Statistical Process Control DELMIA Apriso 2017 Implementation Guide

Transcription

1 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 2016 Dassault Systèmes. Apriso, 3DEXPERIENCE, the Compass logo and the 3DS logo, CATIA, SOLIDWORKS, ENOVIA, DELMIA, SIMULIA, GEOVIA, EXALEAD, 3D VIA, BIOVIA, NETVIBES, and 3DXCITE are commercial trademarks or registered trademarks of Dassault Systèmes or its subsidiaries in the U.S. and/or other countries. All other trademarks are owned by their respective owners. Use of any Dassault Systèmes or its subsidiaries trademarks is subject to their express written approval.

2 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 2 Contents 1 Introduction Scope Intended Audience References 4 2 SPC Overview How to Use SPC Plan Do Check ACT 6 3 SPC Configuration SPC Main Grid Screen SPC Chart Properties Screen SPC Chart Properties Upper and Lower Chart Parameters SPC Alert Rule Properties Calculation and Display Queries SPC Chart Types P Chart NP Chart C Chart U Chart Run Chart X-Bar Average and Range X-Bar Average and Standard Deviation (X-Bar and S [Sigma]) Median Chart Individual Chart Exponentially Weighted Moving Average Chart (EWMA) 27 4 SPC Chart Calculation and Display 28 5 Sample Scenario 29 6 References 31 Figures Figure 1 The PDCA cycle 6 Figure 2 SPC main grid 8 Figure 3 SPC chart properties 9 Figure 4 SPC Chart screen properties section 9 Figure 5 Edit Languages window 10 Figure 6 SPC Chart screen Upper Chart Parameters and Lower Chart Parameters sections 11

3 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 3 Figure 7 SPC Alert Rule properties screen 12 Figure 8 Calculation and Display Queries section 14 Figure 9 Sample P chart 16 Figure 10 P chart data mapping (A) 17 Figure 11 P chart data mapping (B) 18 Figure 12 Sample NP chart 19 Figure 13 Sample C chart 20 Figure 14 C chart data mapping (A) 20 Figure 15 C chart data mapping (B) 21 Figure 16 Sample U chart 22 Figure 17 U chart data mapping 22 Figure 18: Sample Run chart 23 Figure 19: Sample X-Bar Average and Range 24 Figure 20 Sample Median chart 26 Figure 21 Individual chart 27

4 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 4 1 Introduction The purpose of this document is to provide a general overview of the Statistical Process Control (SPC). It describes the three parts of SPC: design, calculation, and display. 1.1 Scope The scope of this document includes the core areas that are divided into three major parts: 1 Configuration Using the SPC Main Administration screen The types of charts supported Creating SPC rules 2 Calculation Using the CalculateChart Business Components (e.g., CalculateChart_v4) 3 Display The Business Components used to show the chart A standard Business Process Flow will be used to demonstrate and outline how to display an SPC chart using the Chart Control Business Control 1.2 Intended Audience This Implementation Guide is for those Process Authors who want to visualize information and have a detailed knowledge of the Quality module and its associated database tables. Typical users can be grouped into the following profiles: Supervisors and Quality Technicians these users have a similar profile to Workers with special privileges within the SPC chart Workers these users are able to view charts and to act upon alerts generated by the SPC calculations DELMIA Apriso Administrators these users are able to create new SPC charts and the rules for displaying them within Processes developed in Process Builder 1.3 References It is preferable that users have knowledge of the following and should have them as references: Business Control implementation guides Process Builder conventions document SPC Chart Design documents on the layouts required for each

