Approach

Page 38: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

38

Defining Lean Six Sigma

Lean Six Sigma Is...

• a management philosophy

• an improvement methodology

• a set of performance standards

Lean Six Sigma Is Not…

• A solution for every problem

• A replacement for common sense decision making

Page 39: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

39

Lean Six Sigma Management Philosophy

Lean

Six

Sigma

Lean EnterpriseImprove process speed by

eliminating non-value added

activities in the process

Key Principles

• Define Value Streams

• Identify Non-Value Added

• Eliminate Non-Value Added

• Create Pull Production

• Continuously Pursue Perfection

Six SigmaImprove process quality by

eliminating sources of variation

in the process

Key Principles

• Define Process Problems

• Measure Process & Inputs

• Analyze Variation in Inputs

• Improve Key Process Inputs

• Control Key Process Inputs

Lean Six Sigma is holistic system for process improvement that

incorporates the waste elimination of Lean Enterprise with the

variation reduction techniques of Six Sigma

Successful application provides significant improvements in

customer satisfaction, employee engagement & shareholder value

while reducing costs and increasing revenues

Page 40: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

40

Lean Six Sigma Improvement Methodology

Lean Tools

• Value Stream Maps

• Kaizen Events

• 5S’s

• Spaghetti Diagrams

• Total Productive

Maintenance (TPM)

• Quick Change Over

(SMED)

• Standardized Work

• Mistake Proofing (Poka-

Yoke)

• Operator Balancing

• Cellular Manufacturing

• Pull Production

• Visual Workplace

Six Sigma Tools

• Project Charter & Plan

• Voice of the Customer

• Key Performance Metrics

(KPI’s)

• Critical-to-Quality

Requirements (CTQ’s)

• Process Maps

• Cause & Effect Diagrams

• Data Collection Plans

• Measurement Analysis

• Hypothesis Tests

• Regression Analysis

• Designed Experiments

• Control Charts

• Dashboards

• Rigorous Training – All employees are trained in varying levels (Champion, Black Belts, etc.)

• Projectized Approach – Events & Projects focused on improving key value stream metrics

• Performance Based – Every project has a financial impact and key performance metrics

