Upon notification and approval of the proposed change by the authorized customer representative, and after change implementation, submission is required unless otlienvise specified. Use of other construction or material For example, other constsuction as documented on than was used in the previously approved a deviation permit or included as a note on the part product design record and not covered by an engineering change as described in Table 3.
Production from new or modified tools This requirement only applies to tools, which due except perishable tools , dies, molds to their unique form or fimction, can be expected patterns, etc.
It is replacement tooling not meant to describe standard tools new or repaired , such as standard measuring devices, drivers manual or power , etc.
Rearrangement is defined as activity that changes the sequence of productlprocess flow from that documented in the process flow diagram including the addition of a new process. Production from tooling and equipment Production process tooling and lor equipment transferred to a different plant site or from transferred between buildings or facilities at one or an additional plant site. Change of supplier for pasts, non- The organization is responsible for approval of equivalent materials, or services e.
Product produced after the tooling has For product that has been produced after tooling been inactive for volume production for has been inactive for twelve months or more: twelve months or more.
Notification is required when the part has had no change in active purchase order and the existing tooling has been inactive for volume production for twelve months or more. The only exception is when the part has low volume, e. However a customer may specify certain PPAP requirements for service parts. Change in testlinspection method - new For change in test method, the organization should technique no effect on acceptance criteria have evidence that the new method has measurement capability equivalent to the old method.
Additionally, for bulk materials: These changes would normally be expected to have an effect on the performance of the product. New source of raw material from new or existing supplier.
The organization shall review and update, as necessary, all applicable items in the PAP file to reflect the production process, regardless of whether or not the customer requests a formal submission. The PPAP file shall contain the name of the authorized customer representative granting the waiver and the date. A new part or product i. Correction of a discrepancy on a previously Submission is required to correct any submitted part.
A "discrepancy" can be related to: e The product performance against the customer requirements 0 Dimensional or capability issues 0 Supplier issues o Approval of a part replacing an interim approval Testing, including material, performance, or engineering validation issues 3. Engineering change to design records, Submission is required on any engineering specifications, or materials for production change to the production productlpart design record. Additionally, for Bulk Materials: 4.
Process technology new to the organization, not previously used for this product. Level 2 Wai-sant with product samples and limited supporting data submitted to the customer. Level 3 Warrant with product samples and complete suppoi-ting data submitted to the customer.
Level 4 Warrant and other requirements as defined by the customer. Level 5 Warrant with product samples and complete supporting data reviewed at the organization's manufacturing location. See RetentiodSubmission Requirements Table 4.
The organization shall use level 3 as the default level for all subinissions unless othenvise specified by the authorized customer representative. I: The authorized customer representative may identify a submission level, different from the default level, that is to be used with each organization, or organization and customer part number combiliation. Different customer locations may assign different submission levels to the same organization manufacturing location.
NOTE 2: All of the f o r m referenced in this document may be replaced by computer-generated facsimiles. Acceptability of these facsimiles is to be confirmed with the authorized customer representative prior to the first submission. Upon approval of the submission, the organization shall assure that future production continues to meet all customer requirements.
NOTE: For those organizations that have been classified as "self certifying" PPAP submission level 1 by a specific customer, submission of the required organization-approved documentation will be considered as customer approval unless the organization is advised otherwise. The organization is therefore authorized to ship production quantities of the product, subject to releases from the customer scheduling activity.
Interim Approval will only be granted when the organization has: 0 clearly defined the non-compliances preventing approval; and, c prepared an action plan agreed upon by the customer.
PPAP re-submission is required to obtain a status of "approved. Note 2: Parts with a status of "Interim Approval" are not to be considered "Approved. No additional shipments are authorized unless an extension of the interim approval is granted. For bulk materials, the organization shall use the "Bulk Material Interim Approval" form, or its equivalent see Appendix F.
The submission shall be approved before production quantities may be shipped. Part Name and 2a. Customer Part Number: Engineering released finished end item part name and number. Org, Part Number: Part number defined by the organization, if any. Shown on Drawing Number: The design record that specifies the customer part number being submitted. Safety andlor Government Regulation: "Yes" if so indicated by the design record, otherwise "No. Weight: Enter the actual weight in kilograms to four decimal places unless otherwise specified by the customer.
Checking Aid Number, Change Level and Date: If requested by the customer, enter the checking aid number, its change level and date. Street Address, Region, Postal Code, Country: Show the complete address of the location where the product was manufactured.
For "Region," enter state, county, province, etc. Customer NameIDivision: Show the corporate name and division or operations group. Application: Enter the model year, vehicle name, engine, transmission, etc. If submitted via other customer format, enter the date customer confirmation was received.
