Validação de design de armazém automatizado com uso de simulação discreta

Dissertação de mestrado em Engenharia de Sistemas

Simulointi- ja ohjausjärjestelmän kehitys siltanosturiavusteiseen automaattivarastoon

Diplomityö tehtiin Konecranes Oyj:lle, joka on nostureita valmistava ja niille kunnossapitopalveluita tarjoava suomalainen pörssiyhtiö. Työn kuluessa suunniteltiin ja toteutettiin siltanosturiavusteisiin automaattivarastoihin soveltuva simulointiohjelmisto ja varastonohjausjärjestelmä. Työssä keskityttiin pääsääntöisesti paperirullavarastoihin, mutta suunnitteluvaiheessa otettiin huomioon myös muut Konecranesin tarjontaan kuuluvat automaattivarastotyypit kuten vaakarulla ja kontti. Simulointiohjelmistolla mallinnetaan automaattivarastossa tapahtuvia liikkeitä. Käyttäjä pystyy näkemään nostureiden ja muiden varastossa olevien komponenttien liikkeet 3D- muotoisena simulaattorin käyttöliittymästä. Simulaattorin tavoitteena on helpottaa automaattivaraston suunnittelua ja nopeuttaa sen käyttöönottoa, sekä toimia myös vakuuttavana myyntityökaluna asiakaskontakteissa. Varastonohjausjärjestelmä tekee päätökset varaston tapahtumista ja ohjaa mm. nostureiden toimintaa. Diplomityön päämääränä oli perehtyä tarkasti nykyisen varastonohjausjärjestelmän toimintaan, kehittää uusi ratkaisumalli puutteiden sekä toiveiden perusteella ja lopulta osoittaa ratkaisumallin toimivuus ohjelmoimalla esittelyversio simulaattorista ja varastonohjausjärjestelmästä. Samaa varastonohjausjärjestelmää on määrä käyttää simulaattorissa ja tulevaisuudessa todellisen varaston ohjaamisessa. Asetetuista vaatimuksista johtuen järjestelmästä suunniteltiin mahdollisimman mukautuva. Työn lopputuloksena saatiin perusominaisuudet kattava 3D-simulaattori ja siihen liitetty varastonohjausjärjestelmä. Toteutuksen avulla oli mahdollista osoittaa ratkaisumallin toimivuus sekä esitellä ideaa laajamittaisemmin. Diplomityön kuluessa saatiin nykyisestä järjestelmästä kattavat tiedot ja pystyttiin määräämään suunta, kuinka kehitystyötä jatketaan.

Comparison Between Automated And Microscopic Analysis In Body Fluids Cytology.

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Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

AUTOMATED DETERMINATION OF [Fe/H] AND [C/Fe] FROM LOW-RESOLUTION SPECTROSCOPY

We develop an automated spectral synthesis technique for the estimation of metallicities ([Fe/H]) and carbon abundances ([C/Fe]) for metal-poor stars, including carbon-enhanced metal-poor stars, for which other methods may prove insufficient. This technique, autoMOOG, is designed to operate on relatively strong features visible in even low- to medium-resolution spectra, yielding results comparable to much more telescope-intensive high-resolution studies. We validate this method by comparison with 913 stars which have existing high-resolution and low- to medium-resolution to medium-resolution spectra, and that cover a wide range of stellar parameters. We find that at low metallicities ([Fe/H] less than or similar to -2.0), we successfully recover both the metallicity and carbon abundance, where possible, with an accuracy of similar to 0.20 dex. At higher metallicities, due to issues of continuum placement in spectral normalization done prior to the running of autoMOOG, a general underestimate of the overall metallicity of a star is seen, although the carbon abundance is still successfully recovered. As a result, this method is only recommended for use on samples of stars of known sufficiently low metallicity. For these low- metallicity stars, however, autoMOOG performs much more consistently and quickly than similar, existing techniques, which should allow for analyses of large samples of metal-poor stars in the near future. Steps to improve and correct the continuum placement difficulties are being pursued.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

Warehouse, PNG Coffee Industry Board Office and Warehouse, Goroka

View of exterior wall to warehouse.

Downpipes, PNG Coffee Industry Board Office and Warehouse, Goroka

Detailed view of downpipes and drainage grill.

PNG Coffee Industry Board Office and Warehouse, Goroka

View past tiered amphitheatre and offices above to air strip beyond.

View along western elevation, PNG Coffee Industry Board Office and Warehouse, Goroka

View past timber blinds to balcony and timber sunscreens.

Under construction, PNG Coffee Industry Board Office and Warehouse, Goroka

View of post being hoisted into position during construction.

Warehouse, PNG Coffee Industry Board Office and Warehouse, Goroka

View of warehouse exterior.

Pole detail, PNG Coffee Industry Board Office and Warehouse, Goroka

Detailed view of poles used in construction. Poles were spliced in their length with steel bars (like 3 pin plugs) and these joints were restrained from splitting with steel strap belts. The belts were tightened with opposing wedges like the old Greene & Greene wrought iron detail.

Warehouse, PNG Coffee Industry Board Office and Warehouse, Goroka

View of warehouse exterior.