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58 Cards in this Set
- Front
- Back
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Total Quality (TQ) |
A total system approach to improving customer satisfaction and lowering real cost through a strategy of continuous improvement and learning |
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Six Sigma |
A methodology that uses measurement and statistical analysis to achieve a level of quality so good that for every million opportunities no more than 3.4 defects will occur
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Quality Control |
A series of inspections and measurements that determine whether quality standards are being met |
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Assignable casuses |
Variations in process outputs that are due to factors such as machine tools wearing out, incorrect machine settings, poor-quality raw materials, operator error, and so on. Corrective action should be taken when assignable causes of output variation are detected |
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Common Causes |
Normal or natural variations in process outputs that are due purely to chance. No corrective action is necessary when output variations are due to common causes |
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Control Chart |
A graphical tool used to help determine whether a process is in control or out of control |
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x chart |
A control chart used when the quality of the output of a process is measured in terms of the mean value of a variable such as a length, weight, temperature, and so on |
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R chart |
A control chart used when the quality of the output of a process is measured in terms of the range of a variable |
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P chart |
A control chart used when the quality of the output of a process is measured in terms of the proportion defective |
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np chart |
A control chart used to monitor the quality of the output of a process in terms of the number of defective items |
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Lot |
A group of items such as incoming shipments of raw materials or purchased parts as well as finished goods from final assembly. |
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Acceptance Sampling |
A statistical method in which the number of defective items found in a sample is used to determine whether a lot should be accepted or rejected |
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Producer's risk |
The risk of rejecting a good-quality lot; a Type I error |
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Consumer's risk |
The risk of accepting a poor-quality lot; a Type II error |
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Acceptance criterion |
The maximum number of defective items that can be found in the sample and still indicate an acceptable lot |
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Operating characteristic (OC) curve |
A graph showing the probability of accepting the lot as a function of the percentage defective in the lot. This curve can be used to help determine whether a particular acceptance sampling plan meets both the producer’s and the consumer’s risk requirements |
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Multiple sampling plan |
A form of acceptance sampling in which more than one sample or stage is used. On the basis of the number of defective items found in a sample, a decision will be made to accept the lot, reject the lot, or continue sampling |
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Quality |
the totality of features and characteristics of a product or service that bears on its ability to satisfy given needs |
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Total quality |
people-focused management system that aims at continual increase in customer satisfaction at continually lower real cost total system approach and an integral part of high-level strategy |
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Total quality is based on three fundamental principles |
1. a focus on customers and stakeholders 2. participation and teamwork throughout the organization 3. a focus on continuous improvement and learning |
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Dr. Walter A. Shewart |
1.developed a set of principles that are the basis for what is known today as process control 2.constructed a diagram that would now be recognized as a statistical control chart 3brought together the disciplines and statistics, engineering, and economics and changed the course of industrial history 4.recognized as the father of statistical quality control 5.first honorary member of ASQ |
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Dr. W. Edwards Deming |
1.helped educate the Japanese on quality management shortly after world war II 2. stressed that the focus on quality must be led by managers 3.developed a list of 14 point she believed represent the key responsibilities of managers 4. japan named its national quality award the Deming prize in his honor |
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Joseph Juran |
1. helped educate the Japanese on quality management shortly after World War II 2. proposed a simple definition of quality: fitness for use 3. his approach to quality focused on three quality processes: quality planning, quality control, and quality improvement |
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Malcolm balridge national quality award |
established in 1987 and given by the U.S. president to organizations that judged to be outstanding in 1. leadership 2. strategic plan 3. customer and market focus 4. measurement, analysis and knowledge mgmt. 5. hum. resource focus 6. process management 7. business results |
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MalcolmBaldrige National Quality Award (
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• The first awards were presented in1988. •The Award is named for MalcolmBaldrige, whowas U.S.Secretary of Commerce from 1981-87 •The U.S. Commerce Department’sNational Institute of Standards and Technology (NIST) managesthe Award.
