920 resultados para Engineering-To-Order


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Business Intelligence (BI) applications have been gradually ported to the Web in search of a global platform for the consumption and publication of data and services. On the Internet, apart from techniques for data/knowledge management, BI Web applications need interfaces with a high level of interoperability (similar to the traditional desktop interfaces) for the visualisation of data/knowledge. In some cases, this has been provided by Rich Internet Applications (RIA). The development of these BI RIAs is a process traditionally performed manually and, given the complexity of the final application, it is a process which might be prone to errors. The application of model-driven engineering techniques can reduce the cost of development and maintenance (in terms of time and resources) of these applications, as they demonstrated by other types of Web applications. In the light of these issues, the paper introduces the Sm4RIA-B methodology, i.e., a model-driven methodology for the development of RIA as BI Web applications. In order to overcome the limitations of RIA regarding knowledge management from the Web, this paper also presents a new RIA platform for BI, called RI@BI, which extends the functionalities of traditional RIAs by means of Semantic Web technologies and B2B techniques. Finally, we evaluate the whole approach on a case study—the development of a social network site for an enterprise project manager.

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This research addresses the problem of cost estimation for product development in engineer-to-order (ETO) operations. An ETO operation starts the product development process with a product specification and ends with delivery of a rather complicated, highly customized product. ETO operations are practiced in various industries such as engineering tooling, factory plants, industrial boilers, pressure vessels, shipbuilding, bridges and buildings. ETO views each product as a delivery item in an industrial project and needs to make an accurate estimation of its development cost at the bidding and/or planning stage before any design or manufacturing activity starts. ^ Many ETO practitioners rely on an ad hoc approach to cost estimation, with use of past projects as reference, adapting them to the new requirements. This process is often carried out on a case-by-case basis and in a non-procedural fashion, thus limiting its applicability to other industry domains and transferability to other estimators. In addition to being time consuming, this approach usually does not lead to an accurate cost estimate, which varies from 30% to 50%. ^ This research proposes a generic cost modeling methodology for application in ETO operations across various industry domains. Using the proposed methodology, a cost estimator will be able to develop a cost estimation model for use in a chosen ETO industry in a more expeditious, systematic and accurate manner. ^ The development of the proposed methodology was carried out by following the meta-methodology as outlined by Thomann. Deploying the methodology, cost estimation models were created in two industry domains (building construction and the steel milling equipment manufacturing). The models are then applied to real cases; the cost estimates are significantly more accurate than the actual estimates, with mean absolute error rate of 17.3%. ^ This research fills an important need of quick and accurate cost estimation across various ETO industries. It differs from existing approaches to the problem in that a methodology is developed for use to quickly customize a cost estimation model for a chosen application domain. In addition to more accurate estimation, the major contributions are in its transferability to other users and applicability to different ETO operations. ^

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This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

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This research focuses on developing a capacity planning methodology for the emerging concurrent engineer-to-order (ETO) operations. The primary focus is placed on the capacity planning at sales stage. This study examines the characteristics of capacity planning in a concurrent ETO operation environment, models the problem analytically, and proposes a practical capacity planning methodology for concurrent ETO operations in the industry. A computer program that mimics a concurrent ETO operation environment was written to validate the proposed methodology and test a set of rules that affect the performance of a concurrent ETO operation. ^ This study takes a systems engineering approach to the problem and employs systems engineering concepts and tools for the modeling and analysis of the problem, as well as for developing a practical solution to this problem. This study depicts a concurrent ETO environment in which capacity is planned. The capacity planning problem is modeled into a mixed integer program and then solved for smaller-sized applications to evaluate its validity and solution complexity. The objective is to select the best set of available jobs to maximize the profit, while having sufficient capacity to meet each due date expectation. ^ The nature of capacity planning for concurrent ETO operations is different from other operation modes. The search for an effective solution to this problem has been an emerging research field. This study characterizes the problem of capacity planning and proposes a solution approach to the problem. This mathematical model relates work requirements to capacity over the planning horizon. The methodology is proposed for solving industry-scale problems. Along with the capacity planning methodology, a set of heuristic rules was evaluated for improving concurrent ETO planning. ^

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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

