967 resultados para Robotics, Automation


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This thesis is based upon a case study of the adoption of digital, electronic, microprocessor-based control systems by Albright & Wilson Limited - a UK chemical producer. It offers an explanation of the company's changing technology policy between 1978 and 1981, by examining its past development, internal features and industrial environment. Part One of the thesis gives an industry-level analysis which relates the development of process control technology to changes in the economic requirements of production . The rapid diffusion of microcomputers and other microelectronic equipment in the chemical industry is found to be a response to general need to raise the efficiency of all processes, imposed by the economic recession following 1973. Part Two examines the impaot of these technical and eoonomic ohanges upon Albright & Wilson Limited. The company's slowness in adopting new control technology is explained by its long history in which trends are identified whlich produced theconservatism of the 1970s. By contrast, a study of Tenneco Incorporated, a much more successful adoptor of automating technology, is offered with an analysis of the new technology policy of adoption of such equipment which it imposed upon Albright & Wilson, following the latter's takeover by Tenneco in 1978. Some indications of the consequences by this new policy of widespread adoptions of microprocessor-based control equipment are derived from a study of the first Albright & Wilson plant to use such equipment. The thesis concludes that companies which fail to adopt rapidly the new control technology may not survive in the recessionary environment, the long- established British companies may lack the flexibility to make such necessary changes and that multi-national companies may have an important role jn the planned transfer and adoption of new production technology through their subsidiaries in the UK.

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Once the factory worker was considered to be a necessary evil, soon to be replaced by robotics and automation. Today, many manufacturers appreciate that people in direct productive roles can provide important flexibility and responsiveness, and so significantly contribute to business success. The challenge is no longer to design people out of the factory, but to design factory environment that help to get the best performance from people. This paper describes research that has set out to help to achieve this by expanding the capabilities of simulation modeling tools currently used by practitioners.

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The article reveals a new technological approach to the creation of adaptive systems of distance learning and knowledge control. The use of the given technology helps to automate the learning process with the help of adaptive system. Developed with the help of the quantum approach of knowledge setting, a programming module-controller guarantees the support of students’ attention and the adaptation of the object language, and this helps to provide the effective interaction between learners and the learning system and to reach good results in the intensification of learning process.

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This article describes some approaches to problem of testing and documenting automation in information systems with graphical user interface. Combination of data mining methods and theory of finite state machines is used for testing automation. Automated creation of software documentation is based on using metadata in documented system. Metadata is built on graph model. Described approaches improve performance and quality of testing and documenting processes.

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The ability of automatic graphic user interface construction is described. It is based on the building of user interface as reflection of the data domain logical definition. The submitted approach to development of the information system user interface enables dynamic adaptation of the system during their operation. This approach is used for creation of information systems based on CASE-system METAS.

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Adaptive critic methods have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, nonlinear and nonstationary environments. In this study, a novel probabilistic dual heuristic programming (DHP) based adaptive critic controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) adaptive critic method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterized by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the critic network is then calculated and shown to be equal to the analytically derived correct value.

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Discrepancies of materials, tools, and factory environments, as well as human intervention, make variation an integral part of the manufacturing process of any component. In particular, the assembly of large volume, aerospace parts is an area where significant levels of form and dimensional variation are encountered. Corrective actions can usually be taken to reduce the defects, when the sources and levels of variation are known. For the unknown dimensional and form variations, a tolerancing strategy is typically put in place in order to minimize the effects of production inconsistencies related to geometric dimensions. This generates a challenging problem for the automation of the corresponding manufacturing and assembly processes. Metrology is becoming a major contributor to being able to predict, in real time, the automated assembly problems related to the dimensional variation of parts and assemblies. This is done by continuously measuring dimensions and coordinate points, focusing on the product's key characteristics. In this paper, a number of metrology focused activities for large-volume aerospace products, including their implementation and application in the automation of manufacturing and assembly processes, are reviewed. This is done by using a case study approach within the assembly of large-volume aircraft wing structures.

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Today, the question of how to successfully reduce supply chain costs whilst increasing customer satisfaction continues to be the focus of many firms. It is noted in the literature that supply chain automation can increase flexibility whilst reducing inefficiencies. However, in the dynamic and process driven environment of distribution, there is the absence of a cohesive automation approach to guide companies in improving network competitiveness. This paper aims to address the gap in the literature by developing a three-level framework automation application approach with the assistance of radio frequency identification (RFID) technology and returnable transport equipment (RTE). The first level considers the automation of data retrieval and highlights the benefits of RFID. The second level consists of automating distribution processes such as unloading and assembling orders. As the labour is reduced with the introduction of RFID enabled robots, the balance between automation and labour is discussed. Finally, the third level is an analysis of the decision-making process at network points and the application of cognitive automation to objects. A distribution network scenario is formed and used to illustrate network reconfiguration at each level. The research pinpoints that RFID enabled RTE offers a viable tool to assist supply chain automation. Further research is proposed in particular, the area of cognitive automation to aide with decision-making.

