On the machinability of medium density fiberboard by drilling

Abstract

Machinability is one of the most important technological properties in the machining process. The machinability index is a numerical value that shows the degree of difficulty or ease with which a material can be machined. The research described herein consisted of drilling blind holes in a medium density fibreboard (MDF) using a cemented carbide tool. Different cutting speeds (vc) and feeds (fn) were used in the tests. The goal was to determine the value of the axial force (Ff), the cutting torque (Mc), and the chip thickness. To analyse signals involving axial force and cutting torque, a methodology for determining the average values of these signals was proposed to avoid random changes in signal values. The results obtained were used to determine the MDF machinability index in the drilling process based on the measurement of the axial force, cutting moment, and shear angle of the chips. The results obtained showed that the machinability index based on the adopted criteria is constant for a given workpiece and does not depend on the cutting parameters.

Full Article

On the Machinability of Medium Density Fiberboard by Drilling

Krzysztof Szwajka^a,* and Tomasz Trzepiecinski ^b

Machinability is one of the most important technological properties in the machining process. The machinability index is a numerical value that shows the degree of difficulty or ease with which a material can be machined. The research described herein consisted of drilling blind holes in a medium density fibreboard (MDF) using a cemented carbide tool. Different cutting speeds (v_c) and feeds (f_n) were used in the tests. The goal was to determine the value of the axial force (F_f), the cutting torque (M_c), and the chip thickness. To analyse signals involving axial force and cutting torque, a methodology for determining the average values of these signals ​​was proposed to avoid random changes in signal values. The results obtained were used to determine the MDF machinability index in the drilling process based on the measurement of the axial force, cutting moment, and shear angle of the chips. The results obtained showed that the machinability index based on the adopted criteria is constant for a given workpiece and does not depend on the cutting parameters.

Keywords: Drilling; Cutting force; Shear angle; Medium density fiberboard (MDF)

Contact information: a: Rzeszow University of Technology, Faculty of Mechanical Engineering and Technology, Kwiatkowskiego 4, 37-450 Stalowa Wola, Poland; b: Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics, al. Powst. Warszawy 8, 35-959 Rzeszów, Poland;

* Corresponding author: kszwajka@prz.edu.pl

INTRODUCTION

Medium density fiberboard (MDF) was commercially produced for the first time in the late 1960s with the intention of competing with particleboard (Clark 1991). Due to their better machinability, dimensional stability, and surface characteristics, MDFs compete with both wood-composite materials and solid wood. Currently, MDFs are mainly used in the production of furniture (Irle and Loxton 1996; Chapman 1998; Sun and Hammett 1999; Szwajka and Trzepieciński 2017). MDFs are usually covered with wood veneer or plastic laminate to simulate the appearance of a solid wood product. For the applications cited, the workability of the MDFs is determined by the quality of the surface machined (Penman et al. 1993; Szwajka and Trzepieciński 2016), which largely depends on the degree of tool wear and the mechanism of chip formation (Bhattacharyya et al. 1993). When parameters such as surface quality, tool wear, chip formation mechanism, and machining forces are discussed in relation to the workpiece material, it is generally referred to as the investigation of the “machinability” of the material. Various studies have elucidated MDF cutting characteristics (Dippon et al. 2000; Engin et al. 2000; Costes and Larricq 2002; Gordon and Hillery 2003), which were mainly focused on measuring cutting forces and friction on the cutting tool using conventional metal cutting theories. The formation of chips was not mentioned.

Lin et al. (2006) described the machinability of MDFs. They used a digital camera to record chip deformation occurring in front of the tool tip and a scanning electron microscope (SEM) for additional analysis of the machined surface. The cited study showed that differences in fiberboard density are closely related to its machinability.

