Computational Design and Digital Manufacturing

This chapter provides a methodological overview of generative design in architecture, especially highlighting the commonalities between three separate lineages of generative approaches in architectural design, namely the mathematical optimization methods for topology optimization and shape optimization, generative grammars (shape grammars and graph grammars), and [agent-based] design games. A comprehensive definition of generative design is provided as an umbrella term referring to the mathematical, grammatical, or gamified methodologies for systematic synthesis, i.e. derivation, itemization, or exploration of configurations. Among other points, it is shown that generative design methods are not necessarily meant to automate design but rather provide structured mechanisms to facilitate participatory design or creative mass customization. Effectively, the chapter provides the theoretical minimum for understanding generative design as a paradigm in computational design; demystifies the term generative design as a technological hype; shows a precis of the history of the generative approaches in architectural design; provides a minimalist methodological framework summarising lessons from the three lineages of generative design; and deepens the technological discourse on generative design methods by reflecting on the topological constructs and techniques required for devising generative systems or design machines, including those equipped with Artificial Intelligence. Moreover, the notions of discrete design and design for discrete assembly are discussed as precursors to the core concept of design as decision-making in generative design, thus hinting to avenues of future research in manufacturing-informed combinatorial mass customization and discrete architecture in tandem with generative design methods.

This chapter proposes a methodology for small-scale prototyping using computational design and digital fabrication by incorporating Augmented Reality (AR), aiming at eliminating errors during the process. In the first stage, the chapter presents an algorithm for evaluating the accuracy of physical prototypes against digital design results, which have been developed in the context of an undergraduate course in computational design and digital fabrication. The errors that arise in each case are indicated based on quantitative and qualitative criteria. In the second stage, the process of fabricating corresponding structures by users with the participation of AR technology is proposed, providing a real-time correlation of the digital results with the physical outcomes throughout the fabrication process. Then, initial and new errors, which are occurred during computational design and fabrication, are compared, presented and discussed. Ultimate aim is the application of AR for eliminating errors in cases where computational design and digital fabrication incorporate human intervention.

The paper focuses on designing and developing an interface for interacting with a mechatronic system through gestures. Using machine vision techniques, a methodology is developed that aims to record and locate the gesture through an image capture system. Once the gesture is isolated and gesture recognition is possible, the appropriate control commands of the system are determined. This makes it possible to control the mechatronic system through a dictionary of movements, called gesture vocabulary. The results of the methodology were applied to a real mechatronic system and showed significant results. The efficiency and effectiveness of the interface emerged from a satisfactory sample of users. It appeared quite easy to use, but also presented some basic difficulties in its application. The conclusion of the research is that controlling mechatronic systems through gestures can be a very important interaction interface.

The recent developments in additive manufacturing technologies lead to rapid production of fully functional customized parts with high geometric complexity and without the limitations of the traditional manufacturing methods, such as machining. Hence, in the last decade, the structural optimization of the existing products has gained increased scientific interest, especially in form of topology optimization. In the current chapter, the basic principles and the main methods of the topology optimization processes are described and analyzed coupled with a novel case study presentation of the topology optimization procedure of a brake caliper designed for additive manufacturing (DfAM). More specifically, the case study focused on the topology optimization of a brake caliper for the automotive industry, in order to reduce the overall weight and enhance the performance of the vehicle. Firstly, an original design of the brake caliper was studied via finite element analyses (FEA) under realistic static loads and the need for the topology optimization of the part was pointed out. Through the topology optimization process, the maximum mass reduction from the original design was achieved by holding the mechanical response of the part on the desired levels, i.e., maintaining the factor of safety above one. To conclude, the topologically optimized design of the brake had a weight of almost 2173 gr compared to the original design of 3195 gr achieving a mass reduction of 32%. It is worth mentioning that the factor of safety for the final design was calculated at 1.325.

