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The role of non-conventional machining processes (NCMPs) in today's manufacturing environment has been well acknowledged. For effective utilization of the capabilities and advantages of different NCMPs, selection of the most appropriate NCMP for a given machining application requires consideration of different conflicting criteria. The right choice of the NCMP is critical to the success and competitiveness of the company. As the NCMP selection problem involves consideration of different conflicting criteria, of different relative importance, the multi-criteria decision making (MCDM) methods are very useful in systematical selection of the most appropriate NCMP. This paper presents the application of a recent MCDM method, i.e., the multi-objective optimization on the basis of ratio analysis (MOORA) method to solve NCMP selection which has been defined considering different performance criteria of four most widely used NCMPs. In order to determine the relative significance of considered quality criteria a pair-wise comparison matrix of the analytic hierarchy process was used. The results obtained using the MOORA method showed perfect correlation with those obtained by the technique for order preference by similarity to ideal solution (TOPSIS) method which proves the applicability and potentiality of this MCDM method for solving complex NCMP selection problems.

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Journal of Engineering Science and Technology

Vol. 10, No.11 (2015) 1441 - 1452

1441

NON-CONVENTIONAL MACHINING PROCESSES

SELECTION USING MULTI-OBJECTIVE OPTIMIZATION

ON THE BASIS OF RATIO ANALYSIS METHOD

MILOŠ MADIĆ*, MIROSLAV RADOVANOVIĆ, DUŠAN PETKOVIĆ

Faculty of Mechanical Engineering in Niš, University of Niš,

A. Medvedeva 14, 18000, Niš, Serbia

*Corresponding Author: madic@masfak.ni.ac.rs

Abstract

The role of non-conventional machining processes (NCMPs) in today's

manufacturing environment has been well acknowledged. For effective

utilization of the capabilities and advantages of different NCMPs, selection of

the most appropriate NCMP for a given machining application requires

consideration of different conflicting criteria. The right choice of the NCMP is

critical to the success and competitiveness of the company. As the NCMP

selection problem involves consideration of different conflicting criteria, of

different relative importance, the multi-criteria decision making (MCDM)

methods are very useful in systematical selection of the most appropriate

NCMP. This paper presents the application of a recent MCDM method, i.e., the

multi-objective optimization on the basis of ratio analysis (MOORA) method to

solve NCMP selection which has been defined considering different

performance criteria of four most widely used NCMPs. In order to determine

the relative significance of considered quality criteria a pair-wise comparison

matrix of the analytic hierarchy process was used. The results obtained using

the MOORA method showed perfect correlation with those obtained by the

technique for order preference by similarity to ideal solution (TOPSIS) method

which proves the applicability and potentiality of this MCDM method for

solving complex NCMP selection problems.

Keywords: Non-conventional machining processes, Multi-criteria decision making,

Selection, MOORA method.

1. Introduction

In today's industry, a number of non-conventional machining processes (NCMPs)

are increasingly being used for processing of different engineering materials

1442 M. Madić et al.

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

Nomenclatures

Comparative importance of criterion i with respect to criterion j

g Number of criteria to be maximized

m Number of alternatives

Average surface roughness, µm

r Number of criteria to be minimized

Weight of the j-th criterion

th alternative with respect to

criterion

Normalized performance measure of i-th alternative with respect

to j-th criterion.

Alternative assessment values

Abbreviations

brasive water jet machining

CHM Chemical machining

EBM Electron beam machining

GM Geometric mean

LBM Laser beam machining

objective optimization on the basis of ratio analysis

NCMPs Non-conventional machining processes

PAM Plasma-arc machining

echnique for order preference by similarity to ideal solution

WEDM Wire electrical discharge machining

WJM Water jet machining

especially advanced materials having improved technological and mechanical

properties. Laser beam machining (LBM), abrasive water jet machining (AWJM),

electrical discharge machining (EDM) and plasma arc machining (PAM) are

particularly used in industry for materials processing. Each of these NCMP is

very complex machining process having its own unique characteristics,

prerequisites and advantages.

For many firms, having some core competency is necessary for making

strategic decisions like technology selection decision. Since some of the

consequences of technology selection occur at long-run, firms' survival at long

term depends heavily on their ability to exploit some core competencies [1].

Making right decision is a basis for achieving high competitiveness on the global

market through increase in productivity, product quality and flexibility. As the

price of machine tools for NCMPs is very high, inadequate selection of the most

appropriate NCMP has long-term consequences on the business of the entire

company. However, selection of the most appropriate NCMP is a challenging task

for decision makers [2] and moreover often a time consuming task [3].

