# SPC - Statistical Process control

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Presentation By Senthilkumar RM SPC

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Presentation By Senthilkumar RM Today Learning's !! 1.Product Characteristics 2.Source of Process 3.Process Types 4.Variation & Its Causes 5.Tolerance 6.Standard Deviation 7.Interpretation of Stdev with Distribution 8.Calculating Std deviation 9. SPC ,Control Chart Selection & It interprets 10.Cp,CpK,Pp,Ppk

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Presentation By Senthilkumar RM Product Characteristics 2 Types of Product Characteristics Variable Attribute Variable – A Characteristics measured in Physical units eg : Millimeter, Volts Attributes – A characteristics measured by comparison eg : Good and Bad

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Presentation By Senthilkumar RM Source of Process

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Presentation By Senthilkumar RM Process Types All Process have Natural Variability (due to Common cause) Un-Natural Variability (due to Special cause) Stable Process – Variation in Output is by only common cause Unstable Process – Variation in Output is by both common & Special cause

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Presentation By Senthilkumar RM Variation & Its causes Variation : Inevitable changes in output over time Two causes of Variation Common Cause : Implemented in process due to design of process Special Cause : Not Present in process arises in certain circumstances Answer : Poor design ? Broken part ?

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Presentation By Senthilkumar RM Tolerance Tolerance : Allowed Maximum variation in dimension Otherwise called as “Engineering Tolerance”

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Presentation By Senthilkumar RM Quick recap Two types of Product characteristics? 5 source of Process? Two types of Process? Two Cause of variation ? What is Engineering Tolerance ? How Process speaks ? What is Within control and Out of control in a process?

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Presentation By Senthilkumar RM Standard Deviation ( σ ) Standard Deviation is a measure of Variability . It is denoted by Greek letter σ . In Other words Data dispersion around mean What is Population and Sample?

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Presentation By Senthilkumar RM Distribution & Standard Deviation and 3 σ Level

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Presentation By Senthilkumar RM Practical example to understand Distribution Now, we can create an example of our own and understand What is Observation X What is Mean (X bar) How to calculate std deviation? What it interprets in distribution? Histogram or Frequency Chart? Explanation How bell curve is derived? Explanation What is 6 σ ? What it tells? % derivation?

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Presentation By Senthilkumar RM What is SPC SPC : Statistical Process control Statistical tool Inspects random sample from a process To determine whether the process is working properly or not Forms Charts with data (Control charts) and Process speaks Developed by Walter Schewart

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Presentation By Senthilkumar RM Why We need to care about SPC ? Suppose Supplier A parts are with in Spec Supplier B parts are within Spec, But DON’T FIT TOGETHER WHY?

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Presentation By Senthilkumar RM Why We need charts Charts Tools Data Information

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Presentation By Senthilkumar RM Control charts It is a Chart, named as control charts because it interprets to Us whether the process is in control or not Remember, Two Types of data Variable data Attribute data Based on data, We need to select the control charts !! There should be some common factor also Sample size

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Presentation By Senthilkumar RM Selection of Control charts Based on Sample size & Data Type – Selection of chart done Variable data Attribute data

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Presentation By Senthilkumar RM I – IR- MR Charts What : “I” stands for Individual; R Stands for Range; MR stands for Moving Range When : Situation like data are limited such as production low, testing or Homogeneous Batches (Heat Treatment) How : By Plotting Individual Measurements and Moving range in separate graph and adding Center line Sample size = 1

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Presentation By Senthilkumar RM X bar – X bar R – X Bar S chart What : “X Bar” stands for average; R Stands for Range; When : Situation like data are limited such as production High, How : By Plotting average Measurements and range in separate graph and adding Center line with spec (Sub Group-- >>>>>) Sample size = 3 ~5

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Presentation By Senthilkumar RM Attribute Charts Cap Loose Label wrong Breakage 19 are “ Count data” where each data is classified in one of two categories eg., Good or Bad ; Pass or Fail Attributes data – Defects – is “ Non conformity ” eg., No.of defects in that unit / board / piece Defectives – is “ Non conformance ” eg., That unit / board / piece which has one or more defects is called defectives Which of the following is the source of Attribute data’s Testing – Why ? Productivity – Why ? Caliper measurement – Why ? Ring gage – Why ? Answer paper– Why ? What are Defects in item 1. Cap loose (one of defect) 2. Label wrong 3. Breakage What is Defective here WATER BOTTLE (unit)

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Presentation By Senthilkumar RM Chart Types

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Presentation By Senthilkumar RM Selection of Chart : Attribute See Sample size first Constant Sample size – C chart or nP chart Variable Sample size – P chart or U chart See type of data Defects – C chart or nP chart Defectives – P chart or U chart

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Presentation By Senthilkumar RM Now Tell

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Presentation By Senthilkumar RM Short Term (Sst) & Long Term (Slt) Standard Deviation

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Presentation By Senthilkumar RM Cp,Cpk,Pp,Ppk Cp – Process Capability – Ability of a production process to meet desired spec Common Cause capability Short –Term Pp – Process Performance – Ability of a production Process to meet desired spec Includes special cause Long – Term Cpk, Ppk are indexes – Numbers of Cp, Pp

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Presentation By Senthilkumar RM Calculate Cp, Cpk Cp = Engineering Tolerance / 6 σ Engineering Tolerance = USL – LSL Engineering Tolerance with Std Deviation = USL- Avg/ 3 σ = Avg – LSL/ 3 σ Cp = Engineering Tolerance / 6 * Sst – (see next page) (Question here) Cpk = Smaller of Engineering Tolerance with Std Deviation (Question here)

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Presentation By Senthilkumar RM

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Presentation By Senthilkumar RM Cp,Cpk,Pp,Ppk

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Presentation By Senthilkumar RM Data for calculating Cp.. Illustration Observations = Customer Spec = 60 +- 5 n= Avg = 3.Std dev = 4.Eng Tolerance = 5.Cp = 6.Cpk = Lets do this XL

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Presentation By Senthilkumar RM Higher the better