Drivers and Barriers of Collaboration in the Value Chain of Paperboard-Packed Consumer Goods

Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.

The Importance of Semantics: Visual World Studies on Drawing Inferences and Resolving Anaphors

The present thesis investigated the importance of semantics in generating inferences during discourse processing. Three aspects of semantics, gender stereotypes, implicit causality information and proto-role properties, were used to investigate whether semantics is activated elaboratively during discourse comprehension and what its relative importance is in backward inferencing compared to discourse/structural cues. Visual world eye-tracking studies revealed that semantics plays an important role in both backward and forward inferencing: Gender stereotypes and implicit causality information is activated elaboratively during online discourse comprehension. Moreover, gender stereotypes, implicit causality and proto-role properties of verbs are all used in backward inferencing. Importantly, the studies demonstrated that semantic cues are weighed against discourse/structural cues. When the structural cues consist of a combination of cues that have been independently shown to be important in backward inferencing, semantic effects may be masked, whereas when the structural cues consist of a combination of fewer prominent cues, semantics can have an earlier effect than structural factors in pronoun resolution. In addition, the type of inference matters, too: During anaphoric inferencing semantics has a prominent role, while discourse/structural salience attains more prominence during non-anaphoric inferencing. Finally, semantics exhibits a strong role in inviting new inferences to revise earlier made inferences even in the case the additional inference is not needed to establish coherence in discourse. The findings are generally in line with the Mental Model approaches. Two extended model versions are presented that incorporate the current findings into the earlier literature. These models allow both forward and backward inferencing to occur at any given moment during the course of processing; they also allow semantic and discourse/structural cues to contribute to both of these processes. However, while the Mental Model 1 does not assume interactions between semantic and discourse/structural factors in forward inferencing, the Mental Model 2 does assume such a link.

Induction Motor Drive Energy Efficiency - Simulation and Analysis

A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.

Tutorials for MeVEA Simulation Software

The objective of the thesis was to create three tutorials for MeVEA Simulation Software to instruct the new users to the modeling methodology used in the MeVEA Simulation Software. MeVEA Simulation Software is a real-time simulation software based on multibody dynamics. The simulation software is designed to create simulation models of complete mechatronical system. The thesis begins with a more detail description of the MeVEA Simulation Software and its components. The thesis presents the three simulation models and written theory of the steps of model creation. The first tutorial introduces the basic features which are used in most simulation models. The basic features include bodies, constrains, forces, basic hydraulics and motors. The second tutorial introduces the power transmission components, tyres and user input definitions for the different components in power transmission systems. The third tutorial introduces the definitions of two different types of collisions and collision graphics used in MeVEA Simulation Software.

ALLOMETRIC MODELS FOR ESTIMATING ABOVEGROUND BIOMASS AND BIOMASS ALLOCATION OF CAPIXINGUI TREES (Croton floribundus Spreng.) IN AN AGRISILVICULTURAL SYSTEM

ABSTRACT The objective of this study was to select allometric models to estimate total and pooled aboveground biomass of 4.5-year-old capixingui trees established in an agrisilvicultural system. Aboveground biomass distribution of capixingui was also evaluated. Single- (diameter at breast height [DBH] or crown diameter or stem diameter as the independent variable) and double-entry (DBH or crown diameter or stem diameter and total height as independent variables) models were studied. The estimated total biomass was 17.3 t.ha-1, corresponding to 86.6 kg per tree. All models showed a good fit to the data (R2ad > 0.85) for bole, branches, and total biomass. DBH-based models presented the best residual distribution. Model lnW = b0 + b1* lnDBH can be recommended for aboveground biomass estimation. Lower coefficients were obtained for leaves (R2ad > 82%). Biomass distribution followed the order: bole>branches>leaves. Bole biomass percentage decreased with increasing DBH of the trees, whereas branch biomass increased.

Thermal comfort in reduced models of broilers' houses, under different types of roofing materials

The research was developed to evaluate the use of different types of roofing materials regularly used in poultry houses. Measurements of thermal comfort were made through the use of techniques such as the Black Globe and Humidity Index (BGHI), the Thermal Heat Load (THL) and Enthalpy (H). Conducted in the State University of Goiás, during the months of April and May, 2011, the experiment was composed of five different treatments: AC - Asbestos cement tiles, BA -Bamboo tiles, BAP - Bamboo tiles painted in white, FB -Vegetable fiber tiles and bitumen, FBP -Vegetable fiber tiles and bitumen painted in white. The experiment consisted in 15 repetitions, which were considered the different days of measurements taken. Throughout the studied period, the time of the day considered the least comfortable was the one observed at 2:00pm, and the coverage of vegetable fiber and bitumen showed the highest value of BGHI (84.1) when compared to other types of coverage, characterizing a situation of lower thermal comfort, and no difference was found for THL and H on treatments in the studied region.

