Item master management in the engineer-to-order supply chain

Diplomityöntavoitteena on tutkia, kuinka nimiketiedon hallinnalla voidaan parantaa kustannustehokkuutta projektiohjautuvassa toimitusketjussa. Työn kohdeyritys on Konecranes Oyj:n tytäryhtiö Konecranes Heavy Lifting Oy. Nimiketiedon hallinta liittyy läheisesti tuotetiedon hallintaan. Teoriaosassa käsitellään toimitusketjuympäristön tekijöitä, modulaarisuuden ja asiakaskohtaisuuden ongelmallisuutta sekä informaatiovirran vaikutuksia eri toiminnoissa. Yritysosassa vertaillaan konsernitason kahta liiketoiminta-aluetta strategiavalintojen, tuotteiden modulaarisuuden sekä tilaus-toimitusprosessissa liikkuvan nimikeinformaation perusteella. Diplomityön tuloksena annetaan suuntaviivat; nimikemassan eheytykseen, strategisten nimikkeiden tunnistamiseen ja määrittämiseen, nimikkeiden hallintaan sekä master-datan sijoittamiseen tietojärjestelmäympäristöön.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Magni Ducatus Finlandiae Russiae partim, partim Sueciae subjecti Sinus item Bothnici ac Finnici nova et accurata delinaetio - [Yleisnäkymä - Overview]

S.l. : Georg. Aug. Vind ca 1750

Differential Regulation of c-FLIP Isoforms Through Post-translational Modifications

Cells are constantly responding to signals from the surrounding tissues and the environment. To dispose of infected and potentially dangerous cells, to ensure the optimal execution of developmental processes and to maintain tissue homeostasis, a multicellular organism needs to tightly control both the number and the quality of its cells. Apoptosis is a form of active cellular self-destruction that enables an organism to regulate its cell number by deleting damaged or potentially dangerous cells. Apoptosis can be induced by death ligands, which bind to death receptors on the cell surface. Ligation of the receptors leads to the formation of an intracellular death inducing signaling complex (DISC). One of the DISC components is caspase-8, a protease that triggers the caspase cascade and is thereby a key initiator of programmed cell death. The activation of caspase-8 is controlled by the cellular FLICE-inhibitory proteins (c-FLIPs). Consequently, sensitivity towards receptor-mediated apoptosis is determined by the amount of c-FLIP, and the c-FLIP levels are actively regulated for example during erythroid differentiation of K562 erythroleukemia cells and by hyperthermia in Jurkat leukemia cells. The aim of my thesis was to investigate how c-FLIP is regulated during these processes. We found that c-FLIP isoforms are short-lived proteins, although c-FLIPS had an even shorter half-life than c-FLIPL. In both experimental models, increased death receptor sensitivity correlated with induced ubiquitylation and consequent proteasomal degradation of c-FLIP. Furthermore, we elucidated how phosphorylation regulates the biological functions and the turnover of c-FLIP, thereby contributing to death receptor sensitivity. We mapped the first phosphorylation sites on c-FLIP and dissected how their phosphorylation affects c-FLIP. Moreover, we demonstrated that phosphorylation of serine 193, a phosphorylated residue common to all c-FLIPs, is primarily mediated by the classical PKC. Furthermore, we discovered a novel connection between the phosphorylation and ubiquitylation of c-FLIP: phosphorylation of S193 protects c-FLIP from ubiquitylation. Surprisingly, although all c-FLIP isoforms are phosphorylated on this conserved residue, the biological outcome is different for the long and short isoforms, since S193 specifically prolongs the half-lives of the short c-FLIP isoforms, but not c-FLIPL. To summarize, we show that c-FLIP proteins are modified by ubiquitylation and phosphorylation, and that the biological outcomes of these modifications are isoform-specifically determined.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Magni ducatus Finlandiae Russiae partim, partim Sueciae subjecti; Sinus item Bothnici ac Finnici nova et accurata delineatio. Calamo et sumtibus Tobiae Conradi Lotter, Geogr. Aug. Vind. Cum Priv. S. Vic. in part. Rheni Suev. et Franc. juris.

