Trosolwg
Rajesh Ransing
Dr Rajesh Ransing
Athro Cyswllt,
Mechanical Engineering
303
Trydydd Llawr
Adeilad Gogleddol Peirianneg
Campws y Bae
Trydydd Llawr
Adeilad Gogleddol Peirianneg
Campws y Bae
Ar gael ar gyfer Goruchwyliaeth Ôl-raddedig
Dolenni Ymchwil
Meysydd Arbenigedd
- Dadansoddeg Gweithgynhyrchu
- Optimeiddio prosesau a dysgu peirianyddol
- Meintioli Ansicrwydd
- Meddwl yn seiliedig ar risg, FMEAs a rheoli gwybodaeth sefydliadol
- Dadansoddiad cerddediad a cherdded deudroed
- Llif hylif ar raddfa nano
- Peirianneg Gyfrifiannol
Uchafbwyntiau Gyrfa
Ymchwil
Gwella prosesau ac optimeiddio prosesau gweithgynhyrchu
Meddwl yn seiliedig ar risg a rheoli gwybodaeth sefydliadol
Meintioli ansicrwydd mewn gweithrediadau gweithgynhyrchu
Modelu cyfrifiannol dadansoddiad cerddediad
Dylunio a gweithgynhyrchu dyluniadau prosthetig/orthotig arloesol
Cyhoeddiadau
Uchafbwyntiau Ymchwil
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Ransing, R., Brown, S., Roshan, H., & Ransing, M. (2017). How to save money in a foundry production with opportunities offered by Industry 4.0 and ISO9001:2015 Standard.. In Plenary Lecture, Jubilee 25th International Scientific and Technical Conference "Foundry production and metallurgy” (pp. 56-64). BNTU.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63492
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Batbooti, R. & Ransing, R. (2023). A novel imputation based predictive algorithm for reducing common cause variation from small and mixed datasets with missing values. Computers and Industrial Engineering, 179, 109230
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Ransing, R. (2022). Thermal irreversibility demystified. International Journal of Numerical Methods for Heat and Fluid Flow, 33(2)
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Mahmoodi, P., Ransing, R., & Friswell, M. (2016). A novel mathematical formulation for predicting symmetric passive bipedal walking motion with unbalanced masses. Applied Mathematical Modelling, 40(5-6), 3895-3906.
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Giannetti, C. & Ransing, R. (2016). Risk based uncertainty quantification to improve robustness of manufacturing operations. Computers & Industrial Engineering, 101, 70-80.
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Ransing, R., Batbooti, R., & Giannetti, C. (2016). A quality correlation algorithm for tolerance synthesis in manufacturing operations. Computers & Industrial Engineering, 93, 1-11.
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Mahmoodi, P., Aristodemou, S., Ransing, R., Owen, N., & Friswell, M. (2016). Prosthetic foot design optimisation based on roll-over shape and ground reaction force characteristics. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
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Batbooti, R., Ransing, R., Ransing, M., & Ransing, R. (2016). A bootstrap method for uncertainty estimation in quality correlation algorithm for risk based tolerance synthesis. Computers & Industrial Engineering
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Hafezi, F., Ransing, R., Lewis, R., & Ransing, R. (2016). The calculation of drag on nano-cylinders. International Journal for Numerical Methods in Engineering, 111(11)
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Charles, W., Mahmoodi, P., Ransing, R., Sazonov, I., & Friswell, M. (2016). Comparison of point foot, collisional and smooth rolling contact models on the bifurcations and stability of bipedal walking. European Journal of Computational Mechanics, 25(3), 273-293.
