Milling Operation and its Optimization – A Literature Review

 

S. S. K. Deepak

Rungta College of Engineering and Technology (R1), Raipur, Chhattisgarh, India, 492099

*Corresponding Author: sskdeepak107@gmail.com

ABSTRACT:

Establishment of efficient machining parameters has been a problem that has confronted manufacturing industries for nearly a century, and is still the subject of many studies. Optimum machining parameters are of great concern in manufacturing environments, where economy of machining operation plays a key role in competitiveness in the market. Determination of the optimal cutting parameters (cutting conditions) like the number of passes, depth of cut for each pass, speed, and feed is considered as a crucial stage of multi-pass machining as in the case of all chip removal processes and especially in milling operation. The effective optimization of these parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper outlines the development of an optimization strategy to determine the optimum cutting parameters for milling operations like plain milling and face milling. This paper also underlies the importance of using optimization strategies rather than handbook recommendations as well as pointing out the superiority of the multi-pass over the single-pass optimization approach. Owing to the significant role that machining parameters play in performing successful and efficient machining operations, determination of the best or optimum machining parameters is still the subject of many studies. The need to use optimum machining parameters to improve machining efficiency is of greater importance when NC machines with high capital cost are employed. This paper describes the various optimization techniques which determine optimum machining parameters for milling operations. These parameters are intended for use by NC machines; however, they can also be used by conventional machines. The paper discusses both single-tool and multi-tool milling operations where emphasis has been placed on the latter. Although many efforts have been made to optimize machining parameters, from the review of the published literature it can be concluded that most of the work done is restricted to turning operations, and other machining operations, including milling, have gained little attention. Owing to the significant role that milling operations play in today's manufacturing world, there is a vital need to optimize machining parameters for this operation, particularly when NC machines are employed.

 

KEY WORDS :cutting parameters, milling, optimization

 

INTRODUCTION:

Milling is a machining operation in which a work piece is fed past a rotating cylindrical tool with multiple cutting edges. The axis of rotation of the tool is perpendicular to the feed direction. The tool is called the milling cutter and the cutting edges are called teeth. Mostly plane surfaces are created through milling. It’s an interrupted cutting operation; the teeth of milling cutter enter and exit work piece during each revolution. So, the tool material and cutter geometry must be chosen carefully to withstand cycles of impact forces and thermal shock.

 

 

Milling is the process of machining flat, curved, or Milling machines are basically classified as vertical or irregular surfaces by feeding the work piece against a rotating horizontal. These machines are also classified as knee-type, cutter containing a number of cutting edges. The milling rams type, manufacturing or bed type, and planer-type. Most machine consists basically of a motor driven spindle, which milling machines have self-contained electric drive motors, mounts and revolves the milling cutter, and a reciprocating coolant systems, variable spindle speeds, and power-operated adjustable worktable, which mounts and feeds the work piece. Different types of milling operations are shown in Figure1:

Figure 1: Different types of milling operations

 

Since the turn of the century quite a number of attempts have been made to find the optimum values of machining parameters. In the efforts made by researchers, different objective functions have been considered, including minimum production cost¹, minimum production time², weighted combination of 1 and 2^3,4, maximum metal removal rate^5,6 and maximum profit rate⁷. Use of many methods has been reported in the literature to solve optimization problems for machining parameters. These methods include various nomograms⁸, graphical methods⁹, performance envelope¹⁰, linear programming¹¹, Lagrangian multipliers¹², geometric programming^{13, 14}, dynamic programming¹⁵, and artificial intelligence¹⁶. Some researchers optimized machining parameters based on a single variable without considering any constraint^{17, 18}. However, it is obvious that the real optimum values of machining parameters cannot be achieved without considering all variables and constraints simultaneously. A direct search procedure on the depth/feed combinations was employed by some researchers^{19, 20}, giving satisfactory chip control. In this method the area in the depth feed region was approximated to a quadrilateral and divided into a 20 by 20 grid. Subsequently, all points on the grid were checked for the constraints. However, this work was limited to calculating the machining parameters only for turning operations. In another work, Enparantza²¹ developed a tool selection module for rough and finish milling based on economic grounds, which has led to the enhancement of an existing package for optimization of cutting conditions. His work led to improvements in economy of machining. However, it is the subject of legitimate criticism. The optimization procedure was based on a general search method, where the objective function was minimized with

 

respect to the cutting speed, keeping other machining parameters constant. In other words, cutting speed has been optimized once other machining parameters have been obtained. Apparently machining parameters are interactive and must be optimized simultaneously in order to achieve the best results. Duffuaa et al.²² compared the performance and utilization of the six optimization methods presented in the literature. Some researchers focused on the optimization

 

of machining parameters for turning operations when more than one machining pass was required^{23, 24, 25}. Attempts have also been made to optimize machining parameters based on cutting forces^{26, 27}. Wang and Armarego²⁸ studied a method to optimize machining parameters for milling operations; however, this work was restricted only to face milling operations. It is surprising that while comprehensive optimization strategies and computer software have been developed for turning operations, optimization of machining parameters for milling operations still rely on methods that neither guarantee the best optimum solutions nor provide clearly defined economic characteristics of the optimization problem²⁹. Another criticism is that some researchers considered power as the only constraint, and ignored other constraints such as cutting force and surface finish. Therefore, there is a vital need to develop a system for milling operations, especially when NC machines are employed.