5 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 5 2 SPC Overview The SPC is used in many organizations to monitor, refine, and control processes. It is most commonly seen in high quality companies that have extensive quality initiatives and continuous improvement programs, such as Six Sigma and lean manufacturing. To ensure that these companies get the most out of the system, the following elements are required: Configuration screens these screens are used to create and configure the chart to be calculated. This includes the subgroup information, WECO rule and custom rule configuration, the calculation and display queries, etc. As SPC charts can have an upper and lower chart, the configuration of tolerance levels and rules can be applied to both the upper and lower charts. Calculation the calculation of SPC charts needs to be flexible. The charts can be calculated: In intervals using Job Scheduler Manually from a Standard Operation As embedded in Processes or on a machine event Via download The calculation is done via the CalculateChart Business Components (e.g., CalculateChart_v4). 2.1 How to Use SPC The SPC controls the Process through statistics. In today s world of lower margins, even a small advantage means a lot. Continuous Process improvement comes about from analysis performed by Process Engineers. The PDCA cycle is a checklist of the four stages that one must go through to get from problem faced to problem solved, as presented in this figure:

6 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 6 Figure 1 The PDCA cycle 1 This does more than just alert Operators about problems. It is a continual process that requires four phases Plan In this phase, the problem is identified along with possible causes. This is done using the SPC and analysis tools. Questions that should be asked include: What can and should be measured, and how often? How are the questions that need to be answered with every Process important to the organization? Do In this phase, changes are made that are designed to correct or improve the situation. This is done through the education of users and Process change. DELMIA Apriso has a tool called Process Builder, which is a Business Process Management tool. This makes enforcing a change in a plant or enterprise possible by giving Process Engineers the ability model/refine the Process to be used by the Operators in the plant Check In this phase (which is also known as the Study phase), the effect of these changes on the situation should be studied. This is where control charts are used, as they show the effects of changes on a Process over time. Evaluate the results and then replicate the change, or abandon it and try something different. The question to be asked here is, did the changes help or hurt? ACT If the result is successful, standardize the changes and then work on further improvements or the next prioritized problem. If the outcome is not yet successful, look for other ways to change the Process or identify the different causes for the problem 1 By en:user:xsmith ( [GFDL ( or CC-BY-SA-3.0 ( via Wikimedia Commons.

7 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 7 This is possible with DELMIA Apriso Global Process Manager, which can deploy Processes throughout the enterprise. This ensures that the new and improved Processes are followed and the benefits are returned in all parts of the organization. In summary, to perform continual improvements, the following elements are required: A plan and the tools for configuring what is to be measured A tool for transforming the calculation to a visual representation of the Process so that the investigation of problems is possible A tool for making changes to the Process in order to correct the problems found in the planning stage Once it is proven that the change has improved the performance and/or quality of the Process, then this Process is to be standardized and pushed out to the enterprise

8 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 8 3 SPC Configuration SPC chart configuration is performed through the SPC Charts administration screen. From here, the user is able to add a complete chart that is ready for calculation. The screen can be navigated to in the DELMIA Apriso Desktop Client. 3.1 SPC Main Grid Screen The SPC main grid first appears when the SPC Charts administration screen is loaded. Figure 2 SPC main grid This grid lists all the existing SPC charts. Users can add, delete, or view/edit the properties of the charts on the grid using the standard DELMIA Apriso buttons (e.g., Add, Delete, View Properties). 3.2 SPC Chart Properties Screen The SPC Chart screen is displayed when adding a new chart or editing an existing chart s properties.

9 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 9 Figure 3 SPC chart properties This screen is used to monitor and maintain the current SPC charts along with their properties. The main properties of a chart are described in the following sections SPC Chart Properties This section of the property sheet allows you to set specific properties for the chart. Figure 4 SPC Chart screen properties section Field Chart ID Chart Name Chart Type Short Description Description This is a read-only field for showing the chart calculations. The name of the chart. The type of the chart. For information about each chart type, see 3.4 SPC Chart Types). A concise localizable chart description.

10 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 10 Medium Description Extended Description Product Characteristic Subgroup Size Weighting Factor Control Limit Factor In Control Standard Deviation A localizable chart description that is of average length. A long localizable chart description. The default product of the SPC chart. This can be overridden in the calculation. The default Characteristic being measured The size of the subgroup. Used in the calculation of the EWMA chart. Used in the calculation of the EWMA chart. Used in the calculation of the EWMA chart. Clicking opens the Edit Languages window, which allows for adding and removing translations for a chosen language: Figure 5 Edit Languages window Upper and Lower Chart Parameters In these sections, parameters for the upper and lower charts (where applicable) can be set. Both sections include an SPC alert rules grid.

