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dc.contributor.authorOmidbakhsh, Navid
dc.date.accessioned2010-09-02 15:49:39 (GMT)
dc.date.available2010-09-02 15:49:39 (GMT)
dc.date.issued2010-09-02T15:49:39Z
dc.date.submitted2010
dc.identifier.urihttp://hdl.handle.net/10012/5474
dc.description.abstractDisinfectants are antimicrobial chemicals that are commonly used in health care facilities to prevent or reduce the spread of pathogenic microorganisms. These products are under national regulations for the claims they make and have to be tested for their microbial activity against different microorganisms. They have to also be tested for product stability, corrosion and toxicity. These tests, especially the microbial efficacy tests, are very expensive and take a long time to perform (anywhere from two days to four months). Disinfectant formulations have to have a balance between their microbial activity, corrosivity, and safety. The more active ingredients in the formulation, the stronger the product, but the higher the corrosivity and toxicity. Therefore, it is desirable to use as low concentrations of ingredients as possible in the formulation to achieve the acceptable antimicrobial activity. The final product has to also be chemically and physically stable for at least one year. Consequently, the product development process takes at least six months and sometimes even up to two years. The cost might also reach hundreds of thousands of dollars. The objective of this project was to design a systematic way to take advantage of the historical data, augment them with some experimental trials, perform a regression analysis using the best possible methods available such as least squares or neural networks, invert the models, and finally use optimization techniques to develop the new products in the shortest period of time. The formulation predicted by this model will be much closer to the final formulation resulting in significant reductions in time and cost of the product development process. Furthermore, the model can be updated with the newly generated data to improve its predictive capability. Lastly, the disinfectant formulation can be viewed as a case study for a broader problem, formulation product design, and can be implemented in similar cases where the formulation of a new product should pass certain interfering criteria, such as adhesives, pharmaceutical drugs, agriculture pesticides, detergents, etc.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.titleComputer Aided Product Design and Development for Peroxide Based Disinfectantsen
dc.typeDoctoral Thesisen
dc.comment.hiddenWe have published three journal papers of my thesis work, however authors were myself and my thesis supervisors.en
dc.pendingfalseen
dc.subject.programChemical Engineeringen
uws-etd.degree.departmentChemical Engineeringen
uws-etd.degreeDoctor of Philosophyen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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