Item-level life-cycle model for maintenance network – from cost to additional value

The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

Value creation in intelligent packaging value chains

The goal of this thesis is to look for and point out problems and bottlenecks related to value chains and networks in initiation and implementation of intelligent packaging. The research is based on interviews in different case companies and is qualitative by nature. The interview results are examined through a framework built upon relevant theory, with the aim to present a useful recommendation for a supplier company for advancing intelligent packaging business. The perspective that is attained through the research questions demonstrates the potential customer companies’ views of possibilities and problems. The key results suggest that intellectual property of relevant products is in an important position from the customers’ perspective. If the supplier does not own a product technology, a sufficiently large company can consider working as an integrator in a network where smaller companies make use of a compiled offering from other smaller actors. The foundation for these networks and company relationships is value creation, which has to be based on profound customer knowledge and research. The framework that is created for this study builds upon earlier research to provide a model that better serves intelligent packaging implementation and includes the notion of importance of value proposition and continuous value co-creation.

The Transformation Problem : an Aleternative Solution with an Identical Aggregate Profit Rate in the Labor value and the Monetary Space.

The aim of this paper is to demonstrate that, even if Marx's solution to the transformation problem can be modified, his basic conclusions remain valid. the proposed alternative solution which is presented hare is based on the constraint of a common general profit rate in both spaces and a money wage level which will be determined simultaneously with prices.

The Transformation Problem : an Aleternative Solution with an Identical Aggregate Profit Rate in the Labor value and the Monetary Space.

The aim of this paper is to demonstrate that, even if Marx's solution to the transformation problem can be modified, his basic conclusions remain valid. the proposed alternative solution which is presented hare is based on the constraint of a common general profit rate in both spaces and a money wage level which will be determined simultaneously with prices.

Carboxydothermus hydrogenoformans comme catalyseur biologique pour la conversion du monoxyde de carbone en hydrogène simultanément a la minéralisation de calcium et phosphate

