Data-Driven Generative Design Integrated with Hybrid Additive Subtractive Manufacturing (HASM) for Smart Cities

Abstract

Generation of smart cities that considers environmental pollution, waste management, energy consumption and human activities has become more important in recent years since it was first introduced in the 1990s. In the smart cities, most of the structures, machines, processes and products will be redesigned in terms of technological developments linked to the fourth industrial revolution, Industry 4.0. This situation introduces the need of new design models that address extended significant parameters for manufacturing. Data-driven generative design methodology is an algorithmic design approach for developing state-of-the-art designs. Generative design may give the decision-makers more sustainable optimized project solutions with the iterative algorithmic process. Many parameters and constraints can be taken into consideration during the designing process, such as lightness, illumination, solar gain, durability, cost, sustainability, mass, factor of safety, mechanical stresses, resilience etc. In the generative design, an iterative process occurs via cyclic algorithm from ideation to evaluation to reveal possible potential design solutions. The increase in design freedom and complexity boosts the importance of new generation manufacturing methods. Hybrid additive subtractive manufacturing (HASM), a key component of Industry 4.0, offers tailored and personalized production capabilities by combining additive and subtractive processes in the same production unit. In today’s digital era, there is a growing need to create an integrated data-driven digital solution which consists of a multidisciplinary functional design integrated with hybrid additive subtractive manufacturing. Generative design integrated with hybrid additive subtractive manufacturing approach offers creating functional multi-criteria-based product combinations with sustainable organic mechanisms for engineering purpose. Alternatively, this approach provides dozens of different solutions for their studies considering multi-criteria, such as determining the convenient sunlight angles for walkways, computing optimum dimensions of smart structures, enabling transportation vehicles to pass underground or bridges etc. The main objective of this chapter is to introduce the importance of generative design and hybrid additive subtractive manufacturing for smart cities and present the critical advantages of a data-driven generative design concept algorithm integrated with hybrid additive subtractive manufacturing approach that will increase the speed of transition to smart cities. This chapter discusses a concept that integrates hybrid additive subtractive manufacturing with a data-driven generative design for the reliable, cost effective and sustainable design of components that can be used for establishment of secure smart cities. After conceptual explanations, the main aim and advantages of the concept are realized by a case study which is about the design of a drone chassis. A drone chassis is selected as a case study since drones will be used extensively for mainly security and logistics purposes in smart cities and design of drone chassis can be optimized by the proposed concept. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.