id ump-4943
recordtype eprints
spelling ump-49432017-04-07T01:58:54Z http://umpir.ump.edu.my/id/eprint/4943/ Prediction of grinding machanability when grinds Haynes 242 using water based coolant Hazwani, Sidik TP Chemical technology Grinding is one of the important finishing machining operations. It is applied at the last stage of manufacturing process so that the high dimensional accuracy and desirable surface finish product can be achieved. However, there is a lot of problem occur in order to achieve the high dimensional accuracy and desirable surface finish. For examples, surface burning due to excessive heat produce and undesirable surface finish outcomes. This report deals with the prediction of grinding machanability when grind Haynes 242 using water based coolant. The aims of this report are to find the optimum parameter of the grinding process which is depth of cut (�m) where the type of surface roughness produces will be investigate and to develop prediction model of surface roughness by using an artificial neural network analysis. This report describes the experimental setups and procedures in finding the optimum value of the depth of cut and thus leading with the development of the prediction model. The material used is Haynes 242 and the depth of cut is independent variables. Calculations of the data were done which had obtained by using Perthometer and analysis was made by using ANN. The grindability results have shown optimum parameter which is gives the lowest surface roughness value. The results from the experiment show that the Al2O3 wheel gives a good surface roughness compare to the SiC at the depth of cut 5μm. By the end of the projects, prediction model had been developed by using ANN and was compared in the graph. The ANN model obtained from predicted value is accurate and effective in predicting the correlation and R-squared which is give 1% of minimum error and 2% of maximum error when using the Al2O3 grinding wheel. 2012-07 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4943/1/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28Table%20of%20content%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/4943/2/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28Abstract%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/4943/3/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28Chapter%201%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/4943/4/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28References%29.pdf Hazwani, Sidik (2012) Prediction of grinding machanability when grinds Haynes 242 using water based coolant. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:75704&theme=UMP2
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
English
English
topic TP Chemical technology
spellingShingle TP Chemical technology
Hazwani, Sidik
Prediction of grinding machanability when grinds Haynes 242 using water based coolant
description Grinding is one of the important finishing machining operations. It is applied at the last stage of manufacturing process so that the high dimensional accuracy and desirable surface finish product can be achieved. However, there is a lot of problem occur in order to achieve the high dimensional accuracy and desirable surface finish. For examples, surface burning due to excessive heat produce and undesirable surface finish outcomes. This report deals with the prediction of grinding machanability when grind Haynes 242 using water based coolant. The aims of this report are to find the optimum parameter of the grinding process which is depth of cut (�m) where the type of surface roughness produces will be investigate and to develop prediction model of surface roughness by using an artificial neural network analysis. This report describes the experimental setups and procedures in finding the optimum value of the depth of cut and thus leading with the development of the prediction model. The material used is Haynes 242 and the depth of cut is independent variables. Calculations of the data were done which had obtained by using Perthometer and analysis was made by using ANN. The grindability results have shown optimum parameter which is gives the lowest surface roughness value. The results from the experiment show that the Al2O3 wheel gives a good surface roughness compare to the SiC at the depth of cut 5μm. By the end of the projects, prediction model had been developed by using ANN and was compared in the graph. The ANN model obtained from predicted value is accurate and effective in predicting the correlation and R-squared which is give 1% of minimum error and 2% of maximum error when using the Al2O3 grinding wheel.
format Undergraduates Project Papers
author Hazwani, Sidik
author_facet Hazwani, Sidik
author_sort Hazwani, Sidik
title Prediction of grinding machanability when grinds Haynes 242 using water based coolant
title_short Prediction of grinding machanability when grinds Haynes 242 using water based coolant
title_full Prediction of grinding machanability when grinds Haynes 242 using water based coolant
title_fullStr Prediction of grinding machanability when grinds Haynes 242 using water based coolant
title_full_unstemmed Prediction of grinding machanability when grinds Haynes 242 using water based coolant
title_sort prediction of grinding machanability when grinds haynes 242 using water based coolant
publishDate 2012
url http://umpir.ump.edu.my/id/eprint/4943/
http://umpir.ump.edu.my/id/eprint/4943/
http://umpir.ump.edu.my/id/eprint/4943/1/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28Table%20of%20content%29.pdf
http://umpir.ump.edu.my/id/eprint/4943/2/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28Abstract%29.pdf
http://umpir.ump.edu.my/id/eprint/4943/3/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28Chapter%201%29.pdf
http://umpir.ump.edu.my/id/eprint/4943/4/Prediction%20of%20grinding%20machanability%20when%20grinds%20Haynes%20242%20using%20water%20based%20coolant%20%28References%29.pdf
first_indexed 2023-09-18T21:59:59Z
last_indexed 2023-09-18T21:59:59Z
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