Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

Label monitoring on document streams

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Terrestrial laser scanning for landslides deformation monitoring

Within last few years a new type of instruments called Terrestrial Laser Scanners (TLS) entered to the commercial market. These devices brought a possibility to obtain completely new type of spatial, three dimensional data describing the object of interest. TLS instruments are generating a type of data that needs a special treatment. Appearance of this technique made possible to monitor deformations of very large objects, like investigated here landslides, with new quality level. This change is visible especially with relation to the size and number of the details that can be observed with this new method. Taking into account this context presented here work is oriented on recognition and characterization of raw data received from the TLS instruments as well as processing phases, tools and techniques to do them. Main objective are definition and recognition of the problems related with usage of the TLS data, characterization of the quality single point generated by TLS, description and investigation of the TLS processing approach for landslides deformation measurements allowing to obtain 3D deformation characteristic and finally validation of the obtained results. The above objectives are based on the bibliography studies and research work followed by several experiments that will prove the conclusions.

Sistema de gestió de tallers: aplicació de tecnologies Web 2.0 a la planificació de la feina d'un taller mecànic

El projecte consisteix en una aplicació que facilita la gestió d'un taller de reparació de vehicles, adquirint especial importància la planificació, control i seguiment dels treballs que porten a terme els operaris. L’aplicatiu es desenvoluparà en entorn web i pretendrà aproximar-se al nivell de prestacions que una aplicació tradicional d'escriptori, gràcies a l'ús de tecnologies Web 2.0 com AJAX, però amb tot el valor afegit que implica una aplicació web.

EuroDia: a beta-cell gene expression resource.

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.

Human mercury exposure associated with small-scale gold mining in Burkina Faso.

PURPOSE: In Burkina Faso, gold ore is one of the main sources of income for an important part of the active population. Artisan gold miners use mercury in the extraction, a toxic metal whose human health risks are well known. The aim of the present study was to assess mercury exposure as well as to understand the exposure determinants of gold miners in Burkinabe small-scale mines.METHODS: The examined gold miners' population on the different selected gold mining sites was composed by persons who were directly and indirectly related to gold mining activities. But measurement of urinary mercury was performed on workers most susceptible to be exposed to mercury. Thus, occupational exposure to mercury was evaluated among ninety-three workers belonging to eight different gold mining sites spread in six regions of Burkina Faso. Among others, work-related exposure determinants were taken into account for each person during urine sampling as for example amalgamating or heating mercury. All participants were medically examined by a local medical team in order to identify possible symptoms related to the toxic effect of mercury.RESULTS: Mercury levels were high, showing that 69% of the measurements exceeded the ACGIH (American Conference of Industrial Hygienists) biological exposure indice (BEI) of 35 µg per g of creatinine (µg/g-Cr) (prior to shift) while 16% even exceeded 350 µg/g-Cr. Basically, unspecific but also specific symptoms related to mercury toxicity could be underlined among the persons who were directly related to gold mining activities. Only one-third among the studied subpopulation reported about less than three symptoms possibly associated to mercury exposure and nearly half of them suffered from at least five of these symptoms. Ore washers were more involved in the direct handling of mercury while gold dealers in the final gold recovery activities. These differences may explain the overexposure observed in gold dealers and indicate that the refining process is the major source of exposure.CONCLUSIONS: This study attests that mercury exposure still is an issue of concern. North-South collaborations should encourage knowledge exchange between developing and developed countries, for a cleaner artisanal gold mining process and thus for reducing human health and environmental hazards due to mercury use.

Nanoparticle usage and protection measures in the manufacturing industry : a representative survey