Check the appropriate box es. For bulk materials, in addition to checking the appropriate box, check "Other" and write "Bulk Material" in the space provided. Check the appropriate boxes for dimensional, material tests, performance tests, appearance evaluation, and statistical data. Check the appropriate box. If "no," enter the explanation in "comments" below. Enter the number of pieces manufactured during the significant production run.
Enter the time in hours taken for the significant production run. Attach additional information as appropriate. Part Name Cust. Part Number Shown on Drawing No. Level 3 - Warrant with product samples and complete supporting data submitted to customer. Level 5 - Warrant with product samples and complete supporting data reviewed at organization's manufacturing location.
I further affirm that these samples were produced at the production rate of 24 ours 1 also certify that documented evidence of such compliance is on file and available for review. FAX No. Weight kg I Checking Aid No. Level 2 - Warrant with product samples and limited supporting data submitted to customer.
Level 4 - Warrant and other requirements as defined by customer. I also certify that documented evidence of such compliance is on file and available for review.
Drawing Number: Use the number of the drawing on which the part is shown if different from the part number. Part Name: Use the finished part name on the part drawing. Organization Name: Organization responsible for submission include supplier if applicable. Manufacturing Location: Location where part was manufactured or assembled.
SupplierNendor Code: Customer-assigned code for organization location where the part was manufactured or assembled. Reason for Submission: Check box es explaining the reason for this submission. Color Suffix: Use alphanumeric or numeric color identification.
Tristimulus Data: List numerical colorimeter data of submission part as compared to the customer-authorized master. Master Number: Enter alphanumeric master identification not used by Ford.
Master Date: Enter the date on which the master was approved. Material Type: Identify first surface finish and substrate e. Material Source: Identify first surface and substrate suppliers. Example: RedspotIDow. Color Shipping Suffix: Color part number suffix or color number. Part Disposition: To be determined by customer approved or rejected.
Comments: General comments by the organization or customer optional. Organization Signature, Phone No. Organizations are responsible for applying PAP to their suppliers of ingredients which have organization-designated special characteristics.
Any customer-specific requirements shall be documented on the Bulk Materials Requirements Checklist. Primary Responsibility - Customer: Identify by name or function the individual who will review and approve the element. Primary Responsibility - Organization: Identify by name or function the individual who will assemble and assure the completeness of the element to be reviewed. Approved by: Enter the initials of the authorized customer representative who has reviewed and accepted the element.
Attributes control charts would be used to monitor and evaluate discrete variables whereas variables control charts would be used to monitor and evaluate continuous variables. J Define the measurement system. Total process variability consists of part-to-part variability and measurement system variability. It is very important to evaluate the effect of the measurement system's variability on the overall process variability and determine whether it is acceptable.
The measurement performance must be predictable in terms of accuracy, precision and stability. Periodic calibration is not enough to validate the measurement system's capability for its intended use.
In addition to being calibrated, the measurement system must be evaluated in terms of its suitability for the intended use. The definition of the measurement system will determine what type of chart, variables or attributes, is appropriate.
Unnecessary external causes of variation should be reduced before the study begins. This could simply mean watching that the process is being operated as intended.
The purpose is to avoid obvious problems that could and should be corrected without use of control charts. This includes process adjustment or over control. In all cases, a process event log may be kept noting all relevant events such as tool changes, new raw material lots, measurement system changes, etc.
This will aid in subsequent process analysis. J Assure selection scheme is appropriate for detecting expected special causes. If one i assumes that it is, and in reality it is not, one carries an unnecessary risk f that may lead to erroneous and or biased conclusions. For more details see Chapter I, Section H. Data Collection 2. Establish Control Limits 3. Interpret for Statistical Control 4. Extend Control Limits for ongoing control see Figure These measurements are combined into a control statistic e.
The measurement data are collected from individual samples from a process stream. The samples are collected in subgroups and may consist of one or more pieces. In general, a larger subgroup size makes it easier to detect small process shifts. Create a Sampling Plan For control charts to be effective the sampling plan should define rational subgroups.
A rational subgroup is one in which the samples are selected so that the chance for variation due to special causes occurring within a subgroup is minimized, while the chance for special cause variation between subgroups is maximized. The key item to remember when developing a sampling plan is that the variation between subgroups is going to be compared to the variation within subgroups.
Taking consecutive samples for the subgroups minimizes the opportunity for the process to change and should minimize the within-subgroup variation. The sampling frequency will determine the opportunity the process has to change between subgroups.
