599 research outputs found
Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for Surface Coal Mining
Data management of production records has become a key element in surface coal mining operations. Information systems (IS) and information technologies (IT) can be used as valuable tools for the production monitoring and analysis of employee and equipment performances. This thesis presents the research results on the development and application of a custom-made Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for surface coal mining. The TCD-ADCS is capable of collecting trucks\u27 production data, delay times, loading and dumping times, travel distance, and GPS coordinates of production events from a mine site. Also, it enables field data transfer through a wireless network to a server located in an office environment. Additionally, the system is compatible with the already developed Integrated Production Management System (IPMS). Data are locally stored in each truck and then synchronized and replicated into a centralized server containing database management system for analysis and reporting. The system relies on motion sensing and distance traveled in order to automatically define the cycle starting/ending points, cycle time, position, and delay time. Connectivity and communication between loading equipment and trucks have also been established. A user-friendly graphic interface has been developed for the communication between the equipment operators and TCD-ADCS system. The infrastructure used for the development of this system application consists in a rugged touch-screen personal computer, 2.4 GHz radio transmitter antenna, and a high-sensitivity commercial GPS receiver. The system was developed, tested, and deployed at a surface coal mines in the U.S
Women of the River: Grassroots Organizing and Natural Disaster
This study, a sub-study of a larger project, the Missouri Mobile Home Estates Project, examines the grassroots efforts of three women in an impoverished Midwestern river community to improve the lives of the children living there. The women’s efforts included infrastructure improvements, a summer meal program for the children, a food bank, and a thrift shop. This community was devastated by floods in 1973, 1986, and 1993; at these times, crisis intervention services were provided to the residents. Yet, it appears little assistance was offered to the community between these floods, despite the community’s well-publicized crime and poverty. Using a social action framework and interpretive phenomenological analysis, the participants in this study were interviewed to examine the following questions: (1) Are the characteristics of grassroots community organizing evident in the grassroots efforts of the women of the river?; (2) How did residing in Missouri Mobile affect the women long term?; (3) How did residing in Missouri Mobile affect their two children?; and (4) What common themes emerged from the women’s and children’s interviews
Towards shoestring solutions for UK manufacturing SMEs
In the Digital Manufacturing on a Shoestring project we focus on low-cost digital solution requirements for UK manufacturing SMEs. This paper shows that many of these fall in the HRI domain while presenting the use of low-cost and off-the-shelf technologies in two demonstrators based on voice assisted production
Tying Together Solutions for Digital Manufacturing: Assessment of Connectivity Technologies & Approaches
This paper concerns the development of low-cost solutions to address challenges in digital manufacturing (DM). Service Oriented Architectures (SOAs) are a promising approach for addressing the requirements of a low-cost DM architecture. Interaction between services in a SOA is facilitated by a connectivity technology, i.e., a framework for interoperable data exchange between heterogeneous participants. We review a variety of connectivity technologies according to their suitability for use in an SME manufacturer’s production environment, and we assess how they have been integrated into past architectures. We then provide insights into an incremental and modular architecture for manufacturing SMEs.Digital Manufacturing on a Shoestring [Digital Shoestring].