11 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 11 Figure 6 SPC Chart screen Upper Chart Parameters and Lower Chart Parameters sections Field Lower Control Limit Upper Control Limit Description The value of the lower control limit for the chart. Leave the field empty in order to have the chart calculate it. The value of the upper control limit for the chart. Leave the field empty in order to have the chart calculate it SPC Alert Rule Properties The SPC Alert Rule properties screen is accessed when clicking the Add or Properties buttons above the Upper Chart Parameters or Lower Chart Parameters grids.

12 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 12 The screen contains the following fields: Field Name Alert Type Alert Class One point outside specification limit Last point outside specification limit One point outside control limit Last point outside control limit Figure 7 SPC Alert Rule properties screen Description The name of the created Alert. The alert type used to create the alert for the SPC chart. The alert class used to create the alert for the SPC chart. Checking this box will enable the alert to be triggered if at least one point on the chart is outside the specification limit. Checking this box will enable the alert to be triggered if the last point on the chart is outside the specification limit. Checking this box will enable the alert to be triggered if at least one point on the chart is outside the control limit. Checking this box will enable the alert to be triggered if the last point on the chart is outside the control limit.

13 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 13 Zone A Zone A is defined as the range in the chart between 2 Sigma and 3 Sigma. The rule for triggering an alert for the zones is to check for each plotted point (the "current check point") if, in the range of Points in range, the number of points occurring in the given zone reaches the value of Number in range. For example, the Zone A check box is selected, 4 is entered in the Points in range field, and 2 is entered in the Number in range field. This means that if 2 points in a range of 4 fall in Zone A, an alert will be generated. The check is performed for each consecutive range of 4 points. Number in range (for Zone A) The minimum number of points required to generate the alert (the check will only be performed when CheckPointsZoneA = True). Points in range (for Zone A) This value indicates how many points from the current check point forward will be examined for the rule (the check will only be performed when CheckPointsZoneA = True). Zone B Zone B is defined as the range in the chart between 1 Sigma and 2 Sigma. The rule for triggering an alert for the zones is to check for each plotted point (the current check point ) if, in the range of Points in range, the number of points occurring in the given zone reaches the value of Number in range. For example, the Zone B check box is selected, 4 is entered in the Points in range field, and 2 is entered in the Number in range field. This means that if 2 points in a range of 4 fall in Zone B, an alert will be generated. The check is performed for each consecutive range of 4 points. Number in range (for Zone B) Points in range (for Zone B) Points in a row The minimum number of points required to generate the alert (the check will only be performed when CheckPointsZoneB = True). This value indicates how many points from the current check point forward will be examined for the rule (the check will only be performed when CheckPointsZoneB = True). This check box indicates that a given number of points in a row will be checked for whether they increase or decrease consecutively. For example, the Points in a row check box is selected, and 5 is entered in the Number of points field. This means that if there are at least 5 consecutive points in a row increasing or decreasing, the alert will be generated.

14 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 14 Number of points Alternating Points The number of points in a row (the check will only be performed when CheckPointsInARow = True). This check box indicates that a given number of points in a row will be checked for whether they alternate (as in, they go up, down, up, down, etc.). For example, the Alternating Points check box is selected, and 5 is entered in the Number of alternating points field. This means that if there are at least 5 consecutive points in a row that alternate (as in, they go up, down, up, down, etc.), the alert will be generated. Number of alternating points WECO Rules Message The number of alternating points (the check will only be performed when CheckAlternatingPoints = True). Determines if the alert should use WECO rules or not. The message to be displayed when the alert is generated. 3.3 Calculation and Display Queries Figure 8 Calculation and Display Queries section Field Default Calculation Query Calculation Query Description The default calculation query used to retrieve the data to calculate the SPC chart points. The calculation query used to retrieve the data to calculate the SPC chart points.

