Design Concept Evaluation and Selection: A Decision Making Approach

2012 ◽  
Vol 155-156 ◽  
pp. 1122-1126 ◽  
Author(s):  
Rizwan Ullah ◽  
De Qun Zhou ◽  
Peng Zhou
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Product Design ◽  
Information Entropy ◽  
Entropy Method ◽  
Design Concept ◽  
Computationally Efficient ◽  
Design Concepts ◽  
Concept Evaluation ◽  
Multi Attribute Decision Making

This study proposes a multi-attribute decision making based approach for product design concept evaluation and selection. The technique for order preference by similarity to ideal solution (TOPSIS) is combined with fuzzy sets and information entropy. While the fuzzy sets theory is employed to capture the associated vagueness in the expert judgment, the combination of information entropy method with multi-attribute decision making makes the approach computationally efficient. We present the results of the evaluation of design concepts which demonstrate the feasibility and practicability of the approach. The proposed approach will result in considerable time and cost saving by identifying the most promising product design concepts and short-listing for further design and development activities.

scholarly journals Metrics for Measuring Sustainable Product Design Concepts

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3469
Author(s):  
Ji Han ◽  
Pingfei Jiang ◽  
Peter R. N. Childs
Keyword(s):  
Product Design ◽  
End Of Life ◽  
Environmental Impacts ◽  
Conceptual Design ◽  
Design Stage ◽  
Sustainable Product Design ◽  
Early Design ◽  
Design Concepts ◽  
Concept Evaluation ◽  
Sustainable Product

Although products can contribute to ecosystems positively, they can cause negative environmental impacts throughout their life cycles, from obtaining raw material, production, and use, to end of life. It is reported that most negative environmental impacts are decided at early design phases, which suggests that the determination of product sustainability should be considered as early as possible, such as during the conceptual design stage, when it is still possible to modify the design concept. However, most of the existing concept evaluation methods or tools are focused on assessing the feasibility or creativity of the concepts generated, lacking the measurements of sustainability of concepts. The paper explores key factors related to sustainable design with regard to environmental impacts, and describes a set of objective measures of sustainable product design concept evaluation, namely, material, production, use, and end of life. The rationales of the four metrics are discussed, with corresponding measurements. A case study is conducted to demonstrate the use and effectiveness of the metrics for evaluating product design concepts. The paper is the first study to explore the measurement of product design sustainability focusing on the conceptual design stage. It can be used as a guideline to measure the level of sustainability of product design concepts to support designers in developing sustainable products. Most significantly, it urges the considerations of sustainability design aspects at early design phases, and also provides a new research direction in concept evaluation regarding sustainability.

Machine Learning-Based Design Concept Evaluation

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Bradley Camburn ◽  
Yuejun He ◽  
Sujithra Raviselvam ◽  
Jianxi Luo ◽  
Kristin Wood
Keyword(s):  
Machine Learning ◽  
Technology Development ◽  
Empirical Evaluation ◽  
Learning Technologies ◽  
Design Concept ◽  
Third Party ◽  
Large Set ◽  
Design Concepts ◽  
Automated Method ◽  
Concept Evaluation

Abstract In order to develop novel solutions for complex systems and in increasingly competitive markets, it may be advantageous to generate large numbers of design concepts and then to identify the most novel and valuable ideas. However, it can be difficult to process, review, and assess thousands of design concepts. Based on this need, we develop and demonstrate an automated method for design concept assessment. In the method, machine learning technologies are first applied to extract ontological data from design concepts. Then, a filtering strategy and quantitative metrics are introduced that enable creativity rating based on the ontological data. This method is tested empirically. Design concepts are crowd-generated for a variety of actual industry design problems/opportunities. Over 4000 design concepts were generated by humans for assessment. Empirical evaluation assesses: (1) correspondence of the automated ratings with human creativity ratings; (2) whether concepts selected using the method are highly scored by another set of crowd raters; and finally (3) if high scoring designs have a positive correlation or relationship to industrial technology development. The method provides a possible avenue to rate design concepts deterministically. A highlight is that a subset of designs selected automatically out of a large set of candidates was scored higher than a subset selected by humans when evaluated by a set of third-party raters. The results hint at bias in human design concept selection and encourage further study in this topic.

scholarly journals TOPSIS Method Based on Complex Spherical Fuzzy Sets with Bonferroni Mean Operators