Addressing the risks of nanoparticles requires knowledge about release into the environment and occupational exposure. However, such information currently is not systematically collected; therefore, this risk assessment lacks quantitative data. The goal was to evaluate the current level of nanoparticle usage in Swiss industry as well as health, safety, and environmental measures, and the number of potentially exposed workers. A representative, stratified mail survey was conducted among 1626 clients of the Swiss National Accident Insurance Fund (SUVA), which insures 80,000 manufacturing firms, representing 84% of all Swiss manufacturing companies (947 companies answered the survey for a 58.3% response rate). The extrapolation to all Swiss manufacturing companies results in 1309 workers (95% confidence interval [CI]: 1073 to 1545) potentially exposed to nanoparticles in 586 companies (95% CI: 145 to 1027). This corresponds to 0.08% of workers (95% CI: 0.06% to 0.09%) and to 0.6% of companies (95% CI: 0.2% to 1.1%). The industrial chemistry sector showed the highest percentage of companies using nanoparticles (21.2%). Other important sectors also reported nanoparticles. Personal protection equipment was the predominant protection strategy. Only a few applied specific environmental protection measures. This is the first nationwide representative study on nanoparticle use in the manufacturing sector. The information gained can be used for quantitative risk assessment. It can also help policymakers design strategies to support companies developing a safer use of nanomaterial. Notingthe current low use of nanoparticles, there is still time to proactively introduce protective methods. If the predicted "nano-revolution" comes true, now is the time to take action. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of occupational and Environmental Hygiene for the following free supplemental resource: a pdf file containing a detailed description of the approach to statistical analyses, English translation of the questionnaire, additional information for Figure 1, and additional information for the SUVA-code.] [Authors]

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Aplicació web per a la vigilància epidemiològica a Barcelona emprant sistemes d'informació geogràfica de programari lliure

This project is about the development of a web that uses the tools offered by the Geographic Information Systems based in open source in order to monitoring and detect legionella clusters in Barcelona. This web also produces thematic maps for the study of epidemiologic diseases and has been made with the colaboration of the Barcelona public health agency.

Web-based Implementation of Winter Maintenance Decision Support System Using GIS and Remote Sensing, May 2005

Winter maintenance, particularly snow removal and the stress of snow removal materials on public structures, is an enormous budgetary burden on municipalities and nongovernmental maintenance organizations in cold climates. Lately, geospatial technologies such as remote sensing, geographic information systems (GIS), and decision support tools are roviding a valuable tool for planning snow removal operations. A few researchers recently used geospatial technologies to develop winter maintenance tools. However, most of these winter maintenance tools, while having the potential to address some of these information needs, are not typically placed in the hands of planners and other interested stakeholders. Most tools are not constructed with a nontechnical user in mind and lack an easyto-use, easily understood interface. A major goal of this project was to implement a web-based Winter Maintenance Decision Support System (WMDSS) that enhances the capacity of stakeholders (city/county planners, resource managers, transportation personnel, citizens, and policy makers) to evaluate different procedures for managing snow removal assets optimally. This was accomplished by integrating geospatial analytical techniques (GIS and remote sensing), the existing snow removal asset management system, and webbased spatial decision support systems. The web-based system was implemented using the ESRI ArcIMS ActiveX Connector and related web technologies, such as Active Server Pages, JavaScript, HTML, and XML. The expert knowledge on snow removal procedures is gathered and integrated into the system in the form of encoded business rules using Visual Rule Studio. The system developed not only manages the resources but also provides expert advice to assist complex decision making, such as routing, optimal resource allocation, and monitoring live weather information. This system was developed in collaboration with Black Hawk County, IA, the city of Columbia, MO, and the Iowa Department of transportation. This product was also demonstrated for these agencies to improve the usability and applicability of the system.

Mining and exploiting domain-specific corpora in the PANACEA platform

The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition,production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.

Monitoring of the Launched Girder Bridge over the Iowa River on US 20, March 2004

The objective of the study presented in this report was to document the launch of the Iowa River Bridge and to monitor and evaluate the structural performance of the bridge superstructure and substructure during the launch. The Iowa Department of Transportation used an incremental launching method, which is relatively unique for steel I-girder bridges, to construct the Iowa River Bridge over an environmentally sensitive river valley in central Iowa. The bridge was designed as two separate roadways consisting of four steel plate girders each that are approximately 11 ft deep and span approximately 301 ft each over five spans. The concrete bridge deck was not placed until after both roadways had been launched. One of the most significant monitoring and evaluation observations related to the superstructure was that the bottom flange (and associated web region) was subjected to extremely large stresses during the crossing of launch rollers. Regarding the substructure performance, the column stresses did not exceed reasonable design limits during the daylong launches. The scope of the study did not allow adequate quantification of the measured applied launch forces at the piers. Future proposed esearch should provide an opportunity to address this. The overall experimental performance of the bridge during the launch was compared with the predicted design performance. In general, the substructure design, girder contact stress, and total launching force assumptions correlated well with the experimental results. The design assumptions for total axial force in crossframe members, on the other hand, differed from the experimental results by as much as 300%.