Elsevier

Materials & Design

Volume 44, February 2013, Pages 240-245
Materials & Design

Technical Report
Hard coating material selection using multi-criteria decision making

https://doi.org/10.1016/j.matdes.2012.08.003Get rights and content

Abstract

The paper deals with the hard coating material selection using various multi-criteria decision making approaches. Large number of materials has stimulated intense research in the field of material selection. Various quantitative decision making approaches are employed to select hard coating material selection. Technique for order preference by similarity to ideal solution (TOPSIS) is used for ranking these materials. Material selection charts (Ashby approach) is used to select hard coating materials. Pareto-optimal hard coating materials are determined for trade-off between hardness (H), H/E and H3/E2 (E: Young’s modulus). Hierarchical clustering is used to classify hard coating materials under study. Pearson correlation coefficients are calculated between the materials properties under study which can be integrated with materials informatics for rapidly screening and designing materials.

Highlights

► Hard coating materials are selected using multiple attribute decision making (MADM) approach (TOPSIS). ► The results are compared with that of material selection using Ashby approach. ► Good concurrence is found between the results of Ashby approach and TOPSIS technique. ► These techniques are efficient in selection and screening of hard coating materials.

Introduction

The primary cause of mechanical failure of majority components is wear of the mating parts after repetitive use. Wear is inevitable in mechanical components where physical contact and relative motion exists. Compared to other modes of failure, wear accounts for over 90% of mechanical failures annually. High wear rates also cause waste of energy in the form of micro-machining thereby adding to the overall cost of the losses by decreasing the efficiency of the machines [1], [2], [3], [4]. Thus, it would be highly beneficial if wear in components could be avoided or reduced to a minimum. Wear can be reduced by altering physical properties of surfaces [5]. One of the most popular ways of improving wear resistant characteristics is to hard coating materials. Many new hard coating materials have been reported and found to be promising. However, a readily available database comparing the effectiveness of the materials is not available to the designers and engineers. Thus, it becomes a cumbersome and tedious task for the designer to select the optimum material for hard coating as selection of hard coating material depends upon several parameters [6]. These parameters include mechanical, thermal, chemical, environmental and cost. Thus, the designer has to rely on the availability of past data, experience and expert judgement to choose a suitable material from a given set of alternatives. This method, however, often leads to sub optimal selections which may drastically affect the working, life, reliability or pricing of the designed component which is highly undesirable. Another way of solving the problem of selection is to use a multi-criteria decision making algorithm. Selection of optimal material from among two or more alternative materials on the basis of two or more properties is a multi-criteria decision making problem (MCDM). MCDM is divided into multi-objective decision making (MODM) and multi-attribute decision making (MADM) techniques. Multiple objective decision making is used for solving optimal design/selection problems in which several (conflicting) objectives are to be achieved simultaneously. The characteristics of MODM are a set of (conflicting) objectives and a set of well-defined constraints. MODM methods are often referred to as supervised selection or screening procedures as they utilise the functional relationships between various attributes of the problem to create figures of merit which are used to rank and compare different alternatives. The procedure involves formulating of performance indices or figures of merits which are based on the functional relationship that exists between the various attributes, such that the maximisation or minimisation of such a function would lead to the satisfaction of a set goal such as low cost, high strength or low weight. MADM methods however, are referred to as un-supervised selection and screening procedures as they do not require the functional relationship between the attributes of the given alternatives but employ several different mathematical models to compare and rank the alternatives with an ideal or predetermined solution that may be either user defined or data generated depending upon the type of algorithm used.

This study deals with hard coating material selection using MODM and MADM methods. TOPSIS which is a MADM technique is used to rank competing materials based on their desirable properties. Ashby approach is used to compare the results obtained from the above technique. Additionally a dendrogram, a hierarchal clustering technique, is plotted in order to better analyse and group the various materials on the basis of their physical behaviour.

Section snippets

Materials properties

A large number of materials are explored and being used for hard coating applications. Technologically important materials are considered for this study which are mentioned in Table 1 [7]. Properties that are considered for the present study are Hardness (HV), Young’s modulus of elasticity (E, GPa) and coefficient of thermal expansion (α, 10−6) which are listed in Table 1.

Classical theories [8], [9] propose hardness as the single most important property for wear resistance. However It is found

Results and discussion

It is clear from Eqs. (1), (3) that higher value of H and lower value of E are beneficial. Thus, for the TOPSIS, the positive ideal solution (most desired solution) is determined by considering the maximum value of H, minimum value of α and minimum value of E, while for the negative ideal solution (least desired solution) minimum value of H, maximum value of α and maximum value of E is preferred. Also, two additional properties are required for the complete evaluation of the candidate

Conclusion

Selection and screening of hard coating materials are studied. Various decision making approaches are employed for this purposes. Results of TOPSIS approach and Ashby method show good agreement with each other. C and MgO materials are found to be most and least desirable materials under study. C, BN, B4C and Si3N4 are found to be Pareto-optimal solution among the materials understudy. Ranking scheme shows that covalent coating materials occupy the highest ranks possible indicating that they are

Acknowledgment

RV acknowledges support from the Indian National Science Academy (INSA), New Delhi, through a grant by the Department of Science and Technology, (DST), New Delhi, under INSPIRE faculty award-2011 (ENG-01).

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