Academic literature on the topic 'Steel Casting Industry'

Thermo-Mechanical Model of Steel Continuous Casting Process In the paper a numerical model of heat and mass transfer in the mould zone in the steel continuous casting technology was presented. The model has been developed using ProCAST software designed for simulation of casting processes. It allows to determine temperature and stress distribution in continuous castings in order to optimize the most important process parameters. In this work calculations were executed for low carbon steel grades casted in the industry. In the simulations the real rheological properties measured in the experimental work and the boundary conditions determined on the basis of the industrial data were used.

Continuous casting is essentially the youngest and most dynamically developing technology in the steel production and casting system as an industrial method of shaped casting process. At present, continuous casting of steel is adopted in more than 90 countries of the world. About 2,000 continuous casting machines (CCMs) of different purposes and designs are now in good operation, which allow casting about 93% of all steel produced in the world. At this time, steel bars with the following maximum cross-sections are produced in the industry: blue 600×670mm, slab 250×3200mm and circular bars with a diameter of 600mm. In many developed countries of the world, almost 95-100% of steel production is produced by continuous casting. is being for example, in 2018, 1.228 billion tons of steel were produced by continuous casting in the world, which is a record in the history of metal production. as a result of experimental studies, proposals were developed for the application of important technologies in the development of non-furnace processing of liquid metal and continuous casting in the Republic. Keywords: Steel making, permanent casting devices, construction, vacuuming, liquid metal, intermediate heat, temperature, impact viscosity, electrometallurgy.

Extensive use has been made by the gas turbine industry of centrispun castings of certain highly alloyed heat resisting steels. The paper outlines the main features of the centrispinning process and discusses the advantages that one could expect, not only in mechanical properties, but also in cost and the casting to shape in refractory molds. Results of mechanical tests on sections cut from representative castings are given and show the high order of the tensile strength to be expected.

Research group of Metallurgy at Aalto University has been developing simulation models and tools for continuous casting since from the early 80s. The main models developed are the heat transfer model, DYN3D, and the solidification and microstructure model IDS. The models have been further developed and integrated to a continuous casting simulator and to a slab simulator. The continuous casting simulator calculates the important phenomena taking place in the strand during casting and the slab simulator calculates the phenomena taking place in the slabs when they are transferred from caster to reheating furnace. The numerical solution algorithms in the simulators are so fast that they can be used in on-line applications. The simulators have today many new options as hydrogen removal and quality prediction modules. In this paper, the simulators and their modules are presented.

AbstractMetal casting is an important manufacturing technology for efficiently producing massive components with complex shape. A large share of industrial castings is made from iron and steel alloys, combining attractive properties and low production cost. Upgrading of properties in cast iron and steel is mainly achieved by alloying and in fewer cases by heat treatment. Molybdenum is an important alloying element in that respect, increasing strength, hardness and toughness. It also facilitates particular heat treatments such as austempering. The paper describes the metallurgical functionality of molybdenum alloying in iron-based castings and demonstrates its effectiveness for applications in the automotive and mining industry.

The production of value added products made of high-alloyed Mn-, Al-, Si-steel grades is coupled to the casting technology. Conventional casting technologies will not fulfill the requirements concerning interaction between steel and casting flux as well as guiding as cast material without stress. Mechanical engineers are invited for further developments in the field of near-net-shape casting technologies to meet above mentioned demands. The Belt Casting Technology seems to be the answer but has to document the potential for an industrial standard process. The main process characteristics of the casting machine are high casting speed, moving mould consisting of a conveyor belt and side dams, complete inertisation and horizontal material flow. The process is already common at the nonferrous metal industry. A labo-ratory caster for steel is located at Clausthal University of Technology.

Abstract The foundry industry occupies an important position in the manufacture of castings, both through the existing production capacities and through the remarkable achievements registered in various fields and industries. The goal of steel foundry industry leaders is to meet the demands of both the entire market and individual customers, to develop new products, to improve available technologies, and to implement new “green” projects while optimizing all processes in the foundry. In this context, this paper presents the possibility of optimizing the process of moulding-casting a steel part that can be used in various industries (mechanics, machine building, mining etc.). The non-conformities of the current moulding-casting technology are identified and actions are proposed to remove them. By applying changes in technology, the rejects registered in the industrial practice is significantly reduced, the quality of the production process is improved, which is reflected in the costs of the enterprise.