La gazéification est aujourd'hui l'une des stratégies les plus prometteuses pour valoriser les déchets en énergie. Cette technologie thermo-chimique permet une réduction de 95 % de la masse des intrants et génère des cendres inertes ainsi que du gaz de synthèse (syngaz). Le syngaz est un combustible gazeux composé principalement de monoxyde de carbone (CO), d'hydrogène (H2) et de dioxyde de carbone (CO2). Le syngaz peut être utilisé pour produire de la chaleur et de l'électricité. Il est également la pierre angulaire d'un grand nombre de produits à haute valeur ajoutée, allant de l'éthanol à l'ammoniac et l'hydrogène pur. Les applications en aval de la production de syngaz sont dictées par son pouvoir calorifique, lui-même dépendant de la teneur du gaz en H2. L’augmentation du contenu du syngaz en H2 est rendu possible par la conversion catalytique à la vapeur d’eau, largement répandu dans le cadre du reformage du méthane pour la production d'hydrogène. Au cours de cette réaction, le CO est converti en H2 et CO2 selon : CO + H2O → CO2 + H2. Ce processus est possible grâce à des catalyseurs métalliques mis en contact avec le CO et de la vapeur. La conversion catalytique à la vapeur d’eau a jusqu'ici été réservé pour de grandes installations industrielles car elle nécessite un capital et des charges d’exploitations très importantes. Par conséquent, les installations de plus petite échelle et traitant des intrants de faible qualité (biomasse, déchets, boues ...), n'ont pas accès à cette technologie. Ainsi, la seule utilisation de leur syngaz à faible pouvoir calorifique, est limitée à la génération de chaleur ou, tout au plus, d'électricité. Afin de permettre à ces installations une gamme d’application plus vaste de leurs syngaz, une alternative économique à base de catalyseur biologique est proposée par l’utilisation de bactéries hyperthermophiles hydrogénogènes. L'objectif de cette thèse est d'utiliser Carboxydothermus hydrogenoformans, une bactérie thermophile carboxydotrophe hydrogénogène comme catalyseur biologique pour la conversion du monoxyde de carbone en hydrogène. Pour cela, l’impact d'un phénomène de biominéralisation sur la production d’H2 a été étudié. Ensuite, la faisabilité et les limites de l’utilisation de la souche dans un bioréacteur ont été évaluées. Tout d'abord, la caractérisation de la phase inorganique prédominante lorsque C. hydrogenoformans est inoculé dans le milieu DSMZ, a révélé une biominéralisation de phosphate de calcium (CaP) cristallin en deux phases. L’analyse par diffraction des rayons X et spectrométrie infrarouge à transformée de Fourier de ce matériau biphasique indique une signature caractéristique de la Mg-whitlockite, alors que les images obtenues par microscopie électronique à transmission ont montré l'existence de nanotiges cristallines s’apparentant à de l’hydroxyapatite. Dans les deux cas, le mode de biominéralisation semble être biologiquement induit plutôt que contrôlé. L'impact du précipité de CaP endogène sur le transfert de masse du CO et la production d’H2 a ensuite été étudié. Les résultats ont été comparés aux valeurs obtenues dans un milieu où aucune précipitation n'est observée. Dans le milieu DSMZ, le KLa apparent (0.22 ± 0.005 min-1) et le rendement de production d’H2 (89.11 ± 6.69 %) étaient plus élevés que ceux obtenus avec le milieu modifié (0.19 ± 0.015 min-1 et 82.60 ± 3.62% respectivement). La présence du précipité n'a eu aucune incidence sur l'activité microbienne. En somme, le précipité de CaP offre une nouvelle stratégie pour améliorer les performances de transfert de masse du CO en utilisant les propriétés hydrophobes de gaz. En second lieu, la conversion du CO en H2 par la souche Carboxydothermus hydrogenoformans fut étudiée et optimisée dans un réacteur gazosiphon de 35 L. Parmi toutes les conditions opérationnelles, le paramètre majeur fut le ratio du débit de recirculation du gaz sur le débit d'alimentation en CO (QR:Qin). Ce ratio impacte à la fois l'activité biologique et le taux de transfert de masse gaz-liquide. En effet, au dessus d’un ratio de 40, les performances de conversion du CO en H2 sont limitées par l’activité biologique alors qu’en dessous, elles sont limitées par le transfert de masse. Cela se concrétise par une efficacité de conversion maximale de 90.4 ± 0.3 % et une activité spécifique de 2.7 ± 0.4 molCO·g–1VSS·d–1. Malgré des résultats prometteurs, les performances du bioréacteur ont été limitées par une faible densité cellulaire, typique de la croissance planctonique de C. hydrogenoformans. Cette limite est le facteur le plus contraignant pour des taux de charge de CO plus élevés. Ces performances ont été comparées à celles obtenues dans un réacteur à fibres creuses (BRFC) inoculé par la souche. En dépit d’une densité cellulaire et d’une activité volumétrique plus élevées, les performances du BRFC à tout le moins cinétiquement limitées quand elles n’étaient pas impactées par le transfert de masse, l'encrassement et le vieillissement de la membrane. Afin de parer à la dégénérescence de C. hydrogenoformans en cas de pénurie de CO, la croissance de la bactérie sur pyruvate en tant que seule source de carbone a été également caractérisée. Fait intéressant, en présence simultanée de pyruvate et de CO, C. hydrogenoformans n’a amorcé la consommation de pyruvate qu’une fois le CO épuisé. Cela a été attribué à un mécanisme d'inhibition du métabolisme du pyruvate par le CO, faisant ainsi du pyruvate le candidat idéal pour un système in situ de secours.

First principles LDA+U and GGA+U study of cerium oxides: Dependence on the effective U-parameter

The electronic structure and properties of cerium oxides (CeO2 and Ce2O3) have been studied in the framework of the LDA+U and GGA(PW91)+U implementations of density functional theory. The dependence of selected observables of these materials on the effective U parameter has been investigated in detail. The examined properties include lattice constants, bulk moduli, density of states, and formation energies of CeO2 and Ce2O3. For CeO2, the LDA+U results are in better agreement with experiment than the GGA+U results whereas for the computationally more demanding Ce2O3 both approaches give comparable accuracy. Furthermore, as expected, Ce2O3 is much more sensitive to the choice of the U value. Generally, the PW91 functional provides an optimal agreement with experiment at lower U energies than LDA does. In order to achieve a balanced description of both kinds of materials, and also of nonstoichiometric CeO2¿x phases, an appropriate choice of U is suggested for LDA+U and GGA+U schemes. Nevertheless, an optimum value appears to be property dependent, especially for Ce2O3. Optimum U values are found to be, in general, larger than values determined previously in a self-consistent way.

