Resumo: O grande número de variáveis envolvidas no processo de fundição de aço o torna muito susceptível a ocorrência de defeitos relacionados à solidificação como rechupes e poros, que elevam o custo de fabricação devido ao sucateamento e retrabalho de peças. Explorando oportunidades neste cenário, esta Tese de Doutorado, desenvolvida dentro do ambiente industrial de uma fundição de aço propõe um modelo matemático capaz de predizer a combinação de níveis de variáveis de processo que minimizam a ocorrência de rechupes e poros relacionados à solidificação em peças fundidas em aço ABNT 1030, moldadas em areia com aglomerante químico e vazamento por gravidade. Empregou-se, no desenvolvimento do trabalho o Planejamento Estatístico de Experimentos com fatorial fracionado na fase exploratória e o método de Taguchi para validação final e desenvolvimento do Modelo matemático. Na fase de validação, utilizou-se um arranjo ortogonal L16 com quatro réplicas. Na fase exploratória, avaliou-se o volume de defeito em uma peça de produção normal da fundição. Na fase de validação, desenvolveram-se corpos de prova em forma de cubo, vazados sem alimentação. Depois de produzidos, os corpos de prova passavam por ensaio de ultrassom para identificação e localização do defeito e corte de serra, para posterior medição do volume do defeito. O sistema de medição foi validado por meio de um estudo de Análise do Sistema de Medição - MSA GR&R. Os resultados dos experimentos mostraram uma grande diferença entre a contração teórica prevista na literatura de 5,5% para o aço estudado para 2% determinado experimentalmente. As variáveis que mais influenciaram no tamanho do defeito foram: o percentual de carbono queimado no processo de elaboração do aço, percentual de alumínio na liga, percentual de óxido de ferro na areia de moldagem e a interação entre... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The number of variables involved in the steel foundry process makes it susceptible to the occurrence of defects related to the solidification, like shrinkages and pores. This charge the foundries scrap and rework costs. Exploring the opportunities at this context, this Thesis, developed inside an industrial environment of a steel foundry, purposes a mathematic model capable to predict the combination of levels of variables that minimizes the occurrence of shrinkage and pores in carbon steel cast parts, through no-bake sand molding and gravity pouring processes. Statistical Design of Experiments with fractional and factorial at the screening step and Taguchi Method for the final validation and development of the mathematic model were used. A L16 orthogonal array with four replicates was used in the validation step. The defect volume inside a regular cast part was evaluated in the screening step. In the validation step, cube form specimens were designed, poured without feeders and ultrasound tested to bound the defect then saw cut to measure the defect's volume. In order to the validation of the measurement system, a MSA - Measurement Systems Analysis and Gauge R & R - Gauge Repeatability and Reproducibility were used. The experiments results shown a considerable difference between the theoretical expected contraction, 5.5%, and the 2% experimentally determined. The variables that influenced the defect size the most were: the carbon drop in the steel making, the Aluminum content of the alloy, the Black Iron Oxide content of the molding sand and the interaction between the pouring temperature and the carbon drop. The mathematic model was validated by experiments, which showed a good performance in the prediction of defects. / Orientador: Messias Borges Silva / Coorientador: Fernando Augusto Silva Marins / Banca: Antonio Fernando Branco Costa / Banca: Marcela Aparecida Guerreiro Machado / Banca: Amiton Sinatora / Banca: Rosinei Batista Ribeiro / Doutor

Im Rahmen des Symposiums gaben Vertreter weltweit agierender Konzerne, wie Audi AG, voestalpine Gießerei Linz, Alstom AG und SITEC GmbH Einblick in ihre Forschungs­aktivitäten im Bereich Mobilität, Energietechnik, Medizintechnik und Sondermaschinenbau. Die schweißtechnischen Institute der Universitäten Aachen, Braunschweig, Clausthal, Dresden, Magdeburg und Graz gaben einen Überblick über universitäre Forschungs­aktivitäten.

