An Application of the Random Balance Method in Conjunction with the Plackett-Burman Screening Design in Metal Cutting Tests

Abstract

This papers deals with an experimental study of metal cutting, particularly gundrilling. It argues that a proper experimental methodology based on the design of experiments (DOE) is an appropriate instrument to improve productivity and efficiency of machining. A screening DOE based on the random balance method and the Plackett-Burman screening design is considered. Such a DOE is referred to as a sieve design. The proposed method has proven to be very useful at the first stage of an experimental study of complex parameters as, for example, tool life testing, where the experimentalist wishes to include into consideration many design and process parameters. Conducting a relatively simple sieve DOE, the experimentalist easily can distinguish significant factors and their interactions of any order to be used in the subsequent full block DOE. A practical example of an application using the proposed DOE, a tool life test of gundrills, is considered in detail.

An investigation into the machining characteristics of titanium using ultrasonic machining

“…There are several approaches to design the experiments such as full factorial designs, fractional factorials, Latin square designs and taguchi's robust design of experiments technique. The identification of all the significant two-way interactions between the different factors cannot be realised effectively by using techniques such as fractional factorials and taguchi's robust design methodology (Astakhov, 2004). Moreover, if any crucial factor is missed at the time of experimentation or any particular combination of the selected factors is not put into trial, sometimes the results obtained might just be inadequate from the point of view of optimisation.…”

Screening the Main Factors Affecting the Wear of the Scraper Conveyor Chute Using the Plackett–Burman Method

“…Plackett-Burman design (PBD) is a kind of balanced incomplete blocks method. It has been proven to play an important role in the first stage of complex parameter experimental research [21][22][23]. In the Plackett-Burman design, at most n-1 variables can be studied by n experiments.…”

Tool life testing in gundrilling: an application of the group method of data handling (GMDH)

“…The techniques of the design of experiments (DOE) allows significant improvements in the methodology of machining tests [2][3][4]. It is true, however, only if DOE is implemented properly.…”

“…Probably the weakest features of implementation of traditional DOE in metal cutting studies are: a very limited number of design/process variables that can be included in the test; pre-set mathematical (statistical) model; subjective pre-process decisions and uncertainties in the machining data collected experimentally [2]. To deal with the number of variables included in the text, an additional screening DOE is often needed [4], while the other mentioned issues cannot be resolved in principle within the scope of traditional DOE. This explains rare use of this experimental technique in metal cutting studies.…”

“…In testing gundrills [4], for example, there are a number of geometry variables (rake angles, flank angles, cutting edge angles, inclination angles, etc.) and design variables (the number of and location of cutting edges, coolant hole shape and location, profile angle of the chip removal flute, shoulder dub-off shape and location, number and location of the supporting pads, back taper, etc.)…”