SQMS – A prototype for a supplier quality management system

Within the supply chain, the customer does not simply buy parts or services from suppliers, but also buys supplier capabilities, which results in quality products and services. Having a tool that handles the Inspection as well as the Nonconformance, Complaint, Corrective Action and Concession processes is key to successfully track the supplier performance. Taking as a case study a Supplier Quality Management (SQM) currently in operation in an Original Equipment Manufacturer (OEM) for automotive industry, this paper presents a platform to support a Supplier Quality Management System (SQMS), that fits the technical specification ISO/TS 16949 requirements. This prototype is composed by a web platform and a mobile App, having flexibility and mobility as key main characteristics.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Model predictive control applied to a supply chain management problem

Supply chains are ubiquitous in any commercial delivery systems. The exchange of goods and services, from different supply points to distinct destinations scattered along a given geographical area, requires the management of stocks and vehicles fleets in order to minimize costs while maintaining good quality services. Even if the operating conditions remain constant over a given time horizon, managing a supply chain is a very complex task. Its complexity increases exponentially with both the number of network nodes and the dynamical operational changes. Moreover, the management system must be adaptive in order to easily cope with several disturbances such as machinery and vehicles breakdowns or changes in demand. This work proposes the use of a model predictive control paradigm in order to tackle the above referred issues. The obtained simulation results suggest that this strategy promotes an easy tasks rescheduling in case of disturbances or anticipated changes in operating conditions. © Springer International Publishing Switzerland 2017

Using SeaDataNet Management System to preserve the XBT Data-Set of the Mediterranean Sea

significant amount of Expendable Bathythermograph (XBT) data has been collected in the Mediterranean Sea since 1999 in the framework of operational oceanography activities. The management and storage of such a volume of data poses significant challenges and opportunities. The SeaDataNet project, a pan-European infrastructure for marine data diffusion, provides a convenient way to avoid dispersion of these temperature vertical profiles and to facilitate access to a wider public. The XBT data flow, along with the recent improvements in the quality check procedures and the consistence of the available historical data set are described. The main features of SeaDataNet services and the advantage of using this system for long-term data archiving are presented. Finally, focus on the Ligurian Sea is included in order to provide an example of the kind of information and final products devoted to different users can be easily derived from the SeaDataNet web portal.

Soil management system effects on N availability and tree productivity in chestnut planatations under Mediterranean conditions

Soil tillage with chisel ploughing is the conventional soil management system in chestnut stands for fruit production in Northern Portugal. A study was developed to assess the effects of three soil management systems on in situ soil N mineralization dynamics, tree nutrition status and fruit productivity, in a 50-yr old chestnut stand. The treatments were: conventional tillage with a chisel ploughing twice a year (CT), no-tillage with rainfed improved pasture with leguminous and grasses plants (NIP), and no-tillage with spontaneous herbaceous vegetation - natural pasture (NP). The CT treatment showed a strong increase of the soil N mineral concentration following soil disturbance by tillage, but the cumulative net N mineralized along the year was significantly lower (51.8 kg ha-1) than in the NIP (85.1 kg ha-1) treatment. The NP treatment (65.9 kg ha-1) did not cause a reduction in the soil N mineralization when compared to the CT treatment. The mineralization rate (g mineralized N kg-1 total N) in 2004 was about 26, 30 and 38 in the treatments CT, NP and NIP, respectively. Treatments showed different soil N dynamics, the proportion of mineralized NO3--N being lower in the NP (10-48%) than in CT and NIP treatments (53-74%). Our study indicates that no-tillage systems improve the tree nutrition status and enhance productivity

Protocolo de la historia clínica de baja visión dentro del marco de la implementación del sistema health information management system (HIMS) en la clínica de optometría de La Universidad de La Salle

Tesis (Optometra). -- Universidad de La Salle, Facultad de Ciencias de La Salud. Programa de Optometria, 2014

A mobile health network disaster management system

A common occurrence in almost all full-scale natural disasters is the rapid destruction of the telecommunication infrastructure as the inevitable unfolds, which tends to halt the necessary communications between the humanitarian operators and the people in need. In such scenarios, the deployment of wireless networks would provide fast and temporary remedies, however these networks normally do not provide services to the end-users and ordinary people, instead they provide connectivity between groups of end-users administered by a local service provider. From a range of services provided to the end-users by the humanitarian operators, healthcare is by far the top priority. This is considered through the utilization of smartphones in a Mobile Health (mHealth) perspective, which is an emerging concept for monitoring and tracking end-user health conditions. This article considers an mHealth system used in a tsunami-stricken disaster scenario, including a discussion on the most recent advances of Device to Device (D2D) and LTE-Direct technologies.