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A content of this thesis is an analysis of a steel castings production mismatch in Tatra Metallurgy foundry. Most common defects found on castings are gas holes. Thesis shows a theoretical research on casting defects caused by gases in steel castings. It also describes melting and degassing problematics of molten steel and procedures to reduce gas contents. The last part of theoretical research describes oxidation of steel in contact with silica mold. Practical part of thesis analysis production of steel castings to determine the cause of origin of gas holes. Main attention is paid to mold mixture, chemical composition, casting temperatures and casting time. The last chapter metallographically analysis two defected castings to determine the origin of defects. Main attention is paid to shape and chemical composition of gas holes and to morphology of steel inclusions.

Im Zusammenhang mit Sanierungsmaßnahmen an bestehenden Brückentragwerken muss auch der Zustand ihrer Lager bewertet werden. Im Falle historischer Brückenlagertechnik bleiben hierbei oft Fragen unbeantwortet, zum Beispiel zu den Möglichkeiten einer zerstörungsfreien Beurteilung des Lagerwerkstoffs. Am Beispiel des ab etwa 1880 zunehmend für Lager verwendeten Werkstoffs Stahlguss – früher zumeist Stahlformguss – verfolgt der Beitrag den Ansatz, die mittels Spektralanalyse ermittelte Werkstoffrezeptur als Ausgangspunkt für zentrale Aussagen zur Werkstofffestigkeit zu nutzen. Der Artikel erläutert die Methodik, diskutiert Ergebnisse des Vorgehens und zeigt eine interessante Option für eine quasi zerstörungsfreie Werkstoffuntersuchung auf.

Modern manufacturing systems need new types of scheduling methods. While traditional scheduling methods are primarily concerned with sequencing of jobs, modern manufacturing environments provide the additional possibility to process jobs in batches. This adds to the complexity of scheduling. There are two types of batching namely: (i) serial batching (jobs may be batched if they share the same setup on a machine and one job is processed at a time. The machine which processes jobs in this manner is called as discrete processor) and (ii) parallel batching (several jobs can be processed simultaneously on a machine at a time. The machine which processes jobs in this manner is called as batch processor or batch processing machine). Parallel batching environments have attracted wide attention of the researchers working in the field of scheduling. Particularly, taking inspiration from studies of scheduling batch processors in semiconductor manufacturing [Mathirajan and Sivakumar (2006b) and Venkataramana (2006)] and in steel casting industries [Krishnaswamy et al. (1998), Shekar (1998) and Mathirajan (2002)] in the Management Studies Department of Indian Institute of Science, this thesis addresses a special problem on scheduling batch processor, observed in the steel casting manufacturing. A fundamental feature of the steel casting industry is its extreme flexibility, enabling castings to be produced with almost unlimited freedom in design over an extremely wide range of sizes, quantities and materials suited to practically every environment and application. Furthermore, the steel casting industry is capital intensive and highly competitive. From the viewpoint of throughput and utilization of the important and costly resources in the foundry manufacturing, it was felt that the process-controlled furnace operations for the melting and pouring operations as well as the heat-treatment furnace operations are critical for meeting the overall production schedules. The two furnace operations are batch processes that have distinctive constraints on job-mixes in addition to the usual capacity and technical constraints associated with any industrial processes. The benefits of effective scheduling of these batch processes include higher machine utilization, lower work-in-process (WIP) inventory, shorter cycle time and greater customer satisfaction [Pinedo (1995)]. Very few studies address the production planning and scheduling models for a steel foundry, considering the melting furnace of the pre-casting stage as the core foundry operation [Voorhis et al. (2001), Krishnaswamy et al. (1998) and Shekar (1998)]. Even though the melting and pouring operations may be considered as the core of foundry operations and their scheduling is of central importance, the scheduling of heat-treatment furnaces is also of considerable importance. This is because the processing time required at the heat treatment furnace is often longer compared to other operations in the steel-casting foundry and therefore considerably affects the scheduling, overall flow time and WIP inventory. Further, the heat-treatment operation is critical because it determines the final properties that enable components to perform under demanding service conditions such as large mechanical load, high temperature and anti-corrosive processing. It is also important to note that the heat-treatment operation is the only predominantly long process in the entire steel casting manufacturing process, taking up a large part of total processing time (taking up to a few days as against other processes that typically take only a few hours). Because of these, the heat-treatment operation is a major bottleneck operation in the entire steel casting process. The jobs in the WIP inventory in front of heat-treatment