Non-conventional Machining Processes Selection Using Multi-objective 1443

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

From the literature (Table 1) it has been observed that different multi-criteria

decision making (MCDM) methods have been applied for solving NCMP

selection problems. MCDM is concerned with those situations where a decision

maker has to rank a set of competitive alternatives and select the best alternative

while considering a set of conflicting criteria [4]. In order to evaluate the overall

performance of the competitive alternatives, the primary objective of an MCDM

method is to identify the relevant selection problem criteria, assess the

alternative's information relating to those criteria and develop methodologies for

determining the relative significance of each criterion.

For solving NCMP selection problems, analytic hierarchy process (AHP) and

technique for order preference by similarity to ideal solution (TOPSIS) methods

were applied [5, 6]. Digraph-based approach was discussed in [2]. Application of

analytic network process (ANP) method was proposed in [7]. Later on, the use of

data envelopment analysis (DEA) method was proposed [8]. Application of

preference ranking organization method for enrichment evaluation

(PROMETHEE) and geometrical analysis for interactive aid (GAIA) method was

discussed in [9]. Recently, the use of fuzzy TOPSIS method and evaluation of

mixed data (EVAMIX) methods was proposed [10, 3]. The potential for solving

NCMP selection problems also has value engineering approach [11].

Table 1. Application of MCDM methods for

solving NCMP selection problems: A review.

Reference MCDM

method Year Considered NCMP

[5] combined

AHP and

TOPSIS

2003 AJM, USM, ECM, CHM, EDM,

EBM, LBM

AHP and

TOPSIS

EDM, WEDM, EBM, LBM

engineering or

value analysis

Different case studies in

manufacturing environment

[2] digraph-based

approach

2009 AJM, USM, CHM, EBM, LBM,

ECM, EDM, PAM

EBM, LBM, PAM, WEDM, WJM

[8] DEA 2011 USM, WJM, AJM, ECM, CHM,

EDM, WEDM, EBM, LBM, PAM

and GAIA

Different case studies from

literature [5, 6, 2]

[10] fuzzy TOPSIS 2013 AJM, WJM, LBM, PAM, Oxy-fuel

machining

Different case studies from

literature [5, 6]

AJM – abrasive-jet machining, USM – ultrasonic machining, ECM – electrochemical

machining, CHM – chemical machining, EDM – electro-discharge machining, EBM –

electron beam machining, LBM – laser beam machining, WJM – water jet machining,

WEDM – wire electrical discharge machining, PAM – plasma-arc machining.

1444 M. Madić et al.

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

Among these different MCDM methods, high potential for solving ranking

and selection problems in manufacturing environment showed a recently

developed method i.e. multi-objective optimization on the basis of ratio analysis

(MOORA) method. Chakraborty [12] explored the application of the MOORA

method to solve different MCDM problems in manufacturing environment

including NCMP selection problem. Karande and Chakraborty [13] applied the

MOORA method to solve some of the common material selection problems. Dey

et al. [14] discussed the application of the MOORA based fuzzy MCDM approach

for supply chain strategy selection. Regarding the application of the MOORA

method [12, 13, 14] it has been observed that the performance of this method is

comparable with other popular and widely used MCDM methods. Moreover,

computationally the method is very simple and can be easily implemented.

In this paper, firstly a MCDM model which can be used to select the most

suitable NCMP considering different performance criteria has been defined. A

pair-wise comparison matrix of the AHP method was then used to determine the

relative significance of considered quality criteria, and finally the competitive

NCMPs were ranked by using the MOORA method. In order to validate the

obtained complete rankings of NCMPs of the MOORA method, the NCMP

selection problem was solved also by using the TOPSIS method.

2. NCMPs Selection Problem

Ability to machine advanced materials and fulfill the requirements of high

dimensional accuracy and surface finish, made NCMPs one of the most used

machining processes in today's industry. Quality performances are very important

aspect for NCMPs because it helps to achieve proper tolerance and the required

quality of cut, thus eliminating the need for post-processing. These are

dependable not only on the machining process itself, but also on the machine tool

and its control capabilities, thickness and type of material being cut and also the

machining process parameter settings.

Process performances are also important aspect while selecting the most

suitable NCMP. It can be considered by taking into account either individually or

collectively several indicators such as the specific cutting energy, cutting speed,

specific cutting power and the like. Among these, cutting speed is one of the most

important factors, and at the same time represents one of the major techno-

economic performances of NCMPs.

2.1. Formulation of the NCPM Selection Model

The present MCDM problem is based on the evaluation of four NCMPs i.e.

LBM, PAM, EDM and AWJM considering 9 criteria. The NCMPs selection

problem was defined considering:

1. Workpiece material (WM): This criterion is concerned with the ability of a

given NCMP to machine a given workpiece material. It is preferable that a given

NCMP has the ability to machine a wider range of materials.