AbstractWith increased efforts across the steel industry to produce steel in more economical ways, interest in near net shape casting has increased. Although much has been reported on the production of exotic alloys via these methods, to make the investment in new casting equipment, capability to produce current high value steels by these methods would derisk the capital expenditure. This study assesses the production of a dual phase steel (DP800) by belt casting and compared to that of conventional continuous casting. Although a drop in yield and tensile strength was seen in the belt cast-produced material, the increased elongation allowed for a comparable/improved UTS × elongation factor. A combination of in situ dendrite measurements, thermal modeling, and lab-scale belt casting has allowed insight into the relationship between cast thickness and final band spacing. The inherent lack of deformation of near net shape casting results in coarser band spacing and is not accounted for by the refinement of the secondary arm spacing caused by the faster solidification rates. This limits the strength achievable for a given martensite volume fraction. This has been predicted across the full range of casting thicknesses (1 to 230 mm) and good agreement has been shown with experimental results.

The use of Aluminum castings parts in the automotive industry has increased dramatically over the past few decades. The driving force for this increased use is vehicle weight reduction for improved performance. In many cases the mechanical properties of the cast aluminum parts are superior to those of the cast iron or wrought steel parts being used.This paper proposes the computer simulation of the sand casting of Aluminum Plate. It aims to study the behavior of fluid flow during mould filling and solidification and to optimize the process parameters, which help to predict and control casting defects such as gas porosity and shrinkage porosity. Here an attempt is being made to model and simulate the casting process using the AutoCAST software. The technological as well as practical aspects of using casting software are illustrated with an industrial case study.

The use of aluminum castings in the automotive industry has increased dramatically over the past two decades. The Al-Si system forms the basis of many important casting alloys, LM 0, LM 2, LM 4, LM 5, LM 6, LM 12, LM 13, LM 24 and LM 26 are the major cast alloys used in aerospace casting (e.g., fuel pump connectors) and premium automotive castings (e.g., suspension arms). The driving force for this increased use is vehicle weight reduction for improved performance, particularly fuel efficiency. In many cases the mechanical properties of the cast aluminum parts are superior to those of the cast iron or wrought steel parts being replaced; however, in some applications, defects in the cast microstructure undermine performance characteristics.

In this study, it was shown that improvements in the quality of continuously cast steel billets, similar to those which can be achieved by electromagnetic stirring (EMS) of the liquid pool during solidification, can be obtained if casting superheats can be consistently controlled at low levels. A lack of casting temperature control is not only detrimental to the quality of the cast product, but also to a shop's overall productivity. The important variables for temperature control in the ladle, tundish and mould were quantified and possible methods of controlling these variables were proposed.
The thermal state of the ladle lining is one of the major contributors to the variability in casting temperature. It was shown that by reducing energy losses from the refractory ladle lining, by way of incorporating an insulating refractory tile between the ladle shell and the safety lining and by using a ladle lid throughout the cycle of the ladle, temperature losses from the liquid steel can be substantially decreased. (Abstract shortened by UMI.)

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.

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.

The recent developments in computational intelligence has enhances the applicability of empirical modelling in different areas particularly in the area of machine learning. These new approaches are based on analysing the data about a system, in particular finding connections between the system state variables (input, internal and output variables) without having precise knowledge about the physical behaviour of the system. These data driven methods explain advances on conventional empirical modelling and include contributions from many overlapping fields like Artificial Intelligence (AI), Computational Intelligence (CI), Soft Computing (SC), Machine Learning (ML), Intelligent Data Analysis (IDA), and Data Mining (DM). The most popular computational intelligence techniques used in process modelling of steel industry includes neural networks, fuzzy rule-based systems, genetic algorithms as well as approaches to model integration. This chapter describes mainly the application of Artificial Neural Network (ANN) in steel industry. ANN has extensively used in improving and controlling different processes of steel industry like steel making, casting and rolling which lead to indirect energy savings through reduced product rejects, improved productivity and reduced down time. The efficiency of artificial neural network tool in handling steel plant processes has been discussed in detail. ANN based models are found to be very potential to handle very complex, dynamic and non-linear problems.

