GoGlobal: How can contemporary design collaboration and e-commerce models grow the creative industries in developing countries?

Using previous case studies by the authors and a current live project, this paper considers whether the creative industries in a developing country (Ghana, Africa) can be nurtured through design collaboration and an e-commerce model to contribute significant economic growth through increasing international trade. The paper draws on practical experience of five annual projects, with a focus on GoGlobal Africa. Initiated in 2005, GoGlobal is a collaborative design research activity between the University of Technology Sydney, the Royal College of Art, the London School of Economics, RMIT Melbourne, and other partnering organisations. GoGlobal Africa was initiated in 2008 with 3 phases: creative studio with design students from the RCA UK and KNUST Ghana; an e-commerce process for supply, distribution and marketing; and a “hub” location to facilitate project delivery and dissemination. The context to GoGlobal is informed by the UNCTAD studies of global creative industries

RoboToy Demoulding: Robotic Demoulding System for Toy Manufacturing Industry

Industrial environments and product manufacturing processes are currently being automated and robotized. Nowadays, it is common to have robots integrated in the automotive industry, robots palletizing in the food industry and robots performing welding tasks in the metal industry. However, there are many traditional and manual sectors out of date with technology, such as the toy manufacturing industry. This work describes a new robotic system able to perform the demoulding task in a toy manufacturing process, which is a tedious labor-intensive and potentially hazardous task for human operators. The system is composed of specialised machinery about the rotational moulding manufacturing process, cameras, actuators, and a collaborative robot. A vision-based algorithm makes this system capable of handling soft plastic pieces which are deformable and flexible during demoulding. The system reduces the stress and potential injuries to human operators, allowing them to perform other tasks wit h higher dexterity requirements or relocate to other sub-tasks of the process where the physical effort is minor

A Strategy For Promoting The Use Of Collective Intelligence Within A Technology Education Context: A Case Study

Abstract: This paper examines and provides a critical analysis of the results of a recent research project/study. This study will show how Australian students in remote and rural locations collaborated on a set of negotiated design projects with partner schools in city locations. We argue the activity of pooling/sharing divergent perspectives and heuristics [collective intelligence] is a powerful educational tool. This study will posit that a central way teachers/academics may help students to identify design issues/problems and formulate ways to address them is by taking advantage of and using collective intelligence in a classroom context. Cooperative learning and collaborative problem solving are effective in improving academic and social skills. Often it is difficult for students, operating in the context of technology education, to experience collaborative design in the same manner as globalised corporations which develop products for distribution around the world. As aspects of the design process become more and more globally distributed, it is increasingly important for technology education students to have the ability to engage with meaningful problems and achieve desirable solutions that parallel and mimic the real world. Further, this paper investigated the strengths, weaknesses, and merits of providing school students with an understanding of the real world experience of collaborative on-line designing 24 hour rapid prototyping and remote realisation and manufacture. The research to be discussed led us to develop a strategy for moving technology education forward towards providing rich learning experiences that develop in students, the abilities to more fully engage in a truly collaborative design process. It is argued this study potentially has wider implications beyond technology education

Material management without forecasting: From MRP to demand driven MRP

Purpose: Efficient Operations and Supply Chain Management is key to building sustainable competitive edge for companies. However, the achievement of this goal is becoming challenging in the present dynamic production environment, as traditional Manufacturing Planning and Control systems were not developed to work in this context. The Demand-Driven Material Requirement Planning (DDMRP) methodology was developed with the aim of addressing this need and deal efficiently with material management. The present work therefore, analyzes the implemented changes and the subsequent qualitative and quantitative results of a company after converting from MRP to DDMRP. Design/methodology/approach: To achieve an in depth understanding of the case study a qualitative approach was taken. Data was collected from semi-structured interviews, documents and archival records enabling triangulation. The results from before and after the implementation of DDMRP were compared, and the evolution of the performance of the company was evaluated. Findings: The results clearly show that using DDMRP the company increased visibility in the supply chain. In addition, the inventory level was reduced by 52.53% while material consumption was increased by 8.7%. These results were achieved while maintaining the high service level. Originality/value: DDMRP is a relatively new methodology and for this reason there is little published data in this field. In addition the few studies found in the literature analyze the performance of DDMRP in simulated environments. The present work aims to go one step further and analyzes the implementation of DDMRP in a real company

