Situación actual de la industria de manufacturas eléctricas en Brasil = Present status of the electrical equipment manufacturing industry in Brazil

Incluye Bibliografía

Demanda de maquinaria y equipo de la minería metalífera en algunos países de América Latina = Demand for machinery and equipment by the metal mining industry in some countries of Latin America

Incluye Bibliografía

Validation of analytical methodology for quantification of cefazolin sodium pharmaceutical dosage form by high performance liquid chromatography to be applied for quality control in pharmaceutical industry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

CHARACTERISTICS OF THE PRIVATE NUISANCE WILDLIFE CONTROL INDUSTRY IN NEW YORK

The nuisance wildlife control industry is rapidly expanding in New York State. To gain additional insight about this industry and the number of animals handled, we reviewed the 1989-90 annual logs submitted by Nuisance Wildlife Control Orators (NWC0s) to the New York State Department of Environmental Conservation (DEC). The specific objectives of this study were to determine: (1) the number and species of different wildlife responsible for damage incidents, (2) the cause of damage complaints, (3) the disposition of animals handled, (4) the location of damage events (i.e., urban, suburban, rural), and (5) an estimate of the economic impact of the nuisance wildlife industry in Upstate New York. The Nuisance Wildlife Logs (NWLs) were examined for 7 urban and 7 rural counties (25.5% of Upstate counties), and these data were used to estimate total NWCO activity in DEC Regions 3 through 9 (excludes Long Island). Approximately 75% of NWCOs licensed by DEC were active during 1989-90, and nearly 2,800 complaints were handled in the 14 counties sampled. More than 90% of complaints came from urban counties, and we estimated that NWC0s responded to more than 11,000 calls in Upstate New York. At a conservative estimate of $35/call, revenue generated by this industry exceeded $385,000 annually. Six wildlife species accounted for 85% of the nuisance complaints in urban and rural counties. During 1986 to 1993, the number of NWCOs licensed by DEC nearly quadrupled, and there is no indication that this trend will change in the near future.

Development of quantitative methods for sustainability assessment in process industry

The increasing aversion to technological risks of the society requires the development of inherently safer and environmentally friendlier processes, besides assuring the economic competitiveness of the industrial activities. The different forms of impact (e.g. environmental, economic and societal) are frequently characterized by conflicting reduction strategies and must be holistically taken into account in order to identify the optimal solutions in process design. Though the literature reports an extensive discussion of strategies and specific principles, quantitative assessment tools are required to identify the marginal improvements in alternative design options, to allow the trade-off among contradictory aspects and to prevent the “risk shift”. In the present work a set of integrated quantitative tools for design assessment (i.e. design support system) was developed. The tools were specifically dedicated to the implementation of sustainability and inherent safety in process and plant design activities, with respect to chemical and industrial processes in which substances dangerous for humans and environment are used or stored. The tools were mainly devoted to the application in the stages of “conceptual” and “basic design”, when the project is still open to changes (due to the large number of degrees of freedom) which may comprise of strategies to improve sustainability and inherent safety. The set of developed tools includes different phases of the design activities, all through the lifecycle of a project (inventories, process flow diagrams, preliminary plant lay-out plans). The development of such tools gives a substantial contribution to fill the present gap in the availability of sound supports for implementing safety and sustainability in early phases of process design. The proposed decision support system was based on the development of a set of leading key performance indicators (KPIs), which ensure the assessment of economic, societal and environmental impacts of a process (i.e. sustainability profile). The KPIs were based on impact models (also complex), but are easy and swift in the practical application. Their full evaluation is possible also starting from the limited data available during early process design. Innovative reference criteria were developed to compare and aggregate the KPIs on the basis of the actual sitespecific impact burden and the sustainability policy. Particular attention was devoted to the development of reliable criteria and tools for the assessment of inherent safety in different stages of the project lifecycle. The assessment follows an innovative approach in the analysis of inherent safety, based on both the calculation of the expected consequences of potential accidents and the evaluation of the hazards related to equipment. The methodology overrides several problems present in the previous methods proposed for quantitative inherent safety assessment (use of arbitrary indexes, subjective judgement, build-in assumptions, etc.). A specific procedure was defined for the assessment of the hazards related to the formations of undesired substances in chemical systems undergoing “out of control” conditions. In the assessment of layout plans, “ad hoc” tools were developed to account for the hazard of domino escalations and the safety economics. The effectiveness and value of the tools were demonstrated by the application to a large number of case studies concerning different kinds of design activities (choice of materials, design of the process, of the plant, of the layout) and different types of processes/plants (chemical industry, storage facilities, waste disposal). An experimental survey (analysis of the thermal stability of isomers of nitrobenzaldehyde) provided the input data necessary to demonstrate the method for inherent safety assessment of materials.