2. Temperature of the cut (TC): This criterion incorporates the fact that during

different NCMPs there exist temperature effects which may have important

impacts on metallurgical properties of the workpiece material.

Non-conventional Machining Processes Selection Using Multi-objective 1445

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

3. Economical workpiece thickness (EWT): Although the considered NCMP

can machine a wide spectrum of material thicknesses, for each NCMP there is an

interval range of material thickness for which the given NCMP is particularly

suitable. In other words, the use of a given NCMP within this range is

economical.

4. Machining accuracy (MA): The machining accuracy is determined by the

characteristics of the coordinate worktable (positioning accuracy) and the quality

of the control unit of machine tool.

5. Kerf taper (KT): Kerf taper is a special and undesirable geometrical feature

inherent to all NCMPs. Kerf taper is normally expressed by kerf taper angle.

Reduced kerf taper angle is very important since it allows better positioning of

parts, elimination of post-processing and finally saving of material.

6. Kerf width (KW): Kerf width and kerf taper are one of the most important

quality performance criteria that directly affect final dimensions of the workpiece.

It can be defined as the width of material that is removed by a given NCMP. Each

NCMP removes a different amount of material i.e. creates different kerf width.

The more precise process, the smaller the kerf width is. Generally, it is mainly

influenced by the cutting speed.

7. Quality of surface roughness (QSR): Assessment of the surface roughness

includes the shape and size of irregularities and in practice comes down to

analysis of particular sections on the cut surface. Surface roughness parameters

defined by international standards are related to the characteristics of the

irregularities profiles. Most frequently used parameters for surface roughness are

maximum height of the assessed profile (R

) and the arithmetic mean deviation of

the profile (R

8. Cutting speed (CS): Higher cutting speeds are always preferable as high

cutting speeds save time during machining i.e. enhance productivity.

9. Burr occurrence (BO): From the techno-economical point of view, burr

occurrence can be regarded as one of the most important criterion for assessing

the performance of different NCMPs. Burr free cutting is desired in order to

reduce or even eliminate the post-processing of the finished parts. Also, burr

formation is undesirable as it causes the release of energy back to the metal

leading to increased heat affected zone.

The initial decision matrix for the NCMP selection problem is given in Table 2.

The decision matrix was developed based by summarizing the available data from

literature [15-18]. It can be observed that except WM and TC, all performance

measures of alternatives with respect to criteria are expressed quantitatively.

2.2. Determination of Criteria Weights

Relative importance of considered criteria is derived using the pair-wise

comparison matrix of the AHP method. The Saaty nine-point preference scale

[20] is adopted for constructing the pair-wise comparison matrix based on the

experience of the authors. A criteria compared with itself is always assigned value

1, so the main diagonal of the pair-wise comparison matrix contains values 1

(Table 3).

1446 M. Madić et al.

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

Table 2. Initial Decision Matrix of NCMPs Selection Problem.

WM TC EWT

(mm)

(º)

(mm)

QSR

(µm)

CS BO

AWJM

All materials Cold

cut

50 0.05 2 0.8 3.2 Slow None

metals

excluding

materials

cut

electrically

conductive

materials

warm

cut

conductive

materials

cut

slow

Table 3. The Pair-wise Comparison Matrix of Considered Criteria.

EWT

MA KT KW

QSR

CS BO

WM 1 5 3 3 3 3 3 1 1

TC 0.2 1 0.2 0.33

0.2 0.33

0.33 0.2 0.2

EWT

0.33 5 1 3 1 5 3 0.5 0.5

MA 0.33 3 0.33 1 0.33

3 0.33 0.33

0.33

KT 0.33 5 1 3 1 5 3 0.5 0.5

KW 0.33 3 0.2 0.33

0.2 1 0.33 0.2 0.2

QSR 0.33 3 0.33 3 0.33

3 1 0.5 0.5

CS 1 5 2 3 2 5 2 1 0.33

BO 1 5 2 3 2 5 2 3 1

Relative criteria weights (w

) were determined by calculating the geometric

mean (GM

) of the i-th row, and normalizing the geometric means of rows in the

comparison matrix by using the following equations:

∏

(1)

∑

(2)

where b

denotes the comparative importance of criterion i with respect to

criterion j (Table 3).

The criteria weights were obtained as:

0.2054 0.1607 0.0763 0.0341 1236.0 0544.0 1236.0 0252.0 1966.0

Non-conventional Machining Processes Selection Using Multi-objective 1447

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

It is observed that the ability of a given NCMP to cut thicker plates of

different materials as well as the ability to produce perpendicular high quality cuts

without burr occurrence at high cutting speed is assigned the greatest importance.

