An Additive Manufacturing Process Selection Approach Based on Fuzzy Archimedean Weighted Power Bonferroni Aggregation Operators

Research output: Contribution to journalArticle

Abstract

Selecting an appropriate additive manufacturing (AM) process or machine to fabricate an end-use product is an important issue in design for AM. One of many types of approaches for AM process selection is based on multi-criteria decision making (MCDM). Most of the MCDM based approaches have an advantage in taking into account the relative importance of performance parameter types and a few of them also consider the interrelationships of performance parameter types. Each of these approaches can work well in its specific context. They are however not entirely satisfactory, as they do not have the capabilities to reduce the influence of the deviation of performance parameter values on the decision-making result and to capture the risk attitudes of users in their decision-making models. In this paper, an MCDM approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators with such capabilities is proposed for AM
process selection. A fuzzy Archimedean weighted power Bonferroni mean operator and a fuzzy Archimedean weighted power geometric Bonferroni mean operator are firstly constructed. Based on these operators, an MCDM approach for selection of AM processes are then developed. After that, four practical examples are adopted to illustrate the developed approach and a set of sensitivity analysis experiments on the basis of these examples are carried out. Finally, qualitative and quantitative comparisons between the approach and the existing MCDM based approaches are reported to demonstrate its feasibility, effectiveness, and advantages.
Original languageEnglish
JournalRobotics and Computer-Integrated Manufacturing
Publication statusAccepted/In press - 11 Dec 2019

Fingerprint

3D printers
Bonferroni
Aggregation Operators
Multicriteria Decision-making
Agglomeration
Manufacturing
Decision making
Operator Mean
Decision Making
Sensitivity Analysis
Deviation
Sensitivity analysis
Operator
Demonstrate
Experiment

Cite this

@article{ba253c5b07a34444bb836d12f521759d,
title = "An Additive Manufacturing Process Selection Approach Based on Fuzzy Archimedean Weighted Power Bonferroni Aggregation Operators",
abstract = "Selecting an appropriate additive manufacturing (AM) process or machine to fabricate an end-use product is an important issue in design for AM. One of many types of approaches for AM process selection is based on multi-criteria decision making (MCDM). Most of the MCDM based approaches have an advantage in taking into account the relative importance of performance parameter types and a few of them also consider the interrelationships of performance parameter types. Each of these approaches can work well in its specific context. They are however not entirely satisfactory, as they do not have the capabilities to reduce the influence of the deviation of performance parameter values on the decision-making result and to capture the risk attitudes of users in their decision-making models. In this paper, an MCDM approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators with such capabilities is proposed for AMprocess selection. A fuzzy Archimedean weighted power Bonferroni mean operator and a fuzzy Archimedean weighted power geometric Bonferroni mean operator are firstly constructed. Based on these operators, an MCDM approach for selection of AM processes are then developed. After that, four practical examples are adopted to illustrate the developed approach and a set of sensitivity analysis experiments on the basis of these examples are carried out. Finally, qualitative and quantitative comparisons between the approach and the existing MCDM based approaches are reported to demonstrate its feasibility, effectiveness, and advantages.",
keywords = "Additive manufacturing process, Process selection, Process performance assessment, User preference assessment, Multi-criteria decision making, Fuzzy information aggregation",
author = "Yuchu Qin and Qunfen Qi and Paul Scott and Jane Jiang",
year = "2019",
month = "12",
day = "11",
language = "English",
journal = "Robotics and Computer-Integrated Manufacturing",
issn = "0736-5845",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - An Additive Manufacturing Process Selection Approach Based on Fuzzy Archimedean Weighted Power Bonferroni Aggregation Operators

AU - Qin, Yuchu

AU - Qi, Qunfen

AU - Scott, Paul

AU - Jiang, Jane

PY - 2019/12/11

Y1 - 2019/12/11

N2 - Selecting an appropriate additive manufacturing (AM) process or machine to fabricate an end-use product is an important issue in design for AM. One of many types of approaches for AM process selection is based on multi-criteria decision making (MCDM). Most of the MCDM based approaches have an advantage in taking into account the relative importance of performance parameter types and a few of them also consider the interrelationships of performance parameter types. Each of these approaches can work well in its specific context. They are however not entirely satisfactory, as they do not have the capabilities to reduce the influence of the deviation of performance parameter values on the decision-making result and to capture the risk attitudes of users in their decision-making models. In this paper, an MCDM approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators with such capabilities is proposed for AMprocess selection. A fuzzy Archimedean weighted power Bonferroni mean operator and a fuzzy Archimedean weighted power geometric Bonferroni mean operator are firstly constructed. Based on these operators, an MCDM approach for selection of AM processes are then developed. After that, four practical examples are adopted to illustrate the developed approach and a set of sensitivity analysis experiments on the basis of these examples are carried out. Finally, qualitative and quantitative comparisons between the approach and the existing MCDM based approaches are reported to demonstrate its feasibility, effectiveness, and advantages.

AB - Selecting an appropriate additive manufacturing (AM) process or machine to fabricate an end-use product is an important issue in design for AM. One of many types of approaches for AM process selection is based on multi-criteria decision making (MCDM). Most of the MCDM based approaches have an advantage in taking into account the relative importance of performance parameter types and a few of them also consider the interrelationships of performance parameter types. Each of these approaches can work well in its specific context. They are however not entirely satisfactory, as they do not have the capabilities to reduce the influence of the deviation of performance parameter values on the decision-making result and to capture the risk attitudes of users in their decision-making models. In this paper, an MCDM approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators with such capabilities is proposed for AMprocess selection. A fuzzy Archimedean weighted power Bonferroni mean operator and a fuzzy Archimedean weighted power geometric Bonferroni mean operator are firstly constructed. Based on these operators, an MCDM approach for selection of AM processes are then developed. After that, four practical examples are adopted to illustrate the developed approach and a set of sensitivity analysis experiments on the basis of these examples are carried out. Finally, qualitative and quantitative comparisons between the approach and the existing MCDM based approaches are reported to demonstrate its feasibility, effectiveness, and advantages.

KW - Additive manufacturing process

KW - Process selection

KW - Process performance assessment

KW - User preference assessment

KW - Multi-criteria decision making

KW - Fuzzy information aggregation

M3 - Article

JO - Robotics and Computer-Integrated Manufacturing

JF - Robotics and Computer-Integrated Manufacturing

SN - 0736-5845

ER -