Quality Control in the Healthcare Industry: An Analysis of Surgery Turnover Times

For virtually all hospitals, utilization rates are a critical managerial indicator of efficiency and are determined in part by turnover time. Turnover time is defined as the time elapsed between surgeries, during which the operating room is cleaned and preparedfor the next surgery. Lengthier turnover times result in lower utilization rates, thereby hindering hospitals’ ability to maximize the numbers of patients that can be attended to. In this thesis, we analyze operating room data from a two year period provided byEvangelical Community Hospital in Lewisburg, Pennsylvania, to understand the variability of the turnover process. From the recorded data provided, we derive our best estimation of turnover time. Recognizing the importance of being able to properly modelturnover times in order to improve the accuracy of scheduling, we seek to fit distributions to the set of turnover times. We find that log-normal and log-logistic distributions are well-suited to turnover times, although further research must validate this finding. Wepropose that the choice of distribution depends on the hospital and, as a result, a hospital must choose whether to use the log-normal or the log-logistic distribution. Next, we use statistical tests to identify variables that may potentially influence turnover time. We find that there does not appear to be a correlation between surgerytime and turnover time across doctors. However, there are statistically significant differences between the mean turnover times across doctors. The final component of our research entails analyzing and explaining the benefits of introducing control charts as a quality control mechanism for monitoring turnover times in hospitals. Although widely instituted in other industries, control charts are notwidely adopted in healthcare environments, despite their potential benefits. A major component of our work is the development of control charts to monitor the stability of turnover times. These charts can be easily instituted in hospitals to reduce the variabilityof turnover times. Overall, our analysis uses operations research techniques to analyze turnover times and identify manners for improvement in lowering the mean turnover time and thevariability in turnover times. We provide valuable insight into a component of the surgery process that has received little attention, but can significantly affect utilization rates in hospitals. Most critically, an ability to more accurately predict turnover timesand a better understanding of the sources of variability can result in improved scheduling and heightened hospital staff and patient satisfaction. We hope that our findings can apply to many other hospital settings.

Automatic quality control in clinical (1) H MRSI of brain cancer.

MRSI grids frequently show spectra with poor quality, mainly because of the high sensitivity of MRS to field inhomogeneities. These poor quality spectra are prone to quantification and/or interpretation errors that can have a significant impact on the clinical use of spectroscopic data. Therefore, quality control of the spectra should always precede their clinical use. When performed manually, quality assessment of MRSI spectra is not only a tedious and time-consuming task, but is also affected by human subjectivity. Consequently, automatic, fast and reliable methods for spectral quality assessment are of utmost interest. In this article, we present a new random forest-based method for automatic quality assessment of (1) H MRSI brain spectra, which uses a new set of MRS signal features. The random forest classifier was trained on spectra from 40 MRSI grids that were classified as acceptable or non-acceptable by two expert spectroscopists. To account for the effects of intra-rater reliability, each spectrum was rated for quality three times by each rater. The automatic method classified these spectra with an area under the curve (AUC) of 0.976. Furthermore, in the subset of spectra containing only the cases that were classified every time in the same way by the spectroscopists, an AUC of 0.998 was obtained. Feature importance for the classification was also evaluated. Frequency domain skewness and kurtosis, as well as time domain signal-to-noise ratios (SNRs) in the ranges 50-75 ms and 75-100 ms, were the most important features. Given that the method is able to assess a whole MRSI grid faster than a spectroscopist (approximately 3 s versus approximately 3 min), and without loss of accuracy (agreement between classifier trained with just one session and any of the other labelling sessions, 89.88%; agreement between any two labelling sessions, 89.03%), the authors suggest its implementation in the clinical routine. The method presented in this article was implemented in jMRUI's SpectrIm plugin. Copyright © 2016 John Wiley & Sons, Ltd.

