A FUZZY LOGIC MODEL TO EVALUATE THRUST FORCE IN THE DRILLING OF MEDIUM DENSITY FIBRE BOARD

Transcription

1 A FUZZY LOGIC MODEL TO EVALUATE THRUST FORCE IN THE DRILLING OF MEDIUM DENSITY FIBRE BOARD S.PRAKASH 1*, J. LILLY MERCY 2, DHRUBAJYOTI BARUAH 3, PUTTI VENKATA SIVA TEJA 4 1 SATHYABAMA UNIVERSITY, CHENNAI, , prakash_s1969@yahoo.com 2 SATHYABAMA UNIVERSITY, CHENNAI, , lillymercy.j@gmail.com 3 SATHYABAMA UNIVERSITY, CHENNAI, , dhruvb88@yahoo.in 4 SATHYABAMA UNIVERSITY, CHENNAI, , pvsteja1990@gmail.com Abstract Medium Density Fibre (MDF) Board is appropriate for many applications in furniture industry due to its better machinability, dimensional stability and surface characteristics. Drilling is the unavoidable machining operation during the assembly of MDF, which plays a major role in the acceptance of the finished product. Thrust force exerted during the drilling operation plays a major role in deciding the damaged area and the extent of defects in the work piece. This work is focussed to study the effect of various drilling parameters like feed rate, spindle speed, drill diameter and board thickness on the thrust force exerted during drilling. Experiments were planned using L 27 orthogonal array and a fuzzy logic rule based model is used to evaluate the effect of these factors on thrust force. The micro structure of drilled holes is studied through Scanning Electron Microscope (SEM) and the results are validated. Keywords: Medium density fibre board (MDF), Scanning Electron microscope (SEM), Thrust Force, FUZZY Logic. 1 Introduction Medium density fibre board, commonly known as MDF is used in furniture industry and is cheaper when it is compared it with normal wood product. Although similar manufacturing processes are used in making all types of fibreboard, MDF has a typical density of kg/m³ or lbs/in 3, in contrast to particle board ( kg/m³) and to high density fibre board ( kg/m³). It is smoother because that the wood fibers used in its manufacture were uniform. MDF is having best properties like surface characteristics dimensional stability and excellent machinability. Machining operations are frequently used in industries to assemble mechanical structures various machining operations includes drilling, milling, turning, etc to obtain the required size and shape. Among these operations drilling is the commonly employed machining operation in Particleboard and MDF. Due to the thrust developed during drilling, many common problems exist. One of the problem causes in drilling is delamination. The thrust force developed in drilling operation is an important concern. Monitoring of thrust force in drilling is needed for the industry So modeling and analysis of the thrust force in drilling of composite materials is needed. Many researchers have analysed the thrust force in drilling operation. Jayabal and Natarajan et al., (2010) studied the coir-glass fibre reinforced composites with HSS drill bit to calculate thrust force under various cutting conditions. MDF has a low coefficient of thermal expansion which can provide a better dimensional stability when required. The machining of MDF is not similar to machining of other boards. Hence the effect of various drilling parameters like feed rate, spindle speed, drill diameter and the board thickness on the thrust force exerted during drilling should be selected carefully. Engin S et al., (2000) proposed that the mechanics of cutting MDF which leads to prediction of cutting forces, torque, power and machining vibrations are important in optimizing the MDF machining process and designing machine tools. C.C.Tsao et al., (2007) presents the study of thrust force and surface roughness in carbon fibre reinforced plastic (CFRP) laminate and experimentally investigated and demonstrated a feasible and an effective method for 271-1

