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Hållbarhetsanalys: En analys av Ahlsells centralterminals koldioxidavtryck från transporter och påverkan på byggavfallsmängd
(2024) Strigén, Erik; Ljungqvist, Konrad; Chalmers tekniska högskola / Institutionen för teknikens ekonomi och organisation; Chalmers University of Technology / Department of Technology Management and Economics; Hanson, Robin; Hanson, Robin
Today's construction industry faces a number of different problems. Two of these are that industry produces large amounts of waste and that construction transport emits large amounts of greenhouse gases. The purpose of this thesis is to investigate how the use of the company Ahslell's consolidation terminal in central Gothenburg affects the amount of waste and emissions from transport connected to the construction industry. In order to do this, data has been collected in the form of semi-structured interviews that have been conducted with people who in various ways work in the construction industry. Data containing driving logs for three construction projects using the terminal has also been analyzed. In addition, a literature study related to material handling, CO2 emissions from transport, and logistics in the construction industry was conducted to create the theoretical framework. The analysis of the results is discussed using the theoretical framework and the information from the interviews in order to understand the terminal's impact on waste and emissions. The conclusion shows that material handling can be improved when using Ahlsell's terminal, which in turn leads to reduced emissions due to fewer unnecessary transports. The data containing driving logs could not be used to calculate how the CO2 emissions would be affected by the use of the terminal. However, the interviews and the literature study could contribute to this information. The study provides both an increased understanding in which ways the terminal contributes to improved material handling and reduced emissions, but also suggestions for what can be further developed.
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Additive Manufacturing Capabilities for Emergency Manufacturing in Healthcare How Additive Manufacturing Capabilities Can Be Utilised to Increase Healthcare Resilience in the Event of a Crisis
(2024) Hörnell, Martin; Lindahl, Ludvig; Chalmers tekniska högskola / Institutionen för teknikens ekonomi och organisation; Chalmers University of Technology / Department of Technology Management and Economics; van Loon, Patricia; Kurdve, Martin
Disruptions in global supply chains can severely impact the availability of medical equip- ment. Additive manufacturing (AM) presents a potential solution for the on-demand, decentralised production of critical medical parts. This master’s thesis investigates the current capabilities of AM for medical equipment manufacturing and what role AM could have in improving the supply chain resilience of medical equipment during a cri- sis. A comprehensive literature review of AM capabilities for medical equipment and areas surrounding the implementation of AM in healthcare, along with data collection through 17 semi-structured interviews with personnel from hospital 3D units and AM companies were conducted. The results of this study suggest that AM capabilities can be used to produce certain critical medical equipment to improve healthcare resilience. Furthermore, AM was found to enable a decentralised manufacturing structure that can further be used to improve resilience toward supply disruptions. This presents an opportunity to create a national collaboration to develop, manufacture and deliver critical items at shorter lead times and increase supply chain robustness. On this ba- sis, this study presents a recommendation to map the existing AM capabilities and production sites and establish collaborations between 3D units and AM companies to manage decentralised manufacturing at various scales effectively. Given the novelty of AM in medical equipment and the limited research that has been conducted in this field, further research is needed to better understand AM’s capabilities and factors for a successful implementation.
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Learning human actions on-demand based on graph theory
(2024) Zhang, Jing; Chalmers tekniska högskola / Institutionen för elektroteknik; Ramirez-Amaro, Karinne
Abstract Collaborative robots (Cobots) are designed to work side-by-side with humans, sharing space and skills to achieve common goals. However, as human tasks become increasingly complex, Cobots must adapt to unfamiliar tasks. Traditional machine learning methods, while offering potential solutions, tend to focus on learning lowlevel physical activities. This lack of interpretability makes it difficult for humans and robots to understand and predict each other’s behavior, hindering effective collaboration. In addition, machine learning methods rely heavily on human demonstrations, limiting the robot’s ability to generalize to new scenarios. In this work, each task (e.g., putting a spoon in the drawer) can be segmented into an interpretable activity sequence (e.g., Open, Grasp, Drop, etc.) based on human activities in real-time. We propose a method that can automatically construct different sequences for different tasks using a single human demonstration. Given that human demonstrations can vary and may include mistakes, this method reconstructs the most representative activity sequence from multiple demonstrations, thus robot could understand and predict human activities, and this method could extend to unseen scenarios. We use a semantic reasoning method to transform low-level data into high-level concepts understandable by humans. Decision trees are trained to capture specific activity characteristics defined by predicates, e.g., when a human grasps a spoon, data about velocity and spatial relations are translated into predicates like inHand(spoon) as the input of decision tree, then this movement is inferred by out method as “Grasp”, allowing real-time prediction and segmentation of human activities into activity sequences even for new experiments. Activities are parameterized using ontology knowledge, enabling robots to adapt to various objects and tasks. If an object, e.g., a bottle, is not inside the ontology, then we use Large Language Models(LLMs) to categorize the object according to the predefined ontology. For instance, both “spoon” and “bottle” belong to the category “Objects,” making the activity “Grasp” identical in a high-level context. Since humans may perform the same task in different ways, de Bruijn graph and sequence assembly algorithms streamline these sequences by eliminating redundant activities and representing repetitive patterns, then reconstructing the most representative activity sequence by finding a path traversing each edge of the graph. This approach enhances the ability of Cobots to understand and predict human activities, thereby improving their collaboration with humans in dynamic environments.