London Creative and Digital Fusion

date-added: 2015-03-24 04:16:59 +0000 date-modified: 2015-03-24 04:16:59 +0000date-added: 2015-03-24 04:16:59 +0000 date-modified: 2015-03-24 04:16:59 +0000The London Creative and Digital Fusion programme of interactive, tailored and in-depth support was designed to support the UK capital’s creative and digital companies to collaborate, innovate and grow. London is a globally recognised hub for technology, design and creative genius. While many cities around the world can claim to be hubs for technology entrepreneurship, London’s distinctive potential lies in the successful fusion of world-leading technology with world-leading design and creativity. As innovation thrives at the edge, where better to innovate than across the boundaries of these two clusters and cultures? This booklet tells the story of Fusion’s innovation journey, its partners and its unique business support. Most importantly of all it tells stories of companies that, having worked with London Fusion, have innovated and grown. We hope that it will inspire others to follow and build on our beginnings.European Regional Development Fund 2007-13

Assessment of Human Performance in Industry 5.0 Research Via Eye-Tracking and Cognitive Biases

Manufacturing assembly is combining previously made components or subassemblies into a final finished product. The assembly process can be manual, hybrid, or fully automated. Human operators who are involved in assembly use their judgment to perform the process. They collaborate with the other work agents such as assembly machines, robots, smart technologies, and computer interfaces. The recent Industrial revolution, Industry 5.0, exploits human expertise in collaboration with efficient and accurate machines. Manufacturing facilities that feature Industry 5.0 work settings require higher expectations, higher accuracy, sustainability solutions, mass customization of products, more human involvement, and digital technologies in smart workstations. Given these features, the cognitive load exerted on human workers in this environment is continuously increasing, leading to the use of cognitive heuristics. Cognitive biases are getting more attention in the cognitive ergonomics field, to help understand the operational behavior of workers. Manufacturing facilities can integrate cognitive assistance systems to work in parallel with physical and sensorial assistance systems. Cognitive assistance systems help toward better work conditions for workers and better overall system performance. This research explores the impact of human thinking style and using a cognitive assistance system on workers\u27 cognitive load, bias-related human performance, and user satisfaction. This research presents the design and experimental implementation of a research framework based on a well-established three-layer model for implementing Industry 5.0 in manufacturing. The research framework was designed to apply the dual-system theory and cognitive assistance in Assembly 5.0. Two experiments are presented to show the effectiveness of the proposed research framework. A cognitive assistance system was designed and compared to a benchmark system from LEGO ® Company. Subjective and objective measures were used to assess the thinking style, cognitive load, bias-related human performance, and user satisfaction in Assembly 5.0. As Industry 5.0 requires higher expectations, higher accuracy, smart workstations, and higher complexity, cognitive assistance systems can reduce the cognitive load and maintain the work efficiency and user satisfaction. Therefore, this work is important to industry to expand the use of cognitive ergonomic tools and employ them for A5.0 workers\u27 benefits

Assessment of Human Performance in Industry 5.0 Research Via Eye-Tracking and Cognitive Biases

Manufacturing assembly is combining previously made components or subassemblies into a final finished product. The assembly process can be manual, hybrid, or fully automated. Human operators who are involved in assembly use their judgment to perform the process. They collaborate with the other work agents such as assembly machines, robots, smart technologies, and computer interfaces. The recent Industrial revolution, Industry 5.0, exploits human expertise in collaboration with efficient and accurate machines. Manufacturing facilities that feature Industry 5.0 work settings require higher expectations, higher accuracy, sustainability solutions, mass customization of products, more human involvement, and digital technologies in smart workstations. Given these features, the cognitive load exerted on human workers in this environment is continuously increasing, leading to the use of cognitive heuristics. Cognitive biases are getting more attention in the cognitive ergonomics field, to help understand the operational behavior of workers. Manufacturing facilities can integrate cognitive assistance systems to work in parallel with physical and sensorial assistance systems. Cognitive assistance systems help toward better work conditions for workers and better overall system performance. This research explores the impact of human thinking style and using a cognitive assistance system on workers\u27 cognitive load, bias-related human performance, and user satisfaction. This research presents the design and experimental implementation of a research framework based on a well-established three-layer model for implementing Industry 5.0 in manufacturing. The research framework was designed to apply the dual-system theory and cognitive assistance in Assembly 5.0. Two experiments are presented to show the effectiveness of the proposed research framework. A cognitive assistance system was designed and compared to a benchmark system from LEGO ® Company. Subjective and objective measures were used to assess the thinking style, cognitive load, bias-related human performance, and user satisfaction in Assembly 5.0. As Industry 5.0 requires higher expectations, higher accuracy, smart workstations, and higher complexity, cognitive assistance systems can reduce the cognitive load and maintain the work efficiency and user satisfaction. Therefore, this work is important to industry to expand the use of cognitive ergonomic tools and employ them for A5.0 workers\u27 benefits

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE