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ISE 5563

Quality & Reliability Exam 1 Study Guide

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Re: Quality & Reliability Engineering

STUDY GUIDE

1. Definitions of Quality:

Conformance to requirements. Crosby

Fitness for use. Juran

Quality is about doing things right the first time and satisfying customers. It plays a key role in keeping costs low, revenue high, and profits robust. Perry Johnson, TQM

Inversely proportional to variability.

Quality is what your customer is asking you to do.

2. Dimensions of Quality (8 of them):

Performance will product perform function?

Reliability will product fail and how often?

Durability effective life of product?

Serviceability how quickly/economically can product be repaired?

Aesthetics does product look appealing?

Features does product have more features than others?

Perceived Quality companys reputation?

Conformance to Standards does product meet the design?

3. Quality Costs:

Costs associated with quality in producing, identifying, avoiding, and repairing products not meeting specs.

Prevention engineering, design, training

Appraisal inspection, test equipment

Internal failure costs scrap, rework, retest, downtime

External failure costs complaints, returned products, warranty charges

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4. DMAIC:

Define opportunities

Measure performance

Analyze opportunities

Improve performance

Control performance Some tools used in DMAIC are Six Sigma, Process maps, cause and effect analysis, process capability analysis, etc.

5. Six Sigma:

Problem solving tool to reduce variations and reduce defects for performance excellence. Six Sigma allows 3.4 defects per million.

6. Statistical Quality Control Methods (3 of them):

Acceptance sampling take statistically determined random sample and use decision rule to determine the acceptance/rejection of the lot based on the number of nonconforming.

Statistical process control (SPC) monitoring a process to identify special causes of variation and signal the need to take corrective action.

Design of experiments determine variables in process/product that are critical and their target values, can study many variables at once.

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7. Process Quality Control Tools (Magnificent 7):

Histogram - Visual display of three properties: shape, location/central tendency, spread - Conclusions: normality, skewness, bimodality, kurtosis

Check sheet - Record & classify observed data (tally)

Pareto chart - Frequency diagram of attribute data frequency of defects (doesnt account for

importance) - Pareto principle - 80% effects come from 20% of causes. - 20% of causes (vital few), remaining 80% of causes (useful many)

Cause-and-effect diagram - Formal tool for identifying underlying causes - Cause category, cause/sub-cause, problem

Defect concentration diagram - Picture of unit with defects drawn on pic - Conveys possible info about causes of defects

Scatter plot - Plot of two variables to find potential relationship between them

Control chart - Used to quickly detect process shifts - Visualizes the variations that occur in central tendency and dispersion of a set of

observations - Outside of control limits unnatural variation, assignable causes - Inside of control limits natural variation, chance causes - Use to estimate process parameters, determine capability

8. When to use variable control charts:

Use when data is measured on numerical scale.

Variables (ch.6) - Continuous scale of measurement

Attributes (ch.7) conforming/non-conforming, counts

9. Sample size and sampling frequency:

Larger samples detect smaller shifts (expensive)

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Larger samples at fewer intervals vs. Small samples at frequent interval (industry practice)

Average Run Length (ARL) average number of points that must be plotted before a point indicates out of control condition - ARL = 1/p, p is probability that point exceeds control limits (3sig, p=0.0027, ARL = 370) - ATS = ARL*h, h is time between samples

10. Subgroups:

Maximize chance for difference between subgroups

Minimize difference within a subgroup

11. Type 1 and 2 Error:

Type I Error - Indication of an out-of-control condition when no assignable cause is present (false alarm)

Type II Error - No indication of an out-of-control condition when there is assignable cause present

12. Specification limits and control limits:

Control limits range in which process is in statistical control

Specification limits permissible variation in production output (customer request)

13. When to use what control charts:

Xbar & Rbar for n10

Moving Range for n=1

14. Process capability:

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15. Computational Questions:

16. During the Exam:

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