Comparative Evaluation of Insulation Cotton Configuration on The Investment Casting Quality of Industrial Valve Parts

Comparative Evaluation of Insulation Cotton Configuration on The Investment Casting Quality of Industrial Valve Parts | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Evaluation of Insulation Cotton Configuration on The Investment Casting Quality of Industrial Valve Parts Kao-Yi Chen, Sukhoiri Khoiruddin, Chieh-Fong Lin, Ming-Hsiu Ho, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4015116/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Aug, 2024 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 5 You are reading this latest preprint version Abstract This study contributed to the comparison of insulation cotton configurations for the investment casting quality of industrial valve parts. Due to the complexity, parts of industrial valve bodies are usually produced by casting. However, the investment casting production process has several problems, such as shrinkage porosity. Currently, the investment casting industry uses cotton configuration to solve the problem of shrinkage porosity. Therefore, this study compared three cotton installation treatments in the mould shell to determine the optimal use of cotton. There are three schemes of the type of cotton installation on the shell that will be observed, including the triangular insulation cotton area denoted as Case A installed 55mm and Case B installed 90mm cotton on the right and left sides, and Case C denoted with adding bracket arms on the upper side. In this study, we used RMM (Retained Melt Modulus) and the finite element model to analyze the shrinkage porosity's location and to monitor the porosity that occurred during the solidification process. The result showed that cotton could reduce shrinkage porosity by 3.30%, 1.95%, and 1.47% for Case A, Case B, and Case C, respectively. Therefore, the best alternative is to add the cotton and bracket arm on the upper side, which is the optimal strategy to prevent shrinkage porosity. Investment Casting Insulation Cotton Configurations Shell Making Shrinkage Porosity Finite Element Model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. Introduction Industrial instruments and valve systems are exposed to high pressures where there is an increased risk of component corrosion and leakage. Industrial valve bodies are usually produced by casting. However, due to casting defects, the sealing performance of components and the mechanical strength will be significantly reduced, impacting economic losses or instability in the production process [1–4]. Precision casting is usually used to manufacture products with smooth surfaces and complex geometric shapes [5–10]. The process of creating investment cast valve bodies is very complex and has substantial differences in thickness ratios, causing compaction shrinkage during the casting process to be non-linear [11–12]. Nowadays, advanced computer-aided engineering (CAE) simulation has many advantages in product improvement, such as product quality, reduction of production costs, and shortening of production cycles [13–15]. Computer-aided engineering simulation analysis is the most effective and profitable technology for evaluating casting quality and predicting defects [16–18]. Casting defects are complicated to predict because it cannot check the flow of solidification trends of molten metal in the mold cavity [8] [12] [17]. Furthermore, the RMM (Retained Melt Modulus) model helps predict the location of shrinkage cavities and then focuses on processing the locations where defects occur and using various means to make the solidification trend more ideal and continuous. Currently, most casting manufacturers use CAE simulation technology to conduct trial production and verification; This study contributed to the comparison of insulation cotton configurations for the investment casting quality of industrial valve parts. Due to the complexity, parts of industrial valve bodies are usually produced by casting. However, the investment casting production process has several problems, such as shrinkage porosity. Currently, the investment casting industry uses cotton configuration to solve the problem of shrinkage porosity. Therefore, this study compared three cotton installation treatments in the mould shell to determine the optimal use of cotton. There are three schemes of the type of cotton installation on the shell that will be observed, including the triangular insulation cotton area denoted as Case A installed 55mm and Case B installed 90mm cotton on the right and left sides, and Case C denoted with adding bracket arms on the upper side. In this study, we used RMM (Retained Melt Modulus) and the finite element model to analyze the shrinkage porosity's location and to monitor the porosity that occurred during the solidification process. The result showed that cotton could reduce shrinkage porosity by 3.30%, 1.95%, and 1.47% for Case A, B, and C, respectively. Therefore, the best alternative is to add the cotton and bracket arm on the upper side, which is the optimal strategy to prevent shrinkage porosity. and improvement of design plans before they can finally proceed to commercial mass production. According to industrial observations, about 5–10% of castings contain casting defects, such as geometric distortion, cracks, flash, slag inclusions, and shrinkage cavities. Defect generation does not depend on the design of the casting plan. Various parameters of the process, from the front wax injection to the generation of the middle shell mold, will affect the generation of casting defects [20]. Of all the factors that deteriorate the properties of castings, macro segregation, and shrinkage porosity are the most important because it is difficult to reduce these defects through subsequent thermomechanical treatment. The rapid development of computer calculations, solidification, segregation and even microstructure evolution All can be predicted by simulating the casting process. In this way, casting has progressed from the invisible to the visible. Therefore, the development of castings that combine computer simulation and non-destructive inspection technology is very attractive because it has many advantages, namely improved quality, reduced costs, and shortened pre-production time [21]. Commonly, the shrinkage cavities are dependent on the geometry of the gating system and the casting process. Previous research revealed by Yu et al [21] that the optimization process often requires understanding the geometry of the gating system and complex process parameters, along with the use of data analysis for producing optimized parameter results, which improve casting quality and shorten design cycles. The study uses machine learning based on RBF (radial basis functions neural network) to design a casting plan targeting porosity-free and high casting. The results show that optimizing gate design can increase the yield of finished castings by 14.91%. Minimizing the PES (percentage of elements with shrinkage defect) value is the indicator of obtaining a good casting system [23–25]. Therefore, we designed and analyzed three different types of gate systems based on the numerical method to calculate the casting process of 316L stainless steel valve housing, which was found in the shrinkage porosity simulation results. 2. Material and Methods 2.1 Internal defects of castings Shrinkage defects commonly occur in the investment casting process. Figure 1 shows the product that we analyzed. The part has a length of 179.83 mm and a width of 141.73 mm. There are two holes on the back side and one hole on the front side. Commonly, the porosity occurred in the hole and the inside of its body. Internal defects that occurred in this part were analyzed by using several methods, such as observing the cross-section of the casting, leakage testing, and X-rays. The advantage of X-ray inspection is that the internal quality inspection results can be obtained without destroying the casting body [1] . There are also corresponding international standards that can define the level of internal defects in castings. However, some castings with more complex geometries have certain technical requirements for non-destructive inspection difficulty. Because X-ray equipment is expensive, and sending it to a professional unit for inspection is time-consuming and expensive, therefore we cut open the trial casting to directly observe whether there are defects inside. Therefore, we divided the part into nine, which can be seen in Figure 2. Figure 2 (a) showed the porosity that we mentioned, Figure 2 (b) showed the body surface, Figure 2 (c) and Figure 2 (d) showed the real parts we have cut into nine and the cutting location details, respectively. The casting part is cut into nine pieces and numbered A1-A9, and then the sectioned casting is sent to a professional unit for X-ray shooting. In order to compare the results of the actual sample delivery, we cut the simulation model into nine equal parts according to the cross-section of the actual sample delivery, as shown in Figure 2(d). Finally, nine sections including A1-A9 can be obtained. In the simulated defect prediction, casting defects will be