Sales Forecasting e Demand Planning all'interno del processo di Sales & Operations Planning: il caso Cefla s.c.

Il presente elaborato di tesi è stato realizzato coerentemente con quanto osservato in Cefla s.c., azienda italiana composta attualmente da 4 Business Unit che operano a livello internazionale in settori distinti. I temi trattati riguardano nel dettaglio la Business Unit Medical Equipment, la quale realizza prodotti a supporto del professionista sanitario in tutte le fasi della sua attività, comprendendo riuniti odontoiatrici, apparecchiature per l’imaging e radiologia digitale e sistemi di sterilizzazione. L’obiettivo di questo elaborato è quello di descrivere l’attuale processo di Sales & Operations Planning all’interno di questa divisione dell’azienda e contribuire alla progettazione del piano per la sua strutturazione, reso necessario dalla situazione di forte criticità che Cefla s.c. è stata costretta ad affrontare. Vengono quindi descritte le problematiche che caratterizzano i processi interni all’azienda allo stato attuale, la cui valutazione è stata supportata da consulenti esterni, al fine di evidenziare gli aspetti più critici ed elaborare proposte di miglioramento. Queste ultime sono distinte in funzione delle diverse figure coinvolte che hanno contribuito alla loro realizzazione e ai sottoprocessi interessati e che costituiscono il Sales & Operations Planning: Sales Forecasting, Demand Planning e Supply Planning. In particolare, vengono approfonditi i processi che riguardano la previsione della domanda, in quanto per essi è stato possibile collaborare nell’elaborazione di proposte di miglioramento mirate. Visti i tempi medio lunghi che caratterizzano le soluzioni proposte all’azienda si è cercato di contribuire con la progettazione di proposte quick-win in ambito di Sales Forecasting e Demand Planning. Infine, si è tentato di quantificare i costi sostenuti da Cefla s.c. per far fronte alla situazione di criticità affrontata tramite valutazioni economiche e KPI, potendo così stimare l’impatto dato dall’implementazione di proposte di miglioramento.

Data analysis and hydrological modelling of rainfall and discharge extremes along the Tione River: implications for the design of water structures

There are many natural events that can negatively affect the urban ecosystem, but weather-climate variations are certainly among the most significant. The history of settlements has been characterized by extreme events like earthquakes and floods, which repeat themselves at different times, causing extensive damage to the built heritage on a structural and urban scale. Changes in climate also alter various climatic subsystems, changing rainfall regimes and hydrological cycles, increasing the frequency and intensity of extreme precipitation events (heavy rainfall).  From an hydrological risk perspective, it is crucial to understand future events that could occur and their magnitude in order to design safer infrastructures. Unfortunately, it is not easy to understand future scenarios as the complexity of climate is enormous.  For this thesis, precipitation and discharge extremes were primarily used as data sources. It is important to underline that the two data sets are not separated: changes in rainfall regime, due to climate change, could significantly affect overflows into receiving water bodies. It is imperative that we understand and model climate change effects on water structures to support the development of adaptation strategies.   The main purpose of this thesis is to search for suitable water structures for a road located along the Tione River. Therefore, through the analysis of the area from a hydrological point of view, we aim to guarantee the safety of the infrastructure over time.   The observations made have the purpose to underline how models such as a stochastic one can improve the quality of an analysis for design purposes, and influence choices.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

Estimativas de insegurança alimentar grave nos municípios Brasileiros

Prevalence of severe food insecurity was estimated for Brazilian municipalities based on the 2004 National Household Sample Survey (PNAD). First, a logistic regression model was developed and tested with this database. The model was then applied to the 2000 census data, generating severe food insecurity estimates for the Brazilian municipalities, which were subsequently analyzed according to the proportion of families exposed to severe food insecurity. Severe food insecurity was mainly concentrated in the North and Northeast regions, where 46.1% and 65.3% of municipalities showed high prevalence of severe food insecurity, respectively. Most municipalities in the Central West region showed intermediate prevalence of severe food insecurity. There was wide intra-regional variation in severe food insecurity, while the South of Brazil showed the most uniform distribution. In conclusion, Brazil displays wide inter and intra-regional variations in the occurrence of severe food insecurity. Such variations should be identified and analyzed in order to plan appropriate public policies.

