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International Journal of Quality & Reliability Management
ISSN : 0265-671X
Article publication date: 26 October 2021
Issue publication date: 17 January 2023
Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.
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Design/methodology/approach
A systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.
This study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.
Research limitations/implications
This paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.
Originality/value
The systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.
- Optimization
- Bibliometric analysis
Suthar, J. , Persis, J. and Gupta, R. (2023), "Critical parameters influencing the quality of metal castings: a systematic literature review", International Journal of Quality & Reliability Management , Vol. 40 No. 1, pp. 53-82. https://doi.org/10.1108/IJQRM-11-2020-0368
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Casting and Casting Processes
39 Pages Posted: 12 Jul 2017
D. G. Mahto
Green Hills Engineering College
Date Written: March 10, 2015
The casting process was discovered probably around 3500 BC in Mesopotamia. Casting is unique manufacturing processes for a variety of reasons. Perhaps the most obvious is the array of molding and casting processes available that are capable of producing complex components in any metal, ranging in weight from less than an ounce to single parts weighing several hundred tons. Foundry processes are available and in use that are economically viable for producing a single prototype part, while others achieve their economies in creating millions of the same part. Virtually any metal that can be melted can and is being cast. Many parts and components are made by casting, including automotive components such as carburettors, engine blocks, crankshafts, agricultural and rail road equipments, pipe and pumping fixtures, power tools, gun barrels and large components of hydraulic turbines etc. Since 1950, partially automated casting processes have been developed for production lines.It is estimated that castings are used in 90% or more of all manufactured goods and in all capital goods machinery used in manufacturing. The diversity in the end use of metal castings is a direct result of the many functional advantages and economic benefits that castings offer compared to other metal forming methods. The beneficial characteristics of a cast component are directly attributable to the inherent versatility of the casting process.
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Dalgobind Mahto (Contact Author)
Green hills engineering college ( email ).
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Continuous casting preparation process of helical fiber-reinforced metal matrix composites.
![ORCID research paper on casting process](https://pub.mdpi-res.com/img/design/orcid.png?0465bc3812adeb52?1721979229)
1. Introduction
2. experimental section, 2.1. design and manufacturing of experimental equipment, 2.2. material, 2.3. process parameters, 2.4. testing, 2.4.1. the shape of helical carbon fiber in composites, 2.4.2. interface and mechanical property of helical carbon fiber-reinforced aluminum composites, 3.1. coordinate system, 3.2. basic assumptions, 3.3. the formation processing of helical fiber, 3.3.1. initial state, 3.3.2. transition state, 3.3.3. stable state, 3.4. the angle θ a b difference between point a and point b, 4. results and discussion, 4.1. shape stability of helical carbon fiber in lead matrix, 4.2. influence of process parameters on the shape of helical carbon fiber in lead matrix, 4.2.1. melting temperature, 4.2.2. cooling intensity, 4.2.3. carbon fiber rotation speed, 4.3. prediction of the helical fiber shape, 4.4. helical carbon fiber-reinforced aluminum matrix composites, 4.4.1. the shape of helical carbon fiber, 4.4.2. interface of carbon fiber and aluminum matrix, 4.4.3. mechanical properties, 5. conclusions, author contributions, data availability statement, conflicts of interest.
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Click here to enlarge figure
Fiber Diameter | Strength (GPa) | Modulus (GPa) | Elongation (%) | Density ) |
---|---|---|---|---|
7 | 3.5 | 230 | 1.5 | 1.78 |
Parameters | Range | |
---|---|---|
Lead Matrix | Aluminum Matrix | |
Carbon fiber rotation speed | 0.67, 1.33 | 0.67 |
Carbon rotation radius | 7.0 | 7.0 |
Melt temperature | 490, 500, 510, 520 | 780 |
Cooling intensity | 350, 450 | 450 |
Continuous casting speed | 5.5 | 5.5 |
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Share and Cite
Yang, H.; Chang, M.; Wu, C. Continuous Casting Preparation Process of Helical Fiber-Reinforced Metal Matrix Composites. Metals 2024 , 14 , 832. https://doi.org/10.3390/met14070832
Yang H, Chang M, Wu C. Continuous Casting Preparation Process of Helical Fiber-Reinforced Metal Matrix Composites. Metals . 2024; 14(7):832. https://doi.org/10.3390/met14070832
Yang, Hui, Ming Chang, and Chunjing Wu. 2024. "Continuous Casting Preparation Process of Helical Fiber-Reinforced Metal Matrix Composites" Metals 14, no. 7: 832. https://doi.org/10.3390/met14070832
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A Critical Review on Casting Types and Defects
![research paper on casting process Profile image of International Journal of Scientific Research in Science, Engineering and Technology IJSRSET](https://0.academia-photos.com/34217662/10032703/11190824/s65_ijsrset.e-journal.jpg)
Casting is the oldest manufacturing method and well known metallurgical process. Casting process basically involves introduction of molten metal into a mold cavity and subsequently the molten metal takes the shape of mold cavity. Very simple and high end complicated shapes and designs can be made from any metal that can be melted. Casting is an integrated process which is considered as an experienced artful work with high end quality aspects. Even though these high quality aspects are considered, defects are very much inherent in casting process. The main objective of the current review is to explain casting types and discuss the possible defects during the process of casting. The scope of the review also includes causes and remedies of casting defects.
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IJAR Indexing
Casting is the one of the oldest manufacturing processes, and even today is the first step in manufacturing most product. In this process the material is first liquefied by proper heating and then this liquefied is poured into a previously prepared mould cavity where it is allowed to solidify and subsequently the product is taken out, cleaned and trimmed to the required shape. During this process there are different critical factors which is contributing in large amount to the defects. These factors are: 1. Design of casting and pattern 2. Moulding sand and design of mould and core. 3. Metal composition. 4. Melting and pouring. 5. Gating system.
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SUPRIYA PRIYADARSINI
Now a day's casting plays a key role for manufacturing industries so its performance should be highly effective in terms of production with minimum number of rejections. So casting yield should be high which can be achieved in highly controlled environment where defects can be minimised so as to minimise the rejections. The challenges of casting defects are to be identified and minimised for effective castings. This paper aims to analyse the causes of different types of defects and provides the remedial measures which will be helpful in improving the quality of product along with increase the productivity. This paper enlists various defects in casting and provides the causes of their occurrence, which will help to analyse the undesirable defects in casting.
IAEME Publication
Casting process is associated with some casting defects that degrade the quality of foundry product. To upgrade the productivity of the organization the casting defects should be minimized. This paper shows the different literature review and root causes of casting defects taken by the different foundry expert's.
IJERA Journal , Madhukar Sorte , Vaibhav Ingle
Many industry aims to improve quality as well as productivity of manufacturing product. So need to number of process parameter to must controlled while casting process, so there are no of uncertainty and defects are face by organizations. In casting process industries are need to technical solution to minimize the uncertainty and defects. In this review paper to represent various casting defects and root causes for engine parts while casting process. Also provide preventive action to improve quality as well as productivity an industrial level.
IAEME PUBLICATION
Global buyers demand defect-free castings and strict delivery schedule, which foundries are finding it verydifficult to meet. Metal casting industry suffers from poor quality and productivity due to the large number of process parameters, combined with lower penetration of manufacturing automation. Casting process involves complex interactions among various parameters and operations related to metal composition, methods design, molding, melting, pouring, shake-out, fettling and machining. For example, if shrinkage porosity is identified as gas porosity, and the pouring temperature is lowered to reduce the same, it may lead to another defect, namely cold shut. Casting defects result in increased unit cost and lower morale of shop floor personnel.Casting defect analysis has been carried out using techniques like cause-effect diagrams, design of experiments, if-then rules (expert systems), and artificial neural networks. Most of the previous work is focused on finding process-related causes for individual defects, and optimizing the parameter values to reduce the defects.The defects are classified in terms of their appearance, size, location, consistency, discovery stage and inspection method. This helps in correct identification of the defects. For defect analysis, the possible causes are grouped into design, material and process parameters. The effect of suspected cause parameters on casting quality is ascertained through simulation. Based on the results and their interpretation, the optimal values of the parameters are determined to eliminate the defects. An integrated understanding of heat transfer during solidification, friction/lubrication at solid–liquid interface, high temperature properties of the solidifying shell etc. is necessary to control the casting process.The influence of steel chemistry on solidification dynamics, particularly with respect to mode of solidification and its consequence on strength and ductility of the solidifying shell, has been dealt with in detail. The application of these basic principles for casting of stainless steel slabs and processing to obtain good quality products has been covered. Castings can unfortunately also sometimes contain other types of defects, such as inclusions of slag or moulding sand, but these are not classified as solidification defects.
Revue des composites et des matériaux avancés
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More reliable and durable parts with high structural integrity are required to meet the increasing advancements in science and technology. This paper reviews five (5) different casting techniques: squeeze casting, sand casting, investment casting, die casting, and continuous casting. Their respective cast products were examined, and their various mechanical properties were discussed. However, these different casting techniques involve a similar fundamental procedure: melting metal, pouring it into a mold, and allowing it to solidify. However, they vary in their physical and mechanical properties, durability, and surface finishing, making one technique more desirable than the other in their application areas. Some techniques were found to be more advantageous and effective than the other, which will aid foundrymen in making the best decision in choosing a technique, considering parameters such as environmental friendliness and cost implications. The appropriate implementation of thes...
Mohammed Ismail
An attempt has been made to describe the casting metallic mold in brief and review the major casting process based on a set of criteria such as step involved, process conceptualization, advantages, disadvantages, and their applications. In addition, the most defects of the casting process are also presented in this study. Based on this review, it can be observed that numerous casting methods are founded and the selection of a process is depend on several factors such as the quality of the casting surface, dimension accuracy, rate production, shape complexity and cost .etc.
International Journal of Scientific Research in Science, Engineering and Technology IJSRSET
Casting process is the most widely used process in manufacturing industries. Production of casting involves various processes like pattern making, molding, and core making and melting. It is very difficult to produce defect free castings. Systematic analysis and identification of sources of product defects are essential for successful manufacturing. Since the quality of casting parts are mostly influenced by process conditions, how to determine the optimum process condition becomes the key to improving part quality. The industry generally tries to eliminate the defects by trial and error method. This paper describes the identification and analysis of the casting defects. Filling related defects, Shape related defects and Thermal related defects of casting products are discussed in this paper. Defects occurred by various gating system parameters are also be identified. So good gating system reduces the defects.
Gourav Vivek Kulkarni
Gourav Kulkarni
In recent times, with the constant utilization of natural resources, every manufacturing unit is turning towards a lean approach. Foundries are no exception to this. Although the fundamental responsibility of a foundry is simply to convert raw metal into a useful casting, it is imperative on their part that the output confirms with the quality as desired and is free from defects of any kind. However, there may be factors like the rate of cooling of molten metal being poured, mould properties, metallurgy of the molten metal being poured and the mould geometry and rigidity to name a few which may have their influence on the casting quality and the overall productivity of the foundry. While striking a balance between the quality and productivity, there may be certain deviations undertaken from the regular course that may lead to casting defects. This paper intends to highlight such interdependencies and suggest indirectly the most feasible means to control casting defects in order to ensure attainment of both quality and productivity. Casting defects considered for this work shall be those observed at a major scale and those which require adequate attention on account of frequency of occurrence. A conclusion shall be drawn towards the end dictating the major findings of the study.
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The paper presents the study of internal defects resulting from the continuous casting of steels. The 50 samples were taken from a total of 20 continuously cast bits of different steel grades. The investigation of the causes of internal defects, shown on the analyzed samples, started from the assumption that the secondary metallurgy was performed correctly. The following internal defects have been evident: internal cracks (axial cracks, section cracks), central porosity and marginal punctuation impurities.
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Influence of Casting Materials on the Microstructure and Mechanical Properties of Gray Cast Iron for Cylinder Liners
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- Shouquan Du ORCID: orcid.org/0009-0004-1551-9507 1 ,
- Chaoyang Chen 2 ,
- Ruirun Chen 1 , 2 ,
- Qi Wang 2 ,
- Xiangyin Cui 1 &
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In this paper, four different casting materials were used to get gray cast iron samples, the effects of different cooling rates caused by different casting materials on graphite distribution, matrix structure and mechanical properties were investigated. The experimental results show that as the cooling rate increases, the graphite form of gray cast iron changed from coarse flake A-type graphite to rosette shaped B-type graphite, graphite increased in quantity and was more evenly distributed. The interlayer spacing of pearlite in matrix decreased with the increase of cooling rate, four different mold casting of cast iron material sample of pearlite lamellar spacing is CO 2 sodium silicate bonded sand mold, 340 nm, oxide ceramic mold, 275 nm, cast iron mold, 141 nm, graphite casting mold, 135 nm, respectively. The reduction of the interlayer spacing of pearlite also significantly improves the tensile strength, compressive strength and hardness. The tensile strength of cast iron specimens cast in graphite casting molds is the highest, at 421 MPa, while the tensile strength of cast iron specimens cast in CO 2 sodium silicate bonded sand molds is the lowest, at 346 MPa. The graphite cast iron sample has the highest compressive strength of 2165 MPa, and the oxide ceramic cast iron sample has the lowest compressive strength of 1115 MPa. The Brinell hardness of the samples cast in cast iron molds is the highest, at 409 HB, while the samples cast in CO 2 sodium silicate bonded sand molds have the lowest Brinell hardness, at 255 HB. In addition, increasing the cooling rate inhibited the diffusion of elements in the melt, reduced the final solidification interval and also reduced the shrinkage porosity and other defects. Fracture analysis shows that cleavage fracture is the main fracture mode of castings. The higher the cooling rate, the smoother the fracture morphology.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Nos. 52425401 and 52374384), Foundation of National Key Laboratory for Precision Hot Processing of Metals (JCKYS2021603C001).
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Du, S., Chen, C., Chen, R. et al. Influence of Casting Materials on the Microstructure and Mechanical Properties of Gray Cast Iron for Cylinder Liners. Inter Metalcast (2024). https://doi.org/10.1007/s40962-024-01413-6
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Machine learning unlocks secrets to advanced alloys
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![research paper on casting process Graphic showing a grid of dots representing atoms in cyan, magenta, and yellow. There are about 40 dots in total.](https://news.mit.edu/sites/default/files/styles/news_article__image_gallery/public/images/202407/sro-high-entropy-alloys_0.png?itok=EUdKQ0mf)
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The concept of short-range order (SRO) — the arrangement of atoms over small distances — in metallic alloys has been underexplored in materials science and engineering. But the past decade has seen renewed interest in quantifying it, since decoding SRO is a crucial step toward developing tailored high-performing alloys, such as stronger or heat-resistant materials.
Understanding how atoms arrange themselves is no easy task and must be verified using intensive lab experiments or computer simulations based on imperfect models. These hurdles have made it difficult to fully explore SRO in metallic alloys.
But Killian Sheriff and Yifan Cao, graduate students in MIT’s Department of Materials Science and Engineering (DMSE), are using machine learning to quantify, atom-by-atom, the complex chemical arrangements that make up SRO. Under the supervision of Assistant Professor Rodrigo Freitas, and with the help of Assistant Professor Tess Smidt in the Department of Electrical Engineering and Computer Science, their work was recently published in The Proceedings of the National Academy of Sciences .
Interest in understanding SRO is linked to the excitement around advanced materials called high-entropy alloys, whose complex compositions give them superior properties.
Typically, materials scientists develop alloys by using one element as a base and adding small quantities of other elements to enhance specific properties. The addition of chromium to nickel, for example, makes the resulting metal more resistant to corrosion.
Unlike most traditional alloys, high-entropy alloys have several elements, from three up to 20, in nearly equal proportions. This offers a vast design space. “It’s like you’re making a recipe with a lot more ingredients,” says Cao.
The goal is to use SRO as a “knob” to tailor material properties by mixing chemical elements in high-entropy alloys in unique ways. This approach has potential applications in industries such as aerospace, biomedicine, and electronics, driving the need to explore permutations and combinations of elements, Cao says.
Capturing short-range order
Short-range order refers to the tendency of atoms to form chemical arrangements with specific neighboring atoms. While a superficial look at an alloy’s elemental distribution might indicate that its constituent elements are randomly arranged, it is often not so. “Atoms have a preference for having specific neighboring atoms arranged in particular patterns,” Freitas says. “How often these patterns arise and how they are distributed in space is what defines SRO.”
Understanding SRO unlocks the keys to the kingdom of high-entropy materials. Unfortunately, not much is known about SRO in high-entropy alloys. “It’s like we’re trying to build a huge Lego model without knowing what’s the smallest piece of Lego that you can have,” says Sheriff.
Traditional methods for understanding SRO involve small computational models, or simulations with a limited number of atoms, providing an incomplete picture of complex material systems. “High-entropy materials are chemically complex — you can’t simulate them well with just a few atoms; you really need to go a few length scales above that to capture the material accurately,” Sheriff says. “Otherwise, it’s like trying to understand your family tree without knowing one of the parents.”
SRO has also been calculated by using basic mathematics, counting immediate neighbors for a few atoms and computing what that distribution might look like on average. Despite its popularity, the approach has limitations, as it offers an incomplete picture of SRO.
Fortunately, researchers are leveraging machine learning to overcome the shortcomings of traditional approaches for capturing and quantifying SRO.
Hyunseok Oh , assistant professor in the Department of Materials Science and Engineering at the University of Wisconsin at Madison and a former DMSE postdoc, is excited about investigating SRO more fully. Oh, who was not involved in this study, explores how to leverage alloy composition, processing methods, and their relationship to SRO to design better alloys. “The physics of alloys and the atomistic origin of their properties depend on short-range ordering, but the accurate calculation of short-range ordering has been almost impossible,” says Oh.
A two-pronged machine learning solution
To study SRO using machine learning, it helps to picture the crystal structure in high-entropy alloys as a connect-the-dots game in an coloring book, Cao says.
“You need to know the rules for connecting the dots to see the pattern.” And you need to capture the atomic interactions with a simulation that is big enough to fit the entire pattern.
First, understanding the rules meant reproducing the chemical bonds in high-entropy alloys. “There are small energy differences in chemical patterns that lead to differences in short-range order, and we didn’t have a good model to do that,” Freitas says. The model the team developed is the first building block in accurately quantifying SRO.
The second part of the challenge, ensuring that researchers get the whole picture, was more complex. High-entropy alloys can exhibit billions of chemical “motifs,” combinations of arrangements of atoms. Identifying these motifs from simulation data is difficult because they can appear in symmetrically equivalent forms — rotated, mirrored, or inverted. At first glance, they may look different but still contain the same chemical bonds.
The team solved this problem by employing 3D Euclidean neural networks . These advanced computational models allowed the researchers to identify chemical motifs from simulations of high-entropy materials with unprecedented detail, examining them atom-by-atom.
The final task was to quantify the SRO. Freitas used machine learning to evaluate the different chemical motifs and tag each with a number. When researchers want to quantify the SRO for a new material, they run it by the model, which sorts it in its database and spits out an answer.
The team also invested additional effort in making their motif identification framework more accessible. “We have this sheet of all possible permutations of [SRO] already set up, and we know what number each of them got through this machine learning process,” Freitas says. “So later, as we run into simulations, we can sort them out to tell us what that new SRO will look like.” The neural network easily recognizes symmetry operations and tags equivalent structures with the same number.
“If you had to compile all the symmetries yourself, it’s a lot of work. Machine learning organized this for us really quickly and in a way that was cheap enough that we could apply it in practice,” Freitas says.
Enter the world’s fastest supercomputer
This summer, Cao and Sheriff and team will have a chance to explore how SRO can change under routine metal processing conditions, like casting and cold-rolling, through the U.S. Department of Energy’s INCITE program , which allows access to Frontier , the world’s fastest supercomputer.
“If you want to know how short-range order changes during the actual manufacturing of metals, you need to have a very good model and a very large simulation,” Freitas says. The team already has a strong model; it will now leverage INCITE’s computing facilities for the robust simulations required.
“With that we expect to uncover the sort of mechanisms that metallurgists could employ to engineer alloys with pre-determined SRO,” Freitas adds.
Sheriff is excited about the research’s many promises. One is the 3D information that can be obtained about chemical SRO. Whereas traditional transmission electron microscopes and other methods are limited to two-dimensional data, physical simulations can fill in the dots and give full access to 3D information, Sheriff says.
“We have introduced a framework to start talking about chemical complexity,” Sheriff explains. “Now that we can understand this, there’s a whole body of materials science on classical alloys to develop predictive tools for high-entropy materials.”
That could lead to the purposeful design of new classes of materials instead of simply shooting in the dark.
The research was funded by the MathWorks Ignition Fund, MathWorks Engineering Fellowship Fund, and the Portuguese Foundation for International Cooperation in Science, Technology and Higher Education in the MIT–Portugal Program.
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- Long paper : Long papers are research or experience papers describing research results, case studies, or insights from industry experience. A research or experience full paper is up to 10 pages plus a maximum of 2 pages for references.
- Short paper : Papers describing new challenges, new research results, visionary ideas, or experiences from, or in cooperation with, practitioners are welcome as short papers. In-progress research with interim results is also appropriate for a short paper. A short paper is up to 5 pages plus a maximum of 1 page for references.
The paper submissions will undergo a double-anonymous review process with three independent reviews and a virtual PC discussion. Acceptance criteria include contribution to the field of software engineering for AI, novelty, research and industrial relevance, soundness, and results. The accepted full and short papers will be published in the ICSE Companion proceedings.
If a paper is rejected as a long paper because the reviewers consider that the research is in the early stages or lacking evaluation, the paper will be reevaluated as a short paper. If accepted as a short paper, authors can choose to accept or decline to resubmit as a short paper.
Important Dates
- Abstracts: Nov 19, 2024, AoE (recommended; used for bidding)
- Papers: Nov 26, 2024, AoE (firm; no extensions)
- Notifications: Jan 21, 2025, AoE
- Camera Ready: Feb 12, 2025, AoE
Scope and Topics of Interest
The area of interest for CAIN is Software Engineering for AI — improving the development of AI-based systems throughout the full life cycle. Topics include but are not limited to:
- System and software requirements and their relationship to AI/ML modeling.
- Data management ensuring relevance and efficiency related to business goals.
- System and software architecture for AI-enabled systems.
- Integration of AI and software development processes into the AI system development life cycle, including continuous integration and deployment, and system and software evolution.
- Ensuring and managing system and software nonfunctional properties and their relationship to AI/ML properties, including runtime properties such as performance, safety, security, and reliability; and life-cycle properties including reusability, maintainability and evolution.
- Collaboration, organizational, and management practices for a successful development of AI-enabled systems.
- Building effective infrastructures to support development of AI systems and components.
- Further clarifications on the CAIN Scope
Note: Submissions that report strictly on data science or model development without any connection to software engineering and AI-enabled systems will be desk-rejected. As stated earlier, there are many venues for those papers where authors would get much more valuable and relevant feedback.
Submission Form
Research and experience papers should be submitted to (TBA). The submission deadline is firm, no extensions.
All submissions must adhere to the following requirements:
- Page limit is 10 pages plus 2 additional pages of references for long papers and 5 pages plus 1 additional page for references for short papers.
- Submissions must be unpublished original work and should not be under review or submitted elsewhere while being under consideration.
- By submitting to CAIN, authors acknowledge that they are aware of and agree to be bound by the ACM Policy and Procedures on Plagiarism and IEEE Plagiarism FAQ . The authors also acknowledge that they conform to the authorship policy of the ACM and the authorship policy of the IEEE .
- Authors’ names must be omitted from the submitted paper.
- All references to the author’s prior work should be in the third person.
- Authors are encouraged to title their submission differently than preprints of the authors on ArXiV or similar sites. During review, authors should not publicly use the submission title.
Submissions must conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf options).
Accepted papers will be published in the ICSE 2025 Co-located Event Proceedings and included in the IEEE and ACM Digital Libraries. Authors of accepted papers are required to register and present their accepted paper at the conference in order for the paper to be included in the proceedings and the Digital Libraries.
The official publication date is the date the proceedings are made available in the ACM or IEEE Digital Libraries. This date may be up to two weeks prior to the first day of ICSE 2025. The official publication date affects the deadline for any patent filings related to published work.
Authors of papers receiving a Conditional Accept decision are expected to submit the revised papers with changes marked in a different color, such as using LaTeXdiff. The authors also need to submit an “Author Response” document capturing the authors’ response to each reviewer comment and how those comments were addressed in the revision. This is similar to the “Summary of Changes and Response” document that is typically submitted by authors for a journal paper major revision. The reviewers will check the revised paper against the original paper and the suggested changes. Conditional Accepts will be checked by only one member of the Program Committee, and this will be done in one pass.
Authors of rejected long papers may receive an acceptance as a short paper if the PC chairs and reviewers agree that it better meets the criteria for short papers. In this case, authors may decide to accept or reject the invitation if they would rather submit as a long paper to a different venue.
Similarly, authors of rejected long and short papers relevant to the field of AI Engineering may have their papers sent to a different CAIN track. Also in this case, authors may decide to accept or reject the invitation.
Submission Process
Research and experience papers should be submitted to HotCrp (link TBD). The submission deadline is firm, with no extensions.
- Submissions must be in PDF and strictly conform to the IEEE conference proceedings formatting instructions. Alterations of spacing, font size, and other changes that deviate from the instructions may result in desk rejection without further review.
- All submissions must conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTeX users must use \documentclass[10pt, conference]{IEEEtran} without including the compsoc or compsocconf options). Submissions must strictly conform to the IEEE conference proceedings formatting instructions specified above. Alterations of spacing, font size, and other changes that deviate from the instructions may result in desk rejection without further review.
- By submitting to CAIN, authors acknowledge that they are aware of and agree to be bound by the ACM Policy and Procedures on Plagiarism and the IEEE Plagiarism FAQ. Papers submitted to CAIN 2025 must not have been published elsewhere and must not be under review or submitted for review elsewhere while under consideration for CAIN 2025. Contravention of this concurrent submission policy will be deemed a serious breach of scientific ethics, and appropriate action will be taken in all such cases. To check for double submission and plagiarism issues, the chairs reserve the right to (1) share the list of submissions with the PC Chairs of other conferences with overlapping review periods and (2) use external plagiarism detection software, under contract to the ACM or IEEE, to detect violations of these policies.
- By submitting to the CAIN, authors acknowledge that they conform to the authorship policy of the ACM, and the authorship policy of the IEEE.
- If the research involves human participants/subjects, the authors must adhere to the ACM Publications Policy on Research Involving Human Participants and Subjects. Upon submitting, authors will declare their compliance with such a policy. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.
- Please ensure that you and your co-authors obtain an ORCID ID, so you can complete the publishing process for your accepted paper. ACM and IEEE have been involved in ORCID and may collect ORCID IDs from all published authors. We are committed to improve author discoverability, ensure proper attribution and contribute to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.
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Watershed Process and Estuary Sustainability Research Group
Wpes begins new colorado river sediment mapping project.
The WPES research group has initiated a new collaborative project focused on mapping channel bottom textures in the Colorado River below Glen Canyon Dam. The work uses data acquired by the USGS during previous river measurement expeditions and expands on techniques described by Buscombe, Grams, and Smith (2015) . The research has relevance to river management decision making, coincidently the focus of interviews on PBS News Hour this week that includes WPES colleague, Dr. Jack Schmidt, from Utah State University.
![research paper on casting process](https://umaine.edu/watershedresearch/wp-content/uploads/sites/554/2024/07/20190414_171405-1024x253.jpg)
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COMMENTS
In this paper the statistical analysis is aimed to optimize process parameters at the case study, i.e. Akaki Basic Metals Industry (ABMI) in Addis Ababa Ethiopia, to minimize major steel casting ...
Abstract: On the way to building smart factories as the vision of Industry 4.0, the casting process. stands out as a specific manufacturing process due to its diversity and complexity. One of the ...
Introduction. Casting is a process in which molten metal flows by gravity or other force into a mold. where it solidifies in the shape of the mold cavity. The term casting also applies to the part ...
The International Journal of Cast Metals Research is devoted to the dissemination of peer reviewed information on the science and engineering of cast metals, solidification and casting processes. Assured production of high integrity castings requires an integrated approach that optimises casting, mould and gating design; mould materials and binders; alloy composition and microstructure; metal ...
On the way to building smart factories as the vision of Industry 4.0, the casting process stands out as a specific manufacturing process due to its diversity and complexity. One of the segments of smart foundry design is the application of artificial intelligence in the improvement of the casting process. This paper presents an overview of the conducted research studies, which deal with the ...
This paper reviews and summarizes the research history and current situation of numerical simulation of casting process. The progress in numerical simulation from five aspects of casting solidification, casting filling, stress field, microstructure, commercial software, is presented.
Continuous casting is a process whereby molten metal is solidified into semi-finished billets, blooms, slabs or strips for subsequent rolling in finishing mills; it is the most frequently used process to cast not only steel, but also aluminum and copper alloys, with the main configurations being as shown in Figure 1.
Casting is a process in which a molten material flows into a mold and is allowed to solidify, taking the shape of the mold. Casting can be done simply (such as gravity-pouring metal into an open mold), or it can be part of a complex process (such as forming a semisolid slurry that is injected into a closed metal mold).
[4] has done a research on minimisation of casting defects by analysing the root causes of some casting defects in ABMI industries. In this paper the statistical analysis is aimed to optimize process parameters at the case study, i.e., Akaki Basic Metals Industry (ABMI) in Addis Ababa Ethiopia, to minimize major steel casting defects.
For the purpose of this paper, process knowledge is defined and understood based on Roshan’s definition. Figure 1 below summarises and illustrates the concept of process knowledge. ... Sand Casting process and sustainability Sand casting also known as sand moulding is a metal manufacturing process categorized by utilizing sand as an ...
Purpose. Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration.
Much research has been carried out on the casting process of the automobile wheel. Zhang et al. [ 1 ] developed a mathematical model of the low-pressure die-casting process for the production of A356 aluminum alloy wheels to predict the evolution of temperature within the wheel and die.
Casting defect analysis is the process of finding root causes of occurrence of defects in the rejection of casting and taking necessary step to reduce the defects and to improve the casting yield. In this review paper an attempt has been made to provide all casting related defect with their causes and remedies.
The casting process was discovered probably around 3500 BC in Mesopotamia. Casting is unique manufacturing processes for a variety of reasons. Perhaps the most obvious is the array of molding and casting processes available that are capable of producing complex components in any metal, ranging in weight from less than an ounce to single parts ...
To improve the strength of the metal while maintaining good plasticity, helical fibers are added to the metal matrix. How to form helical fiber and control its parameters in the preparation process are urgent problems to be solved in the study of helical fiber-reinforced metal matrix composites. In this paper, the continuous casting process of helical fiber-reinforced metal matrix composites ...
Casting defect analysis is the process of finding root causes of occurrence of defects in the rejection of casting and taking necessary step to reduce the defects. A proper methodology is formed consisting of various quality control tools such as Pareto analysis, Ishikawa diagram (cause and effect diagram), brainstorming, why-why analysis.
The present study delves into the intricate domain of advanced casting processes, with a specific emphasis on the areas of design, simulation, and process control.
casting. Casting is the process of filling the liquid metal into a shaped mould to get the desired shape of the product. Filling the mold casting process affects significantly the heat transfer & solidification of the melt. A finite element formulation is to be used for it, which gives temperature profiles at different time steps.
International Journal of Scientific Research in Science, Engineering and Technology (ijsrset.com) 464 However, flaws are very common in sand cast parts and these affects the properties of castings. 2.1.2 DIE CASTING Die casting is a metal casting process that is characterized by forcing molten metal under high pressure into a mold cavity. The mold cavity is created using two hardened tool ...
In this paper, four different casting materials were used to get gray cast iron samples, the effects of different cooling rates caused by different casting materials on graphite distribution, matrix structure and mechanical properties were investigated. The experimental results show that as the cooling rate increases, the graphite form of gray cast iron changed from coarse flake A-type ...
The objective of the paper is provide a comparative study of mold fabrication between traditional sand casting process and new developed 3D printing process. This paper is arranged as follows. In Section 2, the process of 3D printed moldand core will be prese nted due to its uniqueness, followed by assembly of the mold components.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 ... centrifugal casting process studied based on results of complete simulation. Rupesh Kumar Verma Manoj Chocolate [3] This paper delivers a review of the influence of material and process ...
DOI: 10.1016/j.applthermaleng.2024.124005 Corpus ID: 271342408; Research on temperature field and thermal deformation characteristics of casting rollers in twin-roll casting process
Sheriff is excited about the research's many promises. One is the 3D information that can be obtained about chemical SRO. Whereas traditional transmission electron microscopes and other methods are limited to two-dimensional data, physical simulations can fill in the dots and give full access to 3D information, Sheriff says.
These brief, peer-reviewed articles complement full research papers and are an easy way to receive proper credit and recognition for the work you have done. Research elements are research outputs that have come about as a result of following the research cycle - this includes things like data, methods and protocols, software, hardware and more.
A case study detailing concentrations and chemical compositions of microplastic fibers in Frenchman Bay and its upstream estuaries and rivers has been published in the journal Environmental Engineering Science. The paper, Land-Sea Connection of Microplastic Fiber Pollution in Frenchman Bay, Maine, reveals that as many as 400 billion microplastic fibers may be found in the […]
48. Quality improvement of a casting process using design of experiments. 1.INTRODUCTION. Most of the pumping and allied components in today's. world are produced by metal casting. Sand casting ...
Call for Submissions We invite submissions of research and experience papers in two categories: Long paper: Long papers are research or experience papers describing research results, case studies, or insights from industry experience. A research or experience full paper is up to 10 pages plus a maximum of 2 pages for references. Short paper: Papers describing new challenges, new research ...
The WPES research group has initiated a new collaborative project focused on mapping channel bottom textures in the Colorado River below Glen Canyon Dam. The work uses data acquired by the USGS during previous river measurement expeditions and expands on techniques described by Buscombe, Grams, and Smith (2015). The research has relevance to river management […]
Turkiye's defence industry has undergone dramatic changes over the last 50 years and the country has become a significant defence exporter. In this report, as part of a joint project with the IISS, researchers from the Center for Foreign Policy and Peace Research explore this process and the issues lying ahead.