Auf Basis umfangreicher Messdatensätze experimentell und numerisch validierte Regeln zur optimierten Auslegung von Luft-Erdwärmetauschern

Ein Luft-Erdwärmetauscher (L-EWT) kommt wegen seines niedrigen Energiebedarfs und möglicher guter Aufwandszahlen als umweltfreundliche Versorgungskomponente für Gebäude in Betracht. Dabei ist besonders vorteilhaft, dass ein L-EWT die Umgebungsluft je nach Jahreszeit vorwärmen oder auch kühlen kann. Dem zufolge sind L-EWT zur Energieeinsparung nicht nur für den Wohnhausbau interessant, sondern auch dort, wo immer noch große Mengen an fossiler Energie für die Raumkühlung benötigt werden, im Büro- und Produktionsgebäudesektor. Der Einsatzbereich eines L-EWT liegt zwischen Volumenströmen von 100 m3/h und mehreren 100.000 m3/h. Aus dieser Bandbreite und den instationären Randbedingungen entstehen erhebliche Schwierigkeiten, allgemeingültige Aussagen über das zu erwartende thermische Systemverhalten aus der Vielzahl möglicher Konstruktionsvarianten zu treffen. Hauptziel dieser Arbeit ist es, auf Basis umfangreicher, mehrjähriger Messungen an einer eigens konzipierten Testanlage und eines speziell angepassten numerischen Rechenmodells, Kennzahlen zu entwickeln, die es ermöglichen, die Betriebseigenschaften eines L-EWT im Planungsalltag zu bestimmen und ein technisch, ökologisch wie ökonomisch effizientes System zu identifizieren. Es werden die Kennzahlen elewt (Aufwandszahl), QV (Netto-Volumenleistung), ME (Meterertrag), sowie die Kombination aus v (Strömungsgeschwindigkeit) und VL (Metervolumenstrom) definiert, die zu wichtigen Informationen führen, mit denen die Qualität von Systemvarianten in der Planungsphase bewertet werden können. Weiterführende Erkenntnisse über die genauere Abschätzung von Bodenkennwerten werden dargestellt. Die hygienische Situation der durch den L-EWT transportierten Luft wird für die warme Jahreszeit, aufgrund auftretender Tauwasserbildung, beschrieben. Aus diesem Grund werden alle relevanten lufthygienischen Parameter in mehreren aufwendigen Messkampagnen erfasst und auf pathogene Wirkungen überprüft. Es wird über Sensitivitätsanalysen gezeigt, welche Fehler bei Annahme falscher Randbedingungen eintreten. Weiterhin werden in dieser Arbeit wesentliche, grundsätzliche Erkenntnisse aufbereitet, die sich aus der Betriebsbeobachtung und der Auswertung der umfangreich vorliegenden Messdaten mehrerer Anlagen ergeben haben und für die praktische Umsetzung und die Betriebsführung bedeutend sind. Hinweise zu Materialeigenschaften und zur Systemwirtschaftlichkeit sind detailliert aufgeführt.

Hyperspectral field measurements to determine dry matter yield and nutritive value of legume-grass swards

Summary: Productivity, botanical composition and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. As these attributes can vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate a more targeted management of crops, forage and nutrients in the soil-plant-animal system. This study was undertaken to explore the potential of field spectral measurements for a non destructive prediction of dry matter (DM) yield, legume proportion in the sward, metabolizable energy (ME), ash content, crude protein (CP) and acid detergent fiber (ADF) of legume-grass mixtures. Two experiments were conducted in a greenhouse under controlled conditions which allowed collecting spectral measurements which were free from interferences such as wind, passing clouds and changing angles of solar irradiation. In a second step this initial investigation was evaluated in the field by a two year experiment with the same legume-grass swards. Several techniques for analysis of the hyperspectral data set were examined in this study: four vegetation indices (VIs): simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP), two-waveband reflectance ratios, modified partial least squares (MPLS) regression and stepwise multiple linear regression (SMLR). The results showed the potential of field spectroscopy and proved its usefulness for the prediction of DM yield, ash content and CP across a wide range of legume proportion and growth stage. In all investigations prediction accuracy of DM yield, ash content and CP could be improved by legume-specific calibrations which included mixtures and pure swards of perennial ryegrass and of the respective legume species. The comparison between the greenhouse and the field experiments showed that the interaction between spectral reflectance and weather conditions as well as incidence angle of light interfered with an accurate determination of DM yield. Further research is hence needed to improve the validity of spectral measurements in the field. Furthermore, the developed models should be tested on varying sites and vegetation periods to enhance the robustness and portability of the models to other environmental conditions.