mainly distributed on sections of A3 and A7 sections, while A5 will have a small number of defects. Figure 2 (e) shows the initial plan casting defect simulation sectional view. 2.2 Basic information on castings Figure 3 shows simple dimensions and front and rear views of the industrial valve we are going to analyze. This is a rectangular casting with two small nozzles in the center of the front side and a large nozzle in the center of the back. There is a protruding frame on the outermost side of the rectangle. The wall thickness of the large nozzle and the small nozzle in the middle is the largest difference in the thickness of the overall casting. The place. This valve is widely used in industry. The material used for the casting is 316L stainless steel, and its weight is 4.18 kg. Table 1 and Table 2 show the chemical composition and physical properties of stainless steel that we used to this study, respectively. Table 3 shows the casting parameter for a real experiment. Figure 4, we can clearly see the details of initial casting tree plan, including the pouring surface, sprue cup, runner, gate, and cavity. In one tree included two parts. Molten stainless steel is poured from the mouth of the pouring cup and passes through the cubic flow channel before flowing into the mold cavity through the inlet gate. To release the pressure in the pouring system, initial air is discharged through the exhaust hole linking the pouring cup and side runner. 2.3 Tree grouping scheme and establishment of finite element model Table 4 illustrates the details of the finite element model and the parameters of this study's casting simulation. Due to the calculation of the added solid insulation cotton mesh, too fine a mesh size will make computer simulation time-consuming (if the mesh size is 1mm for this solution, it will take about 10 days to calculate a solution), which may cause delays in the casting development schedule. Therefore, we established the FEM mesh model by 1.5mm. We set 1100°C for the shell mold temperature in the simulation because the results we observed with an infrared thermal imaging camera (Ching Hsing Computer-Tech Ltd P384 series, Taiwan). Additionally, the temperature of the shell mold coming out that set in the heating furnace of the oven will not reach 1180°C, and the temperature will drop by 2-4 degrees per second depending on the time of making. Figure 5 shows the 3D models of the gating system in Case A, Case B and Case C. To ensure that the difference in simulation results comes entirely from the differences in casting system geometry, all casting schemes in Figure 5 are actual trial castings, and numerical simulation analyses are used using the same casting conditions. The group tree geometry of Case A and Case B is the same. The difference is that the triangular insulation cotton area framed by the red box is the key to reducing the generation of independent out-of-phase areas caused by the casting's own geometry. The expanded triangular insulation cotton setting of Case B - expanded from 50x55mm to 81x90mm. The difference between Case B and Case C lies in the change in the tree geometry—four new bracket arms are added. The newly added bracket arm comes from practical considerations. In order to drain the wax more cleanly, it can also be vented. The newly added geometric features will facilitate the operator to hold the ceramic shell mold more firmly for movement, increasing the safety of the operation. Due to the difficulty of clamping the original Case B due to its geometric shape, there is actually no trial work for comparison. 3. Results and discussion of Comparison of simulation results and practice of group tree scheme Figure 6 shows the calculated shrinkage cavity distribution positions in the simulation software for Case A. It can be seen that the main shrinkage cavities of the casting are located where the large nozzle wall and the small nozzle wall overlap, which is also where the thickness difference of the casting is greatest. The thickness from the large tube orifice to the small tube orifice is about 60mm, and the average thickness of the castings surrounding the large and small tube orifices, excluding the frame, is about 14mm. Such a large thickness difference causes delayed solidification of the large and small tube orifices, which in turn causes shrinkage defects to be distributed in the tubes around the mouth. Figure 7 shows a comparison between the predicted A3 section of defects in Case A and the X-ray photo of the casting actually located on the same section. As shown in Fig. 7 (a) and Figure (b), the shrinkage cavity defects are all indexed in the thickness between the small tube opening and the large tube opening, and the distribution position is very close to the position detected by X-ray in Fig. 7 (c). The red circle in the X-ray photo is where shrinkage holes actually exist. Figure 7 (c) was reproduced from a traditional film. Since we cannot borrow a scanner that professionally scans X-ray films, capturing the outline of the defect on the film is difficult. Figure 8 shows the X-ray results of the A7 section of other trial castings. Since A3 and A7 are symmetrical two sides of the casting geometry and are also the areas where the simulated shrinkage defects are mainly distributed, the actual X-ray inspection results of the shrinkage defects in the A3 and A7 sections are distributed in similar areas, that is, in this section the thickest area, the location where the defect occurs is the red circle in Fig. 8 . Figure 9 shows the expected defect occurrence areas generated by solidification shrinkage simulations for Cases A to C. The prominent locations where shrinkage defects occur are the same in the three Cases. This is a problem caused by the geometric characteristics of the casting itself. We can only slow down the occurrence of defects through the design of the tree. The defects of all solutions occur in the thickest parts of the large and small nozzles of the casting, and there will be no prediction of casting shrinkage in other areas. Although the locations of defects are similar, it can be seen that the distribution of casting shrinkage on the left and right sides of the nozzle in Case B has been significantly reduced the shrinkage compared to Case A. This is because the area covered by the triangular insulation cotton slows down the solidification speed of the thin parts of the casting. Reduce the large-scale independent liquid phase zone inside the casting's large nozzle and small nozzle, thereby allowing the solidification trend to shrink toward the die head as continuously as possible. As for the difference between Case C and Case B, the only difference is the four bracket arms. The four bracket arms make the wax discharge smoother and play the role of exhaust during the casting process. They can also be used as a structure to facilitate the clamping when the operator moves the tree. Most importantly, during the simulation, adding these four bracket arms also helped reduce shrinkage cavities in castings. Figure 9 shows Case C has fewer defects than Case B. The actual numbers will be described in detail later. The reduction of shrinkage holes should be because the extra material from the four bracket arms can provide some shrinkage. It also has a little thermal insulation effect on the gate, which makes it completely solidify later, allowing more soup from the die to replenish the casting part. The casting is cut into nine pieces and numbered A1-A9. The simulation model is cut into nine equal parts according to the cross-section method of the actual sample delivery, as shown in Fig. 2 (a)-(c). The trial castings made in Case C do not have actual cross-sections and are sent for testing. Instead, the castings are irradiated from multiple angles to avoid any geometric features of the castings that would cause internal defects not to be detected by X-rays. However, the simulation of Case C is also cut into nine sections such as A1-A9 to predict the location of defects in order to compare whether the distribution position of the casting shrinkage is different from Case A. As shown in Fig. 9 (c), The casting defects in Case C will be mainly distributed on the cross-sections of A3 and A7 slices, while small areas of defects will still exist in A5. Compared with the simulation results of Case A in Fig. 9 (a) and case B in Fig. 9 (b), the simulated defects on the A3 and A7 slices of Case C are significantly reduced. Figure 10 shows the prediction of the exact percentage of elements containing shrinkage cavities in the castings from Case A to C. When the triangular insulation cotton area covered on the tree group increases, the percentage of elements containing shrinkage holes decreases (the PES value of plan B is nearly 41% less than that of Case A), which proves that the changed insulation cotton plan causes the internal solidification trend of the casting. It is relatively continuous, alleviating the problem of independent liquid phase zone generation when the thickness difference of castings is too large, allowing the die-feeding function to be fully exerted, which can greatly reduce the occurrence of internal shrinkage cavities. Compared with Case B, Case C adds four new