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1739
Author(s):  
Zeeshan Ali ◽  
Tahir Mahmood ◽  
Miin-Shen Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Unit Interval ◽  
Polar Coordinates ◽  
Topsis Method ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Special Cases ◽  
Order Preference ◽  
Multi Attribute Decision Making

The theory of complex spherical fuzzy sets (CSFSs) is a mixture of two theories, i.e., complex fuzzy sets (CFSs) and spherical fuzzy sets (SFSs), to cope with uncertain and unreliable information in realistic decision-making situations. CSFSs contain three grades in the form of polar coordinates, e.g., truth, abstinence, and falsity, belonging to a unit disc in a complex plane, with a condition that the sum of squares of the real part of the truth, abstinence, and falsity grades is not exceeded by a unit interval. In this paper, we first consider some properties and their operational laws of CSFSs. Additionally, based on CSFSs, the complex spherical fuzzy Bonferroni mean (CSFBM) and complex spherical fuzzy weighted Bonferroni mean (CSFWBM) operators are proposed. The special cases of the proposed operators are also discussed. A multi-attribute decision making (MADM) problem was chosen to be resolved based on the proposed CSFBM and CSFWBM operators. We then propose the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on CSFSs (CSFS-TOPSIS). An application example is given to delineate the proposed methods and a close examination is undertaken. The advantages and comparative analysis of the proposed approaches are also presented.

scholarly journals A Multi-Attribute Pearson’s Picture Fuzzy Correlation-Based Decision-Making Method

Mathematics ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 999 ◽  
Author(s):  
Jin ◽  
Wu ◽  
Sun ◽  
Zeng ◽  
Luo ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Correlation Coefficient ◽  
Ideal Point ◽  
New Correlation ◽  
Fuzzy Correlation ◽  
Relative Proximity ◽  
Fuzzy Madm ◽  
Multi Attribute Decision Making ◽  
Picture Fuzzy Sets

As a generalization of several fuzzy tools, picture fuzzy sets (PFSs) hold a special ability to perfectly portray inherent uncertain and vague decision preferences. The intention of this paper is to present a Pearson’s picture fuzzy correlation-based model for multi-attribute decision-making (MADM) analysis. To this end, we develop a new correlation coefficient for picture fuzzy sets, based on which a Pearson’s picture fuzzy closeness index is introduced to simultaneously calculate the relative proximity to the positive ideal point and the relative distance from the negative ideal point. On the basis of the presented concepts, a Pearson’s correlation-based model is further presented to address picture fuzzy MADM problems. Finally, an illustrative example is provided to examine the usefulness and feasibility of the proposed methodology.

Cubic Pythagorean fuzzy sets and their application to multi-attribute decision making with unknown weight information

2019 ◽  
Vol 37 (1) ◽  
pp. 1529-1544 ◽  
Author(s):  
Syed Zaheer Abbas ◽  
Muhammad Sajjad Ali Khan ◽  
Saleem Abdullah ◽  
Huafei Sun ◽  
Fawad Hussain
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Pythagorean Fuzzy Sets ◽  
Multi Attribute Decision Making

Exploiting Critical Path Method for Evaluation of Conceptual Design

2010 ◽  
Vol 97-101 ◽  
pp. 4429-4432 ◽  
Author(s):  
Mei Yan Wang ◽  
Lian Guan Shen ◽  
Yi Min Deng
Keyword(s):  
Conceptual Design ◽  
Critical Path ◽  
Design Concept ◽  
Design Evaluation ◽  
Critical Path Method ◽  
Design Concepts ◽  
Critical Design ◽  
Concept Evaluation ◽  
Design Requirements

Conceptual design is a critical design phase during which initial design solutions, called design concepts, are developed. These design concepts must be evaluated to ensure they satisfy the specified design requirements and the most appropriate design concept must be selected. It is often difficult for the designer, especially for the novice, to make an appropriate design concept evaluation and selection. Existing work on design evaluation lacks an effective tool for evaluating the temporal performance of the design concepts. To address this problem, a Critical Path Method (CPM) from project management is adapted for design evaluation, whereby a CPM network is converted from a causal behavioral process (CBP) and the methodologies relating to CPM are also applied to design improvement. A case study of a lever-clamp assembly system is also presented to illustrate as well as validate the method.

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