This design-led research investigates the development of a file-to-fabrication framework for mortar-free robotic assembly of masonry walls. In particular, we describe, test and evaluate an algorithmic method enabling the robotic assembly of custom-made, complex, interlocking brick structures which don’t require the use of mortar or adhesives but their stability relies only on their geometric properties. We evaluate the process by conducting three design experiments. Our findings highlight the advantages and challenges of the proposed framework focusing on the relationship between the geometry of the individual bricks and the overall structure as well as the tolerances related to the interlocking mechanism.

The foundation of product conceptual design depends heavily on the amount of knowledge and the usage of knowledge. How to retrieve relevant knowledge from knowledge resources accumulated by the enterprises to support product conceptual design process has become a key technology for product conceptual design. This chapter introduces a function-knowledge reasoning model for product conceptual design that constructs a mapping relationship between sub-functions after decomposition and granular clustered knowledge. It focuses on knowledge-based product conceptual design that helps identify critical issues, and generate new conceptual solutions through configuration. The quality-function deployment (QFD) and axiomatic-design (AD) are used in the function-knowledge model to realize the mapping from user requirements to product functions, and functional decomposition. A similarity algorithm is introduced to implement the mapping from sub-functions to knowledge. This function-knowledge reasoning model, which combines requirement transformation, functional decomposition, and knowledge configuration, helps to achieve intelligent matching and optimization in the product conceptual design stage.

Micro-milling is popular in production of micro-components for various applications and is commonly characterized by low-to-moderate productivity, high geometrical achievable complexity and accuracy, and wide range of available materials. A key factor in improving productivity of micromachining operations is careful process planning, accounting for size effect and aiming to improve surface quality and productivity. This paper investigates equation-driven CNC micro-milling for production of free form metallic micro-components. Spiral type and micro gear 2D freeform models were parametrically designed and machined out of brass.

The generation of high-quality machined surfaces is of great importance for a series of applications. Face milling is one of the most common processes for machining such surfaces; the process is influenced by a series of factors that if not taken into consideration would result in poorly machined surfaces. The cutting parameters, the cutting tool design and the setup of the cutter and the workpiece play a pivotal role in the success of the machining process. In order to understand the effect of each parameter on the resulting surface quality of face milled surfaces, the current research presents a simulation model that is able to incorporate all the factors mentioned above in a CAD-based simulation platform. The results of the model include the resulting surface topography as well as surface roughness metrics. The results of the simulation approach were validated with experimental results.

The chapter presents the using mode of some digital tools in the process of design and manufacturing of an engine block used from lightweight four-stroke engine system for competition kart. The combustion engine from automotive industry has the enlarged future because in the green world is grooving the combustion solution with Liquefied Natural Gas (LNG) and, in the last time, Hydrogen. Different digital environments, including CATIA™, provide a large number of tools for design in order to obtain the best constructive solution for a product and later to manufacture it. The design for disassembling is implemented starting with the concept level of the engine block. For the collision check is used the CATIA™ DMU Space analysis applied on the 3D engine block model. All parts for engine assembly are moved in functional position using the digital tool from Assembly Design module. Another possible issue, the wrong access for assembly tools is validated using the 3D models for the tools safety spaces. To check the most important designed parts in real world are generated the 3D files and are manufactured the real parts using two additive manufacturing systems. The G code for multi-axis machining of the engine block is generated from CATIA™ Machining module and the CNC files are also simulated to be validated in virtual environment.

The use of CAD models is a fundamental part of components development in modern industry. Not only it provides a 3D representation of the piece but it also allows performing simulations to evaluate how it behaves under working conditions. The development of a CAD model involves the use of several operations. The starting point is usually the creation of a 2D sketch. Then, using extrusions and cuts, a 3D model will be created. This process is valid for models where no previous CAD model is available. In this case, the model has to be developed from scratch. However, the industrial brochures where the workpieces are modifications of a ground model present an opportunity to use the programming features of CAD programmes to automate the model development.

The issue of generating surfaces which are ordered curl of surfaces, using profiled tools, is a current concern of the international research teams. The performance of the generating by machining depends by the cutting tool’s geometry, and the 3D modelling allows a simple and rigorous analysis of the actual geometry of tool’s cutting edges.