A web mining-based case adaptation model for quality assurance of pharmaceutical warehouses

Abstract

Quality assurance (QA) of pharmaceutical warehouses is a critical issue for formulating working instructions in accord with many regulations. Currently, such QA planning, relying on human experience, not only increases the chance of errors and quality problems for pharmaceutical products, but also results in high rejection and recall rates. This paper proposes a web mining-based quality assurance system (WMQAS), integrating case-based reasoning (CBR) and a hybrid web mining technique, to facilitate decision-making in QA operations in pharmaceutical warehouses. CBR is applied for solving complex new problems based on past cases, however, current case adaptation processes are mainly based on the experience of expert where past solutions are modified. The proposed system embeds a hybrid web mining technique in the case adaptation engine to extract the useful web information for decision-makers. Consequently, the effectiveness and efficiency of QA processes can be enhanced, and the product quality can be maintained.