A Dynamic MAUT Decision Model for R&amp;#x00026;D Project Selection

Wang, Zhong; Zhang, Shaonan; Kuang, Jianchao

doi:10.1109/ccie.2010.112

Cited by 7 publications

(5 citation statements)

References 10 publications

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“…The utility function is structured by a set of criteria, which reflect the decision maker's preferences. In this function, a utility value is added to each consequence (attribute) of an action on a given problem to identify its best result, calculating the best possible utility (maximum values) (Almeida, 2012;Nikou & Klotz, 2014;Wang et al, 2010).…”

Section: Robust Tool For Determining Critical Components For Maintena...mentioning

confidence: 99%

“…Based on Nikou & Klotz (2014), Almeida (2012), Wang et al (2010), was applied an Entropy-MAUT method approach, and it can be summarised in the following steps shown in Figure 5. The hybrid Entropy-MAUT decision method effectively increases the reliability and accuracy of the Kaplan hydro generator unity critical components.…”

Section: Application Of Decision Model and Datamentioning

confidence: 99%

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Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Bellinello,

Antomarioni,

Souza

et al. 2022

Prod.

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Paper aims: This paper aims to develop a proper maintenance policy directly related to defining critical components for ensuring a high level of safety and high-level in-service quality for all hydro generator units.Originality: An innovative integrated tool that contributes to ensuing assertiveness in decision-making to determine the critical components is presented in this study. Specifically, hydro-generator unit type Kaplan belonging to a Brazilian Hydroelectric power plant is used as an application case to highlight the choice of the most suitable maintenance policy in light of the proposed approach. The selection of the case study is based on the fact that hydroelectric power plants are the basis of the Brazilian energy matrix, accounting for 75% of the demand in the country. Therefore, the need to maintain hydroelectric plants' availability and operational reliability is clear not to compromise the continuity and conformity (quality) of the electrical energy supply.Research method: Seven multi-criteria decision-making methods were applied in addition to two methods for deciding weight (Critic Method and Entropy) have been compared to determine the critical components of the hydro-generator. To investigate the robustness of the classification of the applied Multi-Criteria Decision Making approaches, a sensitivity analysis was performed based on the weight change of each decision criterion. Main findings:As a main result, the Entropy-Multi-Attribute Utility Theory model is proposed as the best approach to guarantee the selection of critical components for the Brazilian hydroelectric power plant case study. The validation sensitivity analysis by critical Fuzzy K-means groups guarantees that it is a robust tool for decision-making.Implications for theory and practice: Ensuring the availability and reliability of hydroelectric plants can be achieved by employing appropriate maintenance policies that reduce the likelihood of failure or even eliminate its root causes, preventing failure from occurring. Consequently, a robust tool for decision-making regarding the Kaplan hydro generator's critical components' monitoring was developed.

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Section: Robust Tool For Determining Critical Components For Maintena...mentioning

confidence: 99%

Section: Application Of Decision Model and Datamentioning

confidence: 99%

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Bellinello,

Antomarioni,

Souza

et al. 2022

Prod.

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show abstract

“…There are several MCDM methods, such as Weighted Product Method (WPM) [32,33], Weighted Sum Method (WSM) [26,34,35], Elimination and Choice Translating Reality (ELECTRE) [36][37][38], Analytical Hierarchy Process (AHP) [39], Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) [40][41][42], Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) [43][44][45][46], Preference Ranking Organization Method (PROMETHE) [47][48][49], and Multi-Attribute Utility Theory (MAUT) [50][51][52]. Each method has its advantages, disadvantages, and application as being summarized in the literature [53][54][55].…”

Section: Introductionmentioning

confidence: 99%

Multicriteria Decision-Making to Determine the Optimal Energy Management Strategy of Hybrid PV–Diesel Battery-Based Desalination System

et al. 2021

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This paper identifies the best energy management strategy of hybrid photovoltaic–diesel battery-based water desalination systems in isolated regions using technical, economic and techno–economic criteria. The employed procedures include Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as tools for the solution. Twelve alternatives, containing three–four energy management strategies; four energy management strategies, load following (LF), cycle charging (CC), combined LF–CC, and predictive strategy; and three different sizes of brackish water reverse osmosis (BWRO) water desalination units, BWRO-150, BWRO-250, and BWRO-500, are investigated with capacity of 150, 250, and 500 m3/day, respectively. Eight attributes comprising different technical and economic metrics are considered during the evaluation procedure. HOMER Pro® software is utilized to perform the simulation and optimization. The main findings confirmed that the best energy management strategies are predictive strategies and the reverse osmosis (RO) unit’s optimal size is RO-250. For such an option, the annual operating cost and initial costs are $4590 and $78,435, respectively, whereas the cost of energy is $0.156/kWh. The excess energy and unmet loads are 27,532 kWh and 20.3 kWh, respectively. The breakeven grid extension distance and the amount of CO2 are 6.02 km and 14,289 kg per year, respectively. Compared with CC–RO-150, the amount of CO2 has been sharply decreased by 61.2%.

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“…Wang ve diğ. [40] Ar-Ge proje seçimi için dinamik bir MAUT (Multi attribute utility theory) karar modeli önermişler ve modelin uygulanabilirliğini ve etkinliğini göstermek için gerçek bir Ar-Ge yatırımı örneği kullanılmışlardır. Verbano ve diğ.…”

Section: Introductionunclassified

A new