5,760 research outputs found

    Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

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    Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl

    An Autonomous Surface Vehicle for Long Term Operations

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    Environmental monitoring of marine environments presents several challenges: the harshness of the environment, the often remote location, and most importantly, the vast area it covers. Manual operations are time consuming, often dangerous, and labor intensive. Operations from oceanographic vessels are costly and limited to open seas and generally deeper bodies of water. In addition, with lake, river, and ocean shoreline being a finite resource, waterfront property presents an ever increasing valued commodity, requiring exploration and continued monitoring of remote waterways. In order to efficiently explore and monitor currently known marine environments as well as reach and explore remote areas of interest, we present a design of an autonomous surface vehicle (ASV) with the power to cover large areas, the payload capacity to carry sufficient power and sensor equipment, and enough fuel to remain on task for extended periods. An analysis of the design and a discussion on lessons learned during deployments is presented in this paper.Comment: In proceedings of MTS/IEEE OCEANS, 2018, Charlesto

    A comparison of processing techniques for producing prototype injection moulding inserts.

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    This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

    Reducing risk in pre-production investigations through undergraduate engineering projects.

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    This poster is the culmination of final year Bachelor of Engineering Technology (B.Eng.Tech) student projects in 2017 and 2018. The B.Eng.Tech is a level seven qualification that aligns with the Sydney accord for a three-year engineering degree and hence is internationally benchmarked. The enabling mechanism of these projects is the industry connectivity that creates real-world projects and highlights the benefits of the investigation of process at the technologist level. The methodologies we use are basic and transparent, with enough depth of technical knowledge to ensure the industry partners gain from the collaboration process. The process we use minimizes the disconnect between the student and the industry supervisor while maintaining the academic freedom of the student and the commercial sensitivities of the supervisor. The general motivation for this approach is the reduction of the entry cost of the industry to enable consideration of new technologies and thereby reducing risk to core business and shareholder profits. The poster presents several images and interpretive dialogue to explain the positive and negative aspects of the student process

    Towards autonomous system: flexible modular production system enhanced with large language model agents

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    In this paper, we present a novel framework that combines large language models (LLMs), digital twins and industrial automation system to enable intelligent planning and control of production processes. Our approach involves developing a digital twin system that contains descriptive information about the production and retrofitting the automation system to offer unified interfaces of fine-granular functionalities or skills executable by automation components or modules. Subsequently, LLM-Agents are designed to interpret descriptive information in the digital twins and control the physical system through RESTful interfaces. These LLM-Agents serve as intelligent agents within an automation system, enabling autonomous planning and control of flexible production. Given a task instruction as input, the LLM-agents orchestrate a sequence of atomic functionalities and skills to accomplish the task. We demonstrate how our implemented prototype can handle un-predefined tasks, plan a production process, and execute the operations. This research highlights the potential of integrating LLMs into industrial automation systems for more agile, flexible, and adaptive production processes, while also underscoring the critical insights and limitations for future work

    Towards a holistic methodology of efficient virtual preparation and commissioning for production systems

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    The industry elaborates on the possibilities of applying virtual engineering work to excel in production system development. For example, Virtual Commissioning as a concept for testing and validating system performance in advance of on-site commissioning has proven beneficial in multiple areas of development. Some areas include reducing on-site commissioning time, guaranteeing functional behavior, and removing potential errors, resulting in a smoother integration of new and upgraded systems.Nevertheless, it has been hard to prove the financial benefits and actual gain from VC compared to the more trusted traditional methods. The lack of standards mixed with the increasing complexity of systems and experience from prior attempts is one of many reasons.This thesis has identified different vital areas crucial for adopting virtual elements into the value chain of the development process within the automotive industry. It is of the highest importance to understand the prerequisites of a project’s ability to integrate virtual preparation for efficient commissioning and further break down the technical requirements of modeling and simulation in a multidisciplinary digital architecture.With more quantified data and insight from Virtual Commissioning attempts, it is possible to adopt knowledge to future projects and find ways to increase the utilization of the invested virtual engineering work.The thesis investigates the challenges of implementing virtual preparational methods for efficient commissioning to achieve flawless launches for all implementation projects of production systems. In addition, the research aims to find ways to increase the utilization of the constructed models, decrease the cost of virtual development and testing, and verify functionality and accuracy for optimal levels of simulation

    Robotization and digitalisation in the construction industry

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    Abstract. Industry 4.0 has emerged as a famous concept in the last few years to describe the significance of digitisation and robotization in the smart manufacturing environment. The advancements in robotics, digital software, and smart technologies have allowed a new wave in the construction industry. The construction industry is the major economic pillar and provides a significant impact on the overall GDP of the country. Despite the predominant pillar, it is considered as the poor innovator and late adopter of new technologies, which ends up with delays and cost overruns in their construction projects. Considering this aspect, the research emphasises the importance of adopting the latest technologies in the construction industry in order to enhance the productivity and efficiency of various processes. This study seeks to examine existing robotization and digitalisation practices in the leading construction companies and intends to provide the required improvement ideas in this research domain. The empirical results revealed that the majority of the case companies lack basis to implement the latest technologies in their construction activities. They believe that effective use of the available technologies is an asset, but it is a long process to be achieved. Thus, the thesis is concluded by providing the critical information regarding the adoption of latest technologies and proposes a framework that can help to enhance the robotization and digitisation practices to improve the performance of the construction activities. The mentioned framework mainly focusses on elements that this research found as a potential need for companies to implement. This framework has a future scope for validation and also key elements of the framework can be utilised for further research
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