Selection of the Optimum Hole Quality Conditions in Manufacturing Environment Using MCDM Approach: A Case Study

  • Ravi Pratap Singh
  • Mohit Tyagi
  • Ravinder KatariaEmail author
Conference paper
Part of the Lecture Notes on Multidisciplinary Industrial Engineering book series (LNMUINEN)


In the current competitive structure of the manufacturing industries, the qualitative decision-making has become an issue of paramount prominence to solve the real-life industrial environment based problems. It becomes further more complex when the decision maker has to be in concern with the multiple constraints at one time. The present article has targeted to select the optimum hole quality conditions for performing ultrasonic machining of a selected composite material through multiple criteria decision-making (MCDM) approaches. The experimentation has been designed according to the Taguchi’s methodology. The hole quality based attributes (out of roundness, hole over size and conicity) have been studied under the influential situations of several selected input variables namely; thickness of workpiece, cobalt content, tool profile, power rating, material of tool and grit size. In addition, two different MCDM approaches called as the additive ratio assessment (ARAS) technique, and the TOPSIS method have been attempted for the selection of the best optimum condition that can offer fruitful hole quality based outcomes for the considered manufacturing environment problem. The optimality function and the specific alternative to the perfect solution to observe the best available alternative have been computed as per the ARAS, and the TOPSIS techniques, respectively. Results revealed that, for both the explored MCDM methods, the 9th experimental run offers the highest value of the calculated hole quality attribute index. This particular conducted test is entailing of the parametric blend as; cobalt content—24%, workpiece thickness—3 mm, tool profile—hollow, material of tool—stainless steel, abrasive grit size—500 (mesh size) and power rating—80%.


ARAS method Decision-making Manufacturing environment MCDM approaches TOPSIS method 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Ravi Pratap Singh
    • 1
  • Mohit Tyagi
    • 1
  • Ravinder Kataria
    • 2
    Email author
  1. 1.Department of Industrial and Production EngineeringDr. B. R. Ambedkar National Institute of TechnologyJalandharIndia
  2. 2.School of Mechanical EngineeringLPUJalandharIndia

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