Alternative plant protein sources for pigs and chickens in the tropics – nutritional value and constraints: a review

In the tropics, a large number of smallholder farms contribute significantly to food security by raising pigs and poultry for domestic consumption and for sale on local markets. The high cost and, sometimes, the lack of availability of commercial protein supplements is one of the main limitations to efficient animal production by smallholders. Locally-grown forages and grain legumes offer ecological benefits such as nitrogen fixation, soil improvement, and erosion control which contribute to improve cropping efficiency. Besides these agronomical assets, they can be used as animal feeds in mixed farming systems. In this paper we review options to include locally-grown forages and grain legumes as alternative protein sources in the diets of pigs and poultry in order to reduce farmers’ dependence on externally-purchased protein concentrates. The potential nutritive value of a wide range of forages and grain legumes is presented and discussed. The influence of dietary fibre and plant secondary metabolites contents and their antinutritive consequences on feed intake, digestive processes and animal performances are considered according to the varying composition in those compounds of the different plant species and cultivars covered in this review. Finally, methods to overcome the antinutritive attributes of the plant secondary metabolites using heat, chemical or biological treatment are reviewed regarding their efficiency and their suitability in low input farming systems.

Validación diagnóstica del test neural 1 para el síndrome de túnel del carpo

El objetivo de este estudio fue realizar una prueba de validez diagnostica del test neural 1 para el diagnóstico del Síndrome de Túnel del Carpo (STC) utilizando como prueba de referencia o de oro el test de conducción nerviosa. En este estudio participaron 115 sujetos, 230 manos con sospecha clínica de STC quienes fueron evaluados con el test de conducción nerviosa y el test neural 1. Se encontró una sensibilidad del 93.0% (IC 95%:88,21-96,79) y una especificidad del 6,67% (IC 95%:0,0-33,59), razón de verosimilitud positiva fue de 1,00 y razón de verosimilitud negativa de 1,05. Valor predictivo positivo de 86,9% y un valor predictivo negativo de 12,5%. Se concluye que el test neural 1 es una prueba clínica de alta sensibilidad y baja especificidad de gran utilidad para el monitoreo e identificación del STC. Es un procedimiento para el diagnóstico clínico de bajo costo que puede incluirse en los exámenes de rutina de los trabajadores como complemento a las pruebas clínicas sugeridas por las Gatiso para dar mayor precisión a la identificación temprana del STC. Se sugiere combinarla con otros test de mayor especificidad para ser aplicada en trabajadores en condiciones de riesgo o que presenten síntomas en miembros superiores y realizar otros estudios en donde participen sujetos sin diagnóstico clínico del STC.

Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Dual technological development in Botswana agriculture: A Stochastic input distance function approach

To improve the welfare of the rural poor and keep them in the countryside, the government of Botswana has been spending 40% of the value of agricultural GDP on agricultural support services. But can investment make smallholder agriculture prosperous in such adverse conditions? This paper derives an answer by applying a two-output six-input stochastic translog distance function, with inefficiency effects and biased technical change to panel data for the 18 districts and the commercial agricultural sector, from 1979 to 1996 This model demonstrates that herds are the most important input, followed by draft power. land and seeds. Multilateral indices for technical change, technical efficiency and total factor productivity (TFP) show that the technology level of the commercial agricultural sector is more than six times that of traditional agriculture and that the gap has been increasing, due to technological regression in traditional agriculture and modest progress in commercial agriculture. Since the levels of efficiency are similar, the same patient is repeated by the TFP indices. This result highlights the policy dilemma of the trade-off between efficiency and equity objectives.