Estimativas de insegurança alimentar grave nos municípios brasileiros

Estimou-se a prevalência de insegurança alimentar grave para os municípios brasileiros, com base na Pesquisa Nacional por Amostra de Domicílios (PNAD) 2004. Inicialmente, foi gerado e testado um modelo por regressão logística multivariada com base nesse banco de dados. O modelo foi aplicado à amostra do Censo Demográfico de 2000, gerando estimativas de prevalências de insegurança alimentar grave para os municípios brasileiros, que foram analisadas de acordo com o percentual de famílias em condição de insegurança alimentar grave. Essa insegurança alimentar está mais concentrada nas regiões Norte e Nordeste, onde 46,1 por cento e 65,3 por cento dos municípios, respectivamente, apresentam altas prevalências de insegurança alimentar grave. Predominam nas regiões Sudeste e Sul municípios com baixa exposição à insegurança alimentar grave. No Centro-oeste a maior parte dos municípios mostra estimativas de insegurança alimentar grave classificadas como médias. Verificou-se grande variação intra-regional na ocorrência da insegurança alimentar, sendo a Região Sul a mais uniforme. Conclui-se que o Brasil apresenta grandes variações inter e intra-regionais na ocorrência da insegurança alimentar, sendo importante realçá-las e analisá-las, no intuito de subsidiar políticas públicas

System Identification and Prediction of Dengue Fever Incidence in Rio de Janeiro

Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.

Methodology to forecast the harvest date of banana bunches

Introduction. This method is used to forecast the harvest date of banana bunches from as early as the plant shooting stage. It facilitates the harvest of bunches with the same physiological age. The principle, key advantages, time required and expected results are presented. Materials and methods. Details of the four steps of the method ( installation of the temperature sensor, tagging bunches at the flowering stage, temperature sum calculation and estimation of bunch harvest date) are described. Possible problems are discussed. Results. The application of the method allows drawing a curve of the temperature sum accumulated by the bunches which have to be harvested at exactly 900 degree-days physiological age.

Shallow landslide prediction in the Serra do Mar, Sao Paulo, Brazil

Various methods are currently used in order to predict shallow landslides within the catchment scale. Among them, physically based models present advantages associated with the physical description of processes by means of mathematical equations. The main objective of this research is the prediction of shallow landslides using TRIGRS model, in a pilot catchment located at Serra do Mar mountain range, Sao Paulo State, southeastern Brazil. Susceptibility scenarios have been simulated taking into account different mechanical and hydrological values. These scenarios were analysed based on a landslide scars map from the January 1985 event, upon which two indexes were applied: Scars Concentration (SC - ratio between the number of cells with scars, in each class, and the total number of cells with scars within the catchment) and Landslide Potential (LP - ratio between the number of cells with scars, in each class, and the total number of cells in that same class). The results showed a significant agreement between the simulated scenarios and the scar's map. In unstable areas (SF <= 1), the SC values exceeded 50% in all scenarios. Based on the results, the use of this model should be considered an important tool for shallow landslide prediction, especially in areas where mechanical and hydrological properties of the materials are not well known.

A possible role of ground-based microorganisms on cloud formation in the atmosphere

The formation of clouds is an important process for the atmosphere, the hydrological cycle, and climate, but some aspects of it are not completely understood. In this work, we show that microorganisms might affect cloud formation without leaving the Earth's surface by releasing biological surfactants (or biosurfactants) in the environment, that make their way into atmospheric aerosols and could significantly enhance their activation into cloud droplets. In the first part of this work, the cloud-nucleating efficiency of standard biosurfactants was characterized and found to be better than that of any aerosol material studied so far, including inorganic salts. These results identify molecular structures that give organic compounds exceptional cloud-nucleating properties. In the second part, atmospheric aerosols were sampled at different locations: a temperate coastal site, a marine site, a temperate forest, and a tropical forest. Their surface tension was measured and found to be below 30 mN/m, the lowest reported for aerosols, to our knowledge. This very low surface tension was attributed to the presence of biosurfactants, the only natural substances able to reach to such low values. The presence of strong microbial surfactants in aerosols would be consistent with the organic fractions of exceptional cloud-nucleating efficiency recently found in aerosols, and with the correlations between algae bloom and cloud cover reported in the Southern Ocean. The results of this work also suggest that biosurfactants might be common in aerosols and thus of global relevance. If this is confirmed, a new role for microorganisms on the atmosphere and climate could be identified.

Cloud condensation nuclei in pristine tropical rainforest air of Amazonia: size-resolved measurements and modeling of atmospheric aerosol composition and CCN activity

Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate. We have measured and characterized CCN at water vapor supersaturations in the range of S=0.10-0.82% in pristine tropical rainforest air during the AMAZE-08 campaign in central Amazonia. The effective hygroscopicity parameters describing the influence of chemical composition on the CCN activity of aerosol particles varied in the range of kappa approximate to 0.1-0.4 (0.16+/-0.06 arithmetic mean and standard deviation). The overall median value of kappa approximate to 0.15 was by a factor of two lower than the values typically observed for continental aerosols in other regions of the world. Aitken mode particles were less hygroscopic than accumulation mode particles (kappa approximate to 0.1 at D approximate to 50 nm; kappa approximate to 0.2 at D approximate to 200 nm), which is in agreement with earlier hygroscopicity tandem differential mobility analyzer (H-TDMA) studies. The CCN measurement results are consistent with aerosol mass spectrometry (AMS) data, showing that the organic mass fraction (f(org)) was on average as high as similar to 90% in the Aitken mode (D <= 100 nm) and decreased with increasing particle diameter in the accumulation mode (similar to 80% at D approximate to 200 nm). The kappa values exhibited a negative linear correlation with f(org) (R(2)=0.81), and extrapolation yielded the following effective hygroscopicity parameters for organic and inorganic particle components: kappa(org)approximate to 0.1 which can be regarded as the effective hygroscopicity of biogenic secondary organic aerosol (SOA) and kappa(inorg)approximate to 0.6 which is characteristic for ammonium sulfate and related salts. Both the size dependence and the temporal variability of effective particle hygroscopicity could be parameterized as a function of AMS-based organic and inorganic mass fractions (kappa(p)=kappa(org) x f(org)+kappa(inorg) x f(inorg)). The CCN number concentrations predicted with kappa(p) were in fair agreement with the measurement results (similar to 20% average deviation). The median CCN number concentrations at S=0.1-0.82% ranged from N(CCN,0.10)approximate to 35 cm(-3) to N(CCN,0.82)approximate to 160 cm(-3), the median concentration of aerosol particles larger than 30 nm was N(CN,30)approximate to 200 cm(-3), and the corresponding integral CCN efficiencies were in the range of N(CCN,0.10/NCN,30)approximate to 0.1 to N(CCN,0.82/NCN,30)approximate to 0.8. Although the number concentrations and hygroscopicity parameters were much lower in pristine rainforest air, the integral CCN efficiencies observed were similar to those in highly polluted megacity air. Moreover, model calculations of N(CCN,S) assuming an approximate global average value of kappa approximate to 0.3 for continental aerosols led to systematic overpredictions, but the average deviations exceeded similar to 50% only at low water vapor supersaturation (0.1%) and low particle number concentrations (<= 100 cm(-3)). Model calculations assuming aconstant aerosol size distribution led to higher average deviations at all investigated levels of supersaturation: similar to 60% for the campaign average distribution and similar to 1600% for a generic remote continental size distribution. These findings confirm earlier studies suggesting that aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the information and parameterizations presented in this paper should enable efficient description of the CCN properties of pristine tropical rainforest aerosols of Amazonia in detailed process models as well as in large-scale atmospheric and climate models.

FORAMINIFERAL RECORD OF CHANGES IN SUMMER MONSOON PRECIPITATION AT THE SOUTHEASTERN BRAZILIAN CONTINENTAL MARGIN SINCE THE LAST GLACIAL MAXIMUM

Changes in the oxygen isotopic composition of the planktonic foraminifer Globigerinoides ruber and in the foraminifera faunal composition in a core retrieved from the southeastern Brazilian continental margin were used to infer past changes in the hydrological balance and monsoon precipitation in the western South Atlantic since the Last Glacial Maximum (LGM). The results suggest a first-order orbital (precessional) control on the South American Monsoon precipitation. This agrees with previous studies based on continental proxies except for LGM estimates provided by pollen records. The causes for this disagreement are discussed.

