Herramientas y conceptos de calidad
• decreases with spec width
Cp - see Natural Tolerance
• decreases with spec width
• Cp = 1 for centered process - natural tolerance =spec width
Cause and Effect Diagram - Fishbone Diagrams - Ishikawa Diagrams
• used to identify and organize potential root causes
• problem solving analysis done by brainstorming
• common categories -Measurement, Materials, People, Process, Equipment, Environment
• ask “Why?” 3 times to get to root cause
• have detailed problem statement at head of fish - “effect”
• need corresponding process map
• should fit on one 8-½ x 11 page
• should have all 6 fishbones and at least 3 levels deep
C-bar
• C-bar is the average of all the subgroup C-values in C-Chart
C – Chart - see Attribute DataControl Charts
• Count chart
• a specialized version of U chart
• used to monitor the number of errors found - occurrences per unit - error count
• number of units or subgroup size MUST remain constant
Census
• count or measurement of the entire population
Continuous Data
• measured – weigh, timed,
• can be measured and broken down into smaller parts and still have meaning. Money,temperature and time are continous.Volume (like volume of water or air) and size are continuous data.
Control Charts
• indicate stability over time
Chart Rules – Control Charts
• P-chart or NP-chart - count number of items in error or defectives
• U-chart or C-chart - count number of errors or defects in items
Common causes - see variation
control limits
• Provide boundariesfor a process running in control
• based upon process data
CTQ - Critical to Quality
• key measurable characteristics of a product or process whose performance standards or specification limits must be met in order to satisfy the customer
• CTQ’s represent the product or service characteristics that are defined by the customer (internal or external). They may include the upper and lowerspecification limits or any other factors related to the product or service.
• the product or service characteristics that are defined by the customer as critical to their needs
• what the customer expects of a product
DATA
Attribute Data Control Charts
• Attribute data - qualitative data that can be counted for recording and analysis good/bad, yes/no
• the average and dispersion are closelyrelated; therefore, only one chart needed
• P-Chart – proportions percent defective with variable or constant sample size
• NP-chart– number of defectives with constant sample size
• C-Chart – count of defects with constant sample size
• U-Chart – defects per unit with variable or constant sample size
Variable Data Control Charts
• Variable data – measured - two types (Discrete) count dataand (Continuous) data
• X and MR – for financial, mtce costs, efficiency ratings, productivity – (usually 2 charts)
• X-bar and Range
• X-bar and S (standard deviation) – X-bar for sample average and “S” to monitor process dispersion
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Defect
• non-conformities – a single characteristic not meeting defined requirements
Defective
• non-conformance – contains one or more defects
DET -see FMEA
Discrete Data
• counted (usually in whole numbers)
DMAIC
• Define – project charter, problem statement, scope, goals, resources, financial, process maps
• Measure – collect data, process maps, fishbone, Pareto, QFD, need accuracy & precision
• Analyze - root cause is verified, hypothesis testing (verifying assumptions and predictions regarding the relationship between processinputs and the CTQ values)
• Improve – brainstorming for ideas & solutions to problems identified in Analyze phase
• Control – helps to reduce variation in the process and eliminate defects
• Control - project responsibilities transition from process improvement team to operations team
• Six Sigma Methodology used for process improvement
DPMO (defects per million opportunities)
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