furnace vary widely in sizes (few grams to a ton) and dimensions (from 10 mm to 2000 mm). Furthermore, castings are primarily classified into a number of job families based on the alloy type, such as low alloy castings and high alloy castings. These job families are incompatible as the temperature requirement for low alloy and high alloy vary for similar type of heat-treatment operation required. These job families are further classified into various sub-families based on the type of heat treatment operations they undergo. These sub-families are also incompatible as each of these sub-families requires a different combination of heat-treatment operation. The widely varying job sizes, job dimensions and multiple incompatible job family characteristic introduce a high degree of complexity into scheduling heat-treatment furnace. Scheduling of heat-treatment furnace with multiple incompatible job families can have profound effect on the overall production rate as the processing time at heat-treatment operation is very much longer. Considering the complexity of the process and time consumed by the heat treatment operation, it is imperative that efficient scheduling of this operation is required in order to maximize throughput and to enhance productivity of the entire steel casting manufacturing process. This is of importance to the firm. The concerns of the management in increasing the throughput of the bottleneck machine, thereby increasing productivity, motivated us to adopt the scheduling objective of makespan. In a recent observation of heat-treatment operations in a couple of steel casting industries and the research studies reported in the literature, we noticed that the real-life problem of dynamic scheduling of heat-treatment furnace with multiple incompatible job families, non-identical job sizes, non-identical job dimensions, non-agreeable release times and due dates to maximize the throughput, higher utilization and minimize the work-in-process inventory is not at all addressed. However, there are very few studies [Mathirajan et al. (2001, 2002, 2004a, 2007)] which have addressed the problem of scheduling of heat-treatment furnace with incompatible job families and non-identical job sizes to maximize the utilization of the furnace. Due to the difference between the real-life situation on dynamic scheduling of heat-treatment furnace of the steel casting manufacturing and the research reported on the same problem, we identified three new class of batch processor problems, which are applicable to a real-life situation based on the type of heat-treatment operation(s) being carried out and the type of steel casting industry (small, medium and large scale steel casting industry) and this thesis addresses these new class of research problems on scheduling of batch processor. The first part of the thesis addresses our new Research Problem (called Research Problem 1) of minimizing makespan (Cmax) on a batch processor (BP) with single job family (SJF), non-identical job sizes (NIJS), and non-identical job dimensions (NIJD). This problem is of interest to small scale steel casting industries performing only one type of heat treatment operation such as surface hardening. Generally, there would be only a few steel casting industries which offer such type of special heat-treatment operation and thus the customer is willing to accept delay in the completion of his orders. So, the due date issues are not important for these types of industries. We formulate the problem as Mixed Integer Linear Programming (MILP) model and validate the proposed MILP model through a numerical example. In order to understand the computational intractability issue, we carry out a small computational experiment. The results of this experiment indicate that the computational time required, as a function of problem size, for solving the MILP model is non-deterministic and non-polynomial. Due to the computational intractability of the proposed MILP model, we propose five variants of a greedy heuristic algorithm and a genetic algorithm for addressing the Research Problem 1. We carry out computational experiments to obtain the performance of heuristic algorithms based on two perspectives: (i) comparison with optimal solution on small scale instances and (ii) comparison with lower bound for large scale instances. We choose five important problem parameters for the computational experiment and propose a suitable experimental design to generate pseudo problem instances. As there is no lower bound (LB) procedure for the Research Problem1, in this thesis, we develop an LB procedure that provides LB on makespan by considering both NIJS and NIJD characteristics together. Before using the proposed LB procedure for evaluating heuristic algorithms, we conduct a computational experiment to obtain the quality of the LB on makespan in comparison with optimal makespan on number of small scale instances. The results of this experiment indicate that the proposed LB procedure is efficient and could be used to obtain LB on makespan for any large scale problem. In the first perspective of the evaluation of the performance of the heuristic algorithms proposed for Research Problem 1, the proposed heuristic algorithms are run through small scale problem instances and we record the makespan values. We solve the MILP model to obtain optimal solutions for these small scale instances. For comparing the proposed heuristic algorithms we