PENELITIAN DESAIN MEBEL BERBASIS PANGKALAN DATA DENGAN METODE DIVERGEN KONVERGEN ITERATIF SEBAGAI STRATEGI R&D & MANUFAKTUR PERUSAHAAN (STUDI KASUS: CORPORATE SPECIALISTS, MALAYSIA & HOMELEGANCE, USA)

Furniture design for mass production & export orientation is complex innature, tend to have a lot of revisions, thus require a lot investment in fund,time, and effort. There are 2 research issue: 1) Mistakes in design proposalsoften occurred (size, construction, style, finishing, price), can not match withfactory production capacity, or buyer’s market target. In this case, factoriesare suppliers of research partner 1 (CS), and buyer is research partner 2(Homelegance). Second issue: 2) Designer’s idea often surrounds in designaesthetic alone, disregard the A-Z aspect in supply & demand chain of amass-produced furniture (production, marketing, packing, shipping, etc).This research uses qualitative research model with many case studies, andapplies 3 methods: 1) divergent convergent iterative design method; 2) 2D &3D database from CS; 3) considering US market response fromHomelegance. This research aims to: 1) providing ways and recommendationfor stakeholder to reduce revisions (time & cost saving), 2) producingdesigns with export oriented quality, 3) providing design insights foracademics about furniture design from early to final phase. Research output(furniture samples) are stored in multiple supplier’s warehouse

Folding Methodology for Flexible Aircraft Interiors

This paper establishes a general furniture folding methodology that is aimed at flexible aircraft cabin interiors. This methodology will allow users to modify existing furniture pieces to their liking and thereby customizing their overall travel experience. The folding methodology also includes a process to quantify the transformation of the furniture pieces. This paper also introduces two design concepts called Open-on-Demand and Reconfiguration to allow passengers to modify an otherwise rigid cabin. The advantages of the multi-functional space saving furniture pieces are also illustrated in this paper. While the general folding methodology was developed for aircraft interiors, it can be adapted for any furniture piece positioned within any environment

PENELITIAN DESAIN FURNITUR BERBASIS PANGKALAN DATA 3D SEBAGAI STRATEGI R&D & MANUFAKTUR PERUSAHAAN STUDI KASUS: CS TRADING SDN BHD, MALAYSIA

AbstractOne of the most competitive markets in product design is furniture market. Every company tries to provide the best in terms of products and services. CS Trading is a Malaysian trading house with top US retailer clients such as Topline and Homelegance. CS provides design services, include receive and modify data from clients, and position themselves as a mediator between retailers and manufacturers. All of CS drawings comein 2D CAD or PDF or other 2D form files, which in current industry competition, it has becoming less representative and not visually attractive. This research aims to create 3D database based on CS existing 2D data. 3D data are then categorized according to furniture items and its components, where new designs can be easily extracted. Fromthe research, 294 furniture databases are made. Modularity and carry over strategy are the most suitable R&D and manufacture strategy, because these strategies are good for companies with large product categories. From the research result, CS Trading can accelerate R&D process and manufacturing. In the long run they can excel in terms ofvariety of products and speed of service.  AbstrakIndustri furnitur adalah salah satu industri desain produk terbesar dan dengan persaingan yang sangat kompetitif. Setiap perusahaan berusaha memberikan produk dan servis yang terbaik. CS. Trading Sdn Bhd. adalah perusahaan trading dengan klien peritel dari Amerika seperti Topline dan Homelegance. Proses desain yang mereka lakukan adalah menerima dan atau memodifikasi gambar dari klien dan menjadi mediator antara klien dan manufaktur. Dengan posisinya sebagai mediator, CS mengalami beberapa kendala dalam proses desain, yaitu proses desain yang masih dalam bentuk gambar 2D, sehingga gambar kurang representatif dan tidak menarik. Penelitian ini bertujuan untuk mengubah proses desain CS dengan strategi membuat data 3D desain berdasarkan data gambar 2D yang ada. Data ini dianalisa dan dibuatkan pangkalan data berdasarkan kategori jenis furnitur dan komponennya, dimana desain baru dengan mudah bisa dihasilkan dengan cepat. Hasil penelitian ini adalah pembuatan 294 database furnitur. Strategi R&D dan manufaktur yangtepat diterapkan pada CS Trading adalah strategi modularitas dan strategicarry over detail. Karena kedua strategi ini cocok bagi perusahaan yang memiliki kategori produk yang banyak. Dengan hasil dari penelitian ini proses desain CS Trading menjadi lebih efektif dan efisien dari sebelumnya sehingga memiliki keunggulan dari sisi keragaman produk dan kecepatan servi

Computational design of steady 3D dissection puzzles

Dissection puzzles require assembling a common set of pieces into multiple distinct forms. Existing works focus on creating 2D dissection puzzles that form primitive or naturalistic shapes. Unlike 2D dissection puzzles that could be supported on a tabletop surface, 3D dissection puzzles are preferable to be steady by themselves for each assembly form. In this work, we aim at computationally designing steady 3D dissection puzzles. We address this challenging problem with three key contributions. First, we take two voxelized shapes as inputs and dissect them into a common set of puzzle pieces, during which we allow slightly modifying the input shapes, preferably on their internal volume, to preserve the external appearance. Second, we formulate a formal model of generalized interlocking for connecting pieces into a steady assembly using both their geometric arrangements and friction. Third, we modify the geometry of each dissected puzzle piece based on the formal model such that each assembly form is steady accordingly. We demonstrate the effectiveness of our approach on a wide variety of shapes, compare it with the state-of-the-art on 2D and 3D examples, and fabricate some of our designed puzzles to validate their steadiness