Simulation of structural stress history based on dynamic analysis

Modern machine structures are often fabricated by welding. From a fatigue point of view, the structural details and especially, the welded details are the most prone to fatigue damage and failure. Design against fatigue requires information on the fatigue resistance of a structure’s critical details and the stress loads that act on each detail. Even though, dynamic simulation of flexible bodies is already current method for analyzing structures, obtaining the stress history of a structural detail during dynamic simulation is a challenging task; especially when the detail has a complex geometry. In particular, analyzing the stress history of every structural detail within a single finite element model can be overwhelming since the amount of nodal degrees of freedom needed in the model may require an impractical amount of computational effort. The purpose of computer simulation is to reduce amount of prototypes and speed up the product development process. Also, to take operator influence into account, real time models, i.e. simplified and computationally efficient models are required. This in turn, requires stress computation to be efficient if it will be performed during dynamic simulation. The research looks back at the theoretical background of multibody dynamic simulation and finite element method to find suitable parts to form a new approach for efficient stress calculation. This study proposes that, the problem of stress calculation during dynamic simulation can be greatly simplified by using a combination of floating frame of reference formulation with modal superposition and a sub-modeling approach. In practice, the proposed approach can be used to efficiently generate the relevant fatigue assessment stress history for a structural detail during or after dynamic simulation. In this work numerical examples are presented to demonstrate the proposed approach in practice. The results show that approach is applicable and can be used as proposed.

Qualitative Characteristics and Quantitative Measures of Solution's Reliability in Discrete Optimization: Traditional Analytical Approaches, Innovative Computational Methods and Applicability

The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

PET Imaging of Osteomyelitis. Feasibility of 18F-FDG, 68Ga-Chloride and 68Ga-DOTAVAP-P1 Tracers in Staphylococcal Bone Infections

Due to technical restrictions of the database system the title of the thesis does not show corretly on this page. Numbers in the title are in superscript. Please see the PDF-file for correct title. ---- Osteomyelitis is a progressive inflammatory disease of bone and bone marrow that results in bone destruction due to an infective microorganism, most frequently Staphylococcus aureus. Orthopaedic concern relates to the need for reconstructive and trauma-related surgical procedures in the fast grow¬ing population of fragile, aged patients, who have an increased susceptibility to surgical site infections. Depending on the type of osteomyelitis, infection may be acute or a slowly progressing, low-grade infection. Peri-implant infections lead to implant loosening. The emerging antibiotic resistance of com¬mon pathogens further complicates the situation. With current imaging methods, significant limitations exist in the diagnosing of osteomyelitis and implant-related infections. Positron emission tomography (PET) with a glucose analogue, 18F-fluoro¬deoxyglucose (18F-FDG), seems to facilitate a more accurate diagnosis of chronic osteomyelitis. The method is based on the increased glucose consumption of activated inflammatory cells. Unfortunately, 18F-FDG accumulates also in sterile inflammation regions and causes false-positive findings, for exam¬ple, due to post-operative healing processes. Therefore, there is a clinical need for new, more infection-specific tracers. In addition, it is still unknown why 18F-FDG PET imaging is less accurate in the detec¬tion of periprosthetic joint infections, most frequently due to Staphylococcus epidermidis. This doctoral thesis focused on testing novel PET tracers (68Ga-chloride and 68Ga-DOTAVAP-P1) for early detections of bone infections and evaluated the role of pathogen-related factors in the appli¬cations of 18F-FDG PET in the diagnostics of bone infections. For preclinical models of S. epidermidis and S. aureus bone/implant infections, the significance of the causative pathogen was studied with respect to 18F-FDG uptake. In a retrospective analysis of patients with confirmed bone infections, the significance of the presence or absence of positive bacterial cultures on 18F-FDG uptake was evalu¬ated. 18F-FDG and 68Ga-chloride resulted in a similar uptake in S. aureus osteomyelitic bones. However, 68Ga-chloride did not show uptake in healing bones, and therefore it may be a more-specific tracer in the early post-operative or post-traumatic phase. 68Ga-DOTAVAP-P1, a novel synthetic peptide bind¬ing to vascular adhesion protein 1 (VAP-1), was able to detect the phase of inflammation in healing bones, but the uptake of the tracer was elevated also in osteomyelitis. Low-grade peri-implant infec¬tions due to S. epidermidis were characterized by a low uptake of 18F-FDG, which reflects the virulence of the causative pathogen and the degree of leukocyte infiltration. In the clinical study, no relationship was found between the level of 18F-FDG uptake and the presence of positive or negative bacterial cul¬tures. Thus 18F-FDG PET may help to confirm metabolically active infection process in patients with culture-negative, histologically confirmed, low-grade osteomyelitis.