2 A FUZZY LOGIC MODEL TO EVALUATE THRUST FORCE IN THE DRILLING OF MEDIUM DENSITY FIBRE BOARD the evaluation of drilling induced thrust force and surface roughness. Paulo et al., (2008) presents the study of surface roughness aspect in milling MDF. In his study, the surface roughness in milling decreases with an increase of spindle speed and increase with feed rate. Langella et al., (2005) suggested that during a drilling process the pre requisites for orthogonal fiber cutting are met for an infinitesimal instant in composite material drilling. Thus for modelling of thrust force, fuzzy logic technique is utilized in this paper. The term "fuzzy logic" was introduced in the year (1965). It was proposed by Lotfi A. Zadeh. Fuzzy logic has been applied to many fields, from control theory to artificial intelligence. Fuzzy logics however had been studied since the 1920s as infinitevalued logics notably by Lucasiewicz and Tarski. During the past decade, fuzzy logic has been incorporated to model complex systems (Filev et al., 1991; Naka-Mori et al., 1994; Pedrycz et al., 1995). Fuzzylogic is a mathematical system in which exhaustive logical mathematics is used to deal with fuzzy information and data that are difficult to compute using conventional mathematics. A large amount of investigations have been targeted to the augury and calculation of thrust forces. The thrustforce generated during drilling have a direct influence on the cutting of material. Wear on the tool, accuracy of the work piece and quality of the hole obtained in drilling mainly depends on thrust force. Balazinski et al. (2001) commenced the fuzzy decision support system for the estimation of the depth of cut and flank wear during the turning process. Yue Jiao et al. (2004) used Fuzzy adaptive networks in machining process modelling. Singh.I et al., (2009) performed finite element analysis on drilling operation on composites reinforced using glass fiber and he also concluded that thrust is predominantly affected by point angle and feed rate. Singh R V S et al., (2009) performed operations using drilling process parameters by developing a fuzzy rule based model for predicting thrust force and torque on GFRP composites with different diameters as per Taguchi s L 27 orthogonal array and found that the delamination tendency can be reduced by increasing the spindle speed and keeping the feed rate and drill diameter as low. B.Latha et al., (2009) have also used fuzzy logic technique to predict thrust force in drilling of composite materials. For modelling thrust force in drilling of MDF fuzzy logic approach is used in this work. Fuzzy logic controller is the application of fuzzy set theory which was introduced by Zadeh in Huan et al., (2014) conducted an experiment on, micro-hole drilling and cutting of different materials using an fs fiber laser were investigated. The quality of drilled holes for different materials was characterized using optical microscope and SEM. This work focusses on modelling the thrust force in terms of drilling parameters using fuzzy logic rule based model which helps in simulating the effect of input parameters on the output response. 4 parameters namely spindle speed, feed, drill diameter and board thickness are simultaneously varied and studied to understand the interaction between them. 2 Experimental Procedure 2.1 Method and Materials The material used in this work is Medium Density Fibre board (MDF) which is manufactured by ASIS India. These boards are normally used in furniture industry. The drilling operations were carried in ARIX VMC 100 CNC drilling machining centre as shown in Figure 1. Drilling experiments were carried out using Brad and Spur drill bits having diameters 6mm, 9mm and 12mm The machining operations were carried out according to L 27 orthogonal array experimental design. The computer controlled data acquisition system was used to collect the data during experiments and the kistler dynamometer was used to record the thrust force. Figure 1 Drilling setup with Thrust force measurement 2.2 Plan of Experiments The Experiments are designed and are analysed using taguchi s L 27 orthogonal array and the factors which are considered into account in this experiment were feed rate, spindle speed, drill diameter and board thickness with their levels are shown in Table 1. The combinations of all input factors with different levels during all trials were conducted and mean thrust force is measured. The experimental results with combinations of input factors and levels are shown in Table 2. The ARIX CNC machining centre used for drilling has the speed range of rpm. Hence the maximum level was set using equipment consideration. The speed and feed range have to be correlated. For eg., if the spindle speed is very less and feed rate is very high, it results in the breakage of drill bit. Hence the feed rate was fixed to suit the speed given. Drill diameter is chosen based on the sizes of holes drilled in the board during assembly process. MDF board was purchased from ASIS India Ltd, having standard sizes of 6,12,18mm

