Mitramatra principles behind spc
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Statistical process control (SPC) uses statistical analysis of process data to monitor and improve processes. It focuses on eliminating unusual variation through measuring the process, identifying assignable causes of variation, and monitoring process performance over time. SPC tools like control charts can identify when a process is unstable or out of control due to assignable causes, helping drive process improvement. Root cause analysis techniques like 5 Whys and fishbone diagrams can further help uncover underlying reasons for process variation or instability.
Mitramatra principles behind spc
- 3. Statistical process control (SPC) is a methodology focused on quality control and improvement, using data analysis WhatisSPC It consists of using valid statistical data analysis to determine and eliminate variation due to assignable causes. It is based on the following principles: - measuring the process - identifying and eliminating unusual variation - improving the process to its best target value - monitoring the process performance over time
- 7. WhatisProcess..? a series of actions or steps taken in order to achieve a particular end > transforms inputs into outputs – such as mathematic formulation (F(x) = Y)
- 8. WhatisProcess..? No thing always same result >Any process will have a certain degree of variation; some variation will be inherent to the process, some will not.
- 9. ProcessVariations Variations in process input cause the variations in the process output (Products). There are three basic kinds of variation: o Common cause variation: is variation inherent to the process. • Irregular variation within an historical experience base • Naturally present within the system • Usually insignificant and predictable o Special (Assignable) cause variation: is variation due to sources outside the process, due to changes in the process input • Variation outside the historical experience base • Assignable to a root cause • Usually significant and unpredictable
- 10. CommonVariation BellShapedNormalDistribution • Not all parts are created equal • Any population under control follows the Normal Curve characteristics: 68% 95% 98% Data found within one standard deviations away from the mean Data found within two standard deviations away from the mean Data found within three standard deviations away from the mean
- 11. ControlChart • A process is said to be in control when data points fall within limits of variation (i.e.: between Upper and Lower Control Limits) Statistical tool used to monitor the stability of a process over time - UCL (Upper Control Limit) = mean + 3*sigma - LCL (Lower Control Limit) = mean – 3*sigma - Central line (mean of data set)
- 12. ControlChartlive It could be need to be investigated – why the result was out of control limit It could be happen after action taken And take benefits of the experience : the un predicted caused will be predicted caused
- 19. Data Collection 1. Measurementsystemvariationalreadystatisticallyin controlled. 2. Determined theneededsample.Toolittlewillbeto risk,Toobigcouldbehighinvestment 3. Whatkindofdata:variable orattribute 4. Identifythesourceofthedata–minimizedany potentialvariationrisk–seepoint1 5. Considerprocessvariationsourcethatcouldbe unpredictablecausedsuchas:shift1dataagainst shift2data 6. Donotmanipulate allthevariationsource–oryou willgetfalsepicture 7. Thenexecuteyourdatacollection..!
- 21. 5WhysRootCausedanalysis Key Points: • The 5 Whys strategy is an easy and often- effective tool for uncovering the root cause of a problem. • Because it's simple, you can adapt it quickly and apply it to almost any problem. • However, it is important to remember, if an intuitive answer is hard to find, then other problem-solving techniques may need to be considered. • Mostly – we not really ask more deeper to ensure what the really problem are Problem solving tool that helps understand the root cause of a problem – by ask the caused in several times (not always or shall be 5 times)
- 23. FISHBONEDIAGRAM RootCausedanalysis Fishbone diagrams: diagram-based technique, which combines brainstorming with a type of mind map, and forces to consider all possible causes of a problem, rather than just the ones that are most obvious. Fishbone diagrams encourage broad thinking Key Points: 1. Identify the problem. 2. Work out the major factors involved. 3. Identify possible causes. 4. Analyse your diagram.
- 24. TheEndNotes • Process has variation – we could controlled it with statistics tools. • Correct Control charts could be powerful instruments that can give visual understanding on the stability of process • Control charts cannot tell what is wrong with process, they can only let we know when something in your process has changed • How ever if we could do everything right : Control charts can confirm the impact of process improvement activities