use the performance measures: (a) number of times the proposed heuristic algorithm solution equal to optimal solution and (b) average loss with respect to optimal solution in percentage. In the second perspective of the evaluation of the performance of the heuristic algorithms, the proposed heuristic algorithms are run through large scale problem instances and we record the makespan values. The LB procedure is also run through these problem instances to obtain LB on makespan. For comparing the performance of heuristic algorithms with respect to LB on makespan, we use the performance measures: (a) number of times the proposed heuristic algorithm solution equal to LB on makespan (b) average loss with respect to LB on makespan in percentage, (c) average relative percentage deviation and (d) maximum relative percentage deviation. We extend the Research Problem 1 by including additional job characteristics: job arrival time to WIP inventory area of heat-treatment furnace, due date and additional constraint on non-agreeable release time and due date (NARD). Due date considerations and the constraint on non-agreeable release times and due date (called Research Problem 2) are imperative to small scale steel casting foundries performing traditional but only one type of heat treatment operation such as annealing where due date compliance is important as many steel casting industries offer such type of heat treatment operations. The mathematical model, LB procedure, greedy heuristic algorithm and genetic algorithm proposed for Research Problem 1, including the computational experiments, are appropriately modified and\or extended for addressing Research Problem 2. Finally, we extend the Research Problem 2 is by including an additional real life dimension: multiple incompatible job families (MIJF). This new Research Problem (called Research Problem 3) is more relevant to medium and large scale steel casting foundries performing more than one type of heat treatment operations such as homogenizing and tempering, normalizing and tempering. The solution methodologies, the LB procedure and the computational experiments proposed for Research Problem 2 are further modified and enriched to address the Research Problem 3. From the detailed computational experiments conducted for each of the research problems defined in this study, we observe that: (a) the problem parameters considered in this study have influence on the performance of the heuristic algorithms, (b) the proposed LB procedure is found to be efficient, (c) the proposed genetic algorithm outperforms among the proposed heuristic algorithms (but the computational time required for genetic algorithm increases as problem size keeps increasing), and (d) in case the decision maker wants to choose an heuristic algorithm which is computationally most efficient algorithm among the proposed algorithms, the variants of greedy heuristic algorithms : SWB, SWB(NARD), SWB(NARD&MIJF) is relatively the best algorithm for Research Problem 1, Research Problem 2 and Research Problem 3 respectively.

This thesis deals with modelling of continuous casting of steel. This process of steel manufacturing has achieved dominant position not only in the Czech Republic but also worldwide. The solved casted bar cross-section shape is circular, because it is rarely studied in academical works nowadays. First part of thesis focuses on creating numerical model of thermal field, using finite difference method with cylindrical coordinates. This model is then employed in optimization part, which represents control problem of abrupt step change of casting speed. The main goal is to find out, whether the computation of numerical model and optimization both can be parallelized using spatial decomposition. To achieve that, Progressive Hedging Algorithm from the field of stochastic optimization has been used.

Continuous casting is a dominant production technology of steelmaking which is currently used for more that 95% of the world steel production. Mathematical modelling and optimal control of casting machine are crucial tasks in continuous steel casting which directly influence productivity and quality of produced steel, competitiveness of steelworks, safety of casting machine operation and its impact on the environment. This thesis concerns with the development and implementation of the numerical model of temperature field for continuously cast steel billets and its use for optimal control of the casting machine. The numerical model was developed and implemented in MATLAB. Due to computational demands the model was parallelized by means of the computation on graphics processing units NVIDIA with the computational architecture CUDA. Validation and verification of the model were performed with the use of operational data from Trinecke zelezarny steelworks. The model was then utilized as a part of the developed model-based predictive control system for the optimal control of dynamic situations in the casting machine operation. The behaviour of the developed control system was examined by means of dynamic model situations that have confirmed the ability of the implemented system to optimally control dynamic operations of the continuous casting machine. Both the numerical model of the temperature field and the model-based predictive control system have been implemented so that they can be modified for any casting machine and this allows for their prospective commercial applications.