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Virtual-build-to-order (VBTO) is a form of order fulfilment system in which the producer has the ability to search across the entire pipeline of finished stock, products in production and those in the production plan, in order to find the best product for a customer. It is a system design that is attractive to Mass Customizers, such as those in the automotive sector, whose manufacturing lead time exceeds their customers' tolerable waiting times, and for whom the holding of partly-finished stocks at a fixed decoupling point is unattractive or unworkable. This paper describes and develops the operational concepts that underpin VBTO, in particular the concepts of reconfiguration flexibility and customer aversion to waiting. Reconfiguration is the process of changing a product's specification at any point along the order fulfilment pipeline. The extent to which an order fulfilment system is flexible or inflexible reveals itself in the reconfiguration cost curve, of which there are four basic types. The operational features of the generic VBTO system are described and simulation is used to study its behaviour and performance. The concepts of reconfiguration flexibility and floating decoupling point are introduced and discussed.

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When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

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Scopolamine is an alkaloid widely used in medicine for its anticholinergic activity. The aim of this review is to show that metabolic engineering techniques constitute a suitable tool to improve the production of tropane alkaloids, focusing in particular on scopolamine. We present an overview of results obtained by various research groups, including our own, who have studied the overexpression of genes involved in the biosynthesis of scopolamine in different plant species that produce tropane alkaloids. Experiments carried out to improve production in hairy root cultures will also be described, as well as those attempting to biotransform hyoscyamine into scopolamine in roots and transgenic tobacco cells.

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The ability to efficiently produce recombinant proteins in a secreted form is highly desirable and cultured mammalian cells such as CHO cells have become the preferred host as they secrete proteins with human-like post-translational modifications. However, attempts to express high levels of particular proteins in CHO cells may consistently result in low yields, even for non-engineered proteins such as immunoglobulins. In this study, we identified the responsible faulty step at the stage of translational arrest, translocation and early processing for such a "difficult-to-express" immunoglobulin, resulting in improper cleavage of the light chain and its precipitation in an insoluble cellular fraction unable to contribute to immunoglobulin assembly. We further show that proper processing and secretion were restored by over-expressing human signal receptor protein SRP14 and other components of the secretion pathway. This allowed the expression of the difficult-to-express protein to high yields, and it also increased the production of an easy-to-express protein. Our results demonstrate that components of the secretory and processing pathways can be limiting, and that engineering of the secretory pathway may be used to improve the secretion efficiency of therapeutic proteins from CHO cells.

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Abstract

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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.

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Kandidaatintyön tavoitteena on tutkia engineer-to-order -toimitusketjun tyypillisiä tärkeimpiä kilpailutekijöitä sekä esittää esimerkkiratkaisu siitä, millaisella suorituskyvyn mittaristolla engineer-to-order toimitusketjua voidaan ohjata kohti tärkeimpien kilpailutekijöiden vahvistamista. Työssä luodaan katsaus ETO -ympäristön erityispiirteisiin ja esitetään tekijöitä, joita suorituskyvyn mittaamisessa tulisi huomioida tässä ympäristössä.

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Tämän kandidaatinyön tavoitteena on selvittää keinoja joilla ETO-yhtiö voi kehittää tuotettaan ja tuotantoaan kohti massakustomointi. Lisäksi selvitetään mitkä asiat vaikuttavat asiakastilauksen kytkentäpisteen asettamiseen siirtyessä massakustomointiin. Työ on tehty kirjallisuuskatsauksena. Esitettyjen tietojen ja tulosten pohjana on alan kirjallisuus sekä julkaistut artikkelit. Työn perusteella voidaan todeta että parhaimmat keinot massakustomoinnin tavoitteluun ETO-yhtiölle ovat; tuotannon ja tuotteiden kehittäminen siten että pystytään hyödyntämään modularisointia ja komponenttien standardointia, lisäksi tuotesuunnitteluun käytettävää aikaa tulee vähentää automatisoimalla tuotesuunnittelua tai käyttämällä standardi suunnitelmia. ETO-yhtiössä siirtyessä massakustomointiin tulee asiakastilauksen kytkentäpisteen paikkaa asetettaessa ottaa huomioon tuotannon ja suunnittelun ulottuvuus kytkettynä asiakkaan vaatimuksiin.