15 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 15 Default Display Query The default display query used to retrieve the SPC chart points for display. Display Query The display query used to retrieve the SPC chart points for display. Copy from Default Copies the query from the default query window to the display query window. Tag List Inserts a variable from the dropdown list (such that will be substituted with the inputted values at runtime. Validate Validates the query. Run Runs the query. 3.4 SPC Chart Types P Chart 2 This Attribute control chart displays the fraction of non-conforming (defective) samples, which is the ratio of non-conforming parts/samples to the total quantity of parts inspected. It is not required, but it is recommended if the sample sizes are the same. When Should This Chart Be Used? This chart type shows a proportion of nonconforming items rather than the actual count of defects. P charts show how a Process changes over time. This chart type is based on a Process Attribute (or Characteristic) that is defined as a Boolean value and is always described in a yes/no, pass/fail, go/no go form. For example: Part cracked? Yes/No Carbon content above 80%? Shiny finish? Oversize diameter? Poor runout? Use P charts when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data a count of nonconforming items per subgroup? 3 Can the counts be converted to proportions? 4 Are there only two outcomes to any given check? 5 Is the time order of subgroups preserved? 2 Some of the information in this section is taken from: PQ Systems, p-chart, accessed April 8, 2015,

16 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 16 Figure 9 Sample P chart 3 3 Statit Software, Inc., p Chart, 2007, Statit.com, (accessed April 21, 2015).

17 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 17 P Chart Data Mapping SampleClass Get Chart Properties Characteristic Sample Size Retrieve all valid test results for the characteristic Questions - How to define date ranges on the number of data to retrieve (should come from the chart) - How to link to the process / operation? SampleGroupNum (int) TotalSamples (int) NumberofNonConforming(int) P (decimal) Create new SampleClass Loop through each of the test results returned above Sample Conforming? No Increment NonConforming Yes Increment TempCounter Check if the temp counter < sample size Yes Continue Looping Update SampleClass with SampleGroupNumber SampleSize NumberOfNonConforming Calculate P = NumberOfNonConforming / SampleSize Create new SampleClass Increment SampleGroupNumber Reset TempCounter Write Data to the Database. (insert or update records. Finish Figure 10 P chart data mapping (A)

18 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 18 Get Chart Properties SampleSize Characteristic temperature Time Range Retrieve Values from the DISPOSITION_TEST table Actual Start Actual Finish Inspection Characteristic Data to be returned SampleGroupNum TotalSamples NumNonConf P Retrieve Values from the DISPOSITION_TEST_READING table Actual Start Actual Finish Inspection Characteristic The issue is that the sample size may NOT be the same as the sample size needed for the chart. If this is the case then it is required to get the information from the disposition test reason NP Chart 4 Figure 11 P chart data mapping (B) This Attribute control chart monitors the number of nonconformances (np). When Should This Chart Be Used? This chart shows the actual count of nonconforming items. These charts are based on a Process Attribute (or Characteristic) that is defined as a Boolean value and is always described in a yes/no, pass/fail, go/no go form. For example: Part cracked? Yes/No Carbon content above 80%? Shiny finish? Oversize diameter Poor runout? NP charts should be used with data collected in subgroups that are the same size and when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data the number of nonconforming items per subgroup? 3 Are the subgroups the same size? 4 Are there only two outcomes to any given check? 5 Is the time order of subgroups preserved? 4 Some of the information in this section is taken from: PQ Systems, np-chart, accessed April 8, 2015,