D

M

A

I

C

Page 41: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

41

Lean Six Sigma Performance Metrics & Standards

• Lean Metrics

• Process Lead Time

• Operational Equipment Effectiveness

• Process Cycle Efficiency

• Six Sigma

• Rolled Throughput Yield

• Cost of Poor Quality

• Sigma Quality Level

Page 42: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

42

Six Sigma Roles & Responsibilities

White Belts

Understand the basic

concepts and tools of

Lean Six Sigma

Yellow Belts

Understands concepts

& learns to use tools as

team member

Green Belts

Lead projects on part-

time basis within their

department

Black Belts

Lead large projects

on full time basis &

coach Green Belts

Master Black Belts

Technical experts &

trainers, coach Black

Belts & lead large,

complex initiatives

Executive Champions

Sponsor improvement

initiatives; initiate &

champion specific projects

Page 43: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

43

Lean Six Sigma Deployment Model

• Train Organization Leaders as Executive Champions

• Conduct Strategic Project Selection & Identify Projects

• Identify & Train Project Leaders

• Form Project Team & Train Team Members

• Execute Projects & Establish Control Plans

• Repeat, Repeat, Repeat Across the Organization

• Support above with the appropriate infrastructure

• Hire/Train Lean Six Sigma Experts

• Establish Process Management Systems

• Align Performance Management Systems

Page 44: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

44

Manufacturing Process Applications

• Improve machine throughput

• Reduce product waste

• Reduce machine setup time

• Reduce equipment downtime

• Reduce work-in-process inventory

• Improve product quality

• Reduce workplace injuries

• Reduce operations cost per unit

• Reduce energy costs

• Eliminate inspection costs

Page 45: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

45

Transactional Process Applications

• Reduce cycle time

• Improve on-time delivery

• Reduce process defects

• Reduce customer returns

• Improve customer response time

• Improve pricing accuracy

• Reduce employee complaints

• Improve employee retention

• Reduce design cycle time

• Increase sales conversion ratio

• Improve advertising response rate

Page 46: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

46

Lean Six Sigma Methodology &

Tools

Page 47: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

47

Lean Six Sigma Problem Solving Roadmap

Identify

Problem &

ObjectivesDEFINE

IMPROVE

CONTROL

Document

Current

Process

Develop

Charter &

Develop Plan

Brainstorm

Potential

Solutions

Conduct

Experiments

to Test

Solutions

Implement

Verified

Solutions

Establish

Process

Control Plan

Validate

Improvements

& Controls

Document

Results &

Close Project

MEASUREDevelop Data

Collection Plan

Assess

Measurement

Systems

Establish

Baseline

Performance

ANALYZEConduct

Process

Analysis

Conduct

Graphical

Analysis

Conduct

Statistical

Analysis

Page 48: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

48

Define PhasePurpose:

•To clarify the problem and plan for improvement

• Problem Statement

• Project Objective

• SIPOC

• Voice of the

Customer

• Stakeholder Analysis

• Project Charter

• Project Plan

• Project Metrics

Primary Tools

Identify

Problem &

ObjectivesDEFINE

Define the

Current State

Develop

Charter, Plan &

Metrics

By the end of the Define phase, you should be able to answer:

•What is the problem we need to solve and the associated costs?

•What is the project objective and related benefits to achieving it?

•What resources will be required to solve the problem?

Page 49: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

49

Identify Problem & ObjectivesIdentify Problem Areas

for Improvement

Narrow Down to

Specific Focus Area

• Business Strategy

• Budget Goals

• Client Feedback

• Financial Metrics

Example:

• Annual product returns

cost $750,000

• Product Types

• Departments

• Customer Segments

Example:

• Assembly errors

represent $225,000 of

total returns

Develop Business

Problem Statement

• Specific metric

• Baseline performance

• Cost of problem

Example:

• In 2013, the assembly

error rate was 5% and

cost $225,000

Develop Specific

Project Objectives

• Metric goal or target

• Due date for project

• Benefits & savings

Example:

• Reduce assembly error

rate by 50% by Sept 30,

saving $100,000

Page 50: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

50

Document Current StateHigh Level Process

Map (SIPOC)

Voice of the Customer

Analysis

Stakeholder

Assessment

Page 51: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

51

Develop Charter, Plan & MetricsProject Charter

Project Plan

Project Dashboard

Page 52: Carl Lefever, Principal Consultant, Improve & Grow, LLC · •Mistake Proofing ... •Utilized Regression Analysis to predict inventory need based on web inquiries, reducing inventory

52

Measure PhasePurpose:

•To gather data on the problem and related variables

• Prioritization Matrix

• Data Collection

Plan

• Data Collection

Forms / Systems

• Variable Gage R&R

• Attribute Gage R&R

• Measurement Audit

• Time Series Chart

• Pareto Chart

• Control Chart

• Histogram

• Capability Study

Primary Tools

By the end of the Measure phase, you should be able to answer:

•What are the variables that are believed to contribute most the problem?

•How good are the data systems we use to measure the process?

•What is the current process capability vs. the process requirements?

MEASUREDevelop Data

Collection Plan

Assess

Measurement

Systems

Establish

Baseline

Performance

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53

Develop Data Collection Plan

Prioritize Key Process Variables

Develop Data Collection Plan

Rating of

Importance to

Customer

7 10 6 8

No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Process

Output

(Y)

Hot

Piz

za

Corr

ect

Ingre

die

nts

Deliv

ery

Tim

e

Pro

perly C

ooked

Total

No.

Process Input

(X)

1 Name 0 0 0 0 0

2 Address 5 0 8 0 83

3 Time 5 0 5 0 65

4 Day 4 0 5 0 58

5 Date 0 0 0 0 0

6 Phone No. 0 0 4 0 24

7 Recipe 0 10 0 4 132

8 Ingredients 4 10 0 4 160

9 Oven Temp 8 0 0 8 120

10 Cook Time 9 0 0 10 143

11 Volume 7 0 8 7 153

12 0

13 0

14 0

15 0

16 0

17 0

18 0

19 0

20 0

Total 294

200

180

264

0 0 0 0 0 0 0 0 0 0 0Measure

Prioritization

Matrix Rank

Type of

Measure Unit Defect What Where When Who

Paint Waste

(Y) Continuous Each Paint > 120%

Std gallons vs.

