Software factory

The development of custom applications is generally expensive and is often plagued by uncertainties, such as the duration of the development cycle or the difficulty of assessing costs. Thus, the tendency to shift software development from individual development to an organizational form of industrial manufacturing—in software factories — is not surprising. 

Cusumano, Japan s software factories a challenge to US management. 

Crocca, E.T. 1993. Review of M. Cusumano, Japan s software factories . Administrative Science Quarterly, 37(4). 

The linear regression calculations for a 2 factorial design are straightforward and can be done without the aid of a sophisticated statistical software package. To simplify the computations, factor levels are coded as +1 for the high level, and -1 for the low level. The relationship between a factor s coded level, Xf, and its actual value, Xf, is given as... 

In this context, 14 different reaction conditions were investigated in 14 hours. By software-supported process optimization (factorial design), the initial yield of 49% could be improved to 78% with a simultaneous increase in keto/enol isomer ratio (A B) of65 35 to95 5. 

Currently Bayer Technology Services considers extending the software BayAPS PP to compute the optimal split of a product between several production lines or factories that can produce it. This split is influenced by uncertain demand with different characteristics in different regions, different cost oftransport and different production cost in the factories. This means that different marginal incomes for the same product occur depending on the place of production and/or the customer group which receives it. The mathematical formulation ofthe optimization criterion again is to maximize the expected service. This has already been solved for several types of constraints. 

Fractional distillation of crude pine oil, 24 510 of crude sulfate turpentine, 24 476 Fractional extraction, 10 745, 759-760 Fractional factorial designs, 8 396 amount of coverage in experimental design texts compared, 8 395t commercial experimental design software compared, 8 398t Fractional velocity plots, 10 319-321 Fractionating towers, in plant layout,... 

A number of software packages or expert systems for ruggedness testing has been developed. RES (commercialized under the name Shaiker ) is an expert system created by Van Leeuwen et al. [4,23] and has been validated and evaluated [42,43]. It uses fractional factorial and Plackett-Burman designs and allows to test the factors at two or three levels. The interpretation criteria used here are the predefined values (see Section 3.4.8). 

This model allows us to estimate a response inside the experimental domain defined by the levels of the factors and so we can search for a maximum, a minimum or a zone of interest of the response. There are two main disadvantages of the complete factorial designs. First, when many factors were defined or when each factor has many levels, a large number of experiments is required. Remember the expression number of experiments = replicates x Oevels) " (e.g. with 2 replicates, 3 levels for each factor and 3 factors we would need 2 x 3 = 54 experiments). The second disadvantage is the need to use ANOVA and the least-squares method to analyse the responses, two techniques involving no simple calculi. Of course, this is not a problem if proper statistical software is available, but it may be cumbersome otherwise. 

Problems encountered in HPLC analysis most often stem from a lack of knowledge of the influence of the slight variation of the experimental parameters (pH, temperature, solvent composition, flow rate, etc.). The analyst has to set up the list of parameters and their possible interactions. There are hardware parameters (e.g., flow control, temperature control, lamp current) and software parameters used to interpret and report the results from stored data. The use of factorial designs is of great help. Software such as Validation Manager, from Merck, produces, in a table for each parameter and interaction, its percentage and confidence interval as well as information to help the analyst in concluding the study. 

The software OQ includes all of the factory acceptance testing and, specifically, the following ... 

To investigate relationships between crustacean grazing rates on Phaeocystis and experimental conditions, a multiple correspondence analysis (MCA) followed by a hierarchical cluster analysis (HCA) was performed using SPAD 3.5 software (Lebart et al. 1988). The combination of MCA and cluster analysis is a common way to explore relationships among a large number of variables and to facilitate interpretation of the correspondence analysis results (Lebart et al. 2000). MCA uses a contingency table as data, which provides a simultaneous representation of the observations (rows) and variables (column) in a factorial space. This form of multivariate analysis describes the total inertia (or variability) of a multidimensional... 

The potential importance for dispersion of main effects for E and F and an EF interaction suggests that this would be a good test case for the McGrath-Lin statistic. The appropriate location model includes main effects and all interactions of factors A, E, and F. That model has zero residuals for all four observations with E and F at their low values. (As in the full factorial, our software actually computes these as machine-zero.) Thus, the McGrath-Lin statistic will indicate strong effects for all three terms. However, the presence of the zero residuals casts questions on the validity of any distributional results for the statistic. 

The linear constraint (5-15) means that (p way) factorial experimentation is impossible, and that special measures must be employed in order to use standard regression analysis software to do least squares equation fitting. We will briefly describe in turn some approaches to experimental design, equation fitting, and presentation of results for the... 

Suppliers conduct factory and site acceptance testing (FAT, SAT). Testing carried out at the factory includes hardware and software tests. Successful completion of the tests allows shipment of the IPC system to site. Tests include ... 

Testing is condncted in several phases depending on the complexity of the software design. The snpplier shall be responsible for developing modnle, integration, factory, and site acceptance test specifications to demonstrate that the design has been fully and accurately implemented. 

Factory Acceptance Testing (FAT) is conducted within a simulated environment to demonstrate that the system meets the URS and FDS. The FAT will only be conducted if the software is a new development or major adaptation of the standard product. The FAT is the first opportunity for the pharmaceutical manufacturer to test the system in its entirety. The scope of the testing should be wide enough to ensure that most problems can be identified and rectified within the development enviromnent. Where tests are not dependent on the operating environment as, for example, in data entry validation, the FAT may serve as the validation record for that function. However, in order to adopt this approach, formal test specifications must be developed and approved prior to executing the tests, and results must be clearly recorded. 

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