Testing results statistical process control

Statistical Control. Statistical quahty control (SQC) is the apphcation of statistical techniques to analytical data. Statistical process control (SPC) is the real-time apphcation of statistics to process or equipment performance. Apphed to QC lab instmmentation or methods, SPC can demonstrate the stabihty and precision of the measurement technique. The SQC of lot data can be used to show the stabihty of the production process. Without such evidence of statistical control, the quahty of the lab data is unknown and can result in production challenging adverse test results. Also, without control, measurement bias cannot be determined and the results derived from different labs cannot be compared (27). 

One approach for using DOE on more complex processes is to do the majority of the process development on smaller, representative sections of material, such as test panels, rather than on full-scale parts, and then to scale up with a more limited experimental matrix. There is no guarantee that experience on small-scale test panels will directly translate to large parts because dimensions and thickness of the part are important variables in their own right. Another way to save on costs is to start with a satisfactory process and to continue, via careful monitoring of process variations and results, to extend the range of experience. This method is variously called statistical process control or statistical quality control. 

Concurrent validation is conducted under a protocol during the course of normal production. The first three production-scale batches must be monitored as comprehensively as possible. The evaluation of the results is used in establishing the acceptance criteria and specifications of subsequent in-process control and final product testing. Some form of concurrent validation, using statistical process control techniques (quality control charting), may be used throughout the product manufacturing life cycle. 

The middle part of Table 7.4 is about more formal statistical tests, where the distributional properties of the residual data are calculated from the residuals themselves. This is more demanding and often requires knowledge of degrees of freedom, which is a difficult subject for three-way residuals. If the residuals are centered around zero, then the sum of squared residuals is approximately x2 distributed [Box 1954], The degrees of freedom can be estimated from the data [Box 1954, Jackson Mudholkar 1979], The resulting statistics are used in multivariate statistical process control (see Chapter 10). 

For either reason one is obliged to test just a few articles and judge the whole of the production by those results. Statistieal processes are employed in this case. If a fixed quantity of produets (random sampling) is tested by this method at regular intervals, the test result allows conclusions to be made with regard to the quahty of all articles produced during that period. These processes are covered by the term SPC = Statistical Process Control. 

Plating, solderability, and soldering in the tin lead world has such a large process window that in the majority the dip and look testing suffices with defects normally in the parts per biUion. The occasional disaster does occur but it is rare and attributable to an assignable cause. This process latitude and statistical process control has resulted in the demise of the incoming inspection departments at the CM or OEM. The technician who wonld have once performed the testing has been replaced by a clerk who only job is to reconcile the pnrchase order quantity with the received qnantity. 

Quality management including inspection and testing, laboratory results, and statistical process control. 

Control limit, n - for validation tests, the maximum difference allowed between a valid analytical result, and a reference method result for the same sample. A measured value that exceeds a control limit requires that action be taken to correct the process. Control limits are statistically determined. 

The use of NIR in polymer process applications has grown tremendously. Results are obtained online in seconds, providing a high measuring frequency, which makes NIR an ideal technique for statistical process analysis. Real-time testing also enables detection of malfunction in time for process corrections to be implemented. Anticipatory process control is especially important for thermosetting materials that, once reacted, are irreversibly formed. 

In quality control of production processes, control charts are applied to display results of statistical sampling tests of products. Basic textbooks propose the use of a confidence interval of +/- three standard deviations in this application (see e.g. Wig, 1996). Lor a stable distribution, 99.7 per cent of the results of the tests will fall within this interval. The underlying... 

SPC does require statistical quantities of product and automated data tracking. The best processes for SPC are those which are used to make large quantities of inexpensive parts. SPC is also difficult to apply to processes where the number of independent variables is large. Automated data acquisition is a must for SPC, but this is becoming inexpensive and common in the workplace. SPC is also a delayed control method. Many defective parts may be made before SPC corrects the process. The longer it takes to evaluate the results of the process, the more delay in the ability to react to process changes. Another important requirement of SPC is attention to detail on the part of the operator and/or process engineer. No battery of QC tests will detect every variation either in materials and process or in final quality. 

Retrospective validation involves using the accumulated in-process production and final product testing and control (numerical) data to establish that the product and its manufacturing process are in a state of control. Valid in-process results should be consistent with the drug products final specifications and should be derived from previous acceptable process average and process variability estimates, where possible, and determined by the application of suitable statistical procedures, that is, quality control charting, where appropriate. The retrospective validation option is selected when manufacturing processes for established products are considered to be stable and when, on the basis of economic considerations and resource limitations, prospective qualification and validation experimentation cannot be justified. 

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