19 Statistical Process Control DELMIA Apriso 2017 Implementation Guide C Chart 5 Figure 12 Sample NP chart This Attribute control chart monitors the number of nonconformities. This chart type is different from the P chart and NP chart, which deal with non-conforming parts. A C chart (or Count chart) displays how the number of defects, or nonconformities, for a Process or system changes over time. The number of defects is collected for the area of opportunity in each subgroup. The area of opportunity can be either a group of units or just one individual unit on which the defect counts are performed. The C chart is an indicator of the consistency and predictability of the level of defects in the Process. When constructing a C chart, it is important that the area of opportunity for a defect be constant from subgroup to subgroup, since the chart shows the total number of defects. When the number of items tested within a subgroup changes, then a U chart should be used, since it shows the number of defects per unit rather than total defects (for details on U charts, see U Chart). An example of this would the 100 check vehicle inspection done at the end of production of an automobile. The subgroup size must be selected. The subgroup size is the area where defects have the opportunity to occur, and it must be constant from subgroup to subgroup. The opportunity for defects to occur must be large. The number of defects that actually occur must be small. When Should This Chart Be Used? This chart shows the actual count of nonconformities, and it should be used for data collected in subgroups that are the same size and when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data the number of nonconformities per subgroup? 5 Some of the information in this section is taken from: PQ Systems, c-chart, accessed April 8, 2015,

20 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 20 3 Are the subgroups the same size? 4 Have the possible nonconformities been identified prior to data collection? 5 Is the time order of subgroups preserved? C Chart Data Mapping Figure 13 Sample C chart Get Chart Properties ProcessID ProductID SampleClass PartNum(int) NumOfNonConformances(int) Retrieve all valid test results. Group by each of the units and number of defects. Questions - Need to define what a unit is. For now this could be a Serial or Lot only! Because there is no sample group size (always 1) Data to be returned ProductNo LotNo Serial NumberofNonConf Prod1 Ser1 2 Prod1 Ser2 4 Prod1 Ser3 6. Write Data to the Database. (insert or update records. Finish Figure 14 C chart data mapping (A)

21 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 21 Get Chart Properties SubGroupSize ProductID Time Range 1 Disposition per Car Disposition Content Where ProductID = Chart.ProductID And WHERE Test is in Chart.TimeRange Data to be returned SampleGroupNum TotalSamples NumNonConf P DISPOSITION Quality Defect table LotNo, SerialNo, Count (Defects) GROUP BY LotNo, SerialNo Create Subgroups based on information U Chart 6 Figure 15 C chart data mapping (B) Similar to the C chart, the U chart is the number of non-conformities per unit. When Should This Chart Be Used? This chart should be used when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data a count of nonconformities per subgroup? 3 Can the counts be converted to proportions? 4 Have the possible nonconformities been identified prior to data collection? 5 Is the time order of subgroups preserved? 6 Some of the information in this section is taken from: PQ Systems, u-chart, accessed April 8, 2015,

22 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 22 U Chart Data Mapping Figure 16 Sample U chart Data to be returned SampleGroupNum TotalSamples NumNonConf P Get Chart Properties ProductID Time Range Disposition Content Where ProductID = Chart.ProductID And WHERE Test is in Chart.TimeRange DISPOSITION Quality Defect table LotNo, SerialNo, Count (Defects) GROUP BY DispositionLineNo, LotNo, SerialNo Figure 17 U chart data mapping

23 Statistical Process Control DELMIA Apriso 2017 Implementation Guide Run Chart Run charts are simply plots of Process Characteristics against time or in chronological sequence. They do not have a statistical basis, but they are useful for revealing trends and relationships between variables. When Should This Chart Be Used? Run charts should be used to show trends and multiple series of information. They are the basis of Attribute control charts X-Bar Average and Range 7 Figure 18: Sample Run chart The purpose of average and range control charts is to control the level of variability of a Process. Average and Range charts are traditionally used in mass production Operations. In general, an average and Range chart requires a minimum of 20 subgroups just to start. An X-Bar and R (Range) chart is a pair of control charts used with Processes that have a subgroup size of two or more. As standard charts for variable data, X-Bar and R charts help determine if a Process is stable and predictable. The X-Bar chart shows how the mean or average changes over time, and the R chart shows how the range of subgroups changes over time. This is also used to monitor the effects of Process improvement theories. Note that this X-Bar chart is displayed over both the Average and Range charts. When Should This Chart Be Used? This chart should be used when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data in variables form? 3 Is the data collected in subgroups larger than one but less than eleven? 4 Is the time order of subgroups preserved? X-Bar and Range charts are used when you can rationally collect measurements in groups (subgroups) of between two and ten observations. Each subgroup represents a "snapshot" of 7 Some of the information in this section is taken from: PQ Systems, X-bar and range chart, accessed April 8, 2015,