Automatic lateral control for unmanned vehicles via genetic algorithms

It is known that the techniques under the topic of Soft Computing have a strong capability of learning and cognition, as well as a good tolerance to uncertainty and imprecision. Due to these properties they can be applied successfully to Intelligent Vehicle Systems; ITS is a broad range of technologies and techniques that hold answers to many transportation problems. The unmannedcontrol of the steering wheel of a vehicle is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle; to reach it, information about the car state while a human driver is handling the car is taken and used to adjust, via iterative geneticalgorithms an appropriated fuzzy controller. To evaluate the obtained controllers, it will be considered the performance obtained in the track following task, as well as the smoothness of the driving carried out.

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Uncertainty Estimation for Performance Evaluation of a Confocal Microscope as Metrology Equipment

Both in industry and research, the quality control of micrometric manufactured parts is based on the measurement of parameters whose traceability is sometimes difficult to guarantee. In some of these parts, the confocal microscopy shows great aptitudes to characterize a measurand qualitatively and quantitatively. The confocal microscopy allows the acquisition of 2D and 3D images that are easily manipulated. Nowadays, this equipment is manufactured by many different brands, each of them claiming a resolution probably not in accord to their real performance. The Laser Center (Technical University of Madrid) has a confocal microscope to verify the dimensions of the micro mechanizing in their own research projects. The present study pretends to confirm that the magnitudes obtained are true and reliable. To achieve this, a methodology for confocal microscope calibration is proposed, as well as an experimental phase for dimensionally valuing the equipment by 4 different standard positions, with its seven magnifications and the six objective lenses that the equipment currently has, in the x–y and z axis. From the results the uncertainty will be estimated along with an effect analysis of the different magnifications in each of the objective lenses.

Loose Coupling Based Reference Scheme for Shop Floor-Control-System/Production-Equipment Integration.

Acoplamiento del sistema informático de control de piso de producción (SFS) con el conjunto de equipos de fabricación (SPE) es una tarea compleja. Tal acoplamiento involucra estándares abiertos y propietarios, tecnologías de información y comunicación, entre otras herramientas y técnicas. Debido a la turbulencia de mercados, ya sea soluciones personalizadas o soluciones basadas en estándares eventualmente requieren un esfuerzo considerable de adaptación. El concepto de acoplamiento débil ha sido identificado en la comunidad de diseño organizacional como soporte para la sobrevivencia de la organización. Su presencia reduce la resistencia de la organización a cambios en el ambiente. En este artículo los resultados obtenidos por la comunidad de diseño organizacional son identificados, traducidos y organizados para apoyar en la solución del problema de integración SFS-SPE. Un modelo clásico de acoplamiento débil, desarrollado por la comunidad de estudios de diseño organizacional, es resumido y trasladado al área de interés. Los aspectos claves son identificados para utilizarse como promotores del acoplamiento débil entre SFS-SPE, y presentados en forma de esquema de referencia. Así mismo, este esquema de referencia es presentado como base para el diseño e implementación de una solución genérica de acoplamiento o marco de trabajo (framework) de acoplamiento, a incluir como etapa de acoplamiento débil entre SFS y SPE. Un ejemplo de validación con varios conjuntos de equipos de fabricación, usando diferentes medios físicos de comunicación, comandos de controlador, lenguajes de programación de equipos y protocolos de comunicación es presentado, mostrando un nivel aceptable de autonomía del SFS. = Coupling shop floor software system (SFS) with the set of production equipment (SPE) becomes a complex task. It involves open and proprietary standards, information and communication technologies among other tools and techniques. Due to market turbulence, either custom solutions or standards based solutions eventually require a considerable effort of adaptation. Loose coupling concept has been identified in the organizational design community as a compensator for organization survival. Its presence reduces organization reaction to environment changes. In this paper the results obtained by the organizational de sign community are identified, translated and organized to support the SFS-SPE integration problem solution. A classical loose coupling model developed by organizational studies community is abstracted and translated to the area of interest. Key aspects are identified to be used as promoters of SFS-SPE loose coupling and presented in a form of a reference scheme. Furthermore, this reference scheme is proposed here as a basis for the design and implementation of a generic coupling solution or coupling framework, that is included as a loose coupling stage between SFS and SPE. A validation example with various sets of manufacturing equipment, using different physical communication media, controller commands, programming languages and wire protocols is presented, showing an acceptable level of autonomy gained by the SFS.

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.