3 Table 1: Input Factors and levels Drilling parameters Levels Spindle Speed [rpm] Feed[mm/min] Drill diameter[mm] Board Thickness [mm] Table 2 Experimental results of Thrust Force S. No. Feed rate (f), mm/min. Spindle speed (N), Rpm Drill diameter (d), mm Board thickness (t) mm Thrust force (F z ), N(exp) Fuzzy Rule Based Modelling Fuzzy logic is a methodology from Artificial Intelligence and is an effective tool to deal with complex nonlinear systems. Fuzzy logic modelling is based on mathematical theory combining multi-valued logic, Probability theory, and Artificial Intelligence methods and can be used to tackle complex problems. In this work, the concept of fuzzy logic rule is applied using Matlab software to evaluate the thrust force while drilling MDF. The structure of a fuzzy logic system consists of three conceptual components: a fuzzy rule base, a data base, and a reasoning mechanism. The fuzzy reasoning for four-input-one-output fuzzy logic unit is described as follows: The fuzzy rule base Consists of a group of IF- ELSE statements with four Inputs, x 1, x 2, x 3, x 4 and an output y, i.e. Rule 1: if x 1 is A 1 and x 2 is B 1 and x 3 is C 1 and x 4 is D 1 then y is E 1 else Rule 2: if x 1 is A 2 and x 2 is B 2 and x 3 is C 2 and x 4 is D 2 then y is E 2 else... Rule n: if x 1 is A n and x 2 is B n and x 3 is C n and x 4 is D n then y is E n. A i, B i, C i, D i and E i are fuzzy subsets defined by the Corresponding membership functions; that is, µ Ai, µ Bi, µ Ci, µ Di and µ Ei. (Oguzhan Yilmaz et al., 2006 ; jang et al., 2005) Let x 1 = Feed rate, x 2 = Spindle speed, x 3 = Drill diameter and x 4 = Board thickness and y= Thrust force are the four input and output values of the fuzzy logic unit as shown in Figure 2, Figure 2 Defining input and output in fuzzy inference system The membership functions can be of different forms like triangular, trapezoidal, Gaussian, sigmoid, etc. In this study, triangular membership function was considered as the error which is occurring is low in triangular membership function. Fig 2 shows the inputs given in fuzzy logic tool box and the output response. All the 27 experimental results are given as fuzzy rules in the form of If-Else statement. Fig 3 shows the pictorial representation of the 27 rules got in the rule viewer of fuzzy logic tool box. Based on these 27 rules, using

4 A FUZZY LOGIC MODEL TO EVALUATE THRUST FORCE IN THE DRILLING OF MEDIUM DENSITY FIBRE BOARD fuzzy logic, modelling is automatically done in the software. 4 Results and Discussions The thrust force developed during drilling of medium density fiber board has been investigated according to the L 27 orthogonal array experiments. Fuzzy rule based model has been developed for predicting thrust force in drilling of MDF. 4.1 SEM Analysis: Figure 5 SEM micrograph at f=500mm/min, N=1000rpm, d= 12mm, t=12mm. The micro structure of drilled holes is studied through Scanning Electron Microscope (SEM). Figure 5 shows the image at low speed and high feed rate. The pulled out cut fibres are clearly visible and shows the irregularity in cutting due to high feed rate. Debonding between adjacent layers happens due to the force shearing the fibres which results in the adhesive layer getting weakened. These cracks formed around the drilled holes, may further propagate decreasing the strength of the base material. Figure 3 Fuzzy rule viewer Figure 4 shows the membership functions for the output response thrust force. The range of thrust force is divided into equal regions and membership functions are specified in those limits. 5 Conclusions From the above discussions on thrust force the following conclusions were drawn. Feed rate and drill diameter were found to be most influencing factors for thrust force. Also fuzzy modeling helps to accurately predict the responses for any values of cutting speed, feed rate, drill diameter and board thickness combinations within the experimental range Figure 4 Experimental output as rules in fuzzy Inference System References Balazinski, Marek., Baron, Luc., Achiche, Sofiane.,(2001), Fuzzy decision support system knowledge base generation using a genetic algorithm, International Journal Of Approximate Reasoning, Vol. 28, pp B. Latha V. S. Senthilkumar, (2009), Vol.24, , Analysis of Thrust Force in Drilling Glass 271-4

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