24 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 24 a Process at a time. The charts' x-axes are time-based, so the charts show the history of the Process. For this reason, you must have data that is time-ordered (that is, entered in the sequence from which it was generated). If this is not the case, then the trends or shifts in the Process may not be detected and instead be attributed to random (common cause) variations. For subgroup sizes greater than 10, use X-Bar and Sigma charts, since the range statistic is a poor estimator of Process sigma for large subgroups. In fact, the subgroup sigma is always a better estimate of subgroup variation than subgroup range. The popularity of the Range chart is only due to its ease of calculation, dating to its use before the advent of computers. For subgroup sizes equal to one, an Individual-X and Moving Range chart can be used, as can EWMA or CUSUM charts. X-Bar charts are efficient at detecting relatively large shifts in the Process average, typically shifts of ±1.5 sigma or larger. The larger the subgroup, the more sensitive the chart will be to shifts, providing a rational subgroup can be formed. For more sensitivity to smaller Process shifts, use an EWMA or CUSUM chart. Figure 19: Sample X-Bar Average and Range X-Bar Average and Standard Deviation (X-Bar and S [Sigma]) 8 An X-Bar and S (Sigma) chart is a special purpose variation of the X-Bar and R chart. Used with Processes that have a subgroup size of 11 or more, X-Bar charts and S charts show if the system is stable and predictable. They are also used to monitor the effects of Process improvement theories. Instead of using a subgroup range to chart variability, these charts use 8 Some of the information in this section is taken from: PQ Systems, X-bar and sigma, accessed April 8, 2015,

25 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 25 a subgroup standard deviation. Because standard deviation uses each individual reading to calculate variability, it provides a more effective measure of the Process spread. Note that this X-Bar chart is displayed over both the Average and Sigma charts. When Should This Chart Be Used? Use the X-Bar and S charts to analyze variable data with subgroups of 11 or more or when you want the most efficient measure of subgroup variability. Use X-Bar and S charts when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data in variables form? 3 Is the data collected in subgroups larger than ten? 4 Is the time order of subgroups preserved? Data Source The data source is the same as for X-Bar Average and Range charts Median Chart 9 A Median control chart ( ) is another alternative to the Average and Range charts. The specific advantages to this chart are as follows: Ease of use and readability No calculations required (just a straight display) The chart shows the spread of the Process output and gives a picture of the Process variation Note that this chart displays over two charts: the top chart is the Median, and the bottom chart is the Range. When Should This Chart Be Used? Use the Median chart when you want to plot all the measured values, not just the subgroup statistics. This may be the case when the subgroup ranges vary a great deal, as showing all the points will emphasize the spread. This chart shows users that individual data points can fall outside the control limits, while the central location is within the limits. Use a Median chart when you can answer yes to these questions: 1 Do you need to assess system stability? 2 Is the data in variables form? 3 Is the data collected in subgroups larger than one? 4 Is the time order of subgroups preserved? 5 Do you want to see individual data points? 6 Do you have subgroups of 10 parts or less? 9 Some of the information in this section is taken from: PQ Systems, Median chart, accessed April 8, 2015,

26 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 26 7 Do you want to see all the test data? Individual Chart Figure 20 Sample Median chart Individual and Moving Range charts (XI RM) use individual readings instead of subgroup averages. Note that this chart displays over both the Individual and Range charts. When Should This Chart Be Used? Use an Individual chart when you can answer yes to these questions: 1 Short production runs. 2 Small amounts of data (destructive testing, special Process tests). 3 When individual measurements are necessary or expensive.

