Data-driven systems engineering for bioinspired integrative design
Engineering design problems can be discussed under the framework of decision making, namely, engineering design decisions. Inherently, accounting for uncertainty factors is an indispensable part of these decision processes. The goal of design decisions is to control or reduce the variational effect in decision consequences induced by many uncertainty factors. If we look at current technological trends, specifically the industry 4.0 movement, we can quickly appreciate the big push in science and technology for the digitalization of design, manufacturing, and management processes to reduce the amount of uncertainty present during innovation attempts. This work explores the value of data-driven integrated design and digital fabrication and how it allowed us to drive innovation in more than one domain. From examples in biomimicry discoveries to prostheses and unmanned aerial vehicle designs to the use of drones for emergency response, the key ideas of the proposed data-driven design paradigm are demonstrated. Earlier works on data-driven design and digital manufacturing have demonstrated its potential to disrupt the way we think about engineering design processes. However, constant modernization in these fields keeps pushing the boundaries on what is possible, and these territories remain relatively uncharted. This research aims to explore how a combination of spatial data sets can serve as a point of entry for data-driven innovative designs. The process starts with a different range of data acquisition tools and processing techniques, followed by computational analysis and optimization designs, all the way to digital manufacturing by means of 3D printing and validation via mechanical and functional testing. These data sets enabled the synthesis of digital twin models, which allowed us to begin a reverse engineering process for a series of multiple purposes.
To begin our study, we focused on new methods of additive manufacturing with a special focus on composite 3D printing. We explored the current state of knowledge in the field of composite additive manufacturing. We investigated all different methods of 3D printing and the current broad range of materials available. We also gained a deep understanding of the different optimization opportunities that can be gained by incorporating fibers, chopped or continuous, into polymer filament additive manufacturing.
Now that we know we can design and manufacture almost anything we can imagine we asked ourselves what would that be? At this point we explored new trends in the field of digital modeling, simulation, and optimization techniques. Starting in the cyber context we can create a digital twin that satisfies the objective functions of an engineering system such as lightweight, strong, controllable, manufacturable, and then use these objective functions as an opportunity to optimize over the design space. To prove this concept, we selected an engineering system design challenge: The design and optimization of a novel box wing vertical takeoff and landing aircraft intended to serve in long endurance environmental and archeological recognition missions as well as serving as the starting point for the development of the next generation of urban air mobility platforms.
During the design of the Prandtl Box wing aircraft system we found that if we wanted to design better aeronautical systems, we needed to find a way to design lighter and stronger structures. This is the point when we decided to look into nature’s library. We dived deep into biomimicry and proved how data and visualization driven research together with traditional mechanical testing, allows us to grasp a better insight on evolutionary optimization and its applications on structural design and material science.
The ability to optimize and build stronger performing structures that follow form to function allowed us to add an extra level of complexity to our engineering system design. We added a human in the loop. This presented us with a unique set of functional requirements. We were faced with the challenge on how to translate these functional requirements into new objective functions. Using this new set of objective functions and the engineering system design methodology developed in previous studies we designed and tested a bioinspired transtibial prosthesis, which can be entirely 3D printed in a single piece allowing us to solve a global accessibility challenge.
Additional work was done where we focused on the use of drones for emergency response after natural events and its applications on data-driven structural damage assessment during and after earthquakes. This work is not presented in this dissertation, but published material can be found online and the vita section of my thesis.