The key practices of customer portfolio management (CPM) process in the medical and healthcare B2B industry

The goal of this study is to deepen the understanding of the customer portfolio management process. There are many models for the process, and they are not necessarily exclusive of each other. Consequently, the inclusion of many models might even prove out to be beneficial. Other theoretical framework include the current economical situation and its propose on customer portfolio management. With an understanding of the theoretical models as a background, the empirical part of this study compares Finnish multinational medical and healthcare technology companies’ customer portfolio management practices. The empirical research was carried out with theme interviews held with 11 sales and marketing managers or directors from four different companies. The goal was to discover the most essential practices of the process steps in the companies. The result of this study is that there is a lack of systematic customer portfolio management, but most companies are aiming to improve this in the near future. The most essential practices are analysis of sales, communication level, learning, and commitment to strategy of the focal company. Special characteristics of this industry include large business networks that include customers, professional end-users, institutions, universities, researchers, and key opinion leaders. The management and analysis of this comprehensive network has been seen to be extremely important for this industry.

Dynamics of coherent vortices in mixing layers using direct numerical and large-eddy simulations

Coherent vortices in turbulent mixing layers are investigated by means of Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES). Subgrid-scale models defined in spectral and physical spaces are reviewed. The new "spectral-dynamic viscosity model", that allows to account for non-developed turbulence in the subgrid-scales, is discussed. Pseudo-spectral methods, combined with sixth-order compact finite differences schemes (when periodic boundary conditions cannot be established), are used to solve the Navier- Stokes equations. Simulations in temporal and spatial mixing layers show two types of pairing of primary Kelvin-Helmholtz (KH) vortices depending on initial conditions (or upstream conditions): quasi-2D and helical pairings. In both cases, secondary streamwise vortices are stretched in between the KH vortices at an angle of 45° with the horizontal plane. These streamwise vortices are not only identified in the early transitional stage of the mixing layer but also in self-similar turbulence conditions. The Re dependence of the "diameter" of these vortices is analyzed. Results obtained in spatial growing mixing layers show some evidences of pairing of secondary vortices; after a pairing of the primary Kelvin-Helmholtz (KH) vortices, the streamwise vortices are less numerous and their diameter has increased than before the pairing of KH vortices.

Numerical Simulation of Stochastic Di erential Equations

Stochastic differential equation (SDE) is a differential equation in which some of the terms and its solution are stochastic processes. SDEs play a central role in modeling physical systems like finance, Biology, Engineering, to mention some. In modeling process, the computation of the trajectories (sample paths) of solutions to SDEs is very important. However, the exact solution to a SDE is generally difficult to obtain due to non-differentiability character of realizations of the Brownian motion. There exist approximation methods of solutions of SDE. The solutions will be continuous stochastic processes that represent diffusive dynamics, a common modeling assumption for financial, Biology, physical, environmental systems. This Masters' thesis is an introduction and survey of numerical solution methods for stochastic differential equations. Standard numerical methods, local linearization methods and filtering methods are well described. We compute the root mean square errors for each method from which we propose a better numerical scheme. Stochastic differential equations can be formulated from a given ordinary differential equations. In this thesis, we describe two kind of formulations: parametric and non-parametric techniques. The formulation is based on epidemiological SEIR model. This methods have a tendency of increasing parameters in the constructed SDEs, hence, it requires more data. We compare the two techniques numerically.