A real-time abnormality detection system for intensive care management

Detecting abnormalities from multiple correlated time series is valuable to those applications where a credible realtime event prediction system will minimize economic losses (e.g. stock market crash) and save lives (e.g. medical surveillance in the operating theatre). For example, in an intensive care scenario, anesthetists perform a vital role in monitoring the patient and adjusting the flow and type of anesthetics to the patient during an operation. An early awareness of possible complications is vital for an anesthetist to correctly react to a given situation. In this demonstration, we provide a comprehensive medical surveillance system to effectively detect abnormalities from multiple physiological data streams for assisting online intensive care management. Particularly, a novel online support vector regression (OSVR) algorithm is developed to approach the problem of discovering the abnormalities from multiple correlated time series for accuracy and real-time efficiency. We also utilize historical data streams to optimize the precision of the OSVR algorithm. Moreover, this system comprises a friendly user interface by integrating multiple physiological data streams and visualizing alarms of abnormalities. © 2013 IEEE.

Control and charge management of a grid-connected photovoltaic system with plug-in hybrid vehicle as energy storage

This paper presents the control and charge management strategy of a photovoltaic system (PV) with plug-in hybrid electric vehicle (PHEV) as energy storage. The hybrid energy storage system (HESS) of PHEV consists of battery and supercapacitor. A simulation model for the PV system with PHEV energy storage has been developed using Matlab/SimpowerSystems. The system consists of PV arrays, SEPIC dc-dc converter with maximum power point tracking (MPPT), hybrid battery-supercapacitor energy storage with bidirectional dc-dc converter and inverter for grid connection. A charge management algorithm for the hybrid energy storage system is proposed to control the power flows among the PV system, energy storage and the grid. Results show that the proposed power management algorithm can control the power flows in an efficient manner.

Identifying an appropriate content management system to develop clinical practice guidelines: a perspective

Clinical Practice Guidelines are widely used to inform and improve the quality and consistency of clinical practice. Developing and publishing Clinical Practice Guidelines is a complex task involving multiple components. Electronic Content Management Systems are increasingly employed to make this task more manageable. The Content Management System market offers a variety of options for publishing content on the Internet. However, there are limited products that comprehensively address the requirements of publishing Clinical Practice Guidelines. The authors are involved in publishing guidelines for remote clinical practitioners in Australia and present their perspective about identifying an appropriate Content Management System. Several elements essential to addressing their unique editing needs are defined in this article. Unfortunately, customisation is very expensive and laborious: few Content Management System providers can comprehensively meet the needs of Clinical Practice Guidelines publishing. Being pragmatic about the level of functionality a product can offer to support publication is essential.

SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

Local Use and Management of Tasba (Senna obtusifolia) in the Traditional Food System of Sanguere Paul, North Cameroon

The purpose of this study is to examine the importance of the wild edible weed tasba (Senna obtusifolia) in Sanguéré Paul, Cameroon by examining how households use and manage the plant. This study found that local management of tasba is minimal compared to other traditional vegetables. Tasba was collected most frequently from en brousse or the communal, fallowed land which is often too degraded for traditional field crops to grow. Women subsistence farmers were closely involved with tasba as they are the ones responsible for food production within the family. Socioeconomic differences between women affects how they manage tasba and other vegetables to form a livelihood strategy to achieve food security within the family. Modifications and changes in management and use of tasba are influenced by time, proximity and income based on her perspective, preferences and resources available. Overall, tasba is an integral part of the traditional food system in Sanguéré Paul, and can play a role in the uncertain ecological and social setting of northern Cameroon.

WAWASH Knowledge Management System

A knowledge management tool developed by the GIS Center for to support project reporting tools, project publications, and a project data portal for materials related to the WAWASH Program.

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^