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    <subfield code="a">Development of 1st and 2nd order tool life model when machining modified AISI P20 tool steel /</subfield>
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    <subfield code="a">Project paper (Bachelor of Mechanical Engineering with Manufacturing Engineering) -- Universiti Malaysia Pahang - 2009</subfield>
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    <subfield code="a">This thesis deals with tool life durability when performing end-milling operation on modified AISI P20 tool steel using TiN coated inserts. The objectives of this thesis is to develop the 1st and 2nd order tool life model when machining modified AISI P20 tool steel and to investigate the relationship between cutting parameters; cutting speed, feedrate, axial depth, radial depth with tool life. This prediction model was then compared with the results obtained experimentally. By using Response Surface Method (RSM) of experiment, first and second order models were developed with 95% confidence level. The 1st order and 2nd order tool life prediction model was developed with the aid of MINITAB software. Modified AISI P20 tool steel were selected as the material in this thesis which commonly used to make plastic injection mold, zinc die-casting, extrusion dies, blow molds, and other structural components. From the results, it is observed that the 2nd order tool life model gives less error percentage compared to the 1st order. Comparing with the 1st order model, 2nd order model gives more accurate value because the average error % shows it has smaller value, which is 0.59%. From both generated regression equation, the relationship between the four cutting parameters with tool life for 1st  and 2nd order model are, the tool life increase with reduction of cutting speed, feedrate, and radial depth excluding the axial depth. For end-milling of P20 tool steel, the optimum conditions that is required to maximize the coated carbide tool life are as follow: cutting speed of 140 m/s, federate of 0.1 mm/rev, axial depth of 1.5 mm and radial depth of 2 mm. Using these parameters, a tool life of 39.46 min was obtained. This value for tool life was obtained from the 2nd order model. Tool life optimization can help to overcome the cutting tool&#x2019;s costs and production time problem.</subfield>
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