Quality-control tests and important process variables

2 Quality-control tests and important process variables 

---

The manufacture of biological products, unlike that of pharmaceuticals, uses materials that present variability. The active substance is generally produced in small quantities and needs to be separated from complex mixtures containing several types of contaminants. Lots are generally small and quality control tests are usually based on biological techniques that present higher variability than physicochemical assays. The processes are also susceptible to microbial contamination. The in-process controls are of fundamental importance to detect quality deviations that cannot be assessed through assays performed only on the final products. 

To solve a flow problem or characterize a given fluid, an instrument must be carefully selected. Many commercial viscometers are available with a variety of geometries for wide viscosity ranges and shear rates (10,21,49). Rarely is it necessary to construct an instrument. However, in choosing a commercial viscometer a number of criteria must be considered. Of great importance is the nature of the material to be tested, its viscosity, its elasticity, the temperature dependence of its viscosity, and other variables. The degree of accuracy and precision required, and whether the measurements are for quality control or research, must be considered. The viscometer must be matched to the materials and processes of interest otherwise, the results may be misleading. 

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. 

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. 

---