Entropy in good manufacturing system: Tool for quality assurance

It has been customary to implement Good Manufacturing Practices (GMP) in pharmaceutical organizations as a systematic and comprehensive quality approach and sometimes by regulatory enforcement. In this scenario, determination of the obvious entropy/disorder arising during the implementation has not been taken care of yet. Therefore, this paper gives the basis for applying query and visual perception of GMP system driven visualization approach, particularly the Laplace equation, to the determination of disorder and deviation pattern inside the GMP system applied in the organization. In this study, a three-dimensional mesh approached with raw and intermediate input handled under GMP parameter is considered to produce high quality products with minimum entropy (variation distribution) by adding the analogy wise different GMP parameters and process variables with Gauss Seidel iteration and thus producing visual picture of the entire system. The approximation involved in applying the equations to the GMP compliant aseptic region was analyzed. Using numerical technique and computer program, the Gauss Seidel iteration equations have been solved with appropriate GMP parameter and process variable. The result indicates that deviations vary over the GMP compliant system and that the process entropy affects the totality of disorderness. Experiments with model of GMP compliant reproductive medicine laboratory confirm that the new method provides optimal manufacturing maintaining GMP and high product quality through the visual representation of the entire system and activity to bring into notice the deviations.