Comparing the strengths and weaknesses of standard risk management techniques, we found that all of them fall short of mastering the simultaneity of complexity and comprehensiveness (Zentis and Schmitt, 2013; Redmill, 2002). In MedTech this is a deteriorating issue, as medical devices become more complex and are increasingly interwoven in device networks, but trading off comprehensiveness is not an option, given that missing out in risk identification corresponds with potential threats to people's life and health. Having further analyzed the flaws actuating the conflict like incompatabilities of professional environments, absent process formalization or uncertainty of coverage (Schmitt and Zentis, 2011), it shows that they are abetted by the document-based approach for which all techniques were designed. Yet, these techniques excel at incorporating the human qualities an expert panel provides and which often cannot be merged into a system model to their full extent.
This poster will illustrate our research on comprehensive model-based risk management, showing our approach to combine computational power and accuracy with human expertise and detailedness. We consider identifying the critical characteristics in every stage of the product life cycle the key step in this effort. Therefore, a vast number of interactions between the product life cycle's elements needs to be searched and compared for similarities with elements with known critical characteristics stemming e.g. from legacy product life cycles or rules like standards or regulations. Thus, the computerized step will deliver comprehensive results, which only depend on data quality and not on human processing. We will explain how we intend to realize this with our tools using UML/SysML, customized databases and open standards for model-based system engineering. Herein, we will also explicate our choice of modeling IDE/platform and the semantic settings developed for the data types.
Carmen Castaño, M.Sc., is a Production Systems Engineer, lecturer at the Technological University of Panama (UTP), currently doing her doctorate in Mechanical Engineering at RWTH Aachen University, NRW, Germany. She leads the Model-Based Risk Management research team within the IT-based Quality Management group at Fraunhofer Institute for Production Technology in Aachen.