Mixed variables

In some cases, one needs to combine variables of mixed types (binary, ordinal or continuous). The usual way to do this is to eliminate the effect of varying ranges by scaling. All variables are transformed, so that they take values from 0 to 1 using range scaling for the continuous variables or the procedure for scaling described 

---

Scale-up involves selec tiug mixing variables to give the desired performance in both pilot and full scale. This is often difficult (sometimes... 

It is seldom possible, either economically or timewise, to study eveiy potential mixing variable or to compare the performance of many impeller types. In many cases, a process needs a specific fluid regime that is relatively independent of the impeller type used to generate it. Because different impellers may require different geometries to achieve an optimum process combination, a random choice of only one diameter of each of two or more impeller types may not tell what is appropriate for the fluid regime ultimately required. 

Performance Relationships for Mixing Variables More Than One Variable Changing or Held Constant... 

Referring to Table 6.3, it can be seen that with geometric similarities in self controls there is no mixing variable. In practice, we would select the important criterion that needs to be controlled and then size the vessel accordingly. 

Froude number, 304 Heal transfer, 312 In baffled tanks, 301 Performance relationships, mixing variables, 306... 

TABLE 5.9. Variable Selection Results for Component A Using the Mixed-Variable Selection Approach ... 

Candidate Tariables were chosen using a mixed-variable selection method and validated based on prediction ability. Separate models (with different measurement variables) were estimated for each of the components. The final models and measures of performance are as follows (see Table 5.11 for a description of these figures of merit) ... 

A mixed variable-selection method is used to select variables with the Proba-biiin to Enter and Probability to Leave values set to 0.05. Separate models are constructed to predict components A and B. The calibration data are used to select the variables to include in the model, and the validation data are used to further refine the model to optimize the predictive ability. 

The mixed-variable selection method is used with the probability to enter and probability to leave values set to 0.03. Only a model for the prediction of caustic concentration is developed, which means that the values for the salt, water, and temperatures are not used in the calculations (even though in this case they are known). The calibration data (X in Figure 5.42) consisting... 

In this context, diffuse reflectance FTIR spectroscopy has been applied to analyze the influence of mixing variables (i.e. treatment concentration, time and temperature of mixing) on both the ultimate flller coating level and possible reaction between the treatment and flller surface [127]. 

J. F. Benders. Partitioning procedures for solving mixed-variables programming problems. Numer. Math., 4 238,1962. 

The next marketing-mix variable is the physical facility, which refers to the setting where the service will be delivered. Usually this is somewhere within the pharmacy. A question is, Does this setting make the patient ready to receive the service For example, does the patient perceive sufficient privacy to participate in a health care service Private or semiprivate consultation areas can create the environment needed to provide pharmacy services satisfactorily. Also, consideration should be given to space and workflow. A new pharmacy layout may be needed to accommodate a new pharmacy service because new equipment or space may need to be put in place. 

The last marketing-mix variable is productivity and quality. One issue here is creating efficiency in pharmacy service activities. This means that monitoring and feedback of service encounters should be performed. Then pharmacists can be trained to be efficient in the time spent with patients when providing services. Time benchmarks can be established for various service offerings. Nonpharmacist personnel should be used where appropriate, such as in scheduling appointments and billing payers. 

The next marketing-mix variables that need careful consideration are the place and physical facility. Care-Rite Pharmacy will be providing the Pharmacy Check-up Service on site. Therefore, pharmacy staff need to consider patient privacy and space to provide the service. In preparation for this service, Carol did some remodeling of her pharmacy. She created two semiprivate patient areas using office partitions. One area was designated as the area where lipid testing... 

Process management, the next marketing-mix variable, refers to how Care-Rite Pharmacy incorporated the new Pharmacy Check-up Service into its existing practice. Workflow decisions were made regarding patient flow during the service. It was decided that the service would be by appointment only to minimize disruption of the other aspects of the practice. Schedules for pharmacists were created so that one pharmacist was responsible for clinic services while another covered the dispensing area. 

Recently, one of the most practical results of these studies has been the ability to design pilot plant experiments (and, in many cases, plant-scale experiments) that can establish the sensitivity of process to macroscale mixing variables (as a function of power, pumping capacity, impeller diameter, impeller tip speeds, and macroscale shear rates) in contrast to microscale mixing variables (which are relative to power per unit volume, rms velocity fluctuations, and some estimation of the size of the microscale eddies). 

It is seldom possible, either economically or time-wise, to study every potential mixing variable or to compare the performance of many impeller types. 

Many processes involve criteria other than solids suspension, for example, crystallization, precipitation, and many types of leaching and chemical reactions. In crystallization, the shear rate around the impeller and other mixing variables can affect the rate of nucleation, and can affect the ultimate particle size. In some cases, the shear rate can be such that it can break down forces within the solid particle and can affect the ultimate particle size and shape. There are some very fragile precipitate crystals that are very much affected by the mixer variables. 

---