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Basic spc class

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Basic SPC Class

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Basic spc class

1. 1. BASICS.P.C.
2. 2. BASIC S.P.C. WHAT IS S.P.C.?STATISTICAL PROCESS CONTROL IS THE USE OF STATISTICAL TECHNIQUES (SUCH AS CONTROL CHARTS) TO ANALYZE A PROCESS OR ITS OUTPUT.S.P.C. HELPS MAINTAIN QUALITY WITHIN A PROCESS BY: Increasing customer satisfaction by reducing the amount of variation, producing a more trouble free product .  Decreases scrap, rework, and inspection costs by controlling the product. Decreases operating costs by optimizing the frequency of tool adjustments and changes. Maximizes productivity by identifying and eliminating the causes of out of control conditions.  Establishes a predictable and consistent level of quality. Eliminates or reduces the need for receiving inspection by the customer.
3. 3. BASIC S.P.C.All production processes have inherent variation. That is, notwo pieces produced are exactly alike if measured withenough precision.Variation can be categorized in terms of "common" and"special" causes:•Common cause variation occurs where a stable processmakes products that vary within a predictable range.•Special cause variation results from unpredictable eventssuch as nonconforming raw material, a broken tool, or apower sag.SPC gives us the tools to measure the degree of both types ofvariation with the goal being to eliminate special causesaltogether, and systematically attack common causes to reducethem over time.Control charts and capability studies are the main tools used todescribe processes graphically. Control charts are composedof sampling results taken over time that are plotted as pointson special graphs. Different kinds of control chartsaccommodate variable or attribute sampling.
4. 4. BASIC S.P.C. VARIABLE & ATTRIBUTE CHARACTERISTICSA variable characteristic is a measurable feature such as height, width, or weight.Variable control charts are composed of two graphs. Thetop graph monitors process statistical location. Itmeasures whether the process is adjustedproperly, comparing the calculated process average tothe print nominal or target value. The bottom graphmonitors process variation.**********************************************************An attribute characteristic is a countable feature such as go/no-go, present/not present or number of defects.Attribute control charts are composed of only one graphthat monitors lot-to-lot variations in terms of percent ornumber nonconforming. While the target fornonconformities is always zero, many unrefinedprocesses exhibit common-cause variation causing a"predicted" nonconforming level above zero.
5. 5. BASIC S.P.C. BASIC STEPS OF S.P.C. All tasks are to be performed during production At predetermined intervals, select a subgroup ofsample products from the process (while it is running) Measure the specified characteristic of each sample Record the measurement values on a control chart Calculate two values for each subgroup:  Average of the samples (X)  Range between the highest and lowest values (R) Plot each subgroup value as a point on thecorresponding chart Draw a line to connect each point to the previous pointon the chart Analyze the patterns that develop as points are addedto the charts
6. 6. BASIC S.P.C.X – R CHARTThe X & R chart is actually two charts, and is the mostcommonly used method of tracking variable characteristics.Only one characteristic can be recorded on each chart.  The X chart monitors subgroup averages  The R chart monitors subgroup ranges A central line, which is a solid line across eachchart, represents the average of the subgroup values  On an X chart, it’s labeled X, and represents the average of all the subgroup averages  On an R chart, it’s labeled R, and represents the average of all of the subgroup ranges Control limits, which appear as dashed lines across eachchart, represent the expected range of variation for thesubgroup values  The upper control limits is typically labeled UCL  The lower control limit is typically labeled LCL  The LCL on the R chart is often zero, and is represented by the bottom edge of the graph
7. 7. BASIC S.P.C. DIFFERENCE BETWEEN CONTROL LIMITS AND SPECIFICATION LIMITS Specification limits define an allowable amount of variationfor a characteristic. These limits are determined when a productis designed. Control limits identify the expected range of variation for acharacteristic. These limits are based on the actualmeasurements of the characteristic, as found during processing. CALCULATING SUBGROUP VALUES To find the X value for a subgroup: • Add the values of all the sample measurements taken • Divide this sum by the number of samples To find the R value for a subgroup: • Find the largest and smallest values in the subgroup • Subtract the smaller value from the larger value
