PENGEMBANGAN INSTRUMEN ESMOCA UNTUK PENGUKURAN SUDUT 3 DIMENSI ALAT GERAK TUBUH BAGIAN ATAS UNTUK PERHITUNGAN GAYA DAN MOMEN BIOMEKANIKA KERJA

Pengembangan instrument ESMOCA (Ergonomi Sisman Motion Capture) pada generasi yang pertama mengalami beberapa kekurangan pada fungsi pengukuran sudut. Berdasarkan evaluasi yang telah dilakukan sebelumnya terhadap instrument ESMOCA generasi pertama, didapatkanlah pengembangan-pengembangan yang akan dilakukan yaitu dengan mengubah dimensi pengukuran menjadi 3 dimensi, mampu mengukur bagian tubuh atas, dan dapat digunakan dalam perhitungan biomekanika kerja. Dibantu dengan software Matlab r2014a dilakukan pendekatan dengan menggunakan model simulasi yang sudah mampu menggambarkan gerakan dari subjek pengamatan. Pada tahap interpretasi data, dilakukan dengan analisis statistik, one sample t test dan independent t test untuk membandingkan dua data. Data yang didapatkan ketika proses kalibrasi adalah data sudut X, Y, Z dari instrument ESMOCA dan alat ukur lain yaitu waterpass dan Busur derajat

Point clouds to direct indoor pedestrian pathfinding

Increase in building complexity can cause difficulties orienting people, especially people with reduced mobility. This work presents a methodology to enable the direct use of indoor point clouds as navigable models for pathfinding. Input point cloud is classified in horizontal and vertical elements according to inclination of each point respect to n neighbour points. Points belonging to the main floor are detected by histogram application. Other floors at different heights and stairs are detected by analysing the proximity to the detected main floor. Then, point cloud regions classified as floor are rasterized to delimit navigable surface and occlusions are corrected by applying morphological operations assuming planarity and taking into account the existence of obstacles. Finally, point cloud of navigable floor is downsampled and structured in a grid. Remaining points are nodes to create navigable indoor graph. The methodology has been tested in two real case studies provided by the ISPRS benchmark on indoor modelling. A pathfinding algorithm is applied to generate routes and to verify the usability of generated graphs. Generated models and routes are coherent with selected motor skills because routes avoid obstacles and can cross areas of non-acquired data. The proposed methodology allows to use point clouds directly as navigation graphs, without an intermediate phase of generating parametric model of surfacesUniversidade de Vigo | Ref. 00VI 131H 641.02Xunta de Galicia | Ref. ED481B 2016/079-0Xunta de Galicia | Ref. ED431C 2016-038Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-77158-C4-2-RMinisterio de Economía, Industria y Competitividad | Ref. RTC-2016-5257-

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