Summary Numerous mismated materials are now a day’s available to upgrade the quality and efficiency of connecting rod. Picking the preeminent one with reference to a connecting rod is a difficult problem. Actually, decision support systems like MCDM techniques may be very much convenient in crafting, as much as potential, an objective and convincing option. Conversely, a definitive response to inquiries: which Multi criteria decision making technique is most appro- priate and which technique is most effectual is still authentic. Hence, this paper explores the applicability and effectiveness of some well-known MCDM techniques for the connecting rod material selection.

Introduction：New market conditions bid manufacturers bring to bear superior quality, better efficiency and inferior cost devel- oped technology to cobble up vehicle components so as to increase their spirited capability and meet up the market compulsion. Though mutually the number of criterion and the number of substitutes usually do not avow the choice maker to unswervingly accomplish a deliberate option that

acquires into account concurrently all the numerous vari- ables engaged, the directed careful picking of the material for connecting rod can be particularly considerable espe- cially when the manufacturer want to accommodate the market requirement. The main goal of the recent effort consists in inspecting the materiality and efficacy of spe- cial ‘‘state-of-the art’’ of MCDM methods for the connecting rod material selection. These MCDM methods are judged against each other in terms of fitness for the particularly contemplated decision task and dealing to several consider- able criterions like affluence of suitability, authenticity and healthiness of the preference, a degree of choice maker’s ascendancy on the result. Actually this paper scrutinizes an assessment of outcomes that were accomplished by employ- ing different MCDM methods.

Table 1 Some important mechanical properties of connecting rod.

Sl. no. Specification Stress (MPa) Avg. Tensile stress

(MPa) Avg. Sertlik

(HRB) Avg. % D  strain Avg. Fatigue limit

(MPa) Avg.

1 Pearlite 560 850 280 10 428.4

2 Bainite 590 920 278 10 463.68

3 Martenzite 892 1100 352 6 554.4

4 Temp. martenzite 612 900 310 9 453.6

5 FRACTIM 540 810 300 12 433.45

6 70MnSV4 570 860 255 11 408.24

Literature review

MCDM approaches are used to get a  respond  to  the query: what’s the augmentation of the various  litera- tures in the arena of  selection  of  the  materials? What are the programmes/arrangement/contrivances for mate- rial selection? Which advancements are especially useful? Is there any drawback of the advancements? In the ter- mination of the study, their research and examination administers confirmation that the MCDM approaches has the prospective to emphatically doctor up the selection methodology and promoted the decision makers in vali- dating the different approaches adequately. Athawale and Chakraborty (2012) adapted ten most regularly employed MCDM methods as contemplated for resolving three dis- similar material assortment problems and compared their analogous ranking performance. Rao (2006) resolved two different material selection pro  a  cryogenic  tank  and for a product blueprinted for functioning in a elevated temperature oxygen loaded environment. (Shanian et al., 2005) investigated the outcomes of various normalization procedures in TOPSIS method whereas resolving a gear material choice problem. Prasad and Chakraborty (2013) resolved a few material assortment problems by employing a ‘‘quality function deployment’’ approach, accommodat- ing the tone of the consumers for a product by means of its methodical requisites. Shanıan and Savadogo (2006) applied TOPSIS process for explaining the material assort- ment problem. Works have previously been executed by the past analysts on material assortment utilizing perse MCDM methods, however very minute exertion has been put to equate the relative performance of perse MCDM meth- ods whereas resolving the material assortment problems (Table 1).