Holl Ymchwil
Erthyglau Cylchgronau
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Batbooti, R. & Ransing, R. (2023). A novel imputation based predictive algorithm for reducing common cause variation from small and mixed datasets with missing values. Computers and Industrial Engineering, 179, 109230
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Ransing, R. (2022). Thermal irreversibility demystified. International Journal of Numerical Methods for Heat and Fluid Flow, 33(2)
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Mahmoodi, P., Aristodemou, S., Ransing, R., Owen, N., & Friswell, M. (2016). Prosthetic foot design optimisation based on roll-over shape and ground reaction force characteristics. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
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Batbooti, R., Ransing, R., Ransing, M., & Ransing, R. (2016). A bootstrap method for uncertainty estimation in quality correlation algorithm for risk based tolerance synthesis. Computers & Industrial Engineering
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Hafezi, F., Ransing, R., Lewis, R., & Ransing, R. (2016). The calculation of drag on nano-cylinders. International Journal for Numerical Methods in Engineering, 111(11)
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Charles, W., Mahmoodi, P., Ransing, R., Sazonov, I., & Friswell, M. (2016). Comparison of point foot, collisional and smooth rolling contact models on the bifurcations and stability of bipedal walking. European Journal of Computational Mechanics, 25(3), 273-293.
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Giannetti, C. & Ransing, R. (2016). Risk based uncertainty quantification to improve robustness of manufacturing operations. Computers & Industrial Engineering, 101, 70-80.
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Ransing, R., Batbooti, R., & Giannetti, C. (2016). A quality correlation algorithm for tolerance synthesis in manufacturing operations. Computers & Industrial Engineering, 93, 1-11.
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Mahmoodi, P., Ransing, R., & Friswell, M. (2016). A novel mathematical formulation for predicting symmetric passive bipedal walking motion with unbalanced masses. Applied Mathematical Modelling, 40(5-6), 3895-3906.
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Giannetti, C., Ransing, M., Ransing, R., Bould, D., Gethin, D., & Sienz, J. (2015). Organisational Knowledge Management for Defect Reduction and Sustainable Development in Foundries. International Journal of Knowledge and Systems Science, 6(3), 18-37.
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Arjunwadkar, S., Ransing, M., & Ransing, R. (2015). Seven Steps to Energy Efficiency for Foundries. Foundry Management and Technology, 143(3), 24-29.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24998
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Giannetti, C., Ransing, R., Ransing, M., Bould, D., Gethin, D., & Sienz, J. (2014). A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data. Computers & Industrial Engineering, 72, 217-229.
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Ransing, R., Giannetti, C., Ransing, M., James, M., Ransing, R., & Giannetti, C. (2013). A coupled penalty matrix approach and principal component based co-linearity index technique to discover product specific foundry process knowledge from in-process data in order to reduce defects. Computers in Industry, 64(5), 514-523.
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Mahmoodi, P., Ransing, R., Friswell, M., Friswell, M., & Ransing, R. (2013). Modelling the effect of ‘heel to toe’ roll-over contact on the walking dynamics of passive biped robots. Applied Mathematical Modelling
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Hafezi, F., Ransing, R., & Ransing, R. (2013). Computational modelling of fluid structure interaction at nano-scale boundaries with modified Maxwellian velocity distribution. Applied Mathematical Modelling
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Ransing, R. (2011). Enhancing undergraduate student skills to meet research challenges: Case Studies and Examples. The Journal of Engineering Education, XII special issue – Research in State Engineering Colleges in – A Road Map, XXV(1-2)SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24897
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Ransing, R. (2009). An innovative extrusion die layout design approach for single-hole dies. Journal of Materials Processing Technology
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R., S., M., P., & Ransing, R. (2006). Optimization in castings—An overview of relevant computational technologies and future challenges. Metallurgical and Materials Transactions B, 37(6), 905-911.
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Harris, A., Hargreaves, A., Southworth, G., & Ransing, R. (2005). Editorial. School Leadership & Management, 25(4), 317-319.
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Ransing, R., Pao, W., Lin, C., Sood, M., Lewis, R., & Ransing, R. (2005). Enhanced medial axis interpolation algorithm and its application to hotspot prediction in a mould–casting assembly. International Journal of Cast Metals Research, 18(1), 1-12.
