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Virtual three-axis milling process simulation and optimizationMerdol, Doruk Sūkrū 05 1900 (has links)
The ultimate goal in the manufacturing of a part is to achieve an economic production plan with precision and accuracy in the first attempt at machining. A physics-based comprehensive modeling of the machining processes is a fundamental requirement in identifying optimal cutting conditions which result in high productivity rates without violating accuracy throughout the part production process.
This thesis presents generalized virtual simulation and optimization strategies to predict and optimize performance of milling processes up to 3-axis. Computationally efficient mathematical models are introduced to predict milling process state variables such as chip load, force, torque, and cutting edge engagement at discrete cutter locations. Process states are expressed explicitly as a function of helical cutting edge - part engagement, cutting coefficient and feedrate. Cutters with arbitrary geometries are modeled parametrically, and the intersection of helical cutting edges with workpiece features are evaluated either analytically or numerically depending on geometric complexity. The dynamics of generalized milling operations are modeled and the stability of the process is predicted using both time and frequency domain based models. These algorithms enable rapid simulation of milling operations in a virtual environment as the part features vary.
In an effort to reduce machining time, a constraint-based optimization scheme is proposed to maximize the material removal rate by optimally selecting the depth of cut, width of cut, spindle speed and feedrate. A variety of user defined constraints such as maximum tool deflection, torque/power demand, and chatter stability are taken into consideration. Two alternative optimization strategies are presented: pre-process optimization provides allowable depth and width of cut during part programming at the computer aided manufacturing stage using chatter constraint, whereas the post-process optimization tunes only feedrate and spindle speed of an existing part program to maximize productivity without violating physical constraints of the process. Optimized feedrates are filtered by considering machine tool axes limitations and the algorithms are tested in machining various industrial parts.
The thesis contributed to the development of a novel 3-axis Virtual Milling System that has been deployed to the manufacturing industry. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate
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Predicting commercial milling results by experimental meansMehrotra, Dinesh January 2011 (has links)
Charts in pocket. / Digitized by Kansas State University Libraries
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Concepts of a single-floor flour millFairchild, Fred January 2011 (has links)
Digitized by Kansas State University Libraries
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Theory and application of impact grindingHibbs, Arthur Nathan. January 1947 (has links)
LD2668 .T4 1947 H5 / Master of Science
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Development of an efficient hammer mill based on energy studies of maize kernel fractureAjayi, O. A. January 1983 (has links)
No description available.
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Three dimensional force modelling for milling operationsFaraz, A. January 1985 (has links)
No description available.
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Intelligent rough machining of sculptured partsLi, Hui 15 May 2017 (has links)
Sculptured parts, characterized by interconnected and bounded parametric surface
patches, are widely used in aerospace, automobile, shipbuilding and plastic mold
industries due to their functional and aesthetic properties. However, adoption
of these sculptured surfaces on mechanical products increases the complexity of
manufacturing and puts forward a challenge to achieve high machining quality
and productivity, as well as low machining cost.
Machining of sculptured parts is mostly carried out on a milling machine. The
milling process can be divided into: rough cut (roughing) and fine cut (finishing)
operations. Rough machining is used to remove excess stock material, while finish
machining is aimed at generating adequate tool paths for producing the final
shape of the part. When a sculptured part is machined from prismatic stock, a
large amount of rough cut, up to 90 percent of the total machining, is required.
Cutting time reduction in rough machining can considerably improve the efficiency
of sculptured part machining, lower production cost.
This research focuses on the productivity improvement of sculptured part
rough milling machining that is affected essentially by CNC tool path and machining
parameters. Two major strategies, machining path strategy and machining
parameter strategy are investigated. A number of new methods are introduced to
generate highly productive CNC tool path and machining parameters.
Study on machining path strategy involves approaches of generating 2½D CNC
tool path trajectory, creating new tool path patterns, and automatically identifying
optimal tool path pattern. While research on machining parameter strategy focuses
on the minimization of cutting time, based upon the changing part geometry
during machining and manufacturing constraints. A method that incorporates an
existing milling process model into the cutting parameter optimization to predict
instantaneous cutting force and identify the most effective cutting parameters is
introduced. An improved model cofficient determination scheme using numerical
optimization and artificial neural network techniques is developed, and extensive
cutting tests are carried to allow the milling process model to fit into the cutting
parameter optimization. A method for the automated formulation and solution
of the cutting time minimization problem is also introduced to allow important
machining parameters, including the number of cutting layers, depth of cut, feed
rate and cross-cutting depth, to be determined without human intervention.
The research directly contributes to automated sculptured part machining, and has a great potential to produce significant economical benefits to manufacturing
industry. The study also establishes a platform for further research and
development on intelligent sculptured part machining. / Graduate
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An investigation of the effectiveness of removing "hidden" infestation in wheat by means of the entoleter scourer-aspiratorSwenson, Eugene Douglas. January 1950 (has links)
Call number: LD2668 .T4 1950 S84 / Master of Science
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Surface roughness prediction when milling with square insertsMunoz-Escalona, Patricia January 2010 (has links)
No description available.
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Flour mill break extractionsWingfield, John G January 2011 (has links)
Digitized by Kansas Correctional Industries
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