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Quality Management Tools, control chart, pareto diagram, data…
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control chart
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types
variable control chart: monitor measurable characteristics (eg. weight or dimensions) + applicable to processes following a normal distribution > X-bar chart: tracks sample means + R chart: tracks range
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pareto diagram
steps
- calculate frequencies: determine how often each cause occurs & its relative importance
- create the diagram > use a bar chart to represent to frequency or percentage of defects for each cause + add a cumulative percentage line to show how much each cause contributes to the total
- collect data: record the frequency of each problem
- focus on major causes: identify the causes that contribute to 80% of the problems
- group causes: limit the number of problems or causes to analyze > can be done using a fishbone diagram or check sheet
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bar chart combined with a line graph that follows the pareto principle (80/20 rule) > helps identify most significant causes of a problem
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data stratification
classification & separation of information into groups or categories with similar characteristics to enable a deeper & more precise analysis of the causes of a problem
on its own > doesn't improve or resolve processes, but it serves as a preliminary tool that aids other methods
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by breaking the problem into parts > the origin or cause often lies in a smaller & seemingly insignificant issue
involves categorizing information eg. defects, causes, phenomena or types of defects into groups with shared traits
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histogram
steps
- determine the number of intervals (K): use the Sturges' rule > K = 1 + 3.322 x log(N) > N = total number of data points
- calculate interval width (H): H = R / K
- calculate the range (R): find the difference between the largest & smallest values in the dataset > R = Vmax - Vmin
- create a frequency tabel: count how many data points fall into each interval
- collect data: record the results
- plot the histogram: X-axis = intervals & Y-axis = frequency
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types
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bell-shaped (normal distribution): data is evenly distributed around the center + indicates a stable process
bar chart used to show the frequency of numeric results > helps to easily identify how often a specific outcome occurs & reveals patterns in the data
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use: identifies stability, trends or anomalies in a process
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scatter diagram
steps
- set scales: find the range of both variables & define scales for the graph
- plot the data: use a graph with 2 axes
- control data collection conditions: ensure data is collected under consistent conditions
- identify correlations: look for patterns in the points to see if a relationship exists
- collect data: gather pairs of data for the 2 variables you want to study
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data collection sheet
practical example
- prejudices: assumptions like "someone isn't doing their job" may be biased
- subjectivity: personal opinions without proof lead to errors
- imprecisions: phrases like "a bunch of complaints" are vague
- emotional bias: accepting a belief just because "the boss said so"
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records data to make conclusions objective (based on facts, not opinions)
matrix diagram
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organizational tool to assign tasks to individuals or departments > highlighting the relationship between specific tasks & their responsible parties
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PERT diagram
characteristics
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each node includes task details: ID, duration, start & end dates
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brainstorming
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execution phases
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- generate ideas: moderator collects ideas from participants > rotating turns until they are exhauseted
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- analyze & select the best ideas
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catchball
execution phase
- catch & reflect: others analyze & reflect on the idea
- improve: suggestions are made to enhance to idea
- launch: a participant shares an idea
- re-launch: improved idea is shared for further refinement
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