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Postek, E., Lewis, R., Gethin, D., Ransing, R., & Ransing, R. (2005). Influence of initial stresses on the cast behaviour during squeeze forming processes. Journal of Materials Processing Technology, 159(3), 338-346.
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Ransing, R., Sood, M., Pao, W., & Ransing, R. (2005). Computer implementation of Heuvers' circle method for thermal optimisation in castings. , 119-126.
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Ransing, R., Savino, S., Lewis, R., & Ransing, R. (2005). Numerical optimisation of tilt casting process. , 109-118.
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Ransing, R. & Ransing, R. (2004). International Journal of Numerical Methods of Heat and Fluid Flow: Editorial. , 14SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24509
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Ransing, R., Lewis, R., & Gethin, D. (2004). Using a deformable discrete-element technique to model the compaction behaviour of mixed ductile and brittle particulate systems. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 362(1822), 1867-1884.
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W.K.S, P., R.S, R., R.W, L., C, L., & Ransing, R. (2004). A medial-axes-based interpolation method for solidification simulation. Finite Elements in Analysis and Design, 40(5-6), 577-593.
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R.W., L., R.S., R., W.K.S., P., K., K., J., B., & Ransing, R. (2004). Alternative techniques for casting process simulation. International Journal of Numerical Methods for Heat & Fluid Flow, 14(2), 145-166.
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Gethin, D., Lewis, R., Ransing, R., & Ransing, R. (2003). A discrete deformable element approach for the compaction of powder systems. Modelling and Simulation in Materials Science and Engineering, 11(1), 101-114.
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Javier, B., Rajesh, R., & Ransing, R. (2003). 10th anniversary conference of ACME-UK. Communications in Numerical Methods in Engineering, 19(9), 657-657.
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Lewis, R., Ransing, M., Ransing, R., & Ransing, R. (2002). An approach for casting defect analysis employing finite element design optimisation, media axis transformation and neural networks. , 15SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24520
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Cox, I., Lewis, R., Ransing, R., Laszczewski, H., Berni, G., & Ransing, R. (2002). Application of neural computing in basic oxygen steelmaking. Journal of Materials Processing Technology, 120(1-3), 310-315.
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D.T, G., R.S, R., R.W, L., M, D., A.J.L, C., & Ransing, R. (2001). Numerical comparison of a deformable discrete element model and an equivalent continuum analysis for the compaction of ductile porous material. Computers & Structures, 79(13), 1287-1294.
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Lewis, R., Manzari, M., Ransing, R., Gethin, D., & Ransing, R. (2000). Casting shape optimization via process modelling. , 21SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24525
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R.W, L., M.T, M., R.S, R., D.T, G., & Ransing, R. (2000). Casting shape optimisation via process modelling. Materials & Design, 21(4), 381-386.
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R.S, R., D.T, G., A.R, K., P, M., R.W, L., & Ransing, R. (2000). Powder compaction modelling via the discrete and finite element method. Materials & Design, 21(4), 263-269.
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R.W., L., R.S., R., & Ransing, R. (2000). The optimal design of interfacial heat transfer coefficients via a thermal stress model. Finite Elements in Analysis and Design, 34(2), 193-209.
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Ransing, R., Lewis, R., Gethin, D., & Ransing, R. (1999). Lewis-Ransing correlation to optimally design the metal-mould heat transfer. , 9SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24528
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Ransing, R., Gethin, D., Lewis, R., Rowe, R., Roberts, R., & Ransing, R. (1999). Modelling and simulation of the compaction of pharmaceutical powders. , 51SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24527
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R.S., R., R.W., L., D.T., G., & Ransing, R. (1999). Lewis‐Ransing correlation to optimally design the metal‐mould heat transfer. International Journal of Numerical Methods for Heat & Fluid Flow, 9(3), 318-334.