To ensure the accuracy of obtained criteria weights, a consistency check was

performed. For nine considered criteria i.e. for random index of 1.45, consistency

index and consistency ratio values of 0.086 and 0.059 were obtained, respectively.

These values show that the estimation of criteria weights is reasonable.

3. MOORA Method

The MOORA (Multi-Objective Optimization on the basis of Ratio Analysis)

method is one of the newly methods for multi-objective optimization with discrete

alternatives proposed by Brauers [19]. The application procedure of the MOORA

method is simple and consists of the following steps:

Step 1: The MOORA method starts with setting the goals and identification of

the relevant criteria for evaluating available alternatives.

Step 2 : In this step, based on the available information about the alternatives,

decision-making matrix or decision table is set. Each row refers to one alternative,

and each column to one criterion. The initial decision matrix, X, is:

11 12 1

21 22 2

1 2

...

x x x

X x

 

= =

 

(3)

where x

is the performance measure of i-th alternative with respect to j-th

criterion, m is the number of alternatives and n is the number of criteria.

For ranking or selecting one or more alternatives from a set of available ones,

the MOORA method considers both beneficial and non-beneficial criteria and in

this step categorization of considered criteria is made. Also, in this step, weights

are assigned to criteria, w

(j =1,2,...,n ). These weights can be determined using the

entropy method or AHP method.

Step 3: Here a ratio system is developed in which each performance measure

of an alternative on a criterion is compared to a denominator which is a

representative for all the alternatives concerning that criterion. For this

denominator the square root of the sum of squares of each alternative per criterion

is chosen [19]. This ratio can be expressed as:

( )

* 2

ij ij ij

= =

∑

(4)

where

is a dimensionless number from the interval [0,1] and represents the

normalized performance measure of i-th alternative with respect to j-th criterion.

Step 4: In this step

values are added in case of beneficial criteria and

subtracted in case of non-beneficial criteria. Then the optimization problem becomes:

1448 M. Madić et al.

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

1 1

j j g

= = +

∑ ∑

(5)

where g is the number of criteria to be maximized (beneficial criteria), n is the

number of criteria to be minimized (non-beneficial criteria) and y

is the

assessment value (composite score) of the i-th alternative with respect to all

considered criteria.

Step 5: Assessment values, y

, may be positive or negative depending upon the

total number of beneficial and non-beneficial criteria in the decision matrix. The

ranking of the alternatives is determined on the basis of the descending order of

the assessment values. Thus, the best alternative has the highest y

value and the

worst alternative has the lowest y

value.

The following flow chart (Fig. 1) illustrates the application steps of the

MOORA method for solving decision making problems.

Fig. 1. Application procedure of the MOORA method.

4. Results and Discussion

In this section applicability of the MOORA method for selection of the most

appropriate NCMP considering different criteria was discussed.

The detailed computational procedure of the MOORA method for solving the

NCMP selection problem considering different criteria is as follows. Among the

considered criteria, WM, EWT and TS are beneficial criteria where higher values

are desirable. On the other hand, TC, MA, KT, KW, QSR and BO are non-

beneficial criteria where smaller values are preferable. Firstly, the qualitative

information of four criteria, i.e., WM, TC, TS and BO are converted into

appropriate quantitative data (crisp values) using the 10-point scale [21]. Hence

the decision matrix has the following form (Table 4).

Table 4. Decision Matrix of the NCMP Selection Problem.

WM TC EWT

(mm)

(degree)

(mm)

QSR

(µm) CS

AWJM

9 0.115 50 0.05 2 0.8 3.2 3 0

LBM 7 0.495 10 0.015 0.5 0.5 1.6 7 3

PAM 5 0.895 10 0.25 8 1.8 12.5 5 5

EDM 3 0.495 100 0.001 0 0.2 0.8 1 0

Table 5 shows the normalized performance measures of alternatives with

respect to the considered criteria, as obtained by using Eq. 4. Subsequently by

using Eq. 5, the assessment values (composite scores) of all alternatives with

Non-conventional Machining Processes Selection Using Multi-objective 1449

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

respect to the considered criteria are estimated. Table 6 exhibits these results of

the MOORA method upon which complete ranking of the NCMPs was obtained.

Table 5. Normalized Decision Matrix of the NCMP Selection Problem.

WM TC EWT

(mm)

(degree)

(mm)

QSR

(µm)

CS BO

AWJM

0.7028

0.1007

0.4437

0.1958

0.2421 0.3918

0.2457

0.3273

LBM 0.5466

0.4334

0.0887

0.0587

0.0605 0.2449

0.1228

0.7638

0.5145

PAM 0.3904

0.7837

0.0887

0.9789

0.9684 0.8815

0.9596

0.5455

0.8575

EDM 0.2343

0.4334

0.8874

0.0039

0 0.0979

0.0614

0.1091

Table 6. Assessment Values and Ranking of Considered NCMPs.