Orthogonal cutting is a form of machining in which the straight cutting edge is perpendicular to the direction of the relative tool movement and is a basic method in the cutting process (Koch 1964). Dippon et al. (2000) presented a mechanical analysis of MDF orthogonal cutting. This investigation adopted the Coulomb friction model on both surfaces of the cutting tool to predict the coefficient of friction on the rake face and tool flank. The cutting forces were expressed as a function of tool geometry, chip thickness, and constant cutting speed. Costes and Larricq (2002) estimated the distribution of stresses on the tool’s rake face in the MDF orthogonal cutting process.

Davim et al. (2007) conducted investigations to determine the relationship between cutting parameters and delamination of the chipboard at the hole entry and exit during drilling of medium-density fibreboard (MDF). An important role was found for the cutting speed with respect to the evolution of the delamination factor as a function of the material removal rate (MRR). The study of Davim et al. (2008) investigated the parametric interaction between cutting speed and feed rate on the delamination factor at entry and exit of the holes in drilling of MDF. Aguilera et al. (2000) found that high density and low chip thickness produce optimal levels of surface roughness in machining of MDF panels.

Concerning the evaluation of delamination around the hole, there are reports (Davim and Reis 2003; Feito et al. 2014) where delamination factors have been used based on the measurement of the maximum diameter of observed delamination, or an area of delamination has been defined. Recently, however, certain workers increasingly use the dimensionless factor to evaluate delamination. Palanikumar et al. (2009) investigated the delamination in drilling of MDF and observed that the delamination can be reduced at low feed rates. Prakash et al. (2009) performed drilling experiments using the Taguchi technique and found that the feed rate and diameter were the most dominant factors that affect the surface quality. Prakash and Palanikumar (2011) found that the increase in drill diameter increases the delamination. Valarmathi and Palanikumar (2011) performed drilling experiments on laminated MDF panels to minimize the delamination and found that thrust force developed in drilling can be reduced with high spindle speed and low feed rate. A similar dependence was confirmed by Valarmathi et al. (2013b). The results showed that the most dominant factors that influence the delamination are the feed rate, followed by the drill diameter. Valarmathi et al. (2013a) measured and analysed the cutting conditions that influence the thrust force in drilling of particleboard panels. The parameters considered were spindle speed, feed rate, and point angle. The results showed that high spindle speed with low feed rate combination minimizes the thrust force in drilling of pre-laminated particleboard panels. Valarmathi et al. (2013c) conducted drilling experiments on plain and laminated MDF panels using drills of 10 mm diameter with different point angles and developed a model to evaluate the effect of drilling parameters on thrust force. They found that high spindle speed and low feed rate are the preferable cutting conditions to reduce the thrust force in drilling of MDF panels. Gaitonde et al. (2008a,b) studied the influence of machining conditions on thrust force and concluded that the feed rate followed by spindle speed were the most significant factors in minimising the thrust force value in drilling MDF panels.

There are several studies of the effect of drill geometry on the processing parameters and delamination of particleboard in drilling operations. Ispas and Răcăşan (2017) analysed the influence of the drill tip angle and feed speed on the processing quality evaluated by the size of delamination at the entrance side and exit side of the hole. The influence of the feed rate and tool geometry was assessed in terms of a non-dimensional quality parameter. It was found that the delamination increased with the increase of the tooth bite (feed rate) for all drill geometry analysed. Ispas et al. (2014) analysed the variation of the torque, thrust force and surface delamination with the drill tip angle and feed per tooth at drilling prelaminated particleboard. They found that a low feed rate generally minimizes both the thrust force, the drilling torque, and delamination. However, a small tip angle generally minimizes the delamination and the thrust force. In other work, Ispas and Răcăşan (2015) measured and analysed the influence of both the kinematic and geometric parameters on the dynamic parameters at drilling with helical drills. It was found that a low feed rate generally minimizes both the thrust force and drilling torque.