EPSRC Reference: EP/R032777/1
VGOS VLBI Intensives between MACGO12M and WETTZ13S for the rapid determination of UT1-UTC
In this work, we present a status update and results of the designated
research and development VLBI Intensive program VGOS-INT-S, observed between
MACGO12M and WETTZ13S for the rapid determination of the Earth's phase of
rotation, expressed via UT1-UTC. The main novelty of these sessions is the use
of a special observation strategy, rapidly alternating between high- and
low-elevation scans, enabling an improved determination of delays caused by the
neutral atmosphere. Since 2021, 25 Intensive sessions have been observed
successfully. In early 2022, VGOS-INT-S was among the most accurate Intensive
programs with an average formal error of 3.1 s and a
bias w.r.t. IERS C04 of 1.1 s. Later, the session performance decreased
due to multiple technical difficulties.Comment: 8 pages, 5 figure
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Digital manufacturing on a shoestring: Low cost digital solutions for SMEs
One of the key findings in a number of recent studies has been that small and medium sized manufacturers (SMEs) have been slow in adopting digital solutions within their organisations. Cost is understood to be one of the key barriers to adoption. Digital Manufacturing on a Shoestring is an approach to increasing the digital capabilities of SMEs via a series of low cost solutions. The programme proposes using off-the-shelf, (possibly non-industrial) components and software to address a company’s (digital) solution needs, adding capabilities one step at a time with minimal a priori infrastructure required. This paper will introduce the Digital Manufacturing on a Shoestring programme as a whole and demonstrate the way in which it addresses the need for low cost digital solutions for SME Manufacturers. It will discuss challenges associated with integrating low cost technologies into industrial solutions and the style of IT architectures best suited for integrating such solutions into industrial environments
SEEMP: A Semantic Interoperability Infrastructure for e-government services in the employment sector
This paper presents SEEMP, a marketplace to coordinate
and integrate public and private employment services (ESs) around the
EU Member States. The need for flexible collaboration in the marketplace
gives rise to the issue of interoperability in both data exchange and
share of services. SEEMP proposes a mixed approach that relies on the
concepts of services and semantics. SEEMP approach combines Software
Engineering and Semantic Web methodologies/tools in an infrastructure
that allows for a meaningful service-based communication among ESs
COSTO AMBIENTAL SOSTENIBLE RELATIVO CON AGREGACIÓN DE BIOMARCADORES PARA LA ESTIMACIÓN DE LA CALIDAD AMBIENTAL EN ECOSISTEMAS ACUÁTICOS
Se realizó un estudio sobre ecotoxicología acuática por exposición a metales en el ecosistema San Juan de Santiago de Cuba, Cuba durante el periodo de lluvia y estiaje del 2018. El objetivo de la investigación fue predecir la ecotoxicología por metales mediante el costo ambiental sostenible, biomarcadores y el modelo computacional Gecotoxic. Se seleccionó, cinco estaciones para estimar el costo ambiental sostenible relativo (COASOR ) según parámetros físico-químicos (PFQ) seleccionados (dureza total: DT, pH, biom sólidos totales: ST, oxígeno disuelto: OD y la demanda bioquímica de oxígeno: DBO . Se determinó la 5,20 concentración de Cu, Zn, Pb, Cd en agua y sedimentos (lluvia). Se utilizó a Gambusia punctata (Poey, 1854) como biomonitor cuantificándose los metales (Ms) en las branquias, hígado y cerebro, además, de medirse el factor de condición de Fulton, reproducción, nivel trófico y la actividad acetilcolinesterasa cerebral. Las mediciones se introdujeron en el modelo computacional Gecotoxic para la predicción ecotoxicológica. La DBO , no cumplió con el límite permisible (≤4.0) cuyos resultados fueron: 29.84 ± 5,20 2.18, (lluvia) y 39.46 ± 2.0 (estiaje). Las concentraciones de los Ms en las aguas superaron los límites máximos permisibles: Cu: 13.55 ± 1.38 (1.0) Zn: 23.36 ± 1.38 (5.0); Pb: 1.27 ± 0.042 (0.5) y Cd: 0.05 ± 0.002 (0.05). El valor que estimó el COASOR fue de 0.75 lo cual significó, categoría poco sostenible biom del recurso. No hubo, correlación entre los Ms y biomarcadores seleccionados, aunque existió comportamiento desigual comparado con la especie referencia ambiental. Gecotoxic señaló, riesgo ecotoxicológico de tipo alto (81%) siendo limitada la calidad ambiental del ecosistema
In-process tool wear prediction system based on machine learning techniques and force analysis
This paper presents an in-process tool wear prediction system, which uses a force sensor to monitor the progression of the tool flank wear and machine learning (ML), more specifically, a Convolutional Neural Network (CNN) as a method to predict tool wear. The proposed methodology is experimentally illustrated using milling as a test process. The experiments are conducted using dry machining with a non-coated ball endmill and a stainless steel workpiece. The measurement of the flank wear is carried on in-situ utilising a digital microscope. The ML model predictions are based on an experience database which contains all the data of the precedent experiments. The proposed in-process tool wear prediction system will be reinforced later by an adaptive control (AC) system that will communicate continuously with the ML model to seek the best adjustment of feed rate and spindle speed that allows the optimization of the flank wear and extend the tool life. The AC model decisions are based on the prediction delivered by the ML model and on the information feedback provided from the force sensor, which captures the change in the cutting forces as a function of the progression of the flank wear. In this work, only the ML model component for the estimation of tool wear based on CNNs is demonstrated. The proposed methodology has shown an estimated accuracy of 90%. Additional experiments will be performed to confirm the repetitiveness of the results and also extend the measurement range to improve accuracy of the measurement system
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