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how do the gurus define quality? |
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Juran- fittness for use Demming- Non Faulty system Crosby- Conformance to requirements |
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statistical process control:
preventing defects by applying statistical methods in controlling processes |
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total quality management-
management approach focused on continuous process and system improvement |
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quality management systems-
comprehensive integrated management system to improve quality |
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Big Q: term used to contrast the difference between managing for quality it ALL part of an organization
Little Q: term used to contract managing for quality in only the products |
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Difference between service and product quality |
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service quality does not have a tangible item
-services are usually consumed as they are produced.
-services generally labor intensive
-service companyies handle large numbers of customer service transactions |
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most organizational processes are..... |
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every system must be sure to have a..... |
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what does every system inevitably have? |
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-reduce variation -dont need a lot of management |
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natural variation: cant avoid, is not employees fauly
Special variation: unpredictable, can be eliminated |
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what is more powerful...intrinsic or extrinsic motivation |
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what is the cycle that involves Plan Do Check Act |
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-Felt management was necessary and had to work from the top down -product performance related to customer satisfaction -freedom from deficciencies, which will avoid customer dissatisfaction |
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-Quality come from top down (management) -"Quality is free" -Zero Defects |
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control--->influence---->concern |
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brainstorming original vs nominal technique |
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Original: -warm up session -everyone throws out ideas -facilitator organizes by category -list is reviewed -duplicates and out of scope ideas removed
NOMINAL: -10 min to write down ideas -everyone says ideas after -good for shy people or groups with really dominating outspoken people -discuss and vote on priorities |
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-man -machine -milieu -materials -method -measurement |
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causal existance vs causal independence vs causal sufficiency |
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causal existance: one link directly causes another
causal sufficiency: there are multiple causes that effect the process at the same time causal independence: there are many caused that independently effect the process |
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attribute data vs variable data |
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attribute data: something you can count like number of people with blue eyes in the room
variable data: something that is measured like caliper of paper |
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Pareto Analysis stated.... |
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most effects come from relatively few causes (separate teh vital few from the useful many) |
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in scatter plots, what is the independent and dependent variable? |
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the x axis is the independent and the y axis is dependent |
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at would cause different distibutions:
-Normal -Narrow -Wide -Truncated -Skewed -Multi-Nodal -Plateau -Comb |
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-Normal -Narrow: bins too large -Wide: bins too small( cobine some) -Truncated: missing data -Skewed -Multi-Nodal: gender or 2 diff printing presses (can it be subcategorized?) -Plateau: too much variation, has the densitometer been calibrated? -Comb |
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how to determine the bin width |
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determine range (max-min) Determine K = number of bins
determine H=R/K
start at R/K and increase in incriments of H |
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difference between correlation and slope |
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slope is how much one variable affects another and correlation is how likely one variable will effect another |
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if you have a narrow or wide distribution what does that mean about your bins? |
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narrow: bins too large wide: bins to small |
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the strength of the effect (how much) -the steeper the slope the greater the effect! |
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the relationship is strongest in scatter plots when.... |
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the r value is closer to 1 |
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-boost moral - goals are good but can lead to frustrations |
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what tool shows variation |
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what is not included in the cost of quality |
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what was the triggering event for prepress paul |
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impositions recieved from customer service |
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preparing to minimize the effect of a problem is called |
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quality tool for finding out which potential root cause has the biggest impact on the problem? |
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first step after collecting data for pareto chart |
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run chart vs control chart |
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run chart: shows data over time
control chart: data over tim with statistical data applied to it
-identifies process and change over time and determines if process in control -common or assignable variation -shows UCL and LCL |
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take into account changed OVER TIME....ITS A SNAPSHOT |
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the width variation over time
if r=o there is no variation |
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what the customer will accept |
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sawtooth patterns show that... |
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sampling from more than one processs |
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simple random sampling vs. systematic sampling |
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simple randon: - can distort results -no correlation over time -hard with large populations
systematic: -sample taken ever x number of people -good for tracking a process -hard to estimate accuracy -should randomize the first measure |
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rule of thumb for systematic sampling |
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-sampling should be frequent enough to adjust process but not TOO frequent to interfere with process
-higher cost data should be tested more often
-sample based on run length |
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accept/reject
-pro: less handling, fewer inspectors, lower costs, faster
-cons: risk of accepting bad ones and rejecting good ones. sample provides lessinfo than 100 percent inspection |
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mil spec 105 standarization levels |
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1. normal 2. tightened 3. relaxed |
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honor le blancs concept of... |
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cumulative total line in pareto chart separates... |
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the vital few from the significant many |
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plan do check act is part of.. |
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for process to be a good candidate for improvement it must be... |
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measurable and repeatable |
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JIT manufacturing comes from... |
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scatter plots help identify |
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how likely and how strongly one variable affects another |
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until the 1980s, most companies maintained quality through |
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whats harder to measure service or product quality |
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whats harder to measure service or product quality |
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view of quality as satisfaction of customer is called |
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benchmarking approaches are... |
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decision nodes have how many options |
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avg company never hears from what percent of dissatisfied customers |
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crosby measure of quality |
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quality tool to identify as many possible root causes as possible |
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hwat is used to monitor continuous variable data |
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process distribution check list |
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pareto charts are diff from histograms because they |
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usually rank and sort by diff causes |
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