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Lewis, R., Ransing, R., & Ransing, R. (1998). Correlation to describe interfacial heat transfer during solidification simulation and its use in the optimal feeding design of castings. , 29SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24532
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Ransing, R., Lewis, R., & Ransing, R. (1998). Recognising patterns in rejection data for diagnosis. , 10SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24530
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R., W., R., S., & Ransing, R. (1998). A correlation to describe interfacial heat transfer during solidification simulation and its use in the optimal feeding design of castings. Metallurgical and Materials Transactions B, 29(2), 437-448.
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Ransing, R., Lewis, R., & Ransing, R. (1997). Optimal design of die coating thickness using the Lewis-Ransing correlation. , 9SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24535
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R., S., R.W., L., & Ransing, R. (1997). A semantically constrained neural network for manufacturing diagnosis. International Journal of Production Research, 35(9), 2639-2660.
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R., W., R.S., R., & Ransing, R. (1997). A semantically constrained Bayesian network for manufacturing diagnosis. International Journal of Production Research, 35(8), 2171-2188.
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R., S., M., N., R., W., & Ransing, R. (1995). ICADA: Intelligent computer aided defect analysis for castings. Journal of Intelligent Manufacturing, 6(1), 29-40.
Llyfrau Awdurol
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Nawi, N., Ransing, R., Salleh, M., Ghazali, R., Hamid, N., & Ransing, R. (2010). Database Theory and Application, Bio-Science and Bio-Technology
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Dyson, P., Ransing, R., Williams, P., & Williams, P. (2008). Fluid Properties at Nano/Meso Scale Wiley.
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Ransing, R., Ransing, M., Lewis, R., & Ransing, R. (2003). On the limitations of neural network techniques for analysing cause and effect relationships in manufacturing processes - A case studySU Repository: https://cronfa.swan.ac.uk/Record/cronfa24515
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Ransing, R., Ransing, M., Lewis, R., & Ransing, R. (2003). The importance of an adaptive gain variation method in back-propagation neural network learning algorithmsSU Repository: https://cronfa.swan.ac.uk/Record/cronfa24513
Cyfraniadau Cynadleddau
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Ransing, R., Brown, S., Roshan, H., & Ransing, M. (2017). How to save money in a foundry production with opportunities offered by Industry 4.0 and ISO9001:2015 Standard.. In Plenary Lecture, Jubilee 25th International Scientific and Technical Conference "Foundry production and metallurgy” (pp. 56-64). BNTU.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63492
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Ransing, M. & Ransing, R. (2014). “If Only My Foundry Knew What it Knows ...”: A 7Epsilon Perspective on Root Cause Analysis and Corrective Action Plans for ISO9001:2008. In Proceedings of the 61nd Annual Technical Conference on Investment Casting, Covington, KY, USA, October 5-8, 2014SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24537
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Roshan , H., Giannetti, C., Ransing, M., & Ransing, R. (2014). “If only my foundry knew what it knows …”: A 7Epsilon perspective on root cause analysis and corrective action plans for ISO9001:2008. In World Foundry Congress 2014SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24479
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Paine, A., Ransing, R., Gethin, D., Sims, G., Richley, J., Boissevain, L., Lewis, M., & Ransing, R. (2013). Challenges faced by a small ship yard in integrating computer aided design and production processes - A real life case study.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24491
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Nazri, M., Rajesh, S., Meghana, R., & Ransing, R. (2008). A New Method to Improve the Gradient Based Search Direction to Enhance the Computational Efficiency of Back Propagation Based Neural Network Algorithms. In 2008 Second Asia International Conference on Modelling & Simulation (AMS)IEEE.
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Nawi, N., Ransing, M., Ransing, R., & Ransing, R. (2007). Improving the gradient based search direction to enhance training efficiency of back propagation based neural network algorithms.
