Characterization and Prediction of Microporosity Defect in Sand Cast WE54 Alloy Castings

Li, Jilin; Chen, Rongshi; Ma, Yuequn; Ke, Wei

doi:10.1016/j.jmst.2014.03.011

Cited by 35 publications

(9 citation statements)

References 9 publications

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“…The optimised factor values improved acceptable quality level from 86.22 to 96.17 per cent and thereby increased the productivity level. Li et al (2014) predicted microporosity defects in sand castings based on the riser size. They determined the optimum values of porosity through simulations.…”

Section: Methodsmentioning

confidence: 99%

Prediction and improvement of iron casting quality through analytics and Six Sigma approach

Mishra

Rane

2019

IJLSS

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Purpose The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a causal relationship between chemical composition and the quality of the iron casting to achieve the global benchmark quality level. Design/methodology/approach The case study-based exploratory research design is used in this study. The problem discovery is done through the literature survey and Delphi method-based expert opinions. The prediction model is built and deployed in 11 cases to validate the research hypothesis. The analytics helps in achieving the statistically significant business goals. The design includes Six Sigma DMAIC (Define – Measure – Analyze – Improve and Control) approach, benchmarking, historical data analysis, literature survey and experiments for the data collection. The data analysis is done through stratification and process capability analysis. The logistic regression-based analytics helps in prediction model building and simulations. Findings The application of prediction model helped in quick root cause analysis and reduction of rejection by over 99 per cent saving over INR6.6m per year. This has also enhanced the reliability of the production line and supply chain with on-time delivery of 99.78 per cent, which earlier was 80 per cent. The analytics with Six Sigma DMAIC approach can quickly and easily be applied in manufacturing domain as well. Research limitations implications The limitation of the present analytics model is that it provides the point estimates. The model can further be enhanced incorporating range estimates through Monte Carlo simulation. Practical implications The increasing use of prediction model in the near future is likely to enhance predictability and efficiencies of the various manufacturing process with sensors and Internet of Things. Originality/value The researchers have used design of experiments, artificial neural network and the technical simulations to optimise either chemical composition or mould properties or melt shop parameters. However, this work is based on comprehensive historical data-based analytics. It considers multiple human and temporal factors, sand and mould properties and melt shop parameters along with their relative weight, which is unique. The prediction model is useful to the practitioners for parameter simulation and quality enhancements. The researchers can use similar analytics models with structured Six Sigma DMAIC approach in other manufacturing processes for the simulation and optimisations.

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Section: Methodsmentioning

confidence: 99%

Prediction and improvement of iron casting quality through analytics and Six Sigma approach

Mishra

Rane

2019

IJLSS

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“… ProCast simulation was carried out on WE54 magnesium alloy with the effect of different riser diameter. Results showed 60 mm riser diameter with the riser length of 80 mm length riser as the most suitable [41].…”

Section: Numerical Simulationmentioning

confidence: 97%

Effectiveness of Feeding System for Enhanced Product Quality in Sand Casting Industries

2019

IJRTE

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This review article deals with the importance of process parameters and the recent developments in modern tool technology in the success of smart productivity for casting process of all types. Various influencing factors such as design, location and the number of gating on feeding mechanism were discussed vis-a-vis casting defects. The review revealed reduction in the defects such as air bubbles, blow holes, shrinkage defects and mechanical properties of the casting parts through selection of an optimum feeding design. Variations in fillet radius and thickness on the feeding system were found to be the factors affecting the location of the hot spot. Accordingly, the mobility of the hot spot was controlled by geometrical modifications in the feeding system. In addition, the formation of pinholes and solidification defects could be reduced through a proper arrangement of the feeding system. The rapid growth in implementing simulation techniques in the casting process can assist the enhancement of yield with minimum production cost. This article provides a data base relating to the merits and demerits of various factors and material systems with their industrial applications for enabling further research in the casting process

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“…Kang [8] predicted the micro-porosity of thin-walled superalloy castings by evaluating the dimensionless Niyama criterion quantitatively. Li et al [9] predicted the microporosity of distribution of WE54 alloy castings by calculating Niyama criterion values according to the size of riser. Majidi et al [10] simulated the mold lling of molten metal in casting and investigated the air entrainment model by changing the various pouring conditions and runner systems to eliminate inclusion defects.…”

Section: Introductionmentioning

confidence: 99%

Improvement of quality and yield for investment casting of centrifugal pump impeller by tilting mold and optimizing runner/riser system

Kim

Paek²,

Ri³

et al. 2022

Preprint

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The impellers must have no defects to endure vibration and centrifugal force. The shell for producing impeller was located at tilt and the runner/riser system was optimized to obtain good quality casting and increase the casting yield. We adopted sprue as riser to increase the casting yield and employed ProCAST to analyze the solidification behavior of molten metal according to the dimension of riser and gate. Although the diameter of riser is change from 133mm to 66mm, the shrinkage defects was removed from the casting due to the proper size and location of runner/riser system. And we predicted the probability occurring gas and non-metal inclusion defects in casting by tilting the shell at 0°, 5°, 10°, 15° and 20°. The ultrasonic detecting results show that the proper designs of the runner/riser systems and mold tiling eliminated casting defects such as shrinkage, gas and non-metal inclusion. In addition, the casting yield was increased from 41.5 to 65.2% with producing a good quality casting.

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Characterization and Prediction of Microporosity Defect in Sand Cast WE54 Alloy Castings

Cited by 35 publications

References 9 publications

Prediction and improvement of iron casting quality through analytics and Six Sigma approach

Prediction and improvement of iron casting quality through analytics and Six Sigma approach

Effectiveness of Feeding System for Enhanced Product Quality in Sand Casting Industries

Improvement of quality and yield for investment casting of centrifugal pump impeller by tilting mold and optimizing runner/riser system

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