Mittakaava [N. 1:1800000]. - Ulkoasu: 1 kartta : vär. ; 48,5 x 56,7 cm, lehti 50,2 x 58,5 cm.

Magni ducatus Finlandiae Russiae partim, partim Sueciae subjecti; Sinus item Bothnici ac Finnici nova et accurata delineatio. Calamo et sumtibus Matthaei Seutteri, S.C.M. Geogr. Aug. Vind. Cum Priv. S. Vic. in part. Rheni Suev. et Franc. juris

Mittakaava: [N. 1:1800000]. - Ulkoasu: 1 kartta : vär. ; 49 x 57,8 cm, lehti 53,5 x 64,3 cm.

Boundary identification in the domain of a parabolic partial differential equation

Bakgrunden och inspirationen till föreliggande studie är tidigare forskning i tillämpningar på randidentifiering i metallindustrin. Effektiv randidentifiering möjliggör mindre säkerhetsmarginaler och längre serviceintervall för apparaturen i industriella högtemperaturprocesser, utan ökad risk för materielhaverier. I idealfallet vore en metod för randidentifiering baserad på uppföljning av någon indirekt variabel som kan mätas rutinmässigt eller till en ringa kostnad. En dylik variabel för smältugnar är temperaturen i olika positioner i väggen. Denna kan utnyttjas som insignal till en randidentifieringsmetod för att övervaka ugnens väggtjocklek. Vi ger en bakgrund och motivering till valet av den geometriskt endimensionella dynamiska modellen för randidentifiering, som diskuteras i arbetets senare del, framom en flerdimensionell geometrisk beskrivning. I de aktuella industriella tillämpningarna är dynamiken samt fördelarna med en enkel modellstruktur viktigare än exakt geometrisk beskrivning. Lösningsmetoder för den s.k. sidledes värmeledningsekvationen har många saker gemensamt med randidentifiering. Därför studerar vi egenskaper hos lösningarna till denna ekvation, inverkan av mätfel och något som brukar kallas förorening av mätbrus, regularisering och allmännare följder av icke-välställdheten hos sidledes värmeledningsekvationen. Vi studerar en uppsättning av tre olika metoder för randidentifiering, av vilka de två första är utvecklade från en strikt matematisk och den tredje från en mera tillämpad utgångspunkt. Metoderna har olika egenskaper med specifika fördelar och nackdelar. De rent matematiskt baserade metoderna karakteriseras av god noggrannhet och låg numerisk kostnad, dock till priset av låg flexibilitet i formuleringen av den modellbeskrivande partiella differentialekvationen. Den tredje, mera tillämpade, metoden kännetecknas av en sämre noggrannhet förorsakad av en högre grad av icke-välställdhet hos den mera flexibla modellen. För denna gjordes även en ansats till feluppskattning, som senare kunde observeras överensstämma med praktiska beräkningar med metoden. Studien kan anses vara en god startpunkt och matematisk bas för utveckling av industriella tillämpningar av randidentifiering, speciellt mot hantering av olinjära och diskontinuerliga materialegenskaper och plötsliga förändringar orsakade av “nedfallande” väggmaterial. Med de behandlade metoderna förefaller det möjligt att uppnå en robust, snabb och tillräckligt noggrann metod av begränsad komplexitet för randidentifiering.

Tuotannon- ja varastonohjausmallien kehittäminen sekä ylläpito kokoonpanotuotannossa

