Learning from failures: Design improvements using a multiple criteria decision-making process

Author(s):  
G G Davidson ◽  
A W Labib

This paper proposes a new concept of decision analysis based on a multiple criteria decision making (MCDM) process. This is achieved through the provision of a systematic and generic methodology for the implementation of design improvements based on experience of past failures. This is illustrated in the form of a case study identifying the changes made to Concorde after the 2000 accident. The proposed model uses the analytic hierarchy process (AHP) mathematical model as a backbone and integrates elements of a modified failure modes and effects analysis (FMEA). The AHP has proven to be an invaluable tool for decision support since it allows a fully documented and transparent decision to be made with full accountability. In addition, it facilitates the task of justifying improvement decisions. The paper is divided as follows: the first section presents an outline of the background to the Concorde accident and its history of related (non-catastrophic) malfunctions. The AHP methodology and its mathematical representation are then presented with the integrated FMEA applied to the Concorde accident. The case study arrives at the same conclusion as engineers working on Concorde after the accident: that the aircraft may fly again if the lining of the fuel tanks are modified.

2015 ◽  
Vol 32 (7) ◽  
pp. 763-782 ◽  
Author(s):  
Hu-Chen Liu ◽  
Jian-Xin You ◽  
Xue-Feng Ding ◽  
Qiang Su

Purpose – The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes. Design/methodology/approach – A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes. Findings – A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies. Practical implications – The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method. Originality/value – This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.


2020 ◽  
Vol 26 (1) ◽  
pp. 103-134 ◽  
Author(s):  
Huchang Liao ◽  
Hongrun Zhang ◽  
Cheng Zhang ◽  
Xingli Wu ◽  
Abbas Mardani ◽  
...  

As a generalized form of both intuitionistic fuzzy set and Pythagorean fuzzy sets, the q-rung orthopair fuzzy set (q-ROFS) has strong ability to handle uncertain or imprecision decisionmaking problems. This paper aims to introduce a new multiple criteria decision making method based on the original gain and lost dominance score (GLDS) method for investment evaluation. To do so, we first propose a new distance measure of q-rung orthopair fuzzy numbers (q-ROFNs), which takes into account the hesitancy degree of q-ROFNs. Subsequently, two methods are developed to determine the weights of DMs and criteria, respectively. Next, the original GLDS method is improved from the aspects of dominance flows and order scores of alternatives to address the multiple criteria decision making problems with q-ROFS information. Finally, a case study concerning the investment evaluation of the BE angle capital is given to illustrate the applicability and superiority of the proposed method.


2019 ◽  
pp. 135481661988520
Author(s):  
Joseph Andria ◽  
Giacomo di Tollo ◽  
Raffaele Pesenti

In this article, we propose a method for ranking tourist destinations and evaluating their performances under a sustainability perspective: a fuzzy multiple criteria decision-making method is applied for determining sustainability performance values and ranking destinations accordingly. We select a set of sustainability evaluation criteria and use a fuzzy analytic hierarchy process to weight the selected criteria. We also optimize each evaluator’s membership function support by means of a fuzzy entropy maximization criteria. A case study is illustrated and results are compared with two data envelopment analysis–based models. The simplicity of the proposed approach along with the easy readability of the results allow its direct applicability for all involved stakeholders.


2019 ◽  
Vol 11 (03) ◽  
pp. 1950029
Author(s):  
Ashoke Kumar Bera ◽  
Dipak Kumar Jana ◽  
Debamalya Banerjee ◽  
Titas Nandy

In today’s highly turbulent and competitive environment, the success of the organization depends on the performance of its suppliers. However, supplier selection problems are complex as they involve a large number of criteria and, frequently, some of the criteria cannot be evaluated precisely. Moreover, fluctuations of supplier performances and unknown information always exist in real-world decision-making. It is a complex multiple-criteria decision-making (MCDM) problem as it involves a trade-off among various criteria with vagueness and imprecision and also involves a group of experts with diverse opinion. Therefore, to make more practical decisions, this paper is intended to propose an integrated technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment with multi-choice goal programming (MCGP) to handle the supplier assessment and order allocation for a battery manufacturing organization. Using linguistic variables, the decision-makers assess the rating of suppliers as well as the importance of various factors. Linguistic variables are expressed in trapezoidal fuzzy numbers (TrFN). Fuzzy-TOPSIS method is proposed to obtain the rank of suppliers and MCGP method is used to allocate suitable orders to the selected suppliers. A case study is implemented to find the applicability and validity of the proposed model. Finally, sensitivity analysis is performed to observe the effect of weights of criteria on supplier evaluation problem.


2018 ◽  
Vol 146 ◽  
pp. 01002 ◽  
Author(s):  
Tomas Vanicek ◽  
Jana Kucerova

Many decision processes in technical and economical sciences require multiple criteria decision making. The most widely applied methods for multiple criteria evaluation of alternatives are based on the evaluation of alternatives in terms of an additive preference function. All of them require the estimation of weights of usually conflicting criteria. There are several methods how to find the weights of the criteria and how to find the evaluation of each solution in each criterion. The decision process based on simple weighted sum of values may not be the best approach in all situations. This paper contains a new approach of the evaluation of measured value set by different mathematical operators than the usually used multiple criteria evaluation methods. The approach was applied in a case study for multiple criteria evaluation. Generally, this new decision-support tool can help in various situations where different types of effects caused by a construction or reconstruction can occur. This is a very frequent situation in dealing with building defects, too.


Sign in / Sign up

Export Citation Format

Share Document