Quality control variable

Step 5 is done next because the control of product quality is closely tied to Step 1 and is a higher priority than the control of inventories. Hence it should be done early when we still have the widest choice of manipulators available. Its importance is based on the issue of variability. which we want to be as small as possible for on-aim product quality control. Variability in inventory control tends to be not as critical, which is the reason it is done in Step 6. 

Two fault categories are associated with quality control—variables and attributes. Variables are those faults that can be measured, usually instrumentally, i.e. dimensional measurements, burst strength, etc. Attributes are those faults which either cannot be accurately assessed (frequently associated with appearance, i.e. visual defects) or can be assessed by go—no go procedures without resorting to accurate measurements. 

As has been seen in Table 4.1, the polymer microstructure influences the application properties of the polymer, such as melt flow index (MFI). The MFI is the mass flow rate [in g (10 min) ] of a HIPS melt that flows through a capillary, when forced by a piston loaded by a constant weight. It indicates the processability of the polymer and it is an important quality control variable in the polymerization process. MFI mainly depends... 

The BMS deviation is a measure of the spread of values for c around the mean. A large value of O indicates that wide variations in c occur. The probability that the controlled variable hes between the values of Cl and C9 is given by the area under the distribution between Ci and Cg (histogram). If the histogram follows a normal probabihty distribution, then 99.7 percent of aU observations should lie with 3o of the mean (between the lower and upper control limits). These Emits are used to determine the quality of control. 

BWRs do not operate with dissolved boron like a PWR but use pure, demineralized water with a continuous water quality control system. The reactivity is controlled by the large number of control rods (>100) containing burnable neutron poisons, and by varying the flow rate through the reactor for normal, fine control. Two recirculation loops using variable speed recirculation pumps inject water into the jet pumps inside of the reactor vessel to increase the flow rate by several times over that in the recirculation loops. The steam bubble formation reduces the moderator density and... 

Infant mortality results in repaired units failing shortly after their return to service. It can be corrected by simplifying repair techniques, quality control of repairs and repair parts, improved starting techniques, etc. Units which have persistent abnormally short lives may have an inherent defect which cannot be corrected by the previous methods. However, the usual characteristic of infant mortality is its variability. Very good pumps of last year become the very bad ones this year and vice versa. Any pump is a potential bad actor. 

In the final analysis, market price and sales volume are functions of the quality standards offered and the buyer s degree of confidence that the product will conform to the standards. Maintenance of buyer s confidence requires inspection to screen out all nonconforming products, or control over variability of quality during production and distribution to a degree where few, if any, products fail to meet the standards. Screening inspection of the finished product cannot improve quality it merely serves to segregate unacceptable from acceptable product, and results in loss of production capacity and costly waste and salvage. The second consideration provides the only sound basis for quality control in frozen food production and distribution. It operates on the old principle that an ounce of prevention is worth a pound of cure. ... 

The manufacturing and quality control departments face higher costs because they have to eliminate process and measurement variability, even if they are already operating at the technological limit. They will have to add people to their staffs to mn all of the investigations and handle the additional paperwork (because malicious intent is suspected, peers and supervisors have to sign off at every step to confirm that each SOP was strictly adhered to whether the SOPs made sense, scientifically speaking, or were installed to satisfy formalistic requirements is of no interest here). 

Process automation implies the real time acquisition and control of process variables such as temperature, agitation, material delivery, or quality control measurements. As far as the MARS system is concerned, a real time process is just like any instrument. The acquisition module merely requires more interactive monitoring, alarms, and control. This can be accomplished by means of a real time multi-tasking data acquisition module. 

However, it has been established that an intense control of certain variables may improve the execution of a hydraulic fracturing job and the success of a stimulation. Therefore an intense quality control is recommended [552,553]. Such a program includes monitoring the breaker performance at low temperatures and measuring the sensitivity of fracturing fluids to variations in crosslinker loading, temperature stabilizers, and other additives at higher temperatures. 