 

MATERIAL AND METHODS:

Plain Milling:

Plain milling, also called surface milling or slab milling is milling flat surfaces with the milling cutter axis parallel to the surface being milled. Generally, plain milling is done with the work piece surface mounted parallel to the surface of the milling machine table and the milling cutter mounted on a standard milling machine arbor. The arbor is well supported in a horizontal plane between the milling machine spindle and one or more arbor supports. The work piece is generally clamped directly to the table or supported in a vise for plain milling. The milling machine table should be checked for alignment before starting to cut. If the work piece surface to be milled is at an angle to the base plane of the piece, the work piece should be mounted in a universal vise or on an adjustable angle plate. The holding device should be adjusted so that the work piece surface is parallel to the table of the milling machine.

Figure 2: Plain milling operation

 

Face Milling:

Face milling is the milling of surfaces that are perpendicular to the cutter axis, as shown in Figure 3. Face milling produces flat surfaces and machines work to the required length. In face milling, the feed can be either horizontal or vertical. In face milling, the teeth on the periphery of the cutter do practically all of the cutting. However, when the cutter is properly ground, the face teeth actually remove a small amount of stock which is left as a result of the springing of the work piece or cutter, thereby producing a finer finish. Large surfaces are generally face milled on a vertical milling machine with the work piece clamped directly to the milling machine table to simplify handling and clamping operations.

 

Figure 3: Face milling operation

 

Development of milling operation:

It is possible to identify two stages of development of milling machine tools and machine centers: (1) pre-1980, when the investment was driven to take advantage of the reduced non-productive time due to numerical control and, simultaneously, a revolution in machine control and machine structure was observed; (2) after 1980, when machining centers focused on reducing the long set-up and tool change times associated with the milling process. After 1980, progress was based on three vectors: development of machines with more degrees of freedom in their motions, development of manufacturing organization and improvement of the properties of cutting edges. Although CAM systems can automatically provide tool paths, recommend tools and cutting conditions according to work-piece materials, cutting operations and cutting types, the heuristic knowledge and accumulated experience of machinists are indispensable for troubleshooting and optimization of cutting conditions beyond the capabilities of data-based recommendations. However, it is difficult to mimic the experience and skills of machinists in selecting tools and cutting conditions. Furthermore, there is some optimization dependence on heuristic knowledge.

 

Optimization of milling operation:

 In general, the selection of parameters is based on acquired experience considering the shape of work-piece, the technological requirements and the capability of the machine, the cutting tool and the work-piece material. The empirical aspects of this selection process do not result in an optimal solution. Thus, it is advisable to use a mathematical formulation aimed at optimization of operating conditions to satisfy an economic objective. Depth of cut, feed rate and cutting speed has the greatest effect on the success of a machining operation. Therefore, in practice, only these parameters are considered. Depth of cut is usually predetermined by the work piece geometry and operation sequence. It is recommended to machine the features with the required depth in one pass to keep machining time and cost low, when possible. Therefore, the problem of determining machining parameters is reduced to determining the proper cutting speed and feed rate combination.

 

For developing a mathematical formulation, the following things are to be known:

Ø  Knowledge of machining (i.e., turning or milling);

Ø  Empirical equations relating the tool life, forces, power, surface finish and arbor deflection, etc., to develop realistic constraints;

Ø  Specification of machine tool capabilities, (i.e., maximum power or maximum feed available from a machine tool);

Ø  Development of an effective optimization criterion, (e.g., maximum production rate, minimum production cost, maximum profit or a combination of these);

Ø  Knowledge of mathematical and numerical optimization techniques, like the Simplex method,

Ø  Search method, Geometric programming and dynamic programming, etc.

 

The progress in developing constrained optimization systems for milling operations has been even slower than for turning operations, since the milling has a more complex cutting mechanism than that of turning. Today, there are only a few works on the optimization of multi-pass milling operations cited in the literature. There are currently two approaches to solve the problem:

Ø  Using computer aided mathematical programming techniques, and

Ø  Using numerical search techniques

 

Recently, Wang³⁰ has developed an optimization software for multi-pass peripheral and end milling operations which use a combination of the above two considerations based on the objective function of “maximum production rate”. He has also verified the superiority of multi-pass over the single-pass by carrying out some simulation tests. In this paper, the development of a constrained optimization system for multi-pass face milling operations is outlined. The optimum number of passes is first determined via dynamic programming, and then the optimal values of the cutting parameters are found based on the objective function “maximum production rate” and using a non-linear programming technique “geometric programming”. The algorithm used in this study is adopted from the study of Agapiou³¹ which is proposed for the multi-pass turning operations. However, the methodology used in this work is rather different because the geometric programming is preferred in lieu of the Nelder–Mead Simplex Search method in the optimization of each stage of the dynamic programming. Also, it is well worth pointing out that the cutting mechanism and constraints to the face milling problem are quite different from those of turning processes.

 

CONCLUSIONS:

Although many efforts have been made to optimize machining parameters, from the review of the published literature it can be concluded that most of the work done is restricted to turning operations, and other machining operations, including milling, have gained little attention. Owing to the significant role that milling operations play in today's manufacturing world, there is a vital need to optimize machining parameters for this operation, particularly when NC machines are employed. Optimization of cutting parameters in milling needs to be studied because of its influence on machining time and cost. Researches on machining time and cost modeling are very scarce. Optimum and economical values of cutting parameters give minimum production time, minimum production cost, maximum production rate and maximum profit rate. this paper describes the development of optimization models and their use to optimize machining parameters for milling operations. In this work, three objective functions, i.e. minimum production cost, minimum production time (maximum production rate) and maximum profit rate (maximum efficiency), have been considered for both single-tool and multi-tool operations. Optimum machining parameters resulting from this work are intended for use by NC machines in order to improve machining efficiency

 

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Received on 25.09.2012                             Accepted on 25.10.2012        

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