The variation within a subgroup represents the piece-to-piece variation over a short period of time. Subgroup Size - The type of process under investigation dictates how the subgroup size is defined. As stated earlier, a larger subgroup size makes it easier to detect small process shifts. The team responsible has to determine the appropriate subgroup size. If the expected shift is relatively small, then a larger subgroup size would be needed compared to that required if the anticipated shift is large.
The calculation of the control limits depends on the subgroup size and if one varies the subgroup size the coiitrol limits will change for that subgroup. There are other teclviiques that deal with variable subgroup sizes; for example, see Montgomeiy and Grant and Leaveiiwortli Su bgrozp Frequency - The subgroups are taken sequentially in time, e.
The goal is to detect changes in the process over time. Subgroups should be collected often enough, and at appropriate times so that they can reflect the potential oppostunities for change. The potential causes of change could be due to worlt-shift differences, relief operators, wanii-up trends, material lots, etc. Number of Subgroups The nuinber of subgroups needed to establish - control limits should satisfy the following criterion: enough subgroups should be gathered to assure that the major sources of variation which can affect the process have had an oppoi-tunity to appear.
Generally, 25 or more subgroups containing about or more individual readings give a good test for stability and, if stable, good estimates of the process location and spread. This number of subgroups ensures that the effect of any extreme values in the range or standard deviation will be minimized.
In some cases, existing data may be available which could accelerate this first stage of the study. However, they should be used only if they are recent and if the basis for establishing subgroups is clearly understood. Before continuing, a rational sampling plan must be developed and documented.
Sampling Scheme - If the special causes affecting the process can occur unpredictably, the appropriate sampling scheme is a random or probability sample. A random sample is one in which every sample point rational subgroup has the same chance probability of being selected. A random sample is systematic and planned; that is, all sainple points are determined before any data are collected. For special causes that are laown to occur at specific times or events, the sampling scheme should utilize this knowledge.
Haphazard sampling or convenieiice sampling not based on the expected occurrence of a specific special cause should be avoided since this type of sampling provides a false sense of security; it can lead to a biased result and coiisequeiitly a possible erroneous decision.
Whichever sampling scheme is used all sainple points should be determined before any data are collected see Deming and Gmslta J Recordingldisplaying the actual data values collected. J For interim data calculations optional for automated charts. This should also include a space for the calculations based on the readings and the calculated control statistic s.
The value for the control statistic is usually plotted on the vertical scale and the horizontal scale is the sequence in time. The data values and the plot points for the control statistic should be aligned vertically. The scale should be broad enough to contain all the variation in the control statistic.
A guideline is that the initial scale could be set to twice the difference between the expected maximum and minimum values. J To log observations. This section should include details such as process adjustments, tooling changes, material changes, or other events which may affect the variability of the process.
Record Raw Data Enter the individual values and the identification for each subgroup. J Log any pertinent observation s. Calculate Sample Control Statistic s for Each Subgroup The control statistics to be plotted are calculated from the subgroup measurement data.
These statistics may be the sample mean, median, range, standard deviation, etc. Calculate the statistics according to the fomulae for the type of chart that is being used. Make sure that the plot points for the corresponding control statistics are aligned vertically. Connect the points with lines to help visualize patterns and trends. The data should be reviewed while they are being collected in order to identify potential problems.
If any points are substantially higher or lower than the others, confirm that the calculations and plots are correct and log any pertinent observations. They define a range of values that the control statistic could randomly fall within, given there is only common cause to the variation. If the average of two different subgroups from the same process is calculated, it is reasonable to expect that they will be about the same. But since they were calculated using different parts, the two averages are not expected to be identical.
Even though the two averages are different, there is a limit to how different they are expected to be, due to random chance.
This defines the location of the control limits. This is the basis for all control chart techniques. If the process is stable i. If the control statistic exceeds the control limits then this indicates that a special cause variation may be present. There are two phases in statistical process control studies. The first is identifying and eliminating the special causes of variation in the process. The objective is to stabilize the process.
A stable, predictable process is said to be in statistical control. The second phase is concerned with predicting future measurements thus verifying ongoing process stability.
During this phase, data analysis and reaction to special causes is done in real time. Once stable, the process can be analyzed to determine if it is capable of producing what the customer desires. Identify the centerline and control limits of the control chart To assist in the graphical analysis of the plotted control statistics, draw lines to indicate the location estimate centerline and control limits of the control statistic on the chart. See Chapter 11, Section C, for the formulas.
Special causes can affect either the process location e. The objective of control chart analysis is to identify any evidence that the process variability or the process location is not operating at a constant level - that one or both ai-e out of statistical control - and to take appropriate action.