27 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 27 Figure 21 Individual chart Exponentially Weighted Moving Average Chart (EWMA) 11 An EWMA (Exponentially Weighted Moving-Average) chart is a control chart for variable data (as in, data that is both quantitative and continuous in measurement, such as a measured dimension or time). It plots weighted moving average values. A weighting factor is chosen by the user to determine how older data points affect the mean value compared to more recent ones. Because a EWMA chart uses information from all samples, it detects much smaller Process shifts than a normal control chart would. When Should This Chart Be Used? Although standard EWMA charts are designed to monitor Processes with a stable mean, a modified EWMA control chart may be used for auto-correlated Processes with a slowly drifting mean 10 National Institute of Standards and Technology, NIST/SEMATECH e-handbook of Statistical Methods, "EWMA Control Charts," 2003, itl.nist.gov, (accessed April 21, 2015). 11 Some of the information in this section is taken from: Quality America Inc., Exponentially Weighted Moving Average (EWMA) Charts, accessed April 20, 2015, Center/statisticalprocesscontrol/exponentially_weighted_moving_average_(ewma)_charts.php.

28 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 28 4 SPC Chart Calculation and Display The following Business Components are used in the calculation and display of SPC charts: CalculateChart_v4 AddModifiyPointNote DeletePointNote ChangePointStatus To learn more about these Business Components, consult the Business Components Documentation.

29 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 29 5 Sample Scenario The sample scenario below will create a Line chart. Start with creating a new SPC_Charts_Op Standard Operation with two steps: 1 Select NewStep1. 2 Add a new Function: Name: SelectChart Type: Input Only Without Validation 3 Add a Function Input: Name: ChartID Data Type: Integer Input Source: User User Interface Control: Drop Down List Desktop: ChartID Input Value List: Database Query: SELECT ID FROM SPC_CHART ORDER BY ID ASC 4 Add a Function Output: Name: ChartID Data Type: Integer Routing Disposition: Session Variable Session Variable Name: ChartID 5 Select NewStep2. 6 Add a new Function: Name: CalculateChart Type: Business Component 7 Link a Business Component: Business Component: FlexNet.BusinessFacade.SPC.ChartDataController Method: CalculateChart_v4 8 Configure the Function Input: Name: ChartID Input Source: Session Variable Session Variable Name: ChartID 9 Add a new Function: Name: GetChartData Type: SQL Query SQL Statement:

30 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 30 SELECT SCD.XAxisValue, SCD.PlottedValue1, SCD.LCLValue1, SCD.UCLValue1, SCD.ControlValue1 FROM SPC_CHART SC INNER JOIN SPC_CHART_CALCULATION SCC ON SC.ID = SCC.SPCChartID AND SCC.IsLastCalculation = 1 INNER JOIN SPC_CHART_DATA SCD ON SCC.SPCChartID = SCD.SPCChartID AND SCC.ID = SCD.SPCChartCalculationID WHERE SC.ID 10 Add a Function Input: Name: ChartID Data Type: Integer Input Source: Session Variable Session Variable Name: ChartID 11 Add Function Outputs with the Data Type List of Decimal: Name: PlottedValue1 Name: XAxisValue Name: LCLValue1 Name: UCLValue1 Name: ControlValue 12 Add a new Function: Name: ShowChartData Type: Business Control 13 Link a Business Control: Business Control: Chart Control 14 Configure the chart to display data from the GetChartData Function.

31 Statistical Process Control DELMIA Apriso 2017 Implementation Guide 31 6 References The document referenced below is available from the DELMIA Apriso Start page, which can be accessed on your DELMIA Apriso server (<server name>/apriso/start). The newest version of the document is available from the 3DS Support. 1 Dassault Systèmes, Business Components Documentation The Business Components Documentation describes the Business Components used in the latest DELMIA Apriso release.