5 resultados para Automatic control equipment industry.

em Helda - Digital Repository of University of Helsinki


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Printing papers have been the main product of the Finnish paper industry. To improve properties and economy of printing papers, controlling of tracheid cross-sectional dimensions and wood viscoelasticity are examined in this study. Controlling is understood as any procedure which yields raw material classes with distinct properties and small internal variation. Tracheid cross-sectional dimensions, i.e., cell wall thickness and radial and tangential diameters can be controlled with methods such as sorting wood into pulpwood and sawmill chips, sorting of logs according to tree social status and fractionation of fibres. These control methods were analysed in this study with simulations, which were based on measured tracheid cross-sectional dimensions. A SilviScan device was used to measure the data set from five Norway spruce (Picea abies) and five Scots pine (Pinus sylvestris) trunks. The simulation results indicate that the sawmill chips and top pulpwood assortments have quite similar cross-sectional dimensions. Norway spruce and Scots pine are on average also relatively similar in their cross-sectional dimensions. The distributions of these species are somewhat different, but from a practical point of view, the differences are probably of minor importance. The controlling of tracheid cross-sectional dimensions can be done most efficiently with methods that can separate fibres into earlywood and latewood. Sorting of logs or partitioning of logs into juvenile and mature wood were markedly less efficient control methods than fractionation of fibres. Wood viscoelasticity affects energy consumption in mechanical pulping, and is thus an interesting control target when improving energy efficiency of the process. A literature study was made to evaluate the possibility of using viscoelasticity in controlling. The study indicates that there is considerable variation in viscoelastic properties within tree species, but unfortunately, the viscoelastic properties of important raw material lots such as top pulpwood or sawmill chips are not known. Viscoelastic properties of wood depend mainly on lignin, but also on microfibrillar angle, width of cellulose crystals and tracheid cross-sectional dimensions.

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The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

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Corporate Social Responsibility (CSR) has become increasingly important topic in forest industries, and other global companies, in recent years. Globalisation, faster information delivery and demand for sustainable development have set new challenges for global companies in their business operations. Also the importance of stakeholder relations, and pressure to become more transparent has increased in the forest industries. Three dimensions of corporate responsibility economic, environmental and social, are often included in the concept of CSR. Global companies mostly claim that these dimensions are equally important. This study analyses CSR in forest industry and has focus on reporting and implementation of social responsibility in three international companies. These case-companies are Stora Enso, SCA and Sappi, and they have different geographical base, product portfolios and therefore present interesting differences about forest industry strategy and CSR. Global Reporting Initiative (GRI) has created the most known and used reporting framework in CSR reporting. GRI Guidelines have made CSR reporting a uniform function, which can also be measured between companies and different sectors. GRI Guidelines have also made it possible to record and control CSR data in the companies. In recent years the use of GRI Guidelines has increased substantially. Typically CSR reporting on economic and environmental responsibility have been systematic in the global companies and often driven by legistlation and other regulations. However the social responsibility has been less regulated and more difficult to compare. Therefore it has previously been often less focused in the CSR reporting of the global companies. The implementation and use of GRI Guidelines have also increased dialogue on social responsibility issues and stakeholder management in global companies. This study analyses the use of GRI´s framework in the forest industry companies´ CSR reporting. This is a qualitative study and the disclosure of data is empricially analysed using content analysis. Content analysis has been selected as a method for this study because it makes it possible to use different sources of information. The data of this study consists of existing academic literature of CSR, sustainability reports of thecase-companies during 2005-2009, and the semi-structured interviews with company representatives. Different sources provide the possibility to look at specific subject from more than one viewpoint. The results of the study show that all case-companies have relatively common themes in their CSR disclosure, and the differences rise mainly from their product-portfolios, and geographic base. Social impacts to local communities, in the CSR of the companies, were mainly dominated by issues concerning creating wealth to the society and impacting communities through creation of work. The comparability of the CSR reporting, and especially social indicators increased significally from 2007 onwards in all case-companies. Even though the companies claim that three dimensions of CSR economic, environmental and social are equally important economic issues and profit improvement still seem to drive most of the operations in the global companies. Many issues that are covered by laws and regulations are still essentially presented as social responsibility in CSR. However often the unwelcome issues in companies like closing operations are covered just briefly, and without adequate explanation. To make social responsibility equally important in the CSR it would demand more emphasis from all the case-companies. A lot of emphasis should be put especially on the detail and extensiveness of the social reponsibility content in the CSR.