In the subsequent discussion, the Average will be used for the location control statistic and the Range for the variation control statistic. The conclusions stated for these control statistics also apply equally to the other possible control statistics. Since the control limits of the location statistic are dependent on the variation statistic, the variation control statistic should be analyzed first for stability. The variation and location statistics are analyzed separately, but comparison of patterns between the two charts may sometimes give added insight into special causes affecting the process A process cannot be said to be stable in statistical control unless both charts have no out-of-control conditions indications of special causes.
Analyze the Data Since the ability to interpret either the subgroup ranges or subgroup averages depends' on the estimate of piece-to-piece variability, the R chart is analyzed first. The data points are compared with the control limits, for points out of control or for unusual patterns or trends see Chapter 11, Section D ecial Causes Range For each indication of a special cause in the range chart data, conduct an analysis of the process operation to deternine the cause and improve process understanding; correct that condition, and prevent it from recurring.
The control chart itself should be a useful guide in problem analysis, suggesting when the condition may have began and how long it continued. However, recognize that not all special causes are negative; some special causes can result in positive process improvement in terms of decreased variation in the range - those special causes should be assessed for possible institutionalization within the process, where appropriate.
Timeliness is important in problem analysis, both in terms of minimizing the production of inconsistent output, and in terms of having fresh evidence for diagnosis.
It should be emphasized that problem solving is often the most difficult and time-consuming step. Statistical input from the control chart can be an appropriate starting point, but other methods such as Pareto charts, cause and effect diagrams, or other graphical analysis can be helpful see Ishikawa Ultimately, however, the explanations for behavior lie within the process and the people who are involved with it.
Thoroughness, patience, insight and understanding will be required to develop actions that will measurably improve performance. CHAPTER I1 - Section A Control Charting Process Recalculate Control Limits Range Chart When conducting an initial process study or a reassessment of process capability, the control limits should be recalculated to exclude the effects of out-of-control periods for which process causes have been clearly identified and removed or institutionalized.
Exclude all subgroups affected by the special causes that have been identified and removed or institutionalized, then recalculate and plot the new average range and control limits.
Confirm that all range points show control when compared to the new limits; if not, repeat the identification, correction, recalculation sequence.
If any subgroups were dropped from the R chart because of identified special causes, they should also be excluded from the chart. NOTE: The exclusion of subgroups representing unstable conditions is not just "throwing away bad data.
This, in turn, gives the most appropriate basis for the control limits to detect future occurrences of special causes of variation.
Be reminded, however, that the process must be changed so the special cause will not recur if undesirable as part of the process. Find and Address Special Causes Average Chart Once the special cause which affect the variation Range Chart have been identified and their effect have been removed, the Average Chart can be evaluated for special causes.
In Figure For each indication of an out-of-control condition in the average chart data, conduct an analysis of the process operation to determine the reason for the special cause; correct that condition, and prevent it from recurring. Use the chart data as a guide to when such conditions began and how long they continued. Timeliness in analysis is important, both for diagnosis and to minimize inconsistent output. Problem solving techniques such as Pareto analysis and cause-and-effect analysis can help.
Ishikawa Recalculate Control Limits Average Chart When conducting an initial process study or a reassessment of process capability, exclude any out-of-control points for which special causes have been found and removed; recalculate and plot the process average and control limits. The preceding discussions were intended to give a functional introduction to control chart analysis. Even though these discussions used the Average and Range Charts, the concepts apply to all control chart approaches.
Furthermore, there are other considerations that can be useful to the analyst. One of the most important is the reminder that, even with processes that are in statistical control, the probability of getting a false signal of a special cause on any individual subgroup increases as more data are reviewed. While it is wise to investigate all signals as possible evidence of special causes, it should be recognized that they may have been caused by the system and that there may be no underlying local process problem.
If no clear evidence of a special cause is found, any "corrective" action will probably serve to increase, rather than decrease, the total variability in the process output. It might be desirable here to adjust the process to the target if the process center is off target. These limits would be used for ongoing monitoring of the process, with the operator and local supervision responding to signs of out-of-control conditions on either the location and variation X or R chart with prompt action see Figure A change in the subgroup sample size would affect the expected average range and the control limits for both ranges and averages.
This situation could occur, for instance, if it were decided to take smaller samples more frequently, so as to detect large process shifts more quickly without increasing the total number of pieces sampled per day. As long as the process remains in control for both averages and ranges, the ongoing limits can be extended for additional periods. If, however, there is evidence that the process average or range has changed in either direction , the cause should be determined and, if the change is justifiable, control limits should be recalculated based on current performance.