Manufacturing a steel product mix (bar, rod, sheet) involves a series of unit operations - primary steel making, secondary steel making (ladle refining and tundish operation), continuous casting, reheating, rolling and annealing. The properties of the final product depend significantly on how each unit operation is carried out. Each unit operation must be operated to meet the requirements of the subsequent operations. The requirements imposed on a particular unit operation are often conflicting and compromises must be made. Also, there is high degree of uncertainty in the operating parameters of each unit operation, which may lead to considerable deviations from the anticipated performance. To ensure that the final quality specifications of the product is not sacrificed and the customer requirements are met, it is essential to manage the conflict and uncertainty involved in each unit operation of the manufacturing process. In this chapter, we illustrate the use of compromise Decision Support Problem (cDSP) construct and ternary plots to overcome the challenges involved in one of the unit operations, namely, the tundish. The construct can be instantiated for other unit operations to cover the entire manufacturing cycle. Exploring the effects of system variables for each process step through experiments and plant trials is time consuming and very costly. The proposed method allows for faster design exploration of the process and thereby provides a reduced search space to a process designer. The process designer, with reduced experimentation requirements, can explore the narrowed search space to find the operating set points for a tundish. This, in turn, reduces the time and cost involved in production of a steel product mix with a new grade of steel in industry.

Manufacturing a steel product mix (bar, rod, sheet) involves a series of unit operations - primary steel making, secondary steel making (ladle refining and tundish operation), continuous casting, reheating, rolling and annealing. The properties of the final product depend significantly on how each unit operation is carried out. Each unit operation must be operated to meet the requirements of the subsequent operations. The requirements imposed on a particular unit operation are often conflicting and compromises must be made. Also, there is high degree of uncertainty in the operating parameters of each unit operation, which may lead to considerable deviations from the anticipated performance. To ensure that the final quality specifications of the product is not sacrificed and the customer requirements are met, it is essential to manage the conflict and uncertainty involved in each unit operation of the manufacturing process. In this chapter, we illustrate the use of compromise Decision Support Problem (cDSP) construct and ternary plots to overcome the challenges involved in one of the unit operations, namely, the tundish. The construct can be instantiated for other unit operations to cover the entire manufacturing cycle. Exploring the effects of system variables for each process step through experiments and plant trials is time consuming and very costly. The proposed method allows for faster design exploration of the process and thereby provides a reduced search space to a process designer. The process designer, with reduced experimentation requirements, can explore the narrowed search space to find the operating set points for a tundish. This, in turn, reduces the time and cost involved in production of a steel product mix with a new grade of steel in industry.

Abstract Iron and steel have been the most useful materials to meet the needs of several industries for many decades. Each iron and steel alloy offers unique attributes that make them the best choice for an application. This chapter provides an overview of each ferrous alloy—gray iron, malleable iron, compacted graphite iron (CGI), ductile iron, austempered ductile iron (ADI), and carbon steel and low-alloy steel; its versatile attributes; and its individual applications. A large section of the chapter covers the impact of electric vehicles on the future of the iron and steel castings industry, including discussion on electric vehicle categories and weights; impact of center of gravity on stability and steering; lightweighting incentives; and engineering for improved suspension.

Abstract Casting molds in the aluminium industry show a short lifespan due to the high corrosiveness of aluminium melts and alternating thermal and mechanical loads. By using new materials, in example pseudoalloys containing tungsten, the lifetime of casting molds can be elongated up to hundredfold. Today, casting molds made of steel are state of the art. In spite of the advantages of pseudoalloys, high manufacturing cost and the increasing commodity price of tungsten prohibit the use of molds consisting of these progressive materials. By coating the standard steel molds with a FeNiW-layer, the excellent thermal and corrosive resistance of the pseudoalloy surface can be combined with minimal manufacturing costs. For present work steel substrates had been coated with FeNiW-pseudoalloys. Therefore, arc spraying and different deposit-welding methods (Laser, Plasma, TIG) had been compared. By modifying the machine parameter set, a smooth transition between substrate and coating was realized. Thermal and chemical resistance of the samples will be tested. In this paper first results are presented.

