Chapter 12 Design for Six Sigma MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson...

Chapter 12Chapter 12

Design forSix Sigma

Thomson Higher Education Publishing1

DFSS Activities• Concept development, determining product functionality

based upon customer requirements, technological capabilities, and economic realities

• Design development, focusing on product and process performance issues necessary to fulfill the product and service requirements in manufacturing or delivery

• Design optimization, seeking to minimize the impact of variation in production and use, creating a “robust” design

• Design verification, ensuring that the capability of the production system meets the appropriate sigma level

Key Idea

Like Six Sigma itself, most tools for DFSS have been around for some time; its uniqueness lies in the manner in which they are integrated into a formal methodology, driven by the Six Sigma philosophy, with clear business objectives in mind.

Tools for Concept Development

• Concept development – the process of applying scientific, engineering, and business knowledge to produce a basic functional design that meets both customer needs and manufacturing or service delivery requirements.

– Quality function deployment (QFD)– Concept engineering

Key Idea

Developing a basic functional design involves translating customer requirements into measurable technical requirements and, subsequently, into detailed design specifications.

Quality Function Deployment

technicalrequirements

componentcharacteristics

processoperations quality plan

Key Idea

QFD benefits companies through improved communication and teamwork between all constituencies in the value chain, such as between marketing and design, between design and manufacturing, and between purchasing and suppliers.

House of Quality

Technical requirements

Voice of the customer

Relationship matrix

Technical requirement priorities

Customerrequirement priorities

Competitive evaluation

Interrelationships

Building the House of Quality

1. Identify customer requirements.2. Identify technical requirements.3. Relate the customer requirements to the

technical requirements.4. Conduct an evaluation of competing products or

services.5. Evaluate technical requirements and develop

targets.6. Determine which technical requirements to

deploy in the remainder of the production/delivery process.

Concept Engineering

• Understanding the customer’s environment.• Converting understanding into requirements. • Operationalizing what has been learned.• Concept generation.• Concept selection.

Tools for Design Development

• Tolerance design• Design failure mode and effects analysis• Reliability prediction

Key Idea

Manufacturing specifications consist of nominal dimensions and tolerances. Nominal refers to the ideal dimension or the target value that manufacturing seeks to meet; tolerance is the permissible variation, recognizing the difficulty of meeting a target consistently.

Tolerance Design

• Determining permissible variation in a dimension

• Understand tradeoffs between costs and performance

Key Idea

Tolerances are necessary because not all parts can be produced exactly to nominal specifications because of natural variations (common causes) in production processes due to the “5 Ms”: men and women, materials, machines, methods, and measurement.

• Design failure mode and effects analysis (DFMEA) – identification of all the ways in which a failure can occur, to estimate the effect and seriousness of the failure, and to recommend corrective design actions.

Reliability PredictionReliability Prediction

• Reliability – Generally defined as the ability of a product to

perform as expected over time– Formally defined as the probability that a

product, piece of equipment, or system performs its intended function for a stated period of time under specified operating conditions

Types of Failures

• Functional failure – failure that occurs at the start of product life due to manufacturing or material detects

• Reliability failure – failure after some period of use

Types of Reliability

• Inherent reliability – predicted by product design

• Achieved reliability – observed during use

Reliability Measurement

• Failure rate (l) – number of failures per unit time

• Alternative measures– Mean time to failure– Mean time between failures

Cumulative Failure Rate Curve

Key Idea

Many electronic components commonly exhibit a high, but decreasing, failure rate early in their lives (as evidenced by the steep slope of the curve), followed by a period of a relatively constant failure rate, and ending with an increasing failure rate.

Failure Rate Curve

“Infant mortality period”

Average Failure Rate

Reliability Function

• Probability density function of failures f(t) = e-t for t > 0

• Probability of failure from (0, T)

F(t) = 1 – e-T

• Reliability function R(T) = 1 – F(T) = e-T

Series Systems

RS = R1 R2 ... Rn

Parallel Systems

RS = 1 - (1 - R1) (1 - R2)... (1 - Rn)

Series-Parallel Systems

• Convert to equivalent series system

RRAA RRBB RRCCRRDD

AA BB C’C’ DD

RRAA RRBB RRDD

RRC’C’ = 1 – (1-R = 1 – (1-RCC)(1-R)(1-RCC))

Tools for Design Optimization

• Taguchi loss function• Optimizing reliability

Key Idea

Design optimization includes setting proper tolerances to ensure maximum product performance and making designs robust, that is, insensitive to variations in manufacturing or the use environment.

Loss Functions

loss lossno loss

nominaltolerance

loss loss

Traditional View

Taguchi’s View

Taguchi Loss Function Calculations

Loss function: L(x) = k(x - T)2

Example: Specification = .500 .020. Failure outside of the tolerance range costs $50 to repair. Thus, 50 = k(.020)2. Solving for k yields k = 125,000. The loss function is:

L(x) = 125,000(x - .500)2

Expected loss = k(2 + D2)

where D is the deviation from the target.

Optimizing Reliability

• Standardization• Redundancy• Physics of failure

Tools for Design Verification

• Reliability testing• Measurement systems evaluation• Process capability evaluation

Key Idea

Design verification is necessary to ensure that designs will meet customer requirements and can be produced to specifications.

Reliability testing

• Life testing• Accelerated life testing• Environmental testing• Vibration and shock testing• Burn-in (component stress testing)

Measurement System Evaluation

• Whenever variation is observed in measurements, some portion is due to measurement system error. Some errors are systematic (called bias); others are random. The size of the errors relative to the measurement value can significantly affect the quality of the data and resulting decisions.

Metrology - Science of Measurement

Accuracy - closeness of agreement between an observed value and a standard

Precision - closeness of agreement between randomly selected individual measurements

Repeatability and Reproducibility

• Repeatability (equipment variation) – variation in multiple measurements by an individual using the same instrument.

• Reproducibility (operator variation) - variation in the same measuring instrument used by different individuals

Repeatability & Reproducibility Studies

• Quantify and evaluate the capability of a measurement system– Select m operators and n parts– Calibrate the measuring instrument– Randomly measure each part by each operator

for r trials– Compute key statistics to quantify repeatability

and reproducibility

Spreadsheet Template

R&R Evaluation

• Under 10% error - OK• 10-30% error - may be OK• over 30% error - unacceptable

Key Idea

One of the most important functions of metrology is calibration — the comparison of a measurement device or system having a known relationship to national standards against another device or system whose relationship to national standards is unknown.

Process Capability

• The range over which the natural variation of a process occurs as determined by the system of common causes

• Measured by the proportion of output that can be produced within design specifications

Types of Capability Studies

Peak performance study - how a process performs under ideal conditions

Process characterization study - how a process performs under actual operating conditions

Component variability study - relative contribution of different sources of variation (e.g., process factors, measurement system)

Process Capability Study

1. Choose a representative machine or process

2. Define the process conditions

3. Select a representative operator

4. Provide the right materials

5. Specify the gauging or measurement method

6. Record the measurements

7. Construct a histogram and compute descriptive statistics: mean and standard deviation

8. Compare results with specified tolerances

Process Capability

specification specification

natural variation natural variation

(a) (b)

natural variation natural variation

(c) (d)

Key Idea

The process capability index, Cp (sometimes called the process potential index), is defined as the ratio of the specification width to the natural tolerance of the process. Cp relates the natural variation of the process with the design specifications in a single, quantitative measure.

Process Capability Index

Cp = UTL - LTL 6

Cpl, Cpu }

UTL - 3

Cpl = - LTL 3

Cpk = min{

Spreadsheet Template

Chapter 12 Design for Six Sigma MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson...

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