Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making (both in daily life or in professional settings). Conflicting criteria are typical in evaluating options: cost or price is usually one of the main criteria, and some measure of quality is typically another criterion, easily in conflict with the cost. In order to survive in the present day global competitive environment, it now becomes essential for the manufacturing organisations to take timely and accurate decisions regarding effective use of their scarce resources. Various multicriteria decision-making (MCDM) methods are now available to help those organisations in choosing the best decisive course of actions. In this project work, the applicability of some newly developed MCDM methods will be explored while solving some discrete manufacturing decision making problems. Integrated decision-making framework will also be developed for effective decision-making. Ranking performances of these methods will also be compared. Decision making that deals with several aspects of a finite set of available alternatives in a given situation is often referred to as multi criteria analysis.
PROJECT 8th SEM - DEVELOPMENT OF SOME INTEGRATED DECISION-MAKING FRAMEWORK FOR ADVANCED MANUFACTURING TECHNOLOGY SELECTION PROBLEMS
1. DEVELOPMENT OF SOME INTEGRATED DECISION-
MAKING FRAMEWORK FOR ADVANCED
MANUFACTURING TECHNOLOGY SELECTION
PROBLEMS
Submitted By University Roll No.
1. Bibek Kumar Buranwal 11600713015
2. Rosan Kumar Pattanayak 11600713037
3. Saksham Pandey 11600713038
4. Souptik Sarkar 11600713045
5. Swagatam Mitra 11600713058
6. Vikash Mohta 11600713059
7. Yash Khara 11600713060
Under The Supervision of Dr. Prasenjit Chatterjee
2. QUICK REVIEW OF PREVIOUS WORKS:
Introduction to MCDM
Methods used for MCDM
• TOPSIS-GRA METHOD
• DENG’s METHOD
Material selection process for MPBR using Deng & TOPSIS-GRA
Material selection process for Armature shaft using Deng & TOPSIS-GRA
Comparison & Discussion of two different methods
Future works-PHASE 2
3. AIMS & OBJECTIVES:
• To know various methods for calculating weight
• To know about integrated MABAC-COV
• Apply Method to solve Problems in Advance manufacturing
technology selection
• Comparison of RANKS by different method
5. PROCESS FOR WEIGHT CALCULATION:
Known Preference Order
AHP(Analytic Hierarchy Process)
ANP(Analytic Network Process)
DEMATEL (Decision Making Trial and Evaluation Laboratory)
Unknown Preference Order
• Entropy Method
• Co-efficient of Variance
6. MATHEMATICAL MODELLING OF ENTROPY
METHOD:
Formation of Normalization Matrix
For efficiency type For cost type
Calculation of Ratio of index value
8. MATHEMATICAL MODEL OF MABAC-COV:
• Formation of Decision matrix
• Calculation of Normalization matrix by formula given below
For Beneficial Type For non-beneficial type
• Calculation of Weight by COV Method given below
𝑛𝑖𝑗 =
𝑥𝑖𝑗 − 𝑥𝑖
−
𝑥𝑖
+
− 𝑥𝑖
− 𝑛𝑖𝑗 =
𝑥𝑖𝑗 − 𝑥𝑖
+
𝑥𝑖
−
− 𝑥𝑖
+
9. • Calculation of weighted matrix
𝑣𝑖𝑗 = 𝑤𝑖. (𝑛𝑖𝑗 + 1)
• Determining the border approximation area matrix (G)
𝑔𝑖 =
𝑗=1
𝑚
𝑣𝑖𝑗
1/𝑚
• Calculation of the distance of the alternative from the border
approximation area for the matrix elements (Q)
𝑄 = 𝑉 − 𝐺 =
𝑣11 𝑣12 … 𝑣1𝑛
𝑣21 𝑣22 … 𝑣2𝑛
… … … …
𝑣 𝑚1 𝑣 𝑚2 … 𝑣 𝑚𝑛
−
𝑔1 𝑔2 … 𝑔 𝑛
𝑔1 𝑔2 … 𝑔 𝑛
… … … …
𝑔1 𝑔2 … 𝑔 𝑛
10. • Calculation of Si, Si = 𝑗=1
𝑚
𝑄𝑖𝑗
• Finally Calculation RANK by maximum value of Si
20. RESULTS:
• Our Spearman’s Co-Relation co-efficient for the selection of robots is
.86 .
• Our Spearman’s Co-Relation co-efficient for the selection of CNC
machine is 1.
• In CNC machine selection we found that ST30SS is the best among the
nine CNC machine.
21. CONCLUSION:
• Various MCDM methods in this project.
• Among all the processes MACBAC-COV gives the satisfactory value.
• It is found that MACBAC-COV is better than rest of the MCDM
methods.
• So Integrated MACBAC-COV is considered as on of the best methods
in Advanced Manufacturing Technology Selection.
22. FUTURE WORKS:
• We confined our research area in CNC machine industry in this
project.
• Satisfactory results has motivated us to use this in other Industries
also.
• Selection of a better material among many attributes given to us can
be done by this method.
23. REFERENCES:
• Xia, Fei, Huan Wei, and Lian Wu Yang. "Improved COPRAS Method and Application in Material
Selection Problem." Applied Mechanics and Materials. Vol. 707. Trans Tech Publications, 2015.
• Pamučar, Dragan, and Goran Ćirović. "The selection of transport and handling resources in
logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC)." Expert
Systems with Applications 42.6 (2015): 3016-3028.
• İç, Yusuf Tansel. "An experimental design approach using TOPSIS method for the selection of
computer-integrated manufacturing technologies." Robotics and Computer-Integrated
Manufacturing 28.2 (2012): 245-256.
24. ACKNOWLEDGEMENT:
We the student of 4TH year MECHANICAL Engineering would like to
show our gratitude to the Department of Mechanical Engineering for
the invaluable knowledge and immense support. And specially cordial
thanks to Dr. Prasenjit Chatterjee for his guidance and helping hands
and Mr. Soutrik Bose for giving us the opportunity.
THANK YOU