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Nazri, N., Meghana, R., Rajesh, R., & Ransing, R. (2006). An Improved Learning Algorithm Based on The Broyden-Fletcher-Goldfarb-Shanno (BFGS) Method For Back Propagation Neural Networks. In Sixth International Conference on Intelligent Systems Design and ApplicationsIEEE.
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Ransing, R., Sood, M., & Ransing, R. (2005). Review of optimization methods for casting simulation.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24503
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Ahmad, R., Gethin, D., Lewis, R., Ransing, R., Postek, E., & Ransing, R. (2005). Thermal optimisation of the squeeze-forming process using genetic algorithms.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24502
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Lewis, R., Postek, E., Ransing, R., Han, Z., Gethin, D., & Ransing, R. (2004). A finite element model of the squeeze casting process.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24511
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Malan, A., Lewis, R., Ransing, R., & Ransing, R. (2003). Modeling Coupled Heat and Mass Transfer in Drying Capillary Hygroscopic and Non-hygroscopic Porous Materials.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24516
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Ransing, R., Pao, W., Lewis, R., & Ransing, R. (2003). Solidification and thermal stress simulation using medial objects.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24514
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X., S., R., W., D., T., R., S., R., C., & Ransing, R. (2002). Discrete-Finite Element Modelling of Pharmaceutical Powder Compaction: A Two-Stage Contact Detection Algorithm for Non-Spherical Particles. In Discrete Element MethodsAmerican Society of Civil Engineers.
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Lewis, R., Cross, J., Gethin, D., Ransing, R., Manzari, M., Rahman, N., & Ransing, R. (1998). Recent developments in heat transfer and porous media.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa24531
Cynnyrch Ymchwil Arall
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Ransing, R. & Ransing, R. (2010). Back to basics: Process optimisation using in-process dataSU Repository: https://cronfa.swan.ac.uk/Record/cronfa24493
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Ransing, R. & Ransing, R. (2010). Challenges in investment casting process controlSU Repository: https://cronfa.swan.ac.uk/Record/cronfa24492
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Nazri, M., Meghana, R., Rajesh, S., & Ransing, R. (2007). Research and Development in Intelligent Systems XXIII
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Ransing, R., Ransing, M., & Ransing, R. (2007). Innovations in machine learning and defect diagnosticsSU Repository: https://cronfa.swan.ac.uk/Record/cronfa24496
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Ransing, R. & Ransing, R. (2006). Software solutions: Recall with X1Recall.comSU Repository: https://cronfa.swan.ac.uk/Record/cronfa24500
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Ransing, R. & Ransing, R. (2005). 'Thinking' software set to revolutionise defect analysisSU Repository: https://cronfa.swan.ac.uk/Record/cronfa24506
Goruchwyliaeth
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Deep Learning in Computational Fluid Dynamics (cyfredol)
PhDGoruchwyliwr arall: Prof Mike Jennings -
Evolution of computational tools and experimental methods for the development of passive prosthetic feet. (dyfarnwyd 2022)
EngDGoruchwyliwr arall: Dr Nicholas Owen -
An investigation into the sterilisation capabilities of biopolymers and the introduction of an organisational knowledge management methodology for the medical device industry. (dyfarnwyd 2022)
MScGoruchwyliwr arall: Dr Will Harrison
Modiwlau a Addysgir
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EG-261 Thermodynamics 2
The module aims to introduce two main concepts: (i) thermodynamic efficiency and (ii) irreversibility applied to a variety of energy conversion processes involving heat to work transfer and vice a versa. Engineering examples will include heat, work and/or mass transfer associated with a number of steady/unsteady flow systems.
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EG-M93 Metallurgy and Alloy Design
The module will be presented with real life scenario of improving mechanical properties of a cast component by providing suggestions for optimising its alloy composition. The module will cover the necessary knowledge required to understand the metallurgical concepts and terminology used in peer-reviewed scientific papers so that students can not only review them but evaluate results and use the information to make informed decisions in the context of alloy design.