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In this Bachelor Thesis I want to provide readers with tools and scripts for the control of a 7DOF manipulator, backed up by some theory of Robotics and Computer Science, in order to better contextualize the work done. In practice, we will see most common software, and developing environments, used to cope with our task: these include ROS, along with visual simulation by VREP and RVIZ, and an almost "stand-alone" ROS extension called MoveIt!, a very complete programming interface for trajectory planning and obstacle avoidance. As we will better appreciate and understand in the introduction chapter, the capability of detecting collision objects through a camera sensor, and re-plan to the desired end-effector pose, are not enough. In fact, this work is implemented in a more complex system, where recognition of particular objects is needed. Through a package of ROS and customized scripts, a detailed procedure will be provided on how to distinguish a particular object, retrieve its reference frame with respect to a known one, and then allow navigation to that target. Together with technical details, the aim is also to report working scripts and a specific appendix (A) you can refer to, if desiring to put things together.

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La tesi approccia in modo transdisciplinare biologia, architettura e robotica, con la finalità di indagare e applicare principi costruttivi attraverso l’interazione tra sciami di droni che depositano materiale fibroso su strutture gonfiabili di supporto. L’attenzione principale è nello sviluppo (attraverso un workflow computazionale che gestisce sciami di agenti costruttori) di una tettonica che integra struttura, spazio e ornamento all’interno dello stesso processo progettuale, il quale si sviluppa coerentemente dall’ideazione fino alla fabbricazione. Sono stati studiati modelli biologici quali le colonie di ragni sociali, i quali costruiscono artefatti di grandi dimensioni relativamente a quelle del singolo individuo grazie ad un’organizzazione coordinata ed emergente e alle proprietà dei sistemi fibrosi. L’auto-organizzazione e la decentralizzazione, insieme alle caratteristiche del sistema materiale, sono stati elementi indispensabili nell’estrapolazione prima e nella codificazione poi di un insieme di regole adatte allo sviluppo del sistema costruttivo. Parallelamente alla simulazione digitale si è andati a sviluppare anche un processo fisico di fabbricazione che, pur tenendo conto dei vincoli economici e tecnici, potesse dimostrarsi una prova di concetto e fattibilità del sistema costruttivo. Sono state investigate le possibilità che un drone offre nel campo della fabbricazione architettonica mediante il rilascio di fili su elementi gonfiabili in pressione. Il processo può risultare vantaggioso in scenari in cui non è possibile allestire infrastrutture costruttive tradizionali (es. gole alpine, foreste). Tendendo conto dei vincoli e delle caratteristiche del sistema di fabbricazione proposto, sono state esplorate potenzialità e criticità del sistema studiato.

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In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.

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With increasing prevalence and capabilities of autonomous systems as part of complex heterogeneous manned-unmanned environments (HMUEs), an important consideration is the impact of the introduction of automation on the optimal assignment of human personnel. The US Navy has implemented optimal staffing techniques before in the 1990's and 2000's with a "minimal staffing" approach. The results were poor, leading to the degradation of Naval preparedness. Clearly, another approach to determining optimal staffing is necessary. To this end, the goal of this research is to develop human performance models for use in determining optimal manning of HMUEs. The human performance models are developed using an agent-based simulation of the aircraft carrier flight deck, a representative safety-critical HMUE. The Personnel Multi-Agent Safety and Control Simulation (PMASCS) simulates and analyzes the effects of introducing generalized maintenance crew skill sets and accelerated failure repair times on the overall performance and safety of the carrier flight deck. A behavioral model of four operator types (ordnance officers, chocks and chains, fueling officers, plane captains, and maintenance operators) is presented here along with an aircraft failure model. The main focus of this work is on the maintenance operators and aircraft failure modeling, since they have a direct impact on total launch time, a primary metric for carrier deck performance. With PMASCS I explore the effects of two variables on total launch time of 22 aircraft: 1) skill level of maintenance operators and 2) aircraft failure repair times while on the catapult (referred to as Phase 4 repair times). It is found that neither introducing a generic skill set to maintenance crews nor introducing a technology to accelerate Phase 4 aircraft repair times improves the average total launch time of 22 aircraft. An optimal manning level of 3 maintenance crews is found under all conditions, the point at which any additional maintenance crews does not reduce the total launch time. An additional discussion is included about how these results change if the operations are relieved of the bottleneck of installing the holdback bar at launch time.

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This paper presents a solution to part of the problem of making robotic or semi-robotic digging equipment less dependant on human supervision. A method is described for identifying rocks of a certain size that may affect digging efficiency or require special handling. The process involves three main steps. First, by using range and intensity data from a time-of-flight (TOF) camera, a feature descriptor is used to rank points and separate regions surrounding high scoring points. This allows a wide range of rocks to be recognized because features can represent a whole or just part of a rock. Second, these points are filtered to extract only points thought to belong to the large object. Finally, a check is carried out to verify that the resultant point cloud actually represents a rock. Results are presented from field testing on piles of fragmented rock. Note to Practitioners—This paper presents an algorithm to identify large boulders in a pile of broken rock as a step towards an autonomous mining dig planner. In mining, piles of broken rock can contain large fragments that may need to be specially handled. To assess rock piles for excavation, we make use of a TOF camera that does not rely on external lighting to generate a point cloud of the rock pile. We then segment large boulders from its surface by using a novel feature descriptor and distinguish between real and false boulder candidates. Preliminary field experiments show promising results with the algorithm performing nearly as well as human test subjects.