Rank

AWJM 0.1704 1

LBM 0.0962 3

PAM -0.2967 4

EDM 0.1541 2

It is observed that AWJM is the most suitable NCMP considering material

application and different performance criteria. From Table 6, it is revealed that

EDM is the second best choice, and that LBM is third choice. PAM is obtained as

the least preferred NCMP. Negative assessment value of PAM is due to fact that

the considered MCDM problem has six non-beneficial criteria against three

beneficial criteria.

For the purpose of validation, the same NCMPs selection problem is solved by

using the TOPSIS method as one of the most commonly used MCDM methods.

The computational details and step-by-step procedure of the TOPSIS method is

explained in details in [22]. The positive ideal solution (S

), negative ideal

solution (S

) and relative closeness to the ideal solution (P

) for each alternative

are given in Table 7.

Table 7. Assessment Values and Ranking of Considered NCMPs.

AWJM 0.0961 0.2368 0.7114

LBM 0.1484 0.1988 0.5726

PAM 0.2619 0.0766 0.2263

EDM 0.1401 0.2517 0.6424

As a result of the application of the TOPSIS method (Table 7) the complete

ranking in descending order was obtained as AWJM-EDM-LBM-PAM. This

result suggests that there is a perfect correlation between rankings obtained by

MOORA and TOPSIS methods.

1450 M. Madić et al.

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

The MOORA method can simultaneously take into account any number of

criteria and offer a very simple computational procedure. As this method is based

on simple ratio system, it involves the least amount of mathematical

computations. This has the double benefit for decision makers. On the one hand,

the implementation of the MOORA method does not necessarily requires strong

background in mathematics and operational research. On the other hand, unlike

many other MCDM methods, which require software packages in order to

efficiently solve a given MCDM problem, all mathematical calculations of the

MOORA can be easily worked in MS Excel.

Regarding required application steps for solving decision making problems,

the MOORA method has advantage over other MCDM methods. While only five

steps are needed to solve a particular decision making method using the MOORA

method, TOPSIS method requires nine steps [22]. Also, unlike many other

MCDM methods, the normalization of decision matrix is done by vector

normalization procedure using only one normalization equation regardless of the

nature of criterion (beneficial or non-beneficial). In such way there is no need to

use additional normalization equations or to transform non-beneficial to beneficial

criteria and vice versa. As noted by Chakraborty [12], another major advantage of

this method is that its calculation procedure is not affected by the introduction of

any additional parameters as it happens in case of other MCDM methods.

The particular benefit of the MOORA method is reflected in the fact that it can

be used in situations where decision maker is faced with the problem of determining

criteria weights. In such cases for the purpose of optimization, Eq. 5 becomes:

1 1

j j g

= = +

= −

(6)

5. Conclusions

In this paper, a MCDM model for the selection of the most appropriate NCMP

considering different criteria, particularly related to quality performance, has been

defined and solved by using the MOORA method. The obtained results suggested

that AWJM is the best alternative, while EDM is the second one. LBM and PAM

were the third and fourth alternatives in the rank. In order to validate the obtained

rankings of NCMPs obtained by the application of the MOORA method, the

considered NCMPs selection problem was solved by using the TOPSIS method. It

was observed that ranking of competitive NCMPs exactly match. The main

advantage of the MOORA method is that it can take into account any number of

criteria, both quantitative and qualitative, and offer a very simple computational

procedure. Moreover, the implementation of MOORA method does not

necessarily requires strong background in mathematics and operational research

as well the use of specialized software packages since it can be easily

implemented in MS Excel.

The advantages and benefits of the MOORA method over other available

MCDM methods are reflected in the following facts: (i) the application of the

MOORA method for solving a particular decision making problems requires

fewer application steps, (ii) single equation is required for the purpose of decision

Non-conventional Machining Processes Selection Using Multi-objective 1451

Journal of Engineering Science and Technology November 2015, Vol. 10(11)

matrix normalization irrespective of the nature of criterion, (iii) it can be applied

in situations where criteria weights are not explicitly given.

Further researches will focus on the consideration of additional criteria that

influence the NCMP selection problem and comparative analysis of the MOORA

method for solving other selection problems in manufacturing environment.

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engineering design. Springer-Verlag.

22. Venkata Rao, R. (2007). Decision making in the manufacturing environment:

using graph theory and fuzzy multiple attribute decision making methods.

Springer-Verlag.

... The mathematical underpinning of both the linear model and the MOORA approach is not complicated, making it simple to comprehend. The steps of the computational approach do not necessitate the use of any software [27]; instead, they can be carried out using the Microsoft Excel application. The time required to make the final decision is not excessive. ...

