Thomas Razafimahefa, Pascal Paper, François Guérin, Patrice Micouin, Roland Becquet, Louis Fabre, Micouin, Patrice, Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Airbus Helicopters, Aeroport International de Marseille-Provence, MathWorks, and Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU)
International audience; Relevant for engineering a wide range of technological systems, Property Model Methodology (PMM) is applied in this paper to the development process of a helicopter function in the frame of the ARP4754A/ED79A. After a short presentation of the method, the case study is presented: "to retract and to extend airborne the landing gear system". Then, each stage of the PMM development process is illustrated by examples from the case study: (1) Modeling the top level requirements specification, (2) Validating the requirements specification by proof and simulation, (3) Modeling the architectural design, Refining the top level requirements into requirements specified to the different subsystems contributing to the function and Modeling the terminal subsystems detailed designs (4) Validating the requirements specified to the contributing subsystems by proof or simulation, (5) Verifying the design models by simulation and finally (6-8) Verifying physical implementations by test on the basis of all validation and verification scenarios accumulated throughout the development. At end, lessons learnt and industrial perspectives are summarized highlighting how PMM is a methodology adapted to the challenges facing to systems engineering by the globalization of development processes and showing how PMM can provide a powerful conceptual framework to support digital continuity within globalized Design Organizations. Modeling, simulation, proof and test generation activities are supported by the MATLAB and Simulink products. Introduction The aeronautic industry has to deliver more and more complicated systems in term of functions while maintaining high level of quality and safety/reliability. In the same time, competition is driving aircraft manufacturers to strongly improve their costs (including non-recurring costs) and development lead time. At the age of globalization, these systems are designed and produced by large, multicultural, geographically distributed teams belonging to different industrial organizations. This evolution introduces additional complexities (the complexity of a goal-oriented process refers to its propensity to fail [Suh, 2005]). To face these challenges, classical systems engineering approaches