8. 8. BASIC S.P.C. 1 2 3 4 5 6 7 8 9 10 38 31 30 32 32 33 33 33 33 30 35 31 30 33 34 38 34 33 36 35DATA FROM EACH 34 34 32 33 37 31 36 36 35 37 SUBGROUP 34 31 29 32 37 33 31 35 34 32 29 32 32 37 35 33 30 36 31 29 TOTAL 170 159 153 167 175 168 164 173 169 163 AVERAGE ( X ) 34.0 31.8 30.6 33.4 35.0 33.6 32.8 34.6 33.8 32.6 RANGE ( R ) 9 3 3 5 5 7 6 3 5 8 37 UPPER CONTROL LIMIT 36CHART OF 35 THE 34AVERAGES 33 X 32 (X) 31 30 LOWER CONTROL LIMIT 29 1 2 3 4 5 6 7 8 9 10 SUBGROUPS 18 16CHART OF 14 THE 12 UPPER CONTROL LIMIT RANGES 10 8 (R) 6 R 4 2 1 2 3 4 5 6 7 8 9 10 SUBGROUPS
9. 9. BASIC S.P.C. PROCESS CAPABILITY AND PERFORMANCEProcess capability is a measure of the ability of a process toproduce products that meet required specifications. It ismeasured by taking variable measurements over TIME from aprocess that is statistically stable (only common cause variationpresent). Process capability is typically reported as a measurablereferred to as the CpK value.Cpk attempts to answer the question “will my process continueto meet specifications in the long run?" Process capabilityevaluation can only be done after the process is brought intostatistical control. The reason is simple: Cpk is a prediction based onvariation within a subgroup, and one can only predict something thatis stable. Think of the Cpk as the potential performance, or thepotential capability. Cpk is the CAPABILITY of your process if allinstability (special causes) were removed (or ignored).Process performance is the actual state of the process at somemoment in time. In essence, a snap shot of the process now. In aminute, hour, day, or week later it probably will be different. Processperformance is typically reported as a measurable referred to as thePpK value.Ppk attempts to answer the question "does my currentproduction sample meet specification?“ Ppk is how the process isactually performing at the time you made the measurements. Think ofPpk as being the actual PERFORMANCE of yourprocess, incorporating all observed variation within the subgroups.
10. 10. STOGRAM 6 5 S.P.C. 4 3 BASIC 2 1 CAPABILITY31 32 33 34 HISTOGRAMS 29 30 ANALYSIS: 35 36 37 38 10 9 X 8 X 7 X XSTOGRAM 6 X X X X 5 X X X X X 4 X X X X X X X 3 X X X X X X X X X HISTOGRAMS 2 X X X X X X X X X X 1 X X X X X X X X X X 29 30 31 32 33 34 35 36 37 38 10 9 X 8 X 7 X X 6 X X X X 5 X X X X X 4 X X X X X X X 3 X X X X X X X X X 2 X X X X X X X X X X 1 X X X X X X X X X X 29 30 31 32 33 34 35 36 37 38 VARIABLE DATA - NORMAL CURVE 1 2 3 4 5 6 7 8 9 10 38 31 30 32 32 33 33 33 33 30 35 31 30 33 34 38 34 33 36 35 DATA FROM EACH 34 34 32 33 37 31 36 36 35 37 SUBGROUP 34 31 29 32 37 33 31 35 34 32 29 32 32 37 35 33 30 36 31 29 TOTAL 170 159 153 167 175 168 164 173 169 163 AVERAGE ( X ) 34.0 31.8 30.6 33.4 35.0 33.6 32.8 34.6 33.8 32.6 RANGE ( R ) 9 3 3 5 5 7 6 3 5 8
11. 11. BASIC S.P.C. Cpk > 1.33 (Capable ) Cpk = 1 to 1.33 (Barely Capable) This process should produce This process will produce less than 64 PPM >64 PPM but < 2700 PPM A Highly Capable Process : Voice of the A Barely Capable Process : Voice of the Process < Specification Process = Customer Specification******************************************** Cpk < 1 (Not Capable ) Cpk < 1 (Not Capable ) This process will also produce This process will produce more than 2700 PPM more than 2700 PPM A Non-Capable Process : Voice of the A Non-Capable Process : Voice of the Process > Customer Specification Process > Customer Specification
12. 12. BASIC S.P.C. CONTROL CHART INTERPRETATIONNATURAL PATTERNS:• Points remain within the control limits and vary randomly on both sidesof the central line • Most points fall near the central line • Some points fall closer to both control limits • No points should fall beyond either control limit•The process is: • In statistical control • Producing products within the expected limits of variation • Operating as well as possible without adjustments • Stable and predictable• Variation is due to common causes – normal factors not easily identifiedor eliminated from a process• Represents a normal distributionUNNATURAL PATTERNS:• The process is: • Out of statistical control •Unstable and unpredictable •Producing unexpected variation among products• Variation may be due to assignable causes – unusual factors that can beidentified and eliminated from a process•Common types are outliers, trends, runs or sudden changes in level
13. 13. BASIC S.P.C. CONTROL CHART INTERPRETATIONNORMAL DISTRIBUTION: Points vary randomly on eitherside of the central line and remain within the control limitsOUT OF CONTROL CONDITION (OCC): One or morepoints outside of the upper or lower control limits (requires auser note and immediate corrective action)
14. 14. BASIC S.P.C. CONTROL CHART INTERPRETATIONTRENDS: A series of 6 or more consecutive points whicheither ascend or descend across the chart; indicates aproblem with the process which must be addressedRUNS: A series of 6 or more consecutive points which falleither above or below the central line
15. 15. BASIC S.P.C.DATALYZERSPECTRUM LEGEND ICONS