Actual gallons Weekly/MonthlyLetitia

Solids @ filter

press (Y) Continuous Cycle TBD Pounds/cycle Filter Press Each Cycle Environmentalists

Paint mix Continuous Batch TBD Gallons/batch Mix Bowl Each Batch Paint Mixers

L2 Reclaim

Compliance 2 Discrete Dove <100%

Compliance to

procedures Dove area Each Dove run Operators

Gram

Application 2 Continuous

Dove, Paint

booth, edge TBD Gram application

Paint Booth,

Dove, Edge Hourly Operators

Flex Edge - Continuous Flex Edge TBD L and b Flex Edge Hourly Operators

DOVE Spray 3

Distance of

gun to board 3 Continuous Dove TBD Distance Dove setup Each run Operators

Pressure (x) 3 Continuous Dove TBD pressure Dove setup Each run Operators

Angle (x) 3 Continuous Dove TBD angle Dove setup Each run Operators

# of sec on

and off (x) 3 Continuous Dove TBD time Dove setup Each run Operators

Clarify Data Collection GoalsOperational Definitions and

ProceduresCollection Plan

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54

Accurate & Precise Accurate, but not Precise

Precise, but not Accurate Not Accurate, Not Precise

Assess Measurement Systems

Measurement System Analysis

• Accuracy: Bias, Linearity &

Stability

• Precision: Repeatability,

Reproducibility, Resolution or

Discrimination

Appraiser

Pe

rce

nt

321

100

90

80

70

60

50

40

95.0% C I

Percent

Appraiser

Pe

rce

nt

321

100

90

80

70

60

50

40

95.0% C I

Percent

Date of study:

Reported by:

Name of product:

Misc:

Assessment Agreement

Within Appraisers Appraiser vs Standard

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55

Establish Baseline PerformanceData Stratification

Process Stability

Process Capability

C1

75706560555045

Dotplot of C1

Date

Da

ta

1/30

/200

4

1/27/200

4

1/24

/200

4

1/21

/200

4

1/18

/200

4

1/15/200

4

1/12

/200

4

1/9/20

04

1/6/20

04

1/3/20

04

19.5

19.0

18.5

18.0

17.5

17.0

16.5

16.0

Time Series Plot of Data

50454035302520

LSL USL

Process Capability of Output

Others

Cables

Filters

Pan Dum

ps

Pumping

Pot Dum

ps

EOR

4.947 16.579 85.965134.568150.789168.211378.744

0.5 1.8 9.114.316.017.940.3

100.0 99.5 97.7 88.6 74.2 58.2 40.3

900

800

700

600

500

400

300

200

100

0

100

80

60

40

20

0

Defect

CountPercentCum %

Perc

en

t

Gallon

s o

f P

ain

t

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56

Analyze Phase

Purpose:

•To isolate the critical few variables for improvement

• Value Stream Map

• Cause & Effect

Diagram

• Pareto Charts

• Scatter Plots

• Box Plots

• Hypothesis Tests

• Regression Analysis

Primary Tools

By the end of the Analyze phase, you should be able to answer:

•What are the critical few variables (X’s)?

•How much of the problem do these variables account for?

ANALYZEConduct

Process

Analysis

Conduct

Graphical

Analysis

Conduct

Statistical

Analysis

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57

Conduct Process Analysis

Cause & Effect Diagram & 5-Why

Analysis

Detail Process Maps and/or Value

Stream Mapping

Why?

Why?

Why?Why?

Why?

