White Papers

Quantisweb Methodology

M’Hammed Mountassir PhD and inventor of the quantisweb methodology has authored a white paper on the subject:

This article introduces a new methodology which combines aspects and approaches of three areas of Applied Mathematics: Decision Theory (AHP approach, Analytical Hierarchical Process), Statistics and Optimization Techniques, in order to efficiently solve formulation problems. The combination of these mathematical areas for formulation achieves a simultaneous a twofold benefit.  First, it allows minimizing the number of required tests ( ), where Np is the number of parameters “Xi”, regardless of their levels.  Second, it eliminates added parameter induced exponential effect, which provides for optimum formulations endowed with global optimality, as all the product characteristics “Yj” are simultaneously optimized. The optimality results from a reduced number of combinations, and is possible due to the interaction of parameters, and each response function, according to their importance in the global objective. These interactions are estimated either by parametric and/or nonparametric methods.

This white paper “Quantisweb Innovative Formulation Methodologies” is the sole and exclusive property of MDM Technologies Inc. This document contains “Confidential and Proprietary Information.”  Any disclosure or reproduction of this document or any of its contents, in whole or in part, must be approved by MDM Technologies, inc.  Should you want to get access to this paper, please contact us…


Mixture Design in the Quantisweb Methodology

This article demonstrates how the Quantisweb methodology, which combines aspects and approaches of three areas of Applied Mathematics: Decision Theory (AHP approach: Analytical Hierarchical Process), Statistics, and Optimization Techniques; is applied in mixtures designs.  A comparison study demonstrates that Quantisweb requires 60% fewer experiments to solve the same problem with standard techniques. The acceptable number of optimal parameter value (OPV) combinations using visual RSM techniques in Design Expert and Minitab gives a desirability rate of at least 85% which shows that the procedure is subject to a great degree of variability.  Whereas, Quantisweb™ gives a single optimal combination of parameter values (X) that corresponds to a desired output based upon the product specifications, and the optimization is done analytically, not visually as it is done with standard techniques.

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