Warranty Prediction Using Weibull Simulation

The main objective of this master’s thesis is to examine if Weibull analysis is suitable method for warranty forecasting in the Case Company. The Case Company has used Reliasoft’s Weibull++ software, which is basing on the Weibull method, but the Company has noticed that the analysis has not given right results. This study was conducted making Weibull simulations in different profit centers of the Case Company and then comparing actual cost and forecasted cost. Simula-tions were made using different time frames and two methods for determining future deliveries. The first sub objective is to examine, which parameters of simulations will give the best result to each profit center. The second sub objective of this study is to create a simple control model for following forecasted costs and actual realized costs. The third sub objective is to document all Qlikview-parameters of profit centers. This study is a constructive research, and solutions for company’s problems are figured out in this master’s thesis. In the theory parts were introduced quality issues, for example; what is quality, quality costing and cost of poor quality. Quality is one of the major aspects in the Case Company, so understand-ing the link between quality and warranty forecasting is important. Warranty management was also introduced and other different tools for warranty forecasting. The Weibull method and its mathematical properties and reliability engineering were introduced. The main results of this master’s thesis are that the Weibull analysis forecasted too high costs, when calculating provision. Although, some forecasted values of profit centers were lower than actual values, the method works better for planning purposes. One of the reasons is that quality improving or alternatively quality decreasing is not showing in the results of the analysis in the short run. The other reason for too high values is that the products of the Case Company are com-plex and analyses were made in the profit center-level. The Weibull method was developed for standard products, but products of the Case Company consists of many complex components. According to the theory, this method was developed for homogeneous-data. So the most im-portant notification is that the analysis should be made in the product level, not the profit center level, when the data is more homogeneous.

Exploring the Impact of Mental Health Education on Adolescents’ Perceptions About Mental Health and Mental Illness. Improving community health

The purpose of this study was to explore perceptions of mental health and mental illness as well as the perceptions towards people with mental illness among adolescents, and further to examine the impact that a mental health educational intervention has on these perceptions. The review of the literature revealed a small number of publications on mental health educational interventions among adolescents which aimed at increasing knowledge and affecting attitudes towards mental illness with positive results. Fifty nine pupils (13-16 years old) from two randomly selected secondary schools around Athens, Greece, participated in this study. These schools were randomly selected as the experimental group (n=28) which participated in the mental health educational intervention, and the comparison group (n=31), which did not receive any intervention. Data were collected using individual interviews with open-ended questions, drawings and a questionnaire (Opinions about Mental Illness - O.M.I. scale). The participants described mental health and mental illness before and after the intervention, using the same expressions for both terms. Among the experimental group, changes were seen within the same expressions after the intervention, although some descriptions did not change. However, after the intervention, participants in the experimental group did not confuse mental health with mental illness and they also included specific diagnostic examples or stated that mental illness can happen to anyone and it can be managed. Moreover, they expressed positive attitudes towards mentally ill people, which they had not done before the intervention. The analysis of the drawings before the intervention showed that mentally ill persons were drawn similarly in both groups. After the intervention, the drawings of the participants in the experimental group changed, including fewer negative elements, while the drawings of the comparison group did not change. Regarding the results on the O.M.I. scale, it was found that the score on the Social Discrimination factor significantly decreased from pre-test to post-test in both study groups. The experimental group had higher levels on Social Discrimination at pre-test compared to the comparison group, but this difference was not significant at post-test. No significant changes were found for the Social Restriction factor for either study group. Scores of the Social Care and Social Integration factors increased significantly only in the intervention group. Overall, the results of this study indicate that the mental health educational intervention had a positive impact on the perceptions about mental health and mental illness among adolescents, and (mental) health professionals can use these results for implementing similar interventions and further research.

Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone

Bioanalytical data from a bioequivalence study were used to develop limited-sampling strategy (LSS) models for estimating the area under the plasma concentration versus time curve (AUC) and the peak plasma concentration (Cmax) of 4-methylaminoantipyrine (MAA), an active metabolite of dipyrone. Twelve healthy adult male volunteers received single 600 mg oral doses of dipyrone in two formulations at a 7-day interval in a randomized, crossover protocol. Plasma concentrations of MAA (N = 336), measured by HPLC, were used to develop LSS models. Linear regression analysis and a "jack-knife" validation procedure revealed that the AUC0-¥ and the Cmax of MAA can be accurately predicted (R²>0.95, bias <1.5%, precision between 3.1 and 8.3%) by LSS models based on two sampling times. Validation tests indicate that the most informative 2-point LSS models developed for one formulation provide good estimates (R²>0.85) of the AUC0-¥ or Cmax for the other formulation. LSS models based on three sampling points (1.5, 4 and 24 h), but using different coefficients for AUC0-¥ and Cmax, predicted the individual values of both parameters for the enrolled volunteers (R²>0.88, bias = -0.65 and -0.37%, precision = 4.3 and 7.4%) as well as for plasma concentration data sets generated by simulation (R²>0.88, bias = -1.9 and 8.5%, precision = 5.2 and 8.7%). Bioequivalence assessment of the dipyrone formulations based on the 90% confidence interval of log-transformed AUC0-¥ and Cmax provided similar results when either the best-estimated or the LSS-derived metrics were used.