UNEQ can be applied when only a few variables must be considered. It is based on the Mahalanobis distance from the centroid of the class. When this distance exceeds a critical distance, the object is an outlier and therefore not part of the class. Since for each class one uses its own covariance matrix, it is somewhat related to QDA (Section 33.2.3). The situation described here is very similar to that discussed for multivariate quality control in Chapter 20. In eq. (20.10) the original variables are used. This equation can therefore also be used for UNEQ. For convenience it is repeated here. 

When developing or routinely using an analytical method, quality control (QC) fortifications can be added to each sample at critical points in the procedure to ensure that sensitive steps in the method were conducted properly and to pinpoint where problems occurred if results are less than satisfactory. For example, if the QC fortification samples for detection and cleanup were to show acceptable results in a batch of samples, but the extraction QC spike gave low recovery and/or high variability, then the analyst could modify instrument conditions or altering cleanup parameters immediately. Likewise, if the QC spike added just before analysis gives poor results, then instrument maintenance could be done and the samples merely re-analyzed rather than re-extracted. 

Identify the key process variables that need to be controlled to achieve the specified product quality. Include control loops using direct measurement of the controlled variable, where possible if not practicable, select a suitable dependent variable. 

If repeatability is the only estimate of precision that is obtained, this is unlikely to be representative of the variability observed when the method is used over a long period of time. Intermediate precision is often more relevant - this expresses the within-laboratory variation or within-laboratory reproducibility (different days, different analysts, different equipment, etc.). This is initially obtained from validation studies and confirmed later by examining the results obtained for quality control material measured over a period of about three months (see the quality control (QC) charts in Chapter 6). 

The endpoint measurement of the ideal test system must be objective, so that a given compound will give similar results when tested using the standard test protocol in different laboratories. If it is not possible to obtain reproductive results in a given laboratory over time or between various laboratories, then the historical database against which new compounds are evaluated will be time- and laboratory-dependent. Along these lines, it is important for the test protocol to incorporate internal standards to serve as quality controls. Thus, test data could be represented utilizing a reference scale based on the test system response to the internal controls. Such normalization, if properly documented, could reduce intertest variability. 

The results described here demonstrate the importance of appropriate treatment and monitoring in actual drinking water processing plants, with attention to the specific requirements of the raw water matrix in use. In particular, the adverse effect of certain processes, namely pre-chlorination, which has been implicated in the inhibition of biodegradation in subsequent steps, and in the formation of alternative metabolites, is highlighted. Furthermore, the variable efficiency of GAC filtration in practice, emphasises the need for regular monitoring and quality control. The duration of specific process steps has also been shown to influence the efficacy of the technique, and should be addressed in application. 

In general, it is preferable to choose excipients and processes for IR dosage forms that do not result in a formulation that requires a particular pH to function well. In the general population, the pH in the stomach is quite variable (see the subsection Choice of Dissolution Test Conditions for Quality Control ) and there is no guarantee that the dosage form will be exposed to acid, so dosage forms that require acid to facilitate release are unlikely to perform robustly in the clinical practice setting. 

In this chapter, the emphasis is on producing physiologically relevant dissolution data sets. Compared to dissolution profiles obtained according to relevant compendia requirements for quality control purposes, biorelevant dissolution data sets collected in closed systems often do not reach 100% dissolved and frequently are associated with higher variability (22). 

Independent of existing intra-lot variability, a sample size of six dosage units is generally recognized to suffice the needs of quality control (QC). In very early development less than six specimens may be used to create data, but as soon as possible tests should be run with at least n = 6. It is advisable to create statistically valid and sound data for manufacturing prototypes even at very early phases of development, in order to be able to identify formulations/batches with unwanted dissolution behavior. In the early phases of a drug product s development, formulations may not be of acceptable stability. This means that stability phenomena may mask... 

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