Statistical Process Control and Six Sigma Flashcards

1
Q

PDCA

A

Plan Do Check Act

DO - {Pi}i=1,2,…

ACT - {Xi}i=1,2,…

Sequence of processes {Pi}

and Resulting Products {Xi}i

such that Pi-1 < Pi implies Xi-1 < Xi

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2
Q

Statistical Process Control

A
  • Understanding the process
  • Understanding the causes of variation
  • Eliminiation of the sources of special cause variation
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3
Q

Usage Control Charts

A

1 Select process

2 Identify product or process characteristics that describe process performance

3 Select the appropriate type of control chart

4 Measure process performance over a period of time

5 Use appropriate calculations based on measurement data to determine center lines and control limits for performance characteristics

6 Plot measurement data on control charts

7 Are all measured values within limits and distributed randomly around centerlines?

8 Process is stable; continue measuring

9 Process is not stable

10 Identify and remove assignable causes (Back to 4)

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4
Q

Common questions for investigating an out-of-control process

A
  • Are there differences in the measurement accuracy of instruments/medhotds used?
  • Are there differences in the methods used by different personnel?
  • Is the process affected by the environment?
  • Has there been a significant change in the environment?
  • Is the process affected by predictable conditions?
  • Were any untrained personnel involved in the process at the time?
  • Has there been a change in the soruce for input to the process?
  • Is the process affected by employee fatigue?
  • Has there been a change in policies or procedures?
  • Is the process adjusted frequently?
  • Did the samples come from different part of the process? Shifts? Individuals?
  • Are employees afraid to report ‘bad news’?

Each team should address each ‘Yes’ answer as a potential source of a special cause.

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5
Q

Fishbone Chart

A
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6
Q

Six Sigma

A
  • A business philosophy focusing on continuous improvement
  • Methodology for improving key processes
  • 2 key methodologies
    • DMAIC
    • DMADV
  • DMAIC is used to improve an existing business process
  • DMADV is used to create new product or process designs for predictable, defect-free performance
  • Is based on the following key underling principles of statistical thinking:
    • Everything is a process
    • All processes have inherent variability
    • Data is used to understand variation and to drive decisions to improve the process
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7
Q

Defects per Million Opportunities

A

A six sigma process is one in which 99.99966% of the products manufactured are statistically expected to be free of defects (3.4 defects per million)

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8
Q

DMAIC

A

A general-purose problem solving methodology

Problem or goal statement (Y)

Define

  • Refine problem and goal statements
  • Define project scope and boundaries

Measure - Analyze - Improve - Control

  • An improvement journey to achieve goals and resolve problems by discovering and understanding relationships between process inputs and outputs, such as.

Y = Effectiveness of inspections
= f(size, complexity, duration, reading technique)

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9
Q

DMAIC Roadmap

A

Define:

  • Define Project Scope
  • Establish formal project

Measure:

  • Identify needed data
  • Obtain data set
  • Evaluate data quality
  • Summarize & baseline data

Analyze:

  • Exploure data
  • Characterize process & problem
  • Update improvement project scope & scale

Improve:

  • Identify possible solutions
  • Select solution
  • Implement (pilot as needed)
  • Evaluate

Control:

  • Define control method
  • Implement
  • Document
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10
Q

Revising and Updating Control Limits

A
  • Revising and updating control charts both involve recalculating the control limits but for different reasons and somtimes in different ways.
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11
Q

Revising Control Limits

A
  • You use the initial or trial limits for an onoing chart to omit the following from calculations:
    • Unrepresentative data
    • Special causes
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12
Q

Updating Control Limits

A
  • You use additional, more recently collected data to re-compute the limits based on the following changes:
    • More data is available
    • The process has shifted
    • A deliberate change ahs been made to the process
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13
Q

Quartiles

A

A quartile is any of the three values which divide the sorted data set into 4 equal parts, so that each part represents 1/4th of the sample or population.

i.e. Sorted data can be scatter plot, bell curve, box plot etc

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14
Q

Box Plot

A

Lower tail, Upper tail

Median

Lower quartile, Upper quartile

Scale

|_____|_____|_____|_____|_____|

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