Cutting forces and surface roughness are two important issues in the machining of wood-based materials that reflect its susceptibility to material processing. Cutting forces have a direct effect on energy consumption, tool wear, heat generation, and the quality of the surface being machined (Marchal et al. 2009; Wyeth et al. 2009; Guo et al. 2014; Szwajka and Trzepieciński 2017). According to Jemielniak (1998), the most important machinability criteria are tool durability, the quality of the surface machined, cutting resistance, and the shape and dimensions of the chips. In the case of drilling with small diameter drills, cutting forces are a very important machinability criterion due to the danger of exceeding the critical value, which leads to drill cracking. This article is devoted to analysis of machinability by means of axial force, cutting moment, and shear chip angle simultaneously when drilling MDF. The aim of this study was to define a machinability index based on the link between axial force, cutting torque, and shear chip angle simultaneously when drilling MDF.

EXPERIMENTAL

Materials

A commercial MDF board with a thickness of 18 mm was used as the workpiece. The mechanical and physical analyses were carried out according to the EN 310 (1994) and EN 323 (1999) standards. The results are presented in Table 1. Using a scanning electron microscope (TESCAN, MIRA3, Brno, Czech Republic) with a TESCAN EDS attachment (Fig. 1a), a microphotograph of a spectral analysis was produced depicting the elements making up the test material (Fig. 1).

Table 1. Selected Mechanical and Physical Properties of MDF

Based on previous reports and industrial applications, an arbor drill with a diameter of ϕ = 9.3 mm was used as the cutting tool. The blades were made of cemented carbide (grade P15) with a cutting edge angle of κ_r = 90° and rake face angle of γ_o = 15° (Fig. 2).

Fig. 1. (a) Scanning electron microscope, (b) a microphotograph, and (c) an EDS spectrum of MDF

Fig. 2. Cutting tool: Shank ISCAR (DCNS 090-027-090B-3D) and blade FPC 093 IC908

Methods

Blind holes were drilled in MDF elements with the dimensions 130 × 30 × 18 mm (Fig. 3a). The values of machining parameters (F_f and M_c) were measured using the KISTLER type 9345B2 piezoelectric industrial sensor (Winterthur, Switzerland). The signals from the sensor were recorded on a personal computer (PC) disk in digital form via an analogue-to-digital National Instruments PCI-6034E converter (Austin, TX, USA).

The sampling rate of F_f and M_c signals during the experiments was 50 kHz per channel. The measurement resolution of the card was 16-bit. Figure 3b shows a diagrammatic representation of the measurement method used in the tests. After each hole was drilled, the thickness of the obtained chip was measured. These measurements were carried out on a Mitutoyo TM microscope (Kawasaki, Japan) equipped with a digital camera.

Fig. 3. (a) Experimental setup and (b) research method

During the tests, a series of holes were made for the sets of cutting parameters adopted. Four cutting speeds (v_c) were used in the tests conducted: 0.24, 0.48, 0.73, and 0.97 m/s. For each cutting speed five feed values f_n were adopted: 0.1, 0.2, 0.3, 0.4, and 0.5 mm/rev. The tests for each set of parameters were repeated three times.