Abstract This paper is aimed at the investigation of the diffusion boundary layer near the cooled casting surface encountered in the horizontal continuous casting process of carbon steel. The strip casting process is a relatively new continuous casting process. This process makes it possible to produce high-quality flat steel products directly, without using hot rolling. This explains why this process is very attractive for industry. Extensive numerical simulations under equilibrium and nonequilibrium assumptions provide valuable insight into the physics of diffusion boundary layer.

<div class="section abstract"><div class="htmlview paragraph">The automotive industry is facing a challenge as efficiency improvements are required to address the strict emission norms which in turn requires high performance downsized, lightweight IC engines. The increasing demand for lightweight engine needs high strength to weight ratio materials. To meet high strength to weight ratio, castings are preferable. However due to strength limitations for critical crankshaft applications, it forces to use costly forgings such as micro alloyed forging steel and Martensitic (after heat treatment) forging steel. To reduce the cost impact, high strength Austempered Ductile iron (ADI) casting is developed for crankshaft applications to substitute steel forgings. Austempered Ductile Iron is having an excellent mechanical properties due to aus-ferritic structure. The improved properties of developed ADI Crankshaft over steel forged crankshaft offers additional weight advantage. The ADI Crankshaft was subjected to rig test and meets the fatigue and durability life at the required Factor of Safety.</div></div>

Due to the stringent requirements of industry, it has become extremely important to have a careful control over the required performance and properties of steels. Performance and properties of advanced high strength steel depend significantly on its cleanliness. Cleanliness is achieved by restricting the inclusion count to a permissible limit. Over the past few years, there has been increased use of tundish, a device that acts as a buffer between ladle and mold, for controlling inclusions. Apart from facilitating inclusion removal, tundish also maintains low dead volume and thermal and chemical homogeneity, which is required for smooth casting operation. Thus, performance of the tundish operation greatly influences the properties and quality of the cast slab. Tundish performance is generally assessed using parameters such as inclusion removal efficiency, dead volume within tundish and effectiveness in maintaining the desired amount of superheat. But, the aforesaid parameters are conflicting in nature. Managing the conflict and providing a satisficing solution based on the customer requirements become essential. In this paper, we present an approach to manage the conflicts involved in designing a tundish. An integrated framework, by linking meta-models with compromise Decision Support Problem (cDSP) construct, is developed to determine a satisficing solution considering conflicting requirements. The utility of the framework is illustrated by providing decision support when an existing configuration for tundish is unable to meet the requirements. This has been done by exploring the design space of tundish and coming up with a design and operating set points suitable for a particular purpose. This approach can be instantiated for other unit operations involved in steel manufacturing. In the future, each unit operation can be integrated to provide a complete picture of steel manufacturing which in turn will help in reducing the time and cost incurred in the development of new materials and products.

Abstract The application of ceramic die coatings on tool steel dies in the casting industry has been common practice for many decades. The main function of these coatings is to provide a thermal barrier to prevent premature solidification during die filling, and protect the tool steel die from the effects of molten metal during casting with aluminium alloys. Although these coatings provide good insulation they are fragile and require on-going in-situ maintenance by machine operators. These inherent poor qualities makes the die casting process difficult to control and to maintain cast product quality because the solidification pattern and porosity changes and leads to increased cast product rejects. To overcome the limitations a novel die coat has been developed for the light metal casting industry utilising thermal spraying of co-deposited MgZrO2 and polymer particles. The coating is then thermally treated to reveal a fine network of porosity that has been found by heat transfer coefficient testing to enhance the thermal properties and overall coating durability during casting. This paper describes the porosity control system which was used to tailor the heat transfer coefficient of co-deposited MgZrO2 and polymer coatings and compare them with the heat transfer coefficient of commercially available die coats. The inherent porosity and the overall coating thickness were found to have a large effect on the heat transfer coefficient. Results of industrial trials are also presented and show that co-deposited MgZrO2 and polymer coatings provide considerable improvements to productivity and enhanced coating life in Gravity and Low Pressure Die casting of aluminium alloys.

