Adaptability in manufacturing is becoming increasingly important, as it provides flexibility without requiring significant up‐front investment. In this paper, we review the history of this concept, indicate issues with prior work and advance our knowledge of this topic. We provide an explanation and analysis on the concept of mission‐based adaptability that adopts a similar definition as the adaptability in ecosystems, which describes a system's adaptive capability relative to on‐going changes. Our analysis shows the mission‐based adaptability's empirical mathematical properties and indicates this formulation is able to resolve previous approaches’ issues at an optimal level of abstraction. We employ extensive tools and analysis on an airplane engine design example case and demonstrate the importance and usefulness of the adaptability metric for decision makers in the manufacturing industry.
E. F. Colombo holds a Ph.D. in Methods and Tools for Product Design. His research focused on systems engineering, industry platform design and open innovation, trying to understand how social and technical factors contribute to a successful development of complex products; his PhD thesis is titled "Open innovation meets customizability: strategic design analyses for cyber-physical industry platforms". He is currently acting as project leader in the digital transformation program of a major telecommunication company.Narek Shougarian graduated with a first-class honours MEng degree in Aeronautical Engineering from Imperial College London in 2011. During his Ph.D. at the Massachusetts Institute of Technology (Department of Aeronautics and Astronautics), his research interests included unconventional air-breathing propulsion systems and computational synthesis of architectures from libraries of components. After graduating, he was recruited at NASA JPL, where he is currently developing software systems for space missions.Kaushik Sinha is senior research scientist at Amazon research science. He holds Ph.D. in Engineering Systems from MIT (2014), his dissertation addressing complexity quantification methodology and complexity metric development for engineered systems. He is interested in complexity quantification for engineered systems & platforms, market system design for industry platforms, system optimization and model-based product development. Prior to joining MIT, he worked as technical manager at Daimler Benz Research and technology and worked in the area of system optimization, computational crash mechanics, composite structures and finite element methods development for automotive and aerospace systems.Prof. Gaetano Cascini holds a Ph.D. in Machine Design and is Full Professor at Politecnico di Milano, Dept. of Mechanical Engineering. His research interests cover Engineering Design Methods and Tools with a focus on the concept generation stages both for product and process innovation.
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