arms for wax discharge, exhaust and convenient clamping in on-site operations. The PES simulation prediction can also achieve the effect of feeding and reducing the generation of shrinkage cavities. In case C, the PES value is reduced by 24.6% compared to case B and 55.5% compared to case A. The slight difference in a good tree assembly plan can significantly improve the quality of castings. Figure 11 (a)-(c) shows the location of virtual thermodynamic sensors (VTDS) placed in each gate system to monitor the temperatures during operation [2] for Case A, Case B, and Case C, respectively. In the schematic, VTDS numbered 1 to 3 are marked on the red dots. The VTDS is placed at the die head's and gate's center, respectively. The position of the VTDS can clearly describe the solidification trend of the entire casting. The solidification time of the gate can be used better to compare the amount of shrinkage cavities inside the casting. The later the gate solidifies, the more molten steel located in the die head enters the cavity of the casting, which means that Fewer shrinkage defects will be generated. At VTDS, Fig. 12 (a)–(c) illustrates the time function of the temperature change of the molten metal for three different casting plans: (a) Case A, (b) Case B, and (c) Case C. In Fig. 12 (a) and Fig. 12 (b), we observe that the molten iron change from its liquidus temperature to its solidus temperature after 2:50 seconds in Case A and 95 seconds in Case B respectively. This time difference shows that adjusting the insulation cotton covering method on the group tree can prevent the solidification process of metal flowing from the runner to the casting by nearly 4 to 5 seconds, nearly twice the time, and allow more molten metal to flow into the mold cavity of the casting, causing Fewer shrinkage voids. According to Fig. 12 (b) and Fig. 12 (c), it can be seen that Case B requires 95 seconds and Case C requires 110 seconds for the molten iron to drop from the liquidus temperature (1400°C) to the solidus temperature (1375°C) at points 2 & 3. This time difference shows that fine-tuning the geometry of the casting system can prevent the solidification process of metal flowing from the runner to the casting by nearly 15 seconds and allow more molten metal to flow into the mold cavity in the casting area, resulting in fewer shrinkage porosity. Figure 13 shows the inspection results after X-ray inspection of the trial casting produced using the tree assembly method and process parameters of the final plan C. This time, we made a trial run of five series trees, that is, there were ten valve castings available for inspection. Five of the ten trial castings were not found to have detectable internal shrinkage cavities, as shown in Fig. 13 (a), (b), (e), (i) and (j). As for the other five test castings with detected shrinkage cavities, the locations of the shrinkage cavities are all distributed at the slice section A5, similar to the prediction in Fig. 13 . As for the A3 and A7 cross-section locations with many internal shrinkage cavities in the initial plan, no shrinkage cavities were detected in these ten test castings. It can be confirmed that adjusting the triangular insulation cotton coverage area and fine-tuning the group tree geometry can significantly reduce the occurrence of shrinkage cavities—position on the casting. For the trial castings with shrinkage cavities, the sizes of the shrinkage cavities are as follows: There are two shrinkage cavities of 0.84mm and 0.94mm in Fig. 13 (c), 1.80mm in Fig. 13 (d), and 0.64mm in Fig. 13 (f). One mm shrinkage hole, one 1.60mm shrinkage hole in Fig. 13 (g), and one 2.49mm and 1.78mm shrinkage hole in Fig. 13 (h). Special attention is paid to the fact that in the middle and outer parts of these ten inner castings, where the thickness is uniform, the inspector has circled some shadows in some places, suspecting the occurrence of sponge-like shrinkage cavities. However, from the perspective of simulation and theory, large-area sponge-like shrinkage cavities can't occur at this location, so a few of them were picked out for cross-sectional inspection. If sponge-like shrinkage cavities occur, the cross-sectional inspection can detect them. It can be concluded that the final result is that there is no sponge-like shrinkage cavity. Judging from the international standard of ASTM E2660, the internal shrinkage detection results of the ten test castings were all below level four, which met the customer's requirements. In order to verify the accuracy of the simulation results, the valve parts were lost-wax cast in the foundry using the casting parameters derived from CAE X-ray inspection used to evaluate the effectiveness of design changes in reducing or avoiding casting defects. Figure 14 (b) illustrates a photo of the wax mold set tree. Figure 14 (c) shows the rough embryo of the assembled tree casting after the ceramic shell mold was shaken off after casting under Plan C. It is confirmed whether there are any defects on the surface of the casting. Figure 14 (d) shows the X-ray image of the casting result, proving the effectiveness of the casting system design and process parameters in Case C. As shown in Fig. 14 (d), in the X-ray photograph, no black spots were detected inside the valve body of Scheme C, meaning no internal defects were produced. Therefore, all the above results provide rigorous evidence for the casting quality of the trial cast stainless steel (316L) valve parts in Case C, improving the effectiveness of valve casting production scheme. 4. Conclusion Based on numerical simulations based, this study determined shrinkage defects are occured in industrial valve parts (316L) made of stainless steel. We used results from real products and simulations to formulate three casting schemes for simulation. Cotton was helpful in preventing shrinkage porosity during the solidification process. The group tree geometry of Case A and B was installed the exact location, but it was set in different cotton sizes and expanded from 50x55mm to 81x90mm. Meanwhile, the difference between plans B and C lies in the change in the tree geometry—four new bracket arms are added. Cutting the part into nine (A1-A9) can show the location of shrinkage location. In our simulations, we demonstrate that installing four new bracket arms (Case C) can reduce the majority of casting defects to 1.47%. The bracket arm and the cotton could trap the inner heat during solidification. So that the heat in the product can be evenly distributed, thus inhibiting shrinkage. As a result, the investment casting strategy described in this paper provides a helpful guide to casting the valve body from the quality and cost points of view. Declarations Conflicts of interest : Authors declare no competing interests Funding: This research is supported and funded by GlobalTek Fabrication Co., Ltd., Taiwan. Author contribution: Yi Chen Kao: writing research result report, Conceptualization, methodology. Cheng-Fu Huang, Sheng-Chan Lee, Chien-Wei Chan: data curation, investigation, formal analysis, supervision, and visualization. Sukhoiri Khoiruddin, Jay-Feng Lin, Ming-Hsiu Ho: Writing manuscript, data validation, arranging research result into manuscript draft. Intan Mardiono: data validation, arranging research result into manuscript draft. Yiin-Kuen Fuh: supervision, Conceptualization, methodology. Acknowledgements This research is supported and funded by GlobalTek Fabrication Co., Ltd., Taiwan. Also, we thank colleagues and experts for their help and reviewers for the improvement comments. References A. D. Plessis and P. 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Tables Table 1 Chemical composition of 316L stainless steel Cr Ni Mn Mo Si N P C S 16.5- 18.5% 10-13% ≤ 2% 2-2.5% ≤ 1% 0.11% 0.05% ≤ 0.03% 0.02% Table 2 Physical properties of 316L stainless steel Density (g/cm³) Elastic modulus (GPa) Hardness, Brinell (HB) Tensile strength (MPa) Yield strength (MPa) Coefficient of thermal expansion Thermal conductivity (W/m*K) Melting point (°C) 8 193 215 Max 500-700 200 1.59E-5 1/K 16.3 1400 Table 3 Casting trial casting parameters Casting material Pouring temperature (°C) Shell mold temperature (°C) Shell mold thickness (mm) Case A 316L 1600 1180 6 Table 4 Basic information and boundary condition settings of finite element model Element size Casting elements Shell mold elements Pouring temperature setting Shell mold temperature setting Heat transfer coefficient from casting to mold Environment temperature 2mm 367824 194712 1600°C 1100°C 2500W/(m*K) 30°C Cite Share Download PDF Status: Published Journal Publication published 01 Aug, 2024 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Minor Revisions Needed 02 Jul, 2024 Reviewers agreed at journal 09 Mar, 2024 Reviewers invited by journal 06 Mar, 2024 Editor assigned by journal 06 Mar, 2024 First submitted to journal 04 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4015116","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276816480,"identity":"30cadd97-e59a-41eb-8ddd-771a687f8d95","order_by":0,"name":"Kao-Yi Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kao-Yi","middleName":"","lastName":"Chen","suffix":""},{"id":276816481,"identity":"d6d99547-d4c2-4354-87d2-2f9f6c574c5b","order_by":1,"name":"Sukhoiri 