Showing posts with label M. Show all posts
Showing posts with label M. Show all posts
Multi-Vari Chart
A multi-vari chart is a tool that graphically displays patterns of variation. It is used to identify possible Xs or families of variation, such as variation within a subgroup, between subgroups, or over time.
Multiple regression
Multiple regression is a method of determining the relationship between a continuous process output (Y) and several factors (Xs).
Multimodal distribution
A combination of more than one distribution that has more than one distinct peak.
Multicolinearity
Multicolinearity is the degree of correlation between Xs. It is an important consideration when using multiple regression on data that has been collected without the aid of a design of experiment (DOE). A high degree of multicolinearity produces unacceptable uncertainty (large variance) in regression coefficient estimates. Specifically, the coefficients can change drastically depending on which terms are in or out of the model and also the order they are placed in the model.
MTTR
Mean time to repair.
This is the average time to repair a machine back to acceptable operating conditions. Also known as tool time, meaning once the machine breaksdown, the actual time spent on arranging spares, resources, planning and executing the tasks and then bringing it back to operating condition. This must be as low as possible.
This is the average time to repair a machine back to acceptable operating conditions. Also known as tool time, meaning once the machine breaksdown, the actual time spent on arranging spares, resources, planning and executing the tasks and then bringing it back to operating condition. This must be as low as possible.
MTBF(mean time between failures)
Mean time between failures.
An average time between machinery breakdowns. If the MTBF decreases, root cause analysis must be carried out to bring the MTBF # to a high, meaning long times between failures. PM, TQM, JIT, better controls are all tools to make MTBF higher.
An average time between machinery breakdowns. If the MTBF decreases, root cause analysis must be carried out to bring the MTBF # to a high, meaning long times between failures. PM, TQM, JIT, better controls are all tools to make MTBF higher.
Moods Median
Mood's median test can be used to test the equality of medians from two or more populations and, like the Kruskal-Wallis Test, provides an nonparametric alternative to the one-way analysis of variance. Mood's median test is sometimes called a median tests
Model selection
Whenever one must choose an accelerated test strategy to address relia bility certfication, it becomes immediately obvious that model selection and test strategy can dramatically affect a product pass versusfail test position.
Mode
The value or item occurring most frequently in a series of observations or statistical data.
The most often occurring value in the data set.
A data set may contain more than one mode, e.g., if there are exactly 2 values or items that appear in the data the same number of times, we say the data set is bi-modal.
The most often occurring value in the data set.
A data set may contain more than one mode, e.g., if there are exactly 2 values or items that appear in the data the same number of times, we say the data set is bi-modal.
Mixture experiments
Variables are expressed as proportions of the whole and sum to unity. Measured responses are assumed to depend only on the proportions of the ingredients and not on the amount of the mixture.
Minor Non-Conformance
The controls are implemented and generally followed except for a minor instance and where there is no decline in overall process capability.
Mid Range
It is also termed as Mid Extreme.
It is nothing but the average of the least value and most value.
Steps involved are...
1. Arrange the numbers or readings in ascending order
2. Add the first number or reading with last number or reading.
3. Divide the sum by 2.
It gives the mid range of the readings.
It is nothing but the average of the least value and most value.
Steps involved are...
1. Arrange the numbers or readings in ascending order
2. Add the first number or reading with last number or reading.
3. Divide the sum by 2.
It gives the mid range of the readings.
Metrics
Things to measure to understand quality levels.
Metric means measurement. Hence the word metric is often used in an organization to understand the metrics of the matrix (The trade off).
Metric means measurement. Hence the word metric is often used in an organization to understand the metrics of the matrix (The trade off).
Median
Relating to or constituting the middle value in a distribution.
The median is the middle point of a data set; 50% of the values are below this point, and 50% are above this point.
Median is the middle value, when all possible values are listed in order. Median is not the same as Average (or Mean)
The median is the middle point of a data set; 50% of the values are below this point, and 50% are above this point.
Median is the middle value, when all possible values are listed in order. Median is not the same as Average (or Mean)
measures of central tendency
numerical measures that depict the center of a data set. The most commonly used measures are the mean and the median.
Measurement System Analysis - MSA
Measurement system analysis (MSA) is an experimental and mathematical method of determining how much the variation within the measurement process contributes to overall process variability.
There are five parameters to investigate in an MSA: bias, linearity, stability, repeatability and reproducibility.
According to AIAG (2002), a general rule of thumb for measurement system acceptability is:
" Under 10 percent error is acceptable.
" 10 percent to 30 percent error suggests that the system is acceptable depending on the importance of application, cost of measurement device, cost of repair, and other factors.
" Over 30 percent error is considered unacceptable, and you should improve the measurement system.
AIAG also states that the number of distinct categories the measurement systems divides a process into should be greater than or equal to 5.
In addition to percent error and the number of distinct categories, you should also review graphical analyses over time to decide on the acceptability of a measurement system.
Reference:
Automotive Industry Action Group (AIAG) (2002). Measurement Systems Analysis Reference Manual. Chrysler, Ford, General Motors Supplier Quality Requirements Task Force.
There are five parameters to investigate in an MSA: bias, linearity, stability, repeatability and reproducibility.
According to AIAG (2002), a general rule of thumb for measurement system acceptability is:
" Under 10 percent error is acceptable.
" 10 percent to 30 percent error suggests that the system is acceptable depending on the importance of application, cost of measurement device, cost of repair, and other factors.
" Over 30 percent error is considered unacceptable, and you should improve the measurement system.
AIAG also states that the number of distinct categories the measurement systems divides a process into should be greater than or equal to 5.
In addition to percent error and the number of distinct categories, you should also review graphical analyses over time to decide on the acceptability of a measurement system.
Reference:
Automotive Industry Action Group (AIAG) (2002). Measurement Systems Analysis Reference Manual. Chrysler, Ford, General Motors Supplier Quality Requirements Task Force.
Mean time between failure(MTBF)
A term that can be used to describe the frequency of failures in a repairable system with a constant failure rate.
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