Dissolved carbon in an urban area of a river in the Brazilian Amazon

The main objective of this study was to evaluate dissolved organic and inorganic carbon dynamics along upstream and downstream reaches of the Acre River draining the city of Rio Branco, in the state of Acre, Brazil. Dissolved organic carbon (DOC) concentrations in the Acre River were significantly higher during the wet season, ranging from 385 +/- A 160 to 430 +/- A 131 mu M among the stations, with no difference in upstream and downstream concentrations. Dissolved inorganic carbon (DIC) showed an inverse pattern, with higher concentrations in the dry season, ranging from 816 +/- A 215 to 998 +/- A 754 mu M among the stations, as well as no difference in upstream and downstream DIC concentrations. Bicarbonate was the dominant DIC fraction and was mainly observed during the dry season. Due to lower pH values during the wet season, CO(2) partial pressure (pCO(2)) in the Acre River was higher in the wet season, with values ranging from 4,567 +/- A 1,813 to 4,893 +/- A 837 ppm among the stations. Our results indicate that, although the Acre River drains a large city with significant sewage disposal into the river, seasonal hydrological processes are the main driver of dissolved carbon dynamics, even in the downstream study reach directly influenced by urbanization.

Effects of land cover on chemical characteristics of streams in the Cerrado region of Brazil

The Cerrado is the second largest Brazilian biome and contains the headwaters of three major hydrological basins in Brazil. In spite of the biological and ecological relevance of this biome, there is little information about how land use changes affect the chemistry of low-order streams in the Cerrado. To evaluate these effects streams that drain areas under natural, rural, and urban land cover were sampled near Brasilia, Brazil. Water samples were collected between September 2004 and December 2006. Chemical concentrations generally followed the pattern of Urban > Rural > Natural. Median conductivity of stream water of 21.6 (interquartile: 22.7) mu S/cm in urban streams was three and five-fold greater relative to rural and natural areas, respectively. In the wet season, despite of increasing discharge, concentration of many solutes were higher, particularly in rural and natural streams. Streams also presented higher total dissolved N (TDN) loads from natural to rural and urban although DIN:DON ratios did not differ significantly. In natural and urban streams TDN was 80 and 77% dissolved organic N, respectively. These results indicate that alterations in land cover from natural to rural and urban are changing stream water chemistry in the Cerrado with increasing solute concentrations, in addition to increased TDN output in areas under urban cover, with potential effects on ecosystem function.

Integrating technology roadmapping and portfolio management at the front-end of new product development

Many authors point out that the front-end of new product development (NPD) is a critical success factor in the NPD process and that numerous companies face difficulties in carrying it out appropriately. Therefore, it is important to develop new theories and proposals that support the effective implementation of this earliest phase of NPD. This paper presents a new method to support the development of front-end activities based on integrating technology roadmapping (TRM) and project portfolio management (PPM). This new method, called the ITP Method, was implemented at a small Brazilian high-tech company in the nanotechnology industry to explore the integration proposal. The case study demonstrated that the ITP Method provides a systematic procedure for the fuzzy front-end and integrates innovation perspectives into a single roadmap, which allows for a better alignment of business efforts and communication of product innovation goals. Furthermore, the results indicated that the method may also improve quality, functional integration and strategy alignment. (C) 2010 Elsevier Inc. All rights reserved.

Rotifer abundance, biomass, and secondary production after the recovery of hydrologic connectivity between a river and two marginal lakes (Sao Paulo, Brazil)

Rotifera density, biomass, and secondary production on two marginal lakes of Paranapanema River were compared after the recovery of hydrologic connectivity with the river (Sao Paulo State, Brazil). Daily samplings were performed in limnetic zone of both lakes during the rainy season immediately after lateral inflow of water and, in the dry period, six months after hydrologic connectivity recovery. In order to identify the factors that affect rotifer population dynamics, lake water level, volume, depth, temperature, transparency, dissolved oxygen, pH, alkalinity, conductivity, suspended solids, nutrients, and chlorophyll-a were determined. Variations of water physical and chemical factors that affect rotifer population were related to the lake-river degree of connection and to water level rising after drought. The water lateral inflow from the river resulted in an increase in lake water volume, depth, and transparency and a decrease in water pH, alkalinity, and suspended solids. The lake with the wider river connection, more frequent biota exchange, and larger amount of particulate and dissolved materials was richer and more diverse, while rotifer density, biomass, and productivity were lower in both periods studied. Density, biomass, and secondary production were higher in the lake with the smaller river connection and the higher physical and chemical stability. Our results show that the connectivity affects the limnological stability, associated to seasonality. Stable conditions, caused by low connectivity in dry periods, were related with high density, biomass and secondary production. Conversely, instability conditions in rainy periods were associated to elevated richness and diversity values, caused by exchange biota due to higher connectivity. (C) 2008 Elsevier GmbH. All rights reserved.