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Huang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Fu","middleName":"","lastName":"Huang","suffix":""},{"id":276816485,"identity":"eaa4a513-ed6b-4275-b784-52bcf5389643","order_by":5,"name":"Sheng-Chan Lee","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Sheng-Chan","middleName":"","lastName":"Lee","suffix":""},{"id":276816486,"identity":"857b3f38-0ef2-4780-9991-8e460a3f9323","order_by":6,"name":"Chien-Wei Chan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Chien-Wei","middleName":"","lastName":"Chan","suffix":""},{"id":276816487,"identity":"a93f9665-9504-4ddc-a8f1-4ada078c79ff","order_by":7,"name":"Intan Mardiono","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYBACNgQzsQFE8jDIHz4ApCVkcGthRtciwZYA0sKD2x64lgQoLcFjANGLA/BJ9x/8XMCwTd68PbnxcUEFg4zu7J7Pr27UWPAwsB8+ugGbw2QOM0vPYLhtOOfMw2bjGWcYeMzunN1mnXMM6DCetLQb2LRIJDNI8zDcZpwhkdgmzdsG1HIgd5txDhtQiwSPGQ4tzL+BWuyRtOQ8M875h1cLG8iWRISWGznMj3Pb8Goxs+YxuJ08gwfoF54zQGVnjpkx5/ZJ8LDh8Iv8jMTHt3kqbtvOYE9/+Jinwsbe7Hjz48853+rk+NkPH8OmBQIM4CwJiNVgEqdyLID5AymqR8EoGAWjYNgDAFFFVy+Hjer2AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-4443-8816","institution":"National Central University","correspondingAuthor":true,"prefix":"","firstName":"Intan","middleName":"","lastName":"Mardiono","suffix":""},{"id":276816488,"identity":"0648355c-7035-4fb1-b3f6-08f80c2fce72","order_by":8,"name":"Yiin-Kuen Fuh","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yiin-Kuen","middleName":"","lastName":"Fuh","suffix":""}],"badges":[],"createdAt":"2024-03-05 04:01:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4015116/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4015116/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00170-024-14178-3","type":"published","date":"2024-08-01T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52451267,"identity":"856cfe79-5942-4efc-8b95-b175f8c2d06f","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":207726,"visible":true,"origin":"","legend":"\u003cp\u003eBasic dimensions of industrial valve castings \u003cstrong\u003e(a)\u003c/strong\u003eCasting drawings and basic dimensions \u003cstrong\u003e(b)\u003c/strong\u003eCasting 3D model\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/a4231d4e600e154369360637.png"},{"id":52451271,"identity":"899b922f-935b-4105-97dc-4336b9b7aae7","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":398871,"visible":true,"origin":"","legend":"\u003cp\u003eIndustrial valve defect occurrence diagram \u003cstrong\u003e(a)\u003c/strong\u003eIndustrial casting surface shrinkage defects \u003cstrong\u003e(b)\u003c/strong\u003e Casting internal defect profile \u003cstrong\u003e(c)\u003c/strong\u003e Initial plan casting slice photo \u003cstrong\u003e(d)\u003c/strong\u003e Initial plan casting model slice schematic \u003cstrong\u003e(e)\u003c/strong\u003e Initial plan casting defect simulation sectional view\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/69a0ee843154bb7ff82db980.png"},{"id":52451270,"identity":"883b9b88-d22c-4733-82be-38b942adbf13","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103090,"visible":true,"origin":"","legend":"\u003cp\u003eSimple dimensional drawing of the initial casting system (dimensions of die head, gate, and exhaust holes)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/1baa0d2da0a37bf6b4576942.png"},{"id":52451272,"identity":"30805f3e-2ff9-42dd-87e3-937cc93ec4b5","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":111772,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the initial casting group tree casting\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/43e0fd8f61c36908b8f2e422.png"},{"id":52451275,"identity":"f2dba1d6-15c4-4418-a063-f1a84601af31","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":113244,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the evolution of the casting group tree scheme\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/3fe84d43c3800da34c20abac.png"},{"id":52451274,"identity":"c9d7a899-c888-4b55-88f1-1437659147b0","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":188786,"visible":true,"origin":"","legend":"\u003cp\u003eCase A simulated defect generation prediction \u003cstrong\u003e(a)\u003c/strong\u003e front view \u003cstrong\u003e(b)\u003c/strong\u003e side view\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/e1b9521ac71f83bfc8b25ed8.png"},{"id":52451277,"identity":"85f105b5-79d5-4802-8274-26003ff581c8","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":275827,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the predicted defect distribution of Case A in simulation and X-ray photos \u003cstrong\u003e(a)\u003c/strong\u003e The simulated defect distribution of Case A in the A3 section \u003cstrong\u003e(b)\u003c/strong\u003e The enlarged view of the simulated A3 section of Case A \u003cstrong\u003e(c)\u003c/strong\u003e The A3 section X of the actual Case A -RAY photos\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/b565cd0096b22065e04e709d.png"},{"id":52451273,"identity":"6f224d09-8552-4e72-bc0c-6db7f5c4bd11","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":430799,"visible":true,"origin":"","legend":"\u003cp\u003eX-ray photo of Case A at A7 section \u003cstrong\u003e(a)\u003c/strong\u003e X-ray photo of A7 section of trial casting No. 1 \u003cstrong\u003e(b)\u003c/strong\u003e X-ray photo of A7 section of trial casting No. 2\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/8a1f779357c67d815fe462f7.png"},{"id":52451276,"identity":"85598460-f48c-49c9-beeb-b2688f2f522e","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":364870,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction of shrinkage cavity locations for all simulation scenarios. \u003cstrong\u003e(a)\u003c/strong\u003e Case A \u003cstrong\u003e(b)\u003c/strong\u003e Case B \u003cstrong\u003e(c)\u003c/strong\u003e Case C\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/3df0521d04b59da7ba3ea3a9.png"},{"id":52451278,"identity":"c7dbe142-704d-432e-8ac7-75880abc6e03","added_by":"auto","created_at":"2024-03-11 19:12:10","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":28155,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of element shrinkage porosity (PES) value comparison chart of Case A to C\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/e442fecdc2139de70f4fe4e4.png"},{"id":52451279,"identity":"739981bc-1cc6-41c9-9d24-44d3b05db5ca","added_by":"auto","created_at":"2024-03-11 19:12:10","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":186693,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram illustrating the placement of virtual thermal dynamic sensors (VTDS) in the gating system and castings. \u003cstrong\u003e(a)\u003c/strong\u003eCase A \u003cstrong\u003e(b)\u003c/strong\u003e Case B \u003cstrong\u003e(c) \u003c/strong\u003eCase C\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/d4bb1241b60e28704b328070.png"},{"id":52451280,"identity":"4136629b-a572-4149-944d-7c179d62e88d","added_by":"auto","created_at":"2024-03-11 19:12:10","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":115078,"visible":true,"origin":"","legend":"\u003cp\u003eTemperature of molten metal at the VTDS (Virtual Thermodynamic Sensor) as a function of time. \u003cstrong\u003e(a)\u003c/strong\u003e Plan A. \u003cstrong\u003e(b)\u003c/strong\u003e Plan B. \u003cstrong\u003e(c)\u003c/strong\u003e Plan C.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/36edb160abdb78519a9250f6.png"},{"id":52451266,"identity":"f1aca7d5-68e6-43ae-8b4c-dab6818486f5","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":112508,"visible":true,"origin":"","legend":"\u003cp\u003eX-ray inspection results of ten test castings of Plan C \u003cstrong\u003e(a)-(j)\u003c/strong\u003e are X-ray photos of ten different\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/57a3411c19cf004f718b6217.png"},{"id":52451268,"identity":"2a61b443-4e9a-47c2-b80a-afc444402248","added_by":"auto","created_at":"2024-03-11 19:12:09","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":344271,"visible":true,"origin":"","legend":"\u003cp\u003ePhotographs and X-rays of the casting in Scheme C. \u003cstrong\u003e(a)\u003c/strong\u003ePhoto of the wax mold set tree. \u003cstrong\u003e(b)\u003c/strong\u003eThe shell mold model of the group of trees after being stained with slurry. \u003cstrong\u003e(c)\u003c/strong\u003e Diagonal view (left) and front view (right) of the plan C casting after shock shell. \u003cstrong\u003e(d)\u003c/strong\u003e X-ray inspection photos of castings.\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/8c2439e9101f1c8b43fb4e6f.png"},{"id":61793712,"identity":"984d499b-db3b-4da9-86e0-812095ac301a","added_by":"auto","created_at":"2024-08-05 16:14:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3287047,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4015116/v1/8338316e-239b-4f45-93b1-5dc35952ce2c.pdf"}],"financialInterests":"","formattedTitle":"Comparative Evaluation of Insulation Cotton Configuration on The Investment Casting Quality of Industrial Valve Parts","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIndustrial instruments and valve systems are exposed to high pressures where there is an increased risk of component corrosion and leakage. Industrial valve bodies are usually produced by casting. However, due to casting defects, the sealing performance of components and the mechanical strength will be significantly reduced, impacting economic losses or instability in the production process [1\u0026ndash;4]. Precision casting is usually used to manufacture products with smooth surfaces and complex geometric shapes [5\u0026ndash;10]. The process of creating investment cast valve bodies is very complex and has substantial differences in thickness ratios, causing compaction shrinkage during the casting process to be non-linear [11\u0026ndash;12].\u003c/p\u003e \u003cp\u003eNowadays, advanced computer-aided engineering (CAE) simulation has many advantages in product improvement, such as product quality, reduction of production costs, and shortening of production cycles [13\u0026ndash;15]. Computer-aided engineering simulation analysis is the most effective and profitable technology for evaluating casting quality and predicting defects [16\u0026ndash;18]. Casting defects are complicated to predict because it cannot check the flow of solidification trends of molten metal in the mold cavity [8] [12] [17]. Furthermore, the RMM (Retained Melt Modulus) model helps predict the location of shrinkage cavities and then focuses on processing the locations where defects occur and using various means to make the solidification trend more ideal and continuous. Currently, most casting manufacturers use CAE simulation technology to conduct trial production and verification; This study contributed to the comparison of insulation cotton configurations for the investment casting quality of industrial valve parts. Due to the complexity, parts of industrial valve bodies are usually produced by casting. However, the investment casting production process has several problems, such as shrinkage porosity. Currently, the investment casting industry uses cotton configuration to solve the problem of shrinkage porosity. Therefore, this study compared three cotton installation treatments in the mould shell to determine the optimal use of cotton. There are three schemes of the type of cotton installation on the shell that will be observed, including the triangular insulation cotton area denoted as Case A installed 55mm and Case B installed 90mm cotton on the right and left sides, and Case C denoted with adding bracket arms on the upper side. In this study, we used RMM (Retained Melt Modulus) and the finite element model to analyze the shrinkage porosity's location and to monitor the porosity that occurred during the solidification process. The result showed that cotton could reduce shrinkage porosity by 3.30%, 1.95%, and 1.47% for Case A, B, and C, respectively. Therefore, the best alternative is to add the cotton and bracket arm on the upper side, which is the optimal strategy to prevent shrinkage porosity. and improvement of design plans before they can finally proceed to commercial mass production.\u003c/p\u003e \u003cp\u003eAccording to industrial observations, about 5\u0026ndash;10% of castings contain casting defects, such as geometric distortion, cracks, flash, slag inclusions, and shrinkage cavities. Defect generation does not depend on the design of the casting plan. Various parameters of the process, from the front wax injection to the generation of the middle shell mold, will affect the generation of casting defects [20]. Of all the factors that deteriorate the properties of castings, macro segregation, and shrinkage porosity are the most important because it is difficult to reduce these defects through subsequent thermomechanical treatment. The rapid development of computer calculations, solidification, segregation and even microstructure evolution\u003c/p\u003e \u003cp\u003eAll can be predicted by simulating the casting process. In this way, casting has progressed from the invisible to the visible. Therefore, the development of castings that combine computer simulation and non-destructive inspection technology is very attractive because it has many advantages, namely improved quality, reduced costs, and shortened pre-production time [21]. Commonly, the shrinkage cavities are dependent on the geometry of the gating system and the casting process. Previous research revealed by Yu et al [21] that the optimization process often requires understanding the geometry of the gating system and complex process parameters, along with the use of data analysis for producing optimized parameter results, which improve casting quality and shorten design cycles. The study uses machine learning based on RBF (radial basis functions neural network) to design a casting plan targeting porosity-free and high casting. The results show that optimizing gate design can increase the yield of finished castings by 14.91%.\u003c/p\u003e \u003cp\u003eMinimizing the PES (percentage of elements with shrinkage defect) value is the indicator of obtaining a good casting system [23\u0026ndash;25]. Therefore, we designed and analyzed three different types of gate systems based on the numerical method to calculate the casting process of 316L stainless steel valve housing, which was found in the shrinkage porosity simulation results.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1\u0026nbsp; \u0026nbsp;\u0026nbsp;Internal defects of castings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShrinkage defects commonly occur in the investment casting process. Figure 1 shows the product that we analyzed. The part has a length of 179.83 mm and a width of 141.73 mm. There are two holes on the back side and one hole on the front side. Commonly, the porosity occurred in the hole and the inside of its body. Internal defects that occurred in this part were analyzed by using several methods, such as observing the cross-section of the casting, leakage testing, and X-rays. The advantage of X-ray inspection is that the internal quality inspection results can be obtained without destroying the casting body [1] . There are also corresponding international standards that can define the level of internal defects in castings. However, some castings with more complex geometries have certain technical requirements for non-destructive inspection difficulty. Because X-ray equipment is expensive, and sending it to a professional unit for inspection is time-consuming and expensive, therefore we cut open the trial casting to directly observe whether there are defects inside.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTherefore, we divided the part into nine, which can be seen in Figure 2. Figure 2 (a) showed the porosity that we mentioned, Figure 2 (b) showed the body surface, Figure 2 (c) and Figure 2 (d) showed the real parts we have cut into nine and the cutting location details, respectively. The casting part is cut into nine pieces and numbered A1-A9, and then the sectioned casting is sent to a professional unit for X-ray shooting. In order to compare the results of the actual sample delivery, we cut the simulation model into nine equal parts according to the cross-section of the actual sample delivery, as shown in Figure 2(d). Finally, nine sections including A1-A9 can be obtained. In the simulated defect prediction, casting defects will be mainly distributed on sections of A3 and A7 sections, while A5 will have a small number of defects. Figure 2 (e) shows the initial plan casting defect simulation sectional view.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2\u0026nbsp; \u0026nbsp;\u0026nbsp;Basic information on castings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 3\u0026nbsp;shows simple dimensions and front and rear views of the industrial valve we are going to analyze. This is a rectangular casting with two small nozzles in the center of the front side and a large nozzle in the center of the back. There is a protruding frame on the outermost side of the rectangle. The wall thickness of the large nozzle and the small nozzle in the middle is the largest difference in the thickness of the overall casting. The place. This valve is widely used in industry. The material used for the casting is 316L stainless steel, and its weight is 4.18 kg. Table 1 and Table 2 show the chemical composition and physical properties of stainless steel that we used to this study, respectively. Table 3 shows the casting parameter for a real experiment. Figure 4, we can clearly see the details of initial casting tree plan, including the pouring surface, sprue cup, runner, gate, and cavity. In one tree included two parts. Molten stainless steel is poured from the mouth of the pouring cup and passes through the cubic flow channel before flowing into the mold cavity through the inlet gate. To release the pressure in the pouring system, initial air is discharged through the exhaust hole linking the pouring cup and side runner.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3\u0026nbsp; \u0026nbsp;\u0026nbsp;Tree grouping scheme and establishment of finite element model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4\u0026nbsp;illustrates the details of the finite element model and the parameters of this study's casting simulation. Due to the calculation of the added solid insulation cotton mesh, too fine a mesh size will make computer simulation time-consuming (if the mesh size is 1mm for this solution, it will take about 10 days to calculate a solution), which may cause delays in the casting development schedule. Therefore, we established the FEM mesh model by 1.5mm. We set 1100°C for the shell mold temperature in the simulation because the results we observed with an infrared thermal imaging camera (Ching Hsing Computer-Tech Ltd P384 series, Taiwan). Additionally, the temperature of the shell mold coming out that set in the heating furnace of the oven will not reach 1180°C, and the temperature will drop by 2-4 degrees per second depending on the time of making.\u003c/p\u003e\n\u003cp\u003eFigure 5\u0026nbsp;shows the 3D models of the gating system in Case A, Case B and Case C. To ensure that the difference in simulation results comes entirely from the differences in casting system geometry, all casting schemes in Figure 5 are actual trial castings, and numerical simulation analyses are used using the same casting conditions. The group tree geometry of Case A and Case B is the same. The difference is that the triangular insulation cotton area framed by the red box is the key to reducing the generation of independent out-of-phase areas caused by the casting's own geometry. The expanded triangular insulation cotton setting of Case B - expanded from 50x55mm to 81x90mm.\u003c/p\u003e\n\u003cp\u003eThe difference between Case B and Case C lies in the change in the tree geometry—four new bracket arms are added. The newly added bracket arm comes from practical considerations. In order to drain the wax more cleanly, it can also be vented. The newly added geometric features will facilitate the operator to hold the ceramic shell mold more firmly for movement, increasing the safety of the operation. Due to the difficulty of clamping the original Case B due to its geometric shape, there is actually no trial work for comparison.\u003c/p\u003e"},{"header":"3. Results and discussion of Comparison of simulation results and practice of group tree scheme","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the calculated shrinkage cavity distribution positions in the simulation software for Case A. It can be seen that the main shrinkage cavities of the casting are located where the large nozzle wall and the small nozzle wall overlap, which is also where the thickness difference of the casting is greatest. The thickness from the large tube orifice to the small tube orifice is about 60mm, and the average thickness of the castings surrounding the large and small tube orifices, excluding the frame, is about 14mm. Such a large thickness difference causes delayed solidification of the large and small tube orifices, which in turn causes shrinkage defects to be distributed in the tubes around the mouth.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows a comparison between the predicted A3 section of defects in Case A and the X-ray photo of the casting actually located on the same section. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (a) and Figure (b), the shrinkage cavity defects are all indexed in the thickness between the small tube opening and the large tube opening, and the distribution position is very close to the position detected by X-ray in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (c). The red circle in the X-ray photo is where shrinkage holes actually exist. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e (c) was reproduced from a traditional film. Since we cannot borrow a scanner that professionally scans X-ray films, capturing the outline of the defect on the film is difficult.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the X-ray results of the A7 section of other trial castings. Since A3 and A7 are symmetrical two sides of the casting geometry and are also the areas where the simulated shrinkage defects are mainly distributed, the actual X-ray inspection results of the shrinkage defects in the A3 and A7 sections are distributed in similar areas, that is, in this section the thickest area, the location where the defect occurs is the red circle in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows the expected defect occurrence areas generated by solidification shrinkage simulations for Cases A to C. The prominent locations where shrinkage defects occur are the same in the three Cases. This is a problem caused by the geometric characteristics of the casting itself. We can only slow down the occurrence of defects through the design of the tree. The defects of all solutions occur in the thickest parts of the large and small nozzles of the casting, and there will be no prediction of casting shrinkage in other areas.\u003c/p\u003e \u003cp\u003eAlthough the locations of defects are similar, it can be seen that the distribution of casting shrinkage on the left and right sides of the nozzle in Case B has been significantly reduced the shrinkage compared to Case A. This is because the area covered by the triangular insulation cotton slows down the solidification speed of the thin parts of the casting. Reduce the large-scale independent liquid phase zone inside the casting's large nozzle and small nozzle, thereby allowing the solidification trend to shrink toward the die head as continuously as possible.\u003c/p\u003e \u003cp\u003eAs for the difference between Case C and Case B, the only difference is the four bracket arms. The four bracket arms make the wax discharge smoother and play the role of exhaust during the casting process. They can also be used as a structure to facilitate the clamping when the operator moves the tree. Most importantly, during the simulation, adding these four bracket arms also helped reduce shrinkage cavities in castings. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows Case C has fewer defects than Case B. The actual numbers will be described in detail later. The reduction of shrinkage holes should be because the extra material from the four bracket arms can provide some shrinkage. It also has a little thermal insulation effect on the gate, which makes it completely solidify later, allowing more soup from the die to replenish the casting part.\u003c/p\u003e \u003cp\u003eThe casting is cut into nine pieces and numbered A1-A9. The simulation model is cut into nine equal parts according to the cross-section method of the actual sample delivery, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (a)-(c). The trial castings made in Case C do not have actual cross-sections and are sent for testing. Instead, the castings are irradiated from multiple angles to avoid any geometric features of the castings that would cause internal defects not to be detected by X-rays. However, the simulation of Case C is also cut into nine sections such as A1-A9 to predict the location of defects in order to compare whether the distribution position of the casting shrinkage is different from Case A.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e(c), The casting defects in Case C will be mainly distributed on the cross-sections of A3 and A7 slices, while small areas of defects will still exist in A5. Compared with the simulation results of Case A in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e(a) and case B in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e (b), the simulated defects on the A3 and A7 slices of Case C are significantly reduced.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e shows the prediction of the exact percentage of elements containing shrinkage cavities in the castings from Case A to C. When the triangular insulation cotton area covered on the tree group increases, the percentage of elements containing shrinkage holes decreases (the PES value of plan B is nearly 41% less than that of Case A), which proves that the changed insulation cotton plan causes the internal solidification trend of the casting. It is relatively continuous, alleviating the problem of independent liquid phase zone generation when the thickness difference of castings is too large, allowing the die-feeding function to be fully exerted, which can greatly reduce the occurrence of internal shrinkage cavities. Compared with Case B, Case C adds four new arms for wax discharge, exhaust and convenient clamping in on-site operations. The PES simulation prediction can also achieve the effect of feeding and reducing the generation of shrinkage cavities. In case C, the PES value is reduced by 24.6% compared to case B and 55.5% compared to case A. The slight difference in a good tree assembly plan can significantly improve the quality of castings.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e (a)-(c) shows the location of virtual thermodynamic sensors (VTDS) placed in each gate system to monitor the temperatures during operation [2] for Case A, Case B, and Case C, respectively. In the schematic, VTDS numbered 1 to 3 are marked on the red dots. The VTDS is placed at the die head's and gate's center, respectively. The position of the VTDS can clearly describe the solidification trend of the entire casting. The solidification time of the gate can be used better to compare the amount of shrinkage cavities inside the casting. The later the gate solidifies, the more molten steel located in the die head enters the cavity of the casting, which means that Fewer shrinkage defects will be generated.\u003c/p\u003e \u003cp\u003eAt VTDS, Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e (a)\u0026ndash;(c) illustrates the time function of the temperature change of the molten metal for three different casting plans: (a) Case A, (b) Case B, and (c) Case C. In Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e(a) and Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e(b), we observe that the molten iron change from its liquidus temperature to its solidus temperature after 2:50 seconds in Case A and 95 seconds in Case B respectively. This time difference shows that adjusting the insulation cotton covering method on the group tree can prevent the solidification process of metal flowing from the runner to the casting by nearly 4 to 5 seconds, nearly twice the time, and allow more molten metal to flow into the mold cavity of the casting, causing Fewer shrinkage voids.\u003c/p\u003e \u003cp\u003eAccording to Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e(b) and Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e(c), it can be seen that Case B requires 95 seconds and Case C requires 110 seconds for the molten iron to drop from the liquidus temperature (1400\u0026deg;C) to the solidus temperature (1375\u0026deg;C) at points 2 \u0026amp; 3. This time difference shows that fine-tuning the geometry of the casting system can prevent the solidification process of metal flowing from the runner to the casting by nearly 15 seconds and allow more molten metal to flow into the mold cavity in the casting area, resulting in fewer shrinkage porosity.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e shows the inspection results after X-ray inspection of the trial casting produced using the tree assembly method and process parameters of the final plan C. This time, we made a trial run of five series trees, that is, there were ten valve castings available for inspection. Five of the ten trial castings were not found to have detectable internal shrinkage cavities, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(a), (b), (e), (i) and (j). As for the other five test castings with detected shrinkage cavities, the locations of the shrinkage cavities are all distributed at the slice section A5, similar to the prediction in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e. As for the A3 and A7 cross-section locations with many internal shrinkage cavities in the initial plan, no shrinkage cavities were detected in these ten test castings. It can be confirmed that adjusting the triangular insulation cotton coverage area and fine-tuning the group tree geometry can significantly reduce the occurrence of shrinkage cavities\u0026mdash;position on the casting. For the trial castings with shrinkage cavities, the sizes of the shrinkage cavities are as follows: There are two shrinkage cavities of 0.84mm and 0.94mm in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(c), 1.80mm in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(d), and 0.64mm in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(f). One mm shrinkage hole, one 1.60mm shrinkage hole in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(g), and one 2.49mm and 1.78mm shrinkage hole in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e(h). Special attention is paid to the fact that in the middle and outer parts of these ten inner castings, where the thickness is uniform, the inspector has circled some shadows in some places, suspecting the occurrence of sponge-like shrinkage cavities. However, from the perspective of simulation and theory, large-area sponge-like shrinkage cavities can't occur at this location, so a few of them were picked out for cross-sectional inspection. If sponge-like shrinkage cavities occur, the cross-sectional inspection can detect them. It can be concluded that the final result is that there is no sponge-like shrinkage cavity. Judging from the international standard of ASTM E2660, the internal shrinkage detection results of the ten test castings were all below level four, which met the customer's requirements.\u003c/p\u003e \u003cp\u003eIn order to verify the accuracy of the simulation results, the valve parts were lost-wax cast in the foundry using the casting parameters derived from CAE X-ray inspection used to evaluate the effectiveness of design changes in reducing or avoiding casting defects. Figure\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e(b) illustrates a photo of the wax mold set tree. Figure\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e(c) shows the rough embryo of the assembled tree casting after the ceramic shell mold was shaken off after casting under Plan C. It is confirmed whether there are any defects on the surface of the casting. Figure\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e(d) shows the X-ray image of the casting result, proving the effectiveness of the casting system design and process parameters in Case C. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e(d), in the X-ray photograph, no black spots were detected inside the valve body of Scheme C, meaning no internal defects were produced. Therefore, all the above results provide rigorous evidence for the casting quality of the trial cast stainless steel (316L) valve parts in Case C, improving the effectiveness of valve casting production scheme.\u003c/p\u003e "},{"header":"4. Conclusion","content":"\u003cp\u003eBased on numerical simulations based, this study determined shrinkage defects are occured in industrial valve parts (316L) made of stainless steel. We used results from real products and simulations to formulate three casting schemes for simulation. Cotton was helpful in preventing shrinkage porosity during the solidification process. The group tree geometry of Case A and B was installed the exact location, but it was set in different cotton sizes and expanded from 50x55mm to 81x90mm. Meanwhile, the difference between plans B and C lies in the change in the tree geometry\u0026mdash;four new bracket arms are added. Cutting the part into nine (A1-A9) can show the location of shrinkage location.\u003c/p\u003e \u003cp\u003eIn our simulations, we demonstrate that installing four new bracket arms (Case C) can reduce the majority of casting defects to 1.47%. The bracket arm and the cotton could trap the inner heat during solidification. So that the heat in the product can be evenly distributed, thus inhibiting shrinkage. As a result, the investment casting strategy described in this paper provides a helpful guide to casting the valve body from the quality and cost points of view.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eConflicts of interest\u003c/b\u003e: \u003cp\u003eAuthors declare no competing interests\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research is supported and funded by GlobalTek Fabrication Co., Ltd., Taiwan.\u003c/p\u003e\u003ch2\u003eAuthor contribution:\u003c/h2\u003e \u003cp\u003eYi Chen Kao: writing research result report, Conceptualization, methodology. Cheng-Fu Huang, Sheng-Chan Lee, Chien-Wei Chan: data curation, investigation, formal analysis, supervision, and visualization. Sukhoiri Khoiruddin, Jay-Feng Lin, Ming-Hsiu Ho: Writing manuscript, data validation, arranging research result into manuscript draft. Intan Mardiono: data validation, arranging research result into manuscript draft. Yiin-Kuen Fuh: supervision, Conceptualization, methodology.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis research is supported and funded by GlobalTek Fabrication Co., Ltd., Taiwan. Also, we thank colleagues and experts for their help and reviewers for the improvement comments.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eA. D. Plessis and P. Rossouw, \u0026quot;X-ray computed tomography of a titanium aerospace investment casting,\u0026quot; Case Studies in Nondestructive Testing and Evaluation, pp. 21-26, 2015. \u003c/li\u003e\n\u003cli\u003eC.-U. Ahn, S. Oh, H.-S. Kim, D.-I. Park and J.-G. Kim, \u0026quot;Virtual Thermal Sensor for Real-Time Monitoring of Electronic Packages in a Totally Enclosed System,\u0026quot; IEEE Access, vol. 10, pp. 50589-50600, 2022. \u003c/li\u003e\n\u003cli\u003eP.-H. Huang, C.-Y. Cheng, W.-J. Huang and C.-S. 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Fuh, \u0026quot;Computer-Aided Engineering (CAE) Simulation for the Robust Gating System Design: Improved Process for Investment Casting Defects of 316L Stainless Steel Valve Housing,\u0026quot; International Journal of Metalcasting, 2022. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Chemical composition of 316L stainless steel\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"603\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24709784411277%\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.945273631840797%\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.12603648424544%\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003eMo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003eSi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.940298507462687%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24709784411277%\"\u003e\n \u003cp\u003e16.5- 18.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.945273631840797%\"\u003e\n \u003cp\u003e10-13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.12603648424544%\"\u003e\n \u003cp\u003e\u0026le; 2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003e2-2.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003e\u0026le; 1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003e0.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613598673300165%\"\u003e\n \u003cp\u003e0.05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.940298507462687%\"\u003e\n \u003cp\u003e\u0026le; 0.03%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e0.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Physical properties of 316L stainless steel\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.578512396694215%\"\u003e\n \u003cp\u003eDensity (g/cm\u0026sup3;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.570247933884298%\"\u003e\n \u003cp\u003eElastic modulus (GPa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.892561983471074%\"\u003e\n \u003cp\u003eHardness, Brinell (HB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.900826446280991%\"\u003e\n \u003cp\u003eTensile strength (MPa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\"\u003e\n \u003cp\u003eYield strength (MPa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.702479338842975%\"\u003e\n \u003cp\u003eCoefficient of thermal expansion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.537190082644628%\"\u003e\n \u003cp\u003eThermal conductivity (W/m*K)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\"\u003e\n \u003cp\u003eMelting point (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.578512396694215%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.570247933884298%\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.892561983471074%\"\u003e\n \u003cp\u003e215 Max\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.900826446280991%\"\u003e\n \u003cp\u003e500-700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.702479338842975%\"\u003e\n \u003cp\u003e1.59E-5 1/K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.537190082644628%\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.909090909090908%\"\u003e\n \u003cp\u003e1400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Casting trial casting parameters\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"539\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.366852886405958%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.50465549348231%\"\u003e\n \u003cp\u003eCasting material\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.042830540037244%\"\u003e\n \u003cp\u003ePouring temperature (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.042830540037244%\"\u003e\n \u003cp\u003eShell mold temperature (\u0026deg;C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.042830540037244%\"\u003e\n \u003cp\u003eShell mold thickness (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.366852886405958%\"\u003e\n \u003cp\u003eCase A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.50465549348231%\"\u003e\n \u003cp\u003e316L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.042830540037244%\"\u003e\n \u003cp\u003e1600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.042830540037244%\"\u003e\n \u003cp\u003e1180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.042830540037244%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eBasic information and boundary condition settings of finite element model\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.742496050552923%\"\u003e\n \u003cp\u003eElement size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.216429699842022%\"\u003e\n \u003cp\u003eCasting elements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.902053712480253%\"\u003e\n \u003cp\u003eShell mold elements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007898894154819%\"\u003e\n \u003cp\u003ePouring temperature setting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.849921011058452%\"\u003e\n \u003cp\u003eShell mold temperature setting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.851500789889414%\"\u003e\n \u003cp\u003eHeat transfer coefficient from casting to mold\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.429699842022117%\"\u003e\n \u003cp\u003eEnvironment temperature\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.742496050552923%\"\u003e\n \u003cp\u003e2mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.216429699842022%\"\u003e\n \u003cp\u003e367824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.902053712480253%\"\u003e\n \u003cp\u003e\u0026nbsp;194712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.007898894154819%\"\u003e\n \u003cp\u003e1600\u0026deg;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.849921011058452%\"\u003e\n \u003cp\u003e1100\u0026deg;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.851500789889414%\"\u003e\n \u003cp\u003e2500W/(m*K)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.429699842022117%\"\u003e\n \u003cp\u003e30\u0026deg;C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-international-journal-of-advanced-manufacturing-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jamt","sideBox":"Learn more about [The International Journal of Advanced Manufacturing Technology](https://www.springer.com/journal/170)","snPcode":"170","submissionUrl":"https://submission.nature.com/new-submission/170/3","title":"The International Journal of Advanced Manufacturing Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Investment Casting, Insulation Cotton Configurations, Shell Making, Shrinkage Porosity, Finite Element Model","lastPublishedDoi":"10.21203/rs.3.rs-4015116/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4015116/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study contributed to the comparison of insulation cotton configurations for the investment casting quality of industrial valve parts. Due to the complexity, parts of industrial valve bodies are usually produced by casting. However, the investment casting production process has several problems, such as shrinkage porosity. Currently, the investment casting industry uses cotton configuration to solve the problem of shrinkage porosity. Therefore, this study compared three cotton installation treatments in the mould shell to determine the optimal use of cotton. There are three schemes of the type of cotton installation on the shell that will be observed, including the triangular insulation cotton area denoted as Case A installed 55mm and Case B installed 90mm cotton on the right and left sides, and Case C denoted with adding bracket arms on the upper side. In this study, we used RMM (Retained Melt Modulus) and the finite element model to analyze the shrinkage porosity's location and to monitor the porosity that occurred during the solidification process. The result showed that cotton could reduce shrinkage porosity by 3.30%, 1.95%, and 1.47% for Case A, Case B, and Case C, respectively. Therefore, the best alternative is to add the cotton and bracket arm on the upper side, which is the optimal strategy to prevent shrinkage porosity.\u003c/p\u003e","manuscriptTitle":"Comparative Evaluation of Insulation Cotton Configuration on The Investment Casting Quality of Industrial Valve Parts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 19:12:04","doi":"10.21203/rs.3.rs-4015116/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revisions Needed","date":"2024-07-02T09:45:49+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-03-09T15:42:19+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-06T17:36:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-06T06:00:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"The International Journal of Advanced Manufacturing Technology","date":"2024-03-04T23:01:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-international-journal-of-advanced-manufacturing-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jamt","sideBox":"Learn more about [The International Journal of Advanced Manufacturing Technology](https://www.springer.com/journal/170)","snPcode":"170","submissionUrl":"https://submission.nature.com/new-submission/170/3","title":"The International Journal of Advanced Manufacturing Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e67b184d-d11e-4b65-8889-543f58f65564","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:05:31+00:00","versionOfRecord":{"articleIdentity":"rs-4015116","link":"https://doi.org/10.1007/s00170-024-14178-3","journal":{"identity":"the-international-journal-of-advanced-manufacturing-technology","isVorOnly":false,"title":"The International Journal of Advanced Manufacturing Technology"},"publishedOn":"2024-08-01 15:57:58","publishedOnDateReadable":"August 1st, 2024"},"versionCreatedAt":"2024-03-11 19:12:04","video":"","vorDoi":"10.1007/s00170-024-14178-3","vorDoiUrl":"https://doi.org/10.1007/s00170-024-14178-3","workflowStages":[]},"version":"v1","identity":"rs-4015116","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4015116","identity":"rs-4015116","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}