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58

Box Plots

Pareto Charts

Scatter Plots

Conduct Graphical Analysis

High: 38 to 40% Std: 34 to 37%

0.9

1.0

1.1

Broke level

Densit y

Macon #3 Machine - 755 Minaboard(means are indicated by solid circles)

High: 38 to 40% Std: 34 to 37%

0.9

1.0

1.1

Broke level

Densit y

Macon #3 Machine - 755 Minaboard(means are indicated by solid circles)

Others

Cables

Filters

Pan Dum

ps

Pumping

Pot Dum

ps

EOR

4.947 16.579 85.965134.568150.789168.211378.744

0.5 1.8 9.114.316.017.940.3

100.0 99.5 97.7 88.6 74.2 58.2 40.3

900

800

700

600

500

400

300

200

100

0

100

80

60

40

20

0

Defect

CountPercentCum %

Perc

en

t

Gallon

s o

f P

ain

t

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59

Conduct Statistical Analysis

Regression Analysis

Hypothesis Testing

High: 38 to 40% Std: 34 to 37%

0.9

1.0

1.1

Broke level

Densit y

Macon #3 Machine - 755 Minaboard(means are indicated by solid circles)

High: 38 to 40% Std: 34 to 37%

0.9

1.0

1.1

Broke level

Densit y

Macon #3 Machine - 755 Minaboard(means are indicated by solid circles)

Hypothesis tests are used to confirm

the significance of a given variable on

the output (ex: effect of Material A or B

on product quality levels)

Regression analysis is used to

determine the degree to which a given

variable affects the output (ex: effect

of temperature on tensile strength)

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60

Improve PhasePurpose:

•Identify and implement solutions to address the critical few variables

• Brainstorming

• Solution Impact

Matrix

• Pilot Runs

• Designed

Experiments

• Risk Analysis

• Action Plans

• Communication Plan

Primary Tools

By the end of the Improve phase, you should be able to answer:

•What solutions are believed to have the most impact on the problem?

•What solutions have been proven to affect the most change?

•How can we ensure a successful implementation of the solutions?

IMPROVEBrainstorm

Potential

Solutions

Conduct

Experiments

to Test

Solutions

Implement

Verified

Solutions

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61

Brainstorm Solutions

Brainstorm Solutions

Solution Impact Matrix

Idea #1

Idea #3

Idea #2

Idea #4

Idea #8 Idea #7

Idea #5

Idea #6

Idea #9

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62

Pilot Runs & Designed Experiments

Brainstorming Data Analysis

Speed

Brake Lathes

Operators

Men

Machines

Materials

Methods

Engager BitsCondensation

Angle SocketsMoisture %

Suppliers TrainingInspectors

Lubricants SupervisorsMicroscopes

Alloys ShiftsMicrometers

Measurements

Environment

Speed

Brake Lathes

Operators

Men

Machines

Materials

Methods

Engager BitsCondensation

Angle SocketsMoisture %

Suppliers TrainingInspectors

Lubricants SupervisorsMicroscopes

Alloys ShiftsMicrometers

Measurements

Environment

1 Select solutions to be tested2 Identify operation conditions for

each solution to be tested

3Select & plan experiment strategy

and communicate plan to affected

parties 4 Train operators, conduct

experiments and collect data

5Analyze and

interpret the

results

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63

Implementation Planning

E = Q x AEffectiveness

of Solution

Quality of

Solution

Acceptance of

Solution

Action PlansRisk Analysis Communication Plans

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64

Control Phase

Purpose:

•To develop a plan to sustain the improvements made by the project

• Control Plan

• Control Charts

• Procedures

• Audit Checklists

• Mistake Proofing

• Hypothesis Testing

• Financial Analysis

• Project Report

• Closing Presentation

• Knowledge Transfer

Primary Tools

By the end of the Control phase, you should be able to answer:

•What is the plan to ensure that project gains are sustained?

•How much improvement was made and what is the impact?

•Where else can the project learning be applied in the organization?

CONTROLEstablish

Process

Control Plan

Validate

Improvements

& Controls

Document

Results &

Close Project

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65

Establish Process Control PlanBusiness Dashboards

Control Plan

Control Charts

Process SOP’s,

Checklists, etc.