•In 2003, the “BaldrigeIndex” ( a hypothetical stock index comprised of BaldrigeAward winnin companies) outperformed the S&P 500 by4.4 to 1. |
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ISO 9000 |
• A series of five standardspublished in 1987 by the International Organization forStandardization in Geneva, Switzerland
•The standards describe the needfor: 1.an effective quality system, 2. ensuring that measuring and testing equipment is calibrated regularly, and 3. maintaining an adequate record-keeping system. • ISO 9000 registration determineswhether a company complies with its own qualitysystem. |
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Six sigma |
this level of quality means that for every million opportunities no more than 3.4defects will occur is a major tool in helpingorganizations achieve Baldrige levels of business performance andprocess quality. Two kinds of Six Sigma projects canbe undertaken: DMAIC(Define, Measure, Analyze, Improve, and Control) DFSS(Design for Six Sigma) |
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Quality assurance |
refers tothe entire system of policies, procedures, and guide- lines established by an organization to achieve and maintain quality. |
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Quality engineering |
Its objective is to include quality in thedesign of products and processes and to identify potential quality problems prior to production. |
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Statistical process control |
Output of the production process is sampled and inspected. UsingSPC methods, it can be determined whether variations in output are due to common causesor assignable causes. Thegoal is decide whether the process can be continued or should be adjusted to achieve adesired quality level. |
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common causes |
1.randomly occurring variations in materials, humidity, temperature, . . . 2.variations the producer cannotcontrol 3.process is in statistical control 4.process does not need to be adjusted things you can't readily control for; things you can't fix |
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assignable causes |
1.non-random variations in output due to tools wearing out, operator error, in correct machine settings, poor quality raw material, . .. 2.variations the producer can control 3.process is out of control 4.corrective action should be taken things you can fix; are in control |
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Null Hypothesis |
H0is formulated in terms of the production process being incontrol. |
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Alternative Hypothesis |
Hais formulated in terms of the production process being outof control. |
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Correct Desicion |
H0 true & in-control accept h0 & continue process |
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Type II error allow out-control- process to continue |
h0 false & out of control accept h0 & continue process |
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Type I error adjust in-control process |
h0 true & in-control reject h0 & adjust process |
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correct desicion |
h0 false & out of control reject h0 & adjust process |
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Control charts |
provide a basis for deciding whether the variation in the output is dueto common causes (in control) or assignable causes (out of control). |
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upper control limit (UCL) lower control limit (LCL) |
two important lines on a control chart |
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in control |
therewill be a high probability that the sample finding will be between the twolines. |
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out of control |
Valuesoutside of the control limits provide strong evidence that the process |
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Acceptance sampling |
statistical method that enables us to base the accept-reject decision on the inspection of a sample of items from the lot |
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Acceptance sampling has advantages over 100% inspection inluding |
1.usually less expensive 2.less product damage due to less handling 3.fewer inspectors required 4.provides only approach possible if destructive testing must be used |
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accept the lot & send to production or customer |
1.lot received 2.sample selected 3.sampled items inspected for quality 4.results compared with specific quality characteristics quality is satisfactory |
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Reject the lot & decide on the disposition of the lot |
1.lot received 2.sample selected 3.sampled items inspected for quality 4.results compared with specific quality characteristics quality is not satisfactory |
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H0 |
good-quality lot |
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Ha |
poor-quality lot |
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Correct decision |
h0 true-good quality lot |
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Type II error-accepting a poor-quality lot |
accept h0-accept the lot ho false-poor-quality lot |
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type I error-rejecting a good-quality lot |
h0 true-good quality lot reject h0-reject the lot |
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Correct desicion |
reject h0-reject the lot h0 false-poor-quality lot |
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Binomial probability function for acceptance sampling |
n=sampling size p=proportion x=number of defective items in lot f(x)=probability of x defective items in sample |
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a |
the probability that a lot with p0 defectives will be rejected |
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b |
the probability that a lot with p1 defectives will be accepted |
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Multiple sampling plan |
uses two or more stages of sampling |
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Decision possibilities |
1.stop sampling and accept the lot 2.stop sampling and reject the lot, or 3.continue sampling |
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Smaller total sample size |
multiple sampling plans often result in a ________ than single-sample plans with the same type 1 error and type II error probabilities |