The goal of the process control charts is not perfection, but a reasonable and economical state of control. For practical purposes, therefore, a coiltrolled process is not one where the chart never goes out of control. Obviously, there are different levels or degrees of statistical control.
The definition of control used can range from mere outliers beyond the control limits , through runs, trends and stratification, to fidl zone analysis.
As the definition of control used advances to fill1 zone analysis, the liltelihood of finding lack of control increases for example, a process with no outliers may demonstrate lack of control though an obvious run still within the control limits.
For this reason, the definition of control used should be consistent with your ability to detect this at the point of control and should remain the same within one time period, within one process. Some suppliers may not be able to apply the hller definitions of conti on the floor on a real-time basis due to immature stages of operator training or lack of sophistication in the operator's ability. The ability to detect lack of control at the point of control on a real-time basis is an advantage of the control chart.
Over-intespretation of the data can be a danger in maintaining a true state of economical control. The presence of one or more points beyond either control limit is primary evidence of special cause variation at that point. This special cause could have occurred prior to this point. Since points beyond the control limits would be rare if only variation from comrnon causes were present, the presumption is that a special cause has accounted for the extreme value. Therefore, any point beyond a control limit is a signal for analysis of the operation for the special cause.
Mark any data points that are beyond the control limits for investigation and corrective action based on when that special cause actually started. A point outside a control limit is generally a sign of one or more of the following: The control limit or plot point has been miscalculated or misplotted.
The piece-to-piece variability or the spread of the distribution has increased i. The measurement system has changed e. For charts dealing with the spread, a point below the lower control limit is generally a sign of one or more of the following: The control limit or plot point is in error.
The spread of the distribution has decreased i. A point beyond either control limit is generally a sign that the process has shifted either at that one point or as part of a trend see Figure When the ranges are in statistical control, the process spread - the within-subgroup variation - is considered to be stable. The averages can then be analyzed to see if the process location is changing over time.
If the averages are not in control, some special causes of variation are malting the process location unstable. This could give the first warning of an unfavorable condition which should be corrected. Conversely, certain patterns or trends could be favorable and should be studied for possible permanent improvement of the process. Comparison of patterns between the range and average charts may give added insight.
There are situations where an "out-of-control pattern" may be a bad event for one process and a good event for another process. An example of this is that in an X and R chart a series of 7 or more points on one side of the centerline may indicate an out-of-control situation.
If this happened in a p chart, the process may actually be improving if the series is below the average line less nonconformances are being produced.
So in this case the series is a good thing - if we identify and retain the cause. Mark the point that prompts the decision; it may be helpful to extend a reference line back to the beginning of the run. Analysis should consider the approximate time at which it appears that the trend or shift first began. J A change in the measurement system e. J A change in the measurement system, which could mask real performance changes. OTE: As the subgroup size n becomes smaller 5 or less , the likelihood of runs below R increases, so a run length of 8 or more could be necessary to signal a decrease in process variability.
A run relative to the process average is generally a sign of one or both of the following: J The process average has changed - and may still be changing.
J The measurement system has changed drift, bias, sensitivity, etc. Care should be taken not to over-interpret the data, since even random i. Examples of nom-andom patterns could be obvious trends even though they did not satisfy the runs tests , cycles, the overall spread of data points within the control limits, or even relationships among values within subgroups e.
One test for the overall spread of subgroup data points is described below. If several process streams are present, they should be identified and tracked separately see also Appendix A. Figure The most commonly used are discussed above. Determination of which of the additional criteria to use depends on the specific process characteristics and special causes which are dominant within the process.
Note 2: Care should be given not to apply multiple criteria except in those cases where it makes sense. The application of each additional criterion increases the sensitivity of finding a special cause but also increases the chance of a Type I error. In reviewing the above, it should be noted that not all these considerations for interpretation of control can be applied on the production floor. There is simply too much for the appraiser to remember and utilizing the advantages of a computer is often not feasible on the production floor.
So, much of this more detailed analysis may need to be done offline rather than in real time. This supports the need for the process event log and for appropriate thoughtfill analysis to be done after the fact. Another consideration is in the training of operators. Application of the additional control criteria should be used on the production floor when applicable, but not until the operator is ready for it; both with the appropriate training and tools.
With time and experience the operator will recognize these patterns in real time. The Average Run Length is the number of sample subgroups expected between out-of-control signals. The in-control Average Run Length A X , is the expected number of subgroup samples between false alai-ins. The ARL is dependent on how out-of-control signals are defined, the true target value's deviation from the estimate, and the tme variation relative to the estimate.
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