Advances in Data-Driven Analysis and Synthesis of 3D Indoor Scenes

This report surveys advances in deep learning-based modeling techniques that address four different 3D indoor scene analysis tasks, as well as synthesis of 3D indoor scenes. We describe different kinds of representations for indoor scenes, various indoor scene datasets available for research in the aforementioned areas, and discuss notable works employing machine learning models for such scene modeling tasks based on these representations. Specifically, we focus on the analysis and synthesis of 3D indoor scenes. With respect to analysis, we focus on four basic scene understanding tasks -- 3D object detection, 3D scene segmentation, 3D scene reconstruction and 3D scene similarity. And for synthesis, we mainly discuss neural scene synthesis works, though also highlighting model-driven methods that allow for human-centric, progressive scene synthesis. We identify the challenges involved in modeling scenes for these tasks and the kind of machinery that needs to be developed to adapt to the data representation, and the task setting in general. For each of these tasks, we provide a comprehensive summary of the state-of-the-art works across different axes such as the choice of data representation, backbone, evaluation metric, input, output, etc., providing an organized review of the literature. Towards the end, we discuss some interesting research directions that have the potential to make a direct impact on the way users interact and engage with these virtual scene models, making them an integral part of the metaverse.Comment: Published in Computer Graphics Forum, Aug 202

Generative design for agile robot based additive manufacturing for sustainable aesthetic furniture products

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThe Furniture manufacturing industry has been slow to adopt the latest manufacturing technologies, relying heavily upon specialised conventional machinery. This approach not only requires high levels of specialist knowledge, training and capital investment, but also suffers from significant traditional subtractive manufacturing waste and high logistics costs due to centralised manufacturing, with high levels of furniture product not re-cycled or re-used at the end of its life cycle. This doctoral research aims to address these problems by establishing a suitable digital manufacturing technology framework concept to create step changes in the furniture design to manufacturing pathway. The design stage has the potential to contribute massively to the environmental impact of products. In this research, a Robot Base Additive Manufacturing Concept cell for future furniture manufacturing is reported. Generative design illustrates its potential contribution to waste reduction, increased manufacturing efficiency, optimised product performance and reduced environmental impact constituting a truly lean and progressive future for Furniture Manufacturing Design. Through case studies the research will show the potential for exploiting Single Minute Exchange of Die (SMED) concepts through the rule-based AI generative design post-processing of geometry for robot manufacturing, examination of different methodologies for printing and thus the resultant potential for ‘Mass Customised’ Furniture. Aesthetics, structures and the use of Smart Materials not previously economic to manufacture will be considered to demonstrate the potential to flatten the traditional Bill of Materials (BOM) and reduce logistical issues. The Furniture Industry has developed from an artisan driven craft industry, whose pioneers saw themselves reflected in their crafts and cherished the sense of pride in the originality of their designs, now largely re-configured to an anonymous collective mass output. Digital technologies and smart materials enhancement allow innovative structural fabrication, presenting a plethora of potential for networked artisan craft industries to create extraordinary aesthetics and customisable product designs. Integrating these developments with the computing power of generative design provides the tools for practitioners to create concepts which are well beyond the insight of even the most consummate traditional designers. This framework is becoming an active area of research for application in many different industries. The step changes are empowering artisans to revolutionise the design to manufacture workflow, giving momentum to the concept of conceiving a pre-industrial model of manufacturing with bespoke sustainable design at its heart. The elements of the framework will be described and illustrated using case study models highlighting the potential for creating unique aesthetics for sustainable furniture products. The research presents the methodology to create and compare iterations employing different rule sets through a commercial generative design application and how these outputs can be further customised using parametric strategies in NURBS modellers, with the ultimate goal of creating aesthetic ‘Lean’ and sustainable innovative furniture of the future, thus illustrating how the creative use of digital networks in linking individual practitioners in the making of aesthetic customised products, manufactured local to their markets, could be achieved using this framework. This research shows a robust ‘green revolution’ is evidently necessary to satisfy the needs of an ever-growing population, allowing the world to thrive within the means of this planet. New approaches to the use of technologies can achieve these changes in Furniture Manufacturing and establish a truly enhanced Circular Economy. Governments around the World are encouraging these initiatives and these approaches are identified and rationalised alongside the drivers for change which will have major impacts on this manufacturing sector. This research critically examines the Furniture Design and Manufacturing technologies presented through a TRIZ framework against the desired outcomes. Using this approach together with the physical development of a robotic test cell, combined with case study data significant contributions to knowledge in the focused area of Furniture Manufacturing are identified, detailed and enhance Furniture Design, Manufacturing and Environmental Impact for the future. The focused approach also serves to highlight areas requiring further research