Asiakkaiden vaatimusten täyttäminen käytössä olevilla resursseilla edellyttää yrityksiltä usein varastojen pitämistä. Varastot aiheuttavat kuluja ja niihin sitoutuu pääomaa, joten niiden hallinta on yritysten mielenkiinnon kohde. Diplomityön tavoitteena on tutkia Peikko Finland Oy:n Teräsosatehtaan varastonohjausmallin toimivuutta sekä luoda ylläpitokelpoinen tapa tuotannonohjausmuodon ja varastoparametrien päivittämiseen. Yritysten käytössä olevien resurssien ollessa rajallisia tulee tärkeiden tuotteiden hallintaan keskittyä. Vähäpätöisempiä nimikkeitäkin on ohjattava, mutta yksinkertaisempien mallien avulla kuin tärkeitä tuotteita. Tuotannon- ja varastonohjauksen tavoitteena on löytää tasapaino pääoman sitoutumisen, asiakkaiden palvelun sekä kapasiteetin käytön väliltä. Niihin vaikuttavat tekijät tulee huomioida mahdollisimman kattavasti tuotannonohjausta ja varastonhallintaa suunniteltaessa, jolloin päästään koko yritystä hyödyttävään lopputulokseen. Yrityksen toimintaympäristö kehittyy jatkuvasti, joten kerran määritetyt tekijä eivät ole relevantteja loputtomiin vaan jatkuvan kehittämisen ja tietojen päivittämisen tulee olla osa yrityksen jokapäiväistä toimintaa. Työssä kehitettiin helposti päivitettävä malli, jonka avulla kohdeyritys pystyy päivittämään nimikkeiden tuotannonohjausmuodot ja varastonohjauksen parametrit.

Joannis Schefferi Argentoratensis Lapponia, Id est, Regionis Lapponum et gentis nova et verissima descriptio. In qua multa de origine, superstitione, sacris magicis, victu, cultu, negotiis Lapponum, item animalium, metallorumque indole quae in terris eorum proveniunt, hactenus incognita. Produntur, [et] eiconibus adjectis cum cura illustrantur

Added engraved title page: Joannis Schefferi Argentoratensis Lapponia.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Differential Evolution approach and parameter estimation of chaotic

Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.

Biodiversity and ecosystem functioning in angiosperm communities in the Baltic Sea

The biological variation in nature is called biodiversity. Anthropogenic pressures have led to a loss of biodiversity, alarming scientists as to what consequences declining diversity has for ecosystem functioning. The general consensus is that diversity (e.g. species richness or identity) affects functioning and provides services from which humans benefit. The aim of this thesis was to investigate how aquatic plant species richness and identity affect ecosystem functioning in terms of processes such as primary production, nutrient availability, epifaunal colonization and properties e.g. stability of Zostera marina subjected to shading. The main work was carried out in the field and ranged temporally from weeklong to 3.5 months-long experiments. The experimental plants used frequently co-occur in submerged meadows in the northern Baltic Sea and consist of eelgrass (Z. marina), perfoliate pondweed (Potamogeton perfoliatus), sago pondweed (P. pectinatus), slender-leaved pondweed (P. filiformis) and horned pondweed (Zannichellia palustris). The results showed that plant richness affected epifaunal community variables weakly, but had a strong positive effect on infaunal species number and functional diversity, while plant identity had strong effects on amphipods (Gammarus spp.), of which abundances were higher in plant assemblages consisting of P. perfoliatus. Depending on the starting standardizing unit, plant richness showed varying effects on primary production. In shoot density-standardized plots, plant richness increased the shoot densities of three out of four species and enhanced the plant biomass production. Both positive complementarity and selection effects were found to underpin the positive biodiversity effects. In shoot biomass-standardized plots, richness effects only affected biomass production of one species. Negative selection was prevalent, counteracting positive complementarity, which resulted in no significant biodiversity effect. The stability of Z. marina was affected by plant richness in such that Z. marina growing in polycultures lost proportionally less biomass than Z. marina in monocultures and thus had a higher resistance to shading. Monoculture plants in turn gained biomass faster, and thereby had a faster recovery than Z. marina growing in polycultures. These results indicate that positive interspecific interactions occurred during shading, while the faster recovery of monocultures suggests that the change from shading stress to recovery resulted in a shift from positive interactions to resource competition between species. The results derived from this thesis show that plant diversity affects ecosystem functioning and contribute to the growing knowledge of plant diversity being an important component of aquatic ecosystems. Diverse plant communities sustain higher primary productivity than comparable monocultures, affect faunal communities positively and enhance stability. Richness and identity effects vary, and identity has generally stronger effects on more variables than richness. However, species-rich communities are likely to contain several species with differing effects on functions, which renders species richness important for functioning. Mixed meadows add to coastal ecosystem functioning in the northern Baltic Sea and may provide with services essential for human well-being.