Conventional manufacturing techniques have not been subject to much scrutiny by industrial ecologists to date. Many newer techniques and products draw more attention as they rise quickly from research to global scales, amplifying their environmental consequences. Despite the presence of new technologies and increased overseas production, casting activity continues to have a strong presence in the US, and represents a stable component in the national economy. Data from the US government, US industry groups, and UK mass balance profiles facilitate an understanding of sand casting and comparison across manufacturing processes. The figures in the US and UK are similar in terms of diversity of metals (where the US is 72%, 13%, 10% and the UK 76%, 13%, 8% for iron, aluminum, and steel, respectively), energy per ton of saleable cast metal (10.1 and 9.3 million Btu/ton in the US and UK), and overall emissions, with notable similarities in benzene and particulate emissions. One notable discrepancy is in sand use, where the US sends to waste 0.5 tons of sand per ton of cast metal, whereas the UK sends 0.25 tons to landfill.

Abstract Plasma transferred arc (PTA) allows to weld a metallic coating to a metal substrate in order to improve their wear and corrosion resistance. This process is mainly used for steel reclamation and the principal applications are coatings of valves, valve seats in automotive industry and extruder screws for plastic industry. This paper describes the tape casting of NiCu and NiCoCrAlTaY particles on Ni-based alloys and the various organic additives used in addition to a homogeneous metallic film. The initial results of treating these films with PTA regeneration are described. Paper includes a German-language abstract.

Abstract. The continuous casting process is one of the initial operations in the entire metal forming chain used in the metallurgical industry. The phenomena of solidification and unification of properties that occur during slab casting are highly dependent on the steel composition and the purity of the metal. The high cleanliness of steel is the determinant of the good quality of the final products, without internal cracks or inhomogeneities in mechanical, thermal or electrical properties. Therefore, one of the production goals is to avoid the non-metallic inclusions in the molten steel by intensifying their removal processes. One of the most important metallurgy equipment responsible for cleaning the steel is the ladle furnace, where special mixing processes are executed to increase the removal process of unfavourable elements. Another critical piece of equipment is the tundish, located just before the slab casting, which can additionally improve the microstructure final composition and homogeneity. Therefore, the investigations presented in the paper are centred on the development of an advanced Computational Fluid Dynamic (CFD) model of the flow behaviour of the molten steel inside the tundish. The key element of the model is to include the effect of an additional electromagnetic stirring device which can improve the cleanliness and the composition of the steel and hence its final properties. The role of this device is often omitted during practical research, but its direct influence on the properties of the steel has a clear impact on the characteristics of the formed metallic parts under further processing operations. Therefore, optimization of the process inside the tundish is essential from an industrial point of view. The paper includes a detailed analysis of the flow and stirring energy distributions to predict and understand the active and dead zones inside the tundish to avoid the regions with stagnant velocity distribution. As an outcome of such a developed coupled electromagnetic/fluid dynamic model, optimizing the mixing processes to control the product's properties is possible.

For more than 60 years now, the nuclear power industry has relied on structural and pressure retaining materials generated via established manufacturing practices such as casting, plate rolling-and-welding, forging, drawing, and/or extrusion. During the past three years, EPRI has been leading the development and introduction of another established process, powder metallurgy and hot isostatic pressing (PM/HIP), for pressure retaining applications in the electric power industry. The research includes assessment of two primary alloys: 316L stainless steel and Grade 91 creep-strength enhanced ferritic steels, for introduction into the ASME Boiler and Pressure Vessel Code. Continuing DOE and EPRI research on other structural/pressure retaining alloys such as Alloy 690, SA 508 Class 1, Alloy 625, hard-facing materials, and others are also underway. This research will have a tremendous impact as we move forward over the next few decades on the selection of new alloys and components for advanced light water reactors and small modular reactors. Furthermore, fabrication of high alloy materials/components may require the use of new manufacturing processes to achieve acceptable properties for higher temperature applications such as those in Generation IV applications. Current research by EPRI and DOE will be reviewed and emphasis will be targeted at advanced applications where PM/HIP may be applied in the future.