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Drone Platform for Safety in Autonomous Vehicle Testing/ Drönarplattform för säkerhet vid testning av autonoma fordon
(2024) Eddin Bilal, Mohi; Ferreira, Daniel; Mörck, David; Sandström, Filip; Svenske, Albin; Särnholm, Andreas; Chalmers tekniska högskola / Institutionen för elektroteknik; Chalmers University of Technology / Department of Electrical Engineering; Ramirez-Amaro, Karinne; Sjöberg, Jonas
Abstract his report details the development and implementation of an automated drone-based surveillance system for use at the AstaZero testing facility for autonomous vehicles. The system visually detects objects present at the test location and compares their position to the positions given by ATOS. If a deviation is deemed to indicate a hazardous situation, the system sends a signal to warn the test supervisor of the hazard. To bring this system into action, an Android application was developed to strategically position the drone over the test area, ensuring comprehensive monitoring and the ability to capture all test objects within its field of view. The captured footage is then transmitted to a computer for object detection, using a custom-trained YOLOv8 model. To enable the computer to communicate with ATOS in order to retrieve test specifications and send warnings, a communication application was also developed. Further specification and research into the classification of hazardous situations is required to get a system that accurately achieves the goal of an automated system.
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Autonomous lawnmower/ Automatisk gräsklippare
(2024) Andersson, Noel; Mark, Anton; Rapp, Lisa; Janmark, Elmer; Walldén, Viktor; Gunnarsson, Adam; Chalmers tekniska högskola / Institutionen för elektroteknik; Chalmers University of Technology / Department of Electrical Engineering; Ramirez-Amaro, Karinne; Fredriksson, Jonas
Sammanfattning De senaste åren har det skett ett alltmer övergående skifte från naturgräsplaner till konstgräsplaner inom bland annat fotboll. Anledningen är att konstgräsplaner kräver mindre manuellt underhåll och minskar därmed kostnaderna för kommuner. Däremot medför skiftet även negativa konsekvenser på exempelvis miljön, då mikroplaster som granulat sprids i naturen. För att minska underhållskostnaderna och därmed motverka skiftet, är syftet med det här arbetet att utveckla och styra en kritmekanism, som kan integreras med en autonom gräsklippare, för autonom kritning av linjerna på en fotbollsplan. För att uppnå autonom kritning krävs att gräsklipparen kan styras så att linjerna inte blir krokiga eller sneda samt att en kritmekanism, som kan krita linjerna på rätt ställe och med rätt bredd, behöver utvecklas. För att möjliggöra detta, delades arbetet upp i två huvudmål, linjeföljning och kritmekanism. För linjeföljningen har en modellbaserad metodik applicerats där bland annat modellering, simulering och implementering har behandlats. Utvecklingen av kritmekanismen följer en produktutvecklingsmetodik där delar som idégenerering, beslutsmatriser och prototyptillverkning har genomförts. Från linjeföljningens metodik blev resultatet att via kombinering av odometrins höga uppdateringfrekvens med RTK-mottagarens höga precision genom ett Extended Kalmanfilter lyckades ett system tas fram som möjliggjorde för gräsklipparen att följa referenslinjer. Detta både i simulering och i verkligheten, med en maximal avvikelse på 7 centimeter över en rak sträcka på 50 meter. Däremot med mer varierande precision för mer komplexa geometrier som cirklar och geometrier med skarpa svängar. Resultatet av produktutvecklingen blev en kritmekanism som kunde applicera färg på rätt ställe och med rätt bredd. Vidare resulterade metodiken i ett förslag på hur en tänkt slutprodukt skulle kunna se ut. Slutsatserna av arbetet är att många av de väsentliga delar som krävs för att möjliggöra autonom kritning av linjer fungerar, men på grund av för låg hastighet på gräsklipparen i kombination med ett för högt flöde av färg från ritmekanismen uppfylls inte huvudmålet med att krita linjerna till en hel fotbollsplan. Vidare arbete med att förfina styrningen av gräsklipparen samt minska flödet av färg från kritmekanismen behövs för att uppfylla projektets mål.