Visual Controls /

Mistake Proofing

28252219161310741

550

500

450

400

350

300

250

200

_X=350.2

UCL=499.9

LCL=200.5

1

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66

Validate Ability to Control & Sustain Improvements

Prior to closing the project, it is critical to validate:

• Process improvements are sustained

• Control mechanisms work

• Process personnel accept changes

• Stakeholders & Customers have positive feedback

Requested On Date

In

div

idu

al

Va

lue

10/23/200609/27/200608/30/200608/10/200607/21/200607/7/200606/13/200605/30/200605/12/200605/2/200604/3/2006

200

150

100

50

0

_X=6.8

UC L=25.7

LB=0

2006 2Q 2006 3Q 2006 4Q

Requested On Date

Mo

vin

g R

an

ge

10/23/200609/27/200608/30/200608/10/200607/21/200607/7/200606/13/200605/30/200605/12/200605/2/200604/3/2006

160

120

80

40

0

UC L=23.2

LC L=0

2006 2Q 2006 3Q 2006 4Q

__MR=7.1

111

111111

1

111

1

1

111111

1

11

11

11

1

1

1

11

1111

11

1

1

111

Marketing Collateral Cycle Time for C Projects Apr - Oct 2006Baseline Period During Project Control Phase

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67

Document Results & Close ProjectProject Evaluation

Did the project attain the desired results?

Have the results been sustained?

Have the savings been validated and

approved by Finance?

Project Documentation

Have all necessary procedures, audits, charts,

etc. been documented and communicated?

Have necessary project documents been

created?

Team Evaluation

Was the project completed on time on on

budget?

Did the Champion provide the right level of

support?

Did everyone on the team participate as

expected?

Key Learning

What were the key discoveries that lead to the

improvement?

What leverage opportunities exist for other

areas?

Is there any unfinished work that needs to be

monitored?

Have any new projects or opportunities been

identified?

Project Closure

Is the project approved for closure by the

Champion and sponsor?

Has a formal closure event been held with the

project team?

Has the project team been appropriately

recognized for their work?

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68

LSS Case Study: Job Planning Waste Reduction

Define Phase

Analyze Phase

Improve Phase

Measure Phase Control Phase

• Press overproduction

averaged 5%, but ranged

from -50% to +62%

• 10% improvement equates

to $350,000 annual savings

in paper waste

• Print targets are determined

by historical job data & gut

feeling of job planner

• Identified over 100 potential

factors, 15 of which were

believed to be critical

0.300.250.200.150.10

30

25

20

15

10

5

0

Planned Run Waste %

Act

Ru

n w

aste

%S 3.71317

R-Sq 24.1%

R-Sq(adj) 23.6%

Regression

95% PI

Fitted Line PlotAct Run waste % = 3.841 + 55.24 Planned Run Waste %

• Isolated 7 significant

factors & developed

prediction model

• New model produces 25%

less overproduction

• Controls in place to ensure

model is updated as process

changes over time

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69

LSS Case Study: Sales Quotation Win RatioDefine Phase

Analyze Phase

Improve Phase

Measure Phase Control Phase

• Sales believes that lagging

quotation cycle time is

leading to lost jobs

• Customer expectation is

found to be same to next

day turnaround on quotes

• Actual performances is

75% within 24-hr period,

goal is to improve to at least

90%

• Turnaround improves and

correlation to sales

conversion is proven!

• Value Stream Map reveals

process can take up to 48

hrs with 50% rework rate

• Team identified 79 different

non-value added activities

within the value stream

• Simple, medium & complex

product lines are created

with streamlined workflows

• Automated tools are

introduced into the process

543210

0.25

0.20

0.15

0.10

0.05

0.00

Avg Project Quote Turn Days

Prob

abili

ty o

f a

Sale

s O

rder

PredProb

ActProb

Variable

P-value = 0.00

Concordant Pairs (R-Sq) = 55.6%

Scatterplot of Probabilty of Sales Order vs. Turn Days

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70

Lean Six Sigma Summary

• The need for improvement is continual and the best

companies utilize formal process improvement

approaches to stay competitive in the marketplace

• Lean Six Sigma is a holistic system for process

improvement built upon the principles and tools of time

tested methods of Lean Enterprise, Six Sigma & others

• The DMAIC problem solving methodology provides a

structured, project driven approach to continual

improvement

• The application of Lean Six Sigma results in delivery of

products and services at the highest speed and quality

levels possible while lowering cost


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