Covid-19 pandemic required all the world to use internet more actively. As a result, individuals and businesses are more open to digital threats. In order to provide security within the network, firewalls should be used. Firewalls act as a gateway between the corporate and the external networks. Therefore, it is more important than ever to choose the right firewall for each network. In this study, a new linear decision making model is proposed in order to find out the most suitable firewall and the estimates are completed according to this new model. Also, this model is compared with multi-objective optimization on the basis of ratio analysis (MOORA) method. This study distinguishes from other studies by proposing a new solution which ranks the firewall alternatives using linear and MOORA approaches. These approaches are used in many fields before but not in information technologies. Thus, this study can be considered quite innovative in terms of the problem it handles and the approaches used. It offers up-to-date and practical suggestions related to a decision making problem that has not been previously studied in the literature.

... MOORA accommodates multiple criteria in simple computational procedures. Thus, a particular single equation is required for decision matrix normalization irrespective of the nature criteria (Madić et al., 2015). This technique has been successfully showing the perfect correlation for order preference to the ideal solution. ...

The lack of optimality in the Field Experience Program (FEP) placement has affected universities' educational services to the stakeholders. Bringing together the stakeholders' needs, university capacities, and participants' willingness to quality and quantity is not easy. This study tries to optimize the placement of FEP by considering the interests of multiple perspectives through the application of Multi-Objective Optimization on the Basic of Ratio Analysis (MOORA) and Rule-Based methods in the form of a decision-making model. MOORA ranked the students based on the FEP committee's perspective and other criteria, such as micro-teaching grades, final GPAs, study programs, number of credits, and student addresses. Meanwhile, the school perspective was ordered based on its accreditations, levels, types, facilities, and performances. To achieve the optimal recommendation of FEP placement, the integration of MOORA and Rule-based intertwined the requirement of such perspectives. A prototype of the system recommendation is then acquired to simplify the decision-making model. As adjudications, a survey from twenty stakeholders evidenced around 86.92% of system user acceptances. The confusion matrix testing defines the accuracy of this method reaches 78.33%. This paper reveals that the recommendation model has been successfully increasing the effectiveness of decision making in FEP placement under the needs and expectations of the entire stakeholders.

... Sarkar et al. (2015) proposed a multi-objective optimization on the basis of ratio analysis (MOORA) method-based decision support system for selection of NTM processes having a given set of quantitative and qualitative selection attributes. Madić et al. (2015b) combined AHP, MOORA and TOPSIS methods for determination of the relative significance of various quality criteria, and hence, selection of the most suitable NTM process for a given application. Based on a hybrid multi-criteria decision making (MCDM) framework, Azaryoon et al. (2015) developed a knowledge-based system for identification of NTM processes. ...

In order to fulfil the ever increasing requirements of various hard and difficult-to-machine materials in automobile, turbine, nuclear, aviation, tool and die making industries, the conventional material removal processes are now being continuously substituted by an array of non-traditional machining (NTM) processes. The efficient and improved capabilities of these NTM processes have made them indispensible for the present day manufacturing industries. While deploying a particular NTM process for a specific machining application, the concerned process engineer must be aware of its capability which is influenced by a large number of controllable parameters. In this paper, an intelligent decision model is designed and developed in VBASIC to guide the concerned process engineer to have an idea about the values of various NTM process responses for a given parametric combination. It would also advise about the tentative settings of different NTM process parameters for achieving a set of target response values. The operational procedure of this developed system is demonstrated with the help of three real time examples.

... In AWJC process, KT is considered to be one of the significant parameters on influencing the geometrical accuracy of end use components. The selection of appropriate process variables is necessary to minimize KT for superior assembly of machined parts and elimination of post-processing operations [46]. It is perceived from ANOVA Table 5, TS is the most significant parameter which influences the KT followed by JP and addition of nano clay whereas SOD is found to be insignificant. ...

The present investigation focused on abrasive waterjet cutting (AWJC) of natural fibre reinforced nano clay filled polyester composites with the objectives of maximizing material removal rate ( MRR) and minimizing the kerf taper ( KT) and surface roughness ( R a ). The influence of nano clay addition, traverse speed (TS), jet pressure (JP) and stand-off distance (SOD) on the AWJC characteristics of fabricated composite laminates are investigated. The natural fibre reinforced composite (NFRC) laminates are fabricated through hand lay-up technique through varying the wt% of nano clay fillers (0, 1 and 2). The AWJC experiments are planned and rigorous experiments were performed by adopting box-behnken design approach. The relative consequence of process variables on response features and quadratic regression models were assessed through analysis of variance (ANOVA). Further, multiple response optimization is carried out using statistical desirability technique to enhance the cut quality characteristics. The optimal AWJC parameters such as JP of 316.24 MPa, SOD of 2 mm and TS of 304.24 mm/min with 1.15 wt% of nano clay addition are determined. Microstructure of cut surface is examined to ascertain the morphological behaviour of AWJC surfaces with different processing conditions.

