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Modular product platforms have been shown to provide substantial cost and time savings while still allowing companies to offer a variety of products. As a result, a multitude of product platform methods have been developed over the last decade within the design research community. However, comparison and integration of suitable methods is difficult since the methods have, for the most part, been developed in isolation from one another. In reviewing the literature in modularity and product platforms, we create a generic set of 13 platform design steps for developing a platform concept. We then examine a set of product platform concept development processes used at several different companies, and from this form a generic sequence of the steps. We then associate the various developed methods to the sequence, thereby enabling the chaining together of the various modular and platform design methods developed by the community.

Unmanned Aerial Vehicles (UAVs) have been developed to perform various military and civilian applications, such as reconnaissance, attack missions, surveillance of pipelines, and interplanetary exploration. The present research is motivated by the need to develop a fast adaptable UAV design technologies for agile, fuel efficient, and flexible structures that are capable of adapting and operating in any environments. The objective of this research is to develop adaptive design technologies by investigating current design methods and knowledge of deployable technologies in the area of engineering design and manufacturing. More specifically, this research seeks to identify one truss lattice with the optimal elastic performance for deployable UAV wing design according to the Hashin & Shtrikman theoretical bounds. We propose three lattice designs -3D Kagome structure, 3D pyramidal structure and the hexagonal diamond structure. The proposed lattice structure designs are fabricated using an Objet 350 3D printer while the material chosen is a polypropylene-like photopolymer called Objet DurusWhite RGD430. Based on compression testing, the proposed inflatable wing design will combine the advantages of compliant mechanisms and deployable structures to maximize flexibilities of movement in UAV design and development.

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Purpose This paper aims to present a hybrid machine learning algorithm for additive manufacturing (AM) design feature recommendation during the conceptual design phase. Design/methodology/approach In the proposed hybrid machine learning algorithm, hierarchical clustering is performed on coded AM design features and target components, resulting in a dendrogram. Existing industrial application examples are used to train a supervised classifier that determines the final sub-cluster within the dendrogram containing the recommended AM design features. Findings Through a case study of designing additive manufactured R/C car components, the proposed hybrid machine learning method was proven useful in providing feasible conceptual design solutions for inexperienced designers by recommending appropriate AM design features. Originality/value The proposed method helps inexperienced designers who are newly exposed to AM capabilities explore and utilize AM design knowledge computationally.

Research in modularization of product families reveals numerous individual cause and effect impacts of modularity on a firm. There are clearly many interrelated positive and negative economic impacts arising from different activities of the firm impacted by the modular product structures. This makes the construction of an economic business case for modularity difficult, where often the benefits are reduced indirect costs. This paper presents a literature-based network model of how modular product structures affect firm’s economics across the design-to-manufacturing life cycle phases. It shows how (1) changes on modularity properties may lead to (2) different effects within the product’s life cycle phases that (3) have an economic impact on the firm. For instance, modularization can prolong development time of a platform, while shortening the subsequent development times of product variants and lowering manufacturing costs. To validate the proposed model, the given effect chains were compared by industrial experts against nine case study modularization projects by marking effects that were experienced and observed in their projects. The results first revealed that in design, an increase of commonality drove component reuse leading to lower development costs per unit. Second, in procurement, it was found that increased modularity caused better predictability, less purchasing orders, and better purchasing conditions that ultimately lead to lower costs. Third, in production, it was found that a smaller variety of components allowed less process variety, leading to fewer and more optimized processes and therefore lower production costs. We present these cause and effect impacts of modularity as drivers for quantifying the economic impact of modularity.

Additive Manufacturing (AM) or 3D printing is a manufacturing technique where successive layers of material are layered to produce parts. The design freedom afforded by AM is ideal for the space industry, where part production is low volume and highly customized. The objective of this paper is to review research in the area of Additive Manufacturing For Space (AMFS) in all areas, from propulsion to electronics to printing of habitats, and to identify the gaps and directions in the research. In this paper we investigate the AMFS research by splitting it into two domains: space and ground-based. Space-based AMFS has been performed on the International Space Station using polymers and we also discuss the future of in-space AM, a subject closely related to more general in-space manufacturing. The ground-based research is split into three categories based on the printing material: metal, polymer, and other. The last category includes regolith, cement, and ceramic. This paper explores AMFS by bringing together as much research information as possible using a combination of papers, presentations, and news articles. We expect that the paper will allow the reader to gain an understanding of the current status of AMFS research and will contribute to the field as a reference and research guidelines.