RESULTS AND DISCUSSION

Thrust Force and Cutting Torque

To analyse the recorded F_f and M_c signals, a computer program was prepared in the LabView programming language manufactured by National Instruments (Austin, TX, USA). The program allowed for the determination, in selected time intervals, of the mean values of the registered axial force and cutting torque signals. The proposed method of machine cutting detection is shown in Fig. 4. The detection of machine cutting is based on the axial force signal F_f and the cutting torque M_c. After a time interval of 50 ms, and after receiving the signal ‘start of feed’ from the machine control system, the offset of the signal was removed. For this purpose, a standard deviation (σ₀) and an average value (S_ave) are determined for the signal coming from a signal fragment sensor with a specified time interval of 100 ms. The average value of the S_ave signal was subtracted from the total signal as an offset, so when the drill was operated in the air the signal should oscillate around approximately zero. The standard deviation calculated during the removal of the offset -σ₀, denoted here as σ₀ (F_f) and σ₀ (M_c), is a measure of signal interference, which may be dependent on spindle rotational speed, feed, etc. Therefore, it can be used to determine the threshold value for cutting detection. After removing the offset, the actual detection of machining begins. From a signal period of 5 ms, S_f and σ_c were determined, where S_f is a low-pass 2^nd order Butterworth filtered signal with a cutoff frequency of 1 kHz, and σ_c is the standard deviation of this signal. The S_f measurement is the most effective when there is an absence of signal drift. The start of cutting is recognized if S_f > 5 or σ_c > 3σ_o for any of the signals above 25 ms. In the example shown in Fig. 4a, the threshold transition appeared at 0.128 s. In the case of the feed force standard deviation, cutting was detected at 0.135 s (Fig. 4b). The end of cutting is recognised when the signal measures fall below the assumed threshold which was determined in the recognition at the start of cutting. The multipliers, 5 for the filtered signal S_f and 3 for the signal’s standard deviation σ_c, were determined on the basis of the authors’ own experience.

After determining the beginning of cutting, the signal was segmented, which consists of dividing the signal into equal time intervals during analysis. From such intervals called segments, the average value of the signals was generated. The program operation involved the automatic determination of the recorded signal value in strictly defined time periods. The signal was divided into equal time fragments in order to prepare it for analysis. The average signal value was generated from such time fragments. Before it was possible to carry out these procedures, it was necessary to select those signal fragments that will provide the best representation of the signal value during processing. Fragments of the stable (invariability) signal are the most suitable. This allows one to avoid random changes in the signal. The method of assessing the invariability of the F_L signal is presented in Fig. 5 and is described by Eq. 1,

 (1)

where MS (t_i-1) is a measure of the signal for time t_i-1, and MS (t_i+1) is a measure of the signal for time t_i+1. A lower value for the F_L signal indicated that the segment was more suitable for determining the signal value.

Fig. 4. Methodology for determining the beginning of cutting with regard to M_c (a) and F_f (b) signals

Fig. 5. Methodology for the determining the F_f (a) and M_c (b) signal values

To determine the best signal fragments for the average value evaluation from each recorded signal (during the machining of one hole), the signal segments with the best rating were selected. The methodology is shown in Fig. 5. This procedure was carried out for all recorded signals received for each of the holes drilled. The final selection consists of the selection of such signal fragments (in the same time interval) and for which the invariability of F_L is the smallest.

Figure 6 shows the variation of axial force (F_f) and cutting torque (M_c) in relation to the value of uncut chip thickness and cutting speed. Both the value of the axial force and the cutting torque increased with uncut chip thickness. A significant effect of cutting speed was observed on the axial force value.

Fig. 6. Influence of uncut chip thickness on the value of thrust force and cutting moment for cutting speeds: (a) 0.24, (b) 0.48, (c) 0.73, and (d) 0.97 m/s.

The Process of Chip Formation

An important parameter of the machining process which characterises the amount of deformation in the shear zone is the shear angle ϕ (Fig. 7a) contained between the cutting speed direction and the shear surface. A smaller value indicates a greater shear zone length I_sh (Fig. 7b). The shear angle also affects the thickness of the chip (h_ch). The ratio of this thickness (h_ch) to the thickness of the machined layer (h) is called the cutting ratio (Λ_h), which is a measure of deformation in the shear zone, as shown in Eq. 2,

 (2)

where the h_ch is the thickness of the chip and h is thickness of the machined layer.

Fig. 7. (a) Shear angle and (b) cutting ratio

Table 2 shows the shape of chips obtained during the tests depending on the cutting parameters used. The chip thickness (h_ch) was measured using an optical microscope. Results of chip thickness are shown in Table 3. Figure 8 shows an example view of the chip thickness measuring method.

Table 2. Chip Shapes