... • Based on the available criteria information, correspondingly to the alternatives' performances concerning each of the mentioned criteria, a decision matrix is set; • MOORA model creation is the process where the performance value of each alternative, with respect to each criterion, is divided by a certain representative measure of the performance value of all alternatives, also with respect to each criterion. It can be seen from the example of the following formula (Madić et al. 2015): ...

José G Vargas-Hernández
Lic. Kurt Tonatiuh Tonatiuh Winkler Benítez

The objective of this brief general market analysis is to determine with the VRIO framework how the Posadas group has managed to maintain itself in the Mexican lodging market. The aim is to understand how in the current panorama of tourism are the main challenges of the Posadas group. The main question that generated this analysis was: Is Grupo Posadas the current leader in the hospitality sector in Mexico? The hypothesis is that the strategies implemented by Grupo Posadas have allowed it to remain in the lodging sector; however, the current elements are not strong enough to be the market leader. So, combining the analysis elements of the market and the VRIO, results were obtained that pointed to Posadas shares, the leadership with IHG Hotels which begins to generate a more marked oligopolistic competition in the field of tourism

... The integrated AHP and TOPSIS offer a number of advantages amid the assorted MCDM approaches owing to reliable and precise in view of complex MCDM problems and pair-wise correlation with hierarchic arrangement as well flexibility in studies of decision process. 18,[24][25][26] Nontraditional machining has been used on steel and duralumin alloy for surface revolution feature and attributes, reported by Chakladar and Chakraborty. 27 The design of machining attributes and decision making used TOPSIS-AHP-based expert system. ...

A systematic and efficient approach for the selection of material is necessary to choose a best alternative for the structure or component under consideration. The multi-criteria decision making (MCDM) approaches are well suited to deal intricacy in judgment of material assortment. In this paper, integrated MCDM approaches like analytical hierarchy process (AHP)–technique for order preference by the resemblance to an ideal solution (TOPSIS) and AHP–multi-objective optimization on the basis of ratio analysis (MOORA) methods are used to rank aluminum-coconut shell ash (CSA) composites. The weightage for each criterion is calculated by AHP method and utilized in the TOPSIS and MOORA approaches to rank the materials. The target-based attributes such as density (physical property), hardness, tensile strength, toughness (mechanical properties), wear rate, and coefficient of friction (tribological properties) of the prepared composites are considered in the selection of criteria process. The composites are fabricated using stir-casting process by varying the volume fraction (5, 10, 15, and 20%) of CSA incorporated with Al-1100 matrix. A detailed study on the MCDM approaches revealed that Al-15% CSA composite emerged as the best material followed by Al-10% CSA composite among all, whereas the base matrix is found as the poor performed material in this study.

Microelectro-chemical spark machining (micro-ECSM) is a novel hybrid unconventional machining process which has the capability to fabricate sophisticated and intrinsic microcomponents with high-dimensional accuracy. It is based on the principle which combines the microelectrochemical and microelectric discharge machining process. This process has potential to machine both conductive as well as nonconductive material with high precession without any physical contact, which makes it a unique machining process and raises its demand in different fields starting from aviation to medical sector. The present article describes the mechanism of spark formation and material removal process. The tool feed mechanism and the variants of the micro-ECSM process are elaborated. This article also outlines the various material machined by micro-ECSM process and the enhancements of the machining potential by its hybrid variant and provides new prospect in technological advancement of micro-ECSM process.

With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM) processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation) and GAIA (geometrical analysis for interactive aid) method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.

To acquire the competitive advantages in order to survive in the global business scenario, modern companies are now facing the problems of selecting key supply chain strategies. Strategy selection becomes difficult as the number of alternatives and conflicting criteria increases. Multi criteria decision making (MCDM) methodologies help the supply chain managers to take a lead in a complex industrial set-up. The present investigation applies fuzzy MCDM technique entailing multi-objective optimization on the basis of ratio analysis (MOORA) in selection of alternatives in a supply chain. The MOORA method is utilized to three suitable numerical examples for the selection of supply chain strategies (warehouse location selection and vendor/supplier selection). The results obtained by using current approach almost match with those of previous research works published in various open journals. The empirical study has demonstrated the simplicity and applicability of this method as a strategic decision making tool in a supply chain.

