Surface roughness in lathe boring operation
Optimizing the cutting parameters is important to obtain the best surface roughness, to minimize the cost of production and to increase productivity. The main objective of the project are to study the optimum cutting parameters that are the cutting speed, feed rate and depth of cut for single tool b...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2012
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| Online Access: | http://umpir.ump.edu.my/id/eprint/7652/ http://umpir.ump.edu.my/id/eprint/7652/1/ALISANDRA_ARIEZA_FOU_BT_MUHD_FARID_FOU.PDF |
| _version_ | 1848818052319150080 |
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| author | Alisandra Arieza Fou, Muhd Farid Fou |
| author_facet | Alisandra Arieza Fou, Muhd Farid Fou |
| author_sort | Alisandra Arieza Fou, Muhd Farid Fou |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Optimizing the cutting parameters is important to obtain the best surface roughness, to minimize the cost of production and to increase productivity. The main objective of the project are to study the optimum cutting parameters that are the cutting speed, feed rate and depth of cut for single tool boring process to obtain the best surface roughness. The Brinell hardness of the material tested is 151. In this study, the Design of Experiment (DOE) with Box-Behnken design is used. By using the STATISTICA software a table of run was generated based on the full factorial with three factor and three levels. Twenty seven experiments are then run according to the "Table of run" generated by the STATISTICA software and the surface roughness value is recorded. Analysis of variance (ANOVA) was used to identify the significant cutting parameters that affect the surface roughness. The ANOVA table has shown that from the 27 experiments, cutting speeds and depth of cut are significant. From the experiment, rough optimization values are obtained. The rough optimizations of cutting speeds are 110 mlmin and the depths of cut are , 0.278 mm gives a surface roughness value of 2.18 pm. The experiments are continued by another ten experiments to find the fine optimized cutting speed and depth of cut to obtain the best surface roughness. It was concluded that the fine optimization cutting speeds for the mild steel (AISI 1019) are 112 m/min and the depths of cut are 0.182 mm gives a surface roughness of 2.06 pm for the specific machine. The usage of a harder material which is commonly used in industry and cutting parameter such as tool nose radius and length of the boring tool is highly recommended to find the optimization parameter for the best surface roughness in the boring operation. |
| first_indexed | 2025-11-15T01:31:32Z |
| format | Undergraduates Project Papers |
| id | ump-7652 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:31:32Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-76522021-05-28T13:23:05Z http://umpir.ump.edu.my/id/eprint/7652/ Surface roughness in lathe boring operation Alisandra Arieza Fou, Muhd Farid Fou TA Engineering (General). Civil engineering (General) Optimizing the cutting parameters is important to obtain the best surface roughness, to minimize the cost of production and to increase productivity. The main objective of the project are to study the optimum cutting parameters that are the cutting speed, feed rate and depth of cut for single tool boring process to obtain the best surface roughness. The Brinell hardness of the material tested is 151. In this study, the Design of Experiment (DOE) with Box-Behnken design is used. By using the STATISTICA software a table of run was generated based on the full factorial with three factor and three levels. Twenty seven experiments are then run according to the "Table of run" generated by the STATISTICA software and the surface roughness value is recorded. Analysis of variance (ANOVA) was used to identify the significant cutting parameters that affect the surface roughness. The ANOVA table has shown that from the 27 experiments, cutting speeds and depth of cut are significant. From the experiment, rough optimization values are obtained. The rough optimizations of cutting speeds are 110 mlmin and the depths of cut are , 0.278 mm gives a surface roughness value of 2.18 pm. The experiments are continued by another ten experiments to find the fine optimized cutting speed and depth of cut to obtain the best surface roughness. It was concluded that the fine optimization cutting speeds for the mild steel (AISI 1019) are 112 m/min and the depths of cut are 0.182 mm gives a surface roughness of 2.06 pm for the specific machine. The usage of a harder material which is commonly used in industry and cutting parameter such as tool nose radius and length of the boring tool is highly recommended to find the optimization parameter for the best surface roughness in the boring operation. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7652/1/ALISANDRA_ARIEZA_FOU_BT_MUHD_FARID_FOU.PDF Alisandra Arieza Fou, Muhd Farid Fou (2012) Surface roughness in lathe boring operation. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. |
| spellingShingle | TA Engineering (General). Civil engineering (General) Alisandra Arieza Fou, Muhd Farid Fou Surface roughness in lathe boring operation |
| title | Surface roughness in lathe boring operation |
| title_full | Surface roughness in lathe boring operation |
| title_fullStr | Surface roughness in lathe boring operation |
| title_full_unstemmed | Surface roughness in lathe boring operation |
| title_short | Surface roughness in lathe boring operation |
| title_sort | surface roughness in lathe boring operation |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://umpir.ump.edu.my/id/eprint/7652/ http://umpir.ump.edu.my/id/eprint/7652/1/ALISANDRA_ARIEZA_FOU_BT_MUHD_FARID_FOU.PDF |