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Listeria monocytogenes is the causative agent of the severe foodborne infection listeriosis. The number of listeriosis cases in recent years has increased in many European countries, including Finland. Contamination of the pathogen needs to be minimized and growth to high numbers in foods prevented in order to reduce the incidence of human cases. The aim of this study was to evaluate contamination routes of L. monocytogenes in the food chain and to investigate methods for control of the pathogen in food processing. L. monocytogenes was commonly found in wild birds, the pig production chain and in pork production plants. It was found most frequently in birds feeding at landfill site, organic farms, tonsil samples, and sites associated with brining. L. monococytogenes in birds, farms, food processing plant or foods did not form distinct genetic groups, but populations overlapped. The majority of genotypes recovered from birds were also detected in foods, food processing environments and other animal species and birds may disseminate L. monocytogenes into food chain. Similar genotypes were found in different pigs on the same farm, as well as in pigs on farms and later in the slaughterhouse. L. monocytogenes contamination spreads at farm level and may be a contamination source into slaughterhouses and further into meat. Incoming raw pork in the processing plant was frequently contaminated with L. monocytogenes and genotypes in raw meat were also found in processing environment and in RTE products. Thus, raw material seems to be a considerable source of contamination into processing facilities. In the pork processing plant, the prevalence of L. monocytogenes increased in the brining area, showing that the brining was an important contamination site. Recovery of the inoculated L. monocytogenes strains showed that there were strain-specific differences in the ability to survive in lettuce and dry sausage. The ability of some L. monocytogenes strains to survive well in food production raises a challenge for industry, because these strains can be especially difficult to remove from the products and raises a need to use an appropriate hurdle concept to control most resistant strains. Control of L. monocytogenes can be implemented throughout the food chain. Farm-specific factors affected the prevalence of L. monocytogenes and good farm-level practices can therefore be utilized to reduce the prevalence of this pathogen on the farm and possibly further in the food chain. Well separated areas in a pork production plant had low prevalences of L. monocytogenes, thus showing that compartmentalization controls the pathogen in the processing line. The food processing plant, especially the brining area, should be subjected to disassembling, extensive cleaning and disinfection to eliminate persistent contamination by L. monocytogenes, and replacing brining with dry-salting should be considered. All of the evaluated washing solutions decreased the populations of L. monocytogenes on precut lettuce, but did not eliminate the pathogen. Thus, the safety of fresh-cut produce cannot rely on washing with disinfectants, and high-quality raw material and good manufacturing practices remain important. L. monocytogenes was detected in higher levels in sausages without the protective culture than in sausages with this protective strain, although numbers of L. monocytogenes by the end of the ripening decreased to the level of < 100 MPN/g in all sausages. Protective starter cultures provide an appealing hurdle in dry sausage processing and assist in the control of L. monocytogenes.

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Human sport doping control analysis is a complex and challenging task for anti-doping laboratories. The List of Prohibited Substances and Methods, updated annually by World Anti-Doping Agency (WADA), consists of hundreds of chemically and pharmacologically different low and high molecular weight compounds. This poses a considerable challenge for laboratories to analyze for them all in a limited amount of time from a limited sample aliquot. The continuous expansion of the Prohibited List obliges laboratories to keep their analytical methods updated and to research new available methodologies. In this thesis, an accurate mass-based analysis employing liquid chromatography - time-of-flight mass spectrometry (LC-TOFMS) was developed and validated to improve the power of doping control analysis. New analytical methods were developed utilizing the high mass accuracy and high information content obtained by TOFMS to generate comprehensive and generic screening procedures. The suitability of LC-TOFMS for comprehensive screening was demonstrated for the first time in the field with mass accuracies better than 1 mDa. Further attention was given to generic sample preparation, an essential part of screening analysis, to rationalize the whole work flow and minimize the need for several separate sample preparation methods. Utilizing both positive and negative ionization allowed the detection of almost 200 prohibited substances. Automatic data processing produced a Microsoft Excel based report highlighting the entries fulfilling the criteria of the reverse data base search (retention time (RT), mass accuracy, isotope match). The quantitative performance of LC-TOFMS was demonstrated with morphine, codeine and their intact glucuronide conjugates. After a straightforward sample preparation the compounds were analyzed directly without the need for hydrolysis, solvent transfer, evaporation or reconstitution. The hydrophilic interaction technique (HILIC) provided good chromatographic separation, which was critical for the morphine glucuronide isomers. A wide linear range (50-5000 ng/ml) with good precision (RSD<10%) and accuracy (±10%) was obtained, showing comparable or better performance to other methods used. In-source collision-induced dissociation (ISCID) allowed confirmation analysis with three diagnostic ions with a median mass accuracy of 1.08 mDa and repeatable ion ratios fulfilling WADA s identification criteria. The suitability of LC-TOFMS for screening of high molecular weight doping agents was demonstrated with plasma volume expanders (PVE), namely dextran and hydroxyethylstarch (HES). Specificity of the assay was improved, since interfering matrix compounds were removed by size exclusion chromatography (SEC). ISCID produced three characteristic ions with an excellent mean mass accuracy of 0.82 mDa at physiological concentration levels. In summary, by combining TOFMS with a proper sample preparation and chromatographic separation, the technique can be utilized extensively in doping control laboratories for comprehensive screening of chemically different low and high molecular weight compounds, for quantification of threshold substances and even for confirmation. LC-TOFMS rationalized the work flow in doping control laboratories by simplifying the screening scheme, expediting reporting and minimizing the analysis costs. Therefore LC-TOFMS can be exploited widely in doping control, and the need for several separate analysis techniques is reduced.