Usage of non-traditional machining (NTM) processes has increased recently since demand for materials like high strength and temperature resistant alloys has expanded proportionally to the improvements in technologically advanced industries such as aeronautics, nuclear reactors, automobiles, and etc. Such developments in the field of material science points out them as indispensable processes due to some benefits such as economic cutting speed, production of complex shapes. In this respect; the selection process for the proper NTM process requires the usage of multi criteria decision making (MCDM) methods due to conflicting criterions such as initial cost of technology, quality of surface finished, environmental impact, time of process, and etc. This study provides distinct systematic approaches both in fuzzy and crisp environments to deal with the selection problem of appropriate NTM process and proposes a decision support model helping decision makers to assess potentials of distinct NTM processes. The required data for decision matrixes is obtained via a questionnaire to specialists as well as deep discussions with experts, and making use of past studies. An application of the proposed model is also performed to show the applicability of the model.

Ravipudi Venkata Rao

Manufacturing is the backbone of any industrialized nation. Recent worldwide advances in manufacturing technologies have brought about a metamorphosis in industry. Fast-changing technologies on the product front have created a need for an equally fast response from manufacturing industries. To meet these challenges, manufacturing industries have to select appropriate manufacturing strategies, product designs, manufacturing processes, work piece and tool materials, and machinery and equipment. The selection decisions are complex, as decision making is more challenging today. Decision makers in the manufacturing sector frequently face the problem of assessing a wide range of options and selecting one based on a set of conflicting criteria. Decision Making in the Manufacturing Environment demonstrates how graph theory and matrix approach, and fuzzy multiple attribute decision making methods can be effectively used for decision making in various situations of the manufacturing environment. Divided into two parts; Part I introduces the decision making situations in the manufacturing environment and presents decision making methods; Part II uses case studies to present the applications of these methods in real manufacturing situations. Decision Making in the Manufacturing Environment will be very useful to decision makers in the manufacturing sector as it makes decision making easier, more logical, systematic, efficient and effective. It is intended for designers, manufacturing engineers, practitioners, managers, institutes involved in design and manufacturing related projects, applied research workers, academics, and graduate students in mechanical, industrial, and manufacturing engineering.

ABDOLHAMID S. GHADIKOLAEI
SEYED M. BAGHERI
Elham Keshavarz

One of the distinctive attributes of today's successful companies is having at least one competitive advantage in one known area. Technological competency is an important advantage which helps improve the firm's competitiveness. In fact, suitable use of new technologies can dramatically influence the innovation speed, decrease the time of product development cycle and also increase the rate of new product introduction. Firm-specific technological competencies help explain why a firm is different, how it changes over time, and whether it is capable of remaining competitive. In this study, technological competency factors (technology management, process technology, product technology) are prioritized according to the competitive advantage levels(customer satisfaction, brand reputation, new product introduction, market share) and competitive priorities (cost, price, quality, flexibility, time) using fuzzy Analytic hierarchy process (FAHP) with the aim of maximizing the nonfinancial performance at coil manufacture industry. The results indicate that within Iran coil industry, process technology is of greater importance than technology management and product technology.

D. Podaru

The non-conventional methods which can be used in the spinning of flax are classified. They include: open-end spinning (rotor, vortex, friction); Murata air-jet spinning; twistless spinning; and wrap spinning.

Features Presents guidelines for selecting the proper engineering materials, manufacturing processes, and equipment Covers the basics as well as the most recent advances in manufacturing technology Introduces new trends in surface hardening technology Explores the environmental aspects related to manufacturing and clean factories Explains the principles of near net shape processing, rapid prototyping, and manufacturing design Discusses the surface characteristics as a result of manufacturing operations Includes many solved examples, case studies, and review questions Solutions manual available upon qualifying course adoption Summary Individuals who will be involved in design and manufacturing of finished products need to understand the grand spectrum of manufacturing technology. Comprehensive and fundamental, Manufacturing Technology: Materials, Processes, and Equipment introduces and elaborates on the field of manufacturing technology—its processes, materials, tooling, and equipment. The book emphasizes the fundamentals of processes, their capabilities, typical applications, advantages, and limitations. Thorough and insightful, it provides mathematical modeling and equations as needed to enhance the basic understanding of the material at hand. Designed for upper-level undergraduates in mechanical, industrial, manufacturing, and materials engineering disciplines, this book covers complete manufacturing technology courses taught in engineering colleges and institutions worldwide. The book also addresses the needs of production and manufacturing engineers and technologists participating in related industries.

Thomas L. Saaty

In our everyday life, we must constantly make choices concerning what tasks to do or not to do, when to do them, and whether to do them at all.

Source: https://www.researchgate.net/publication/284921178_Non-conventional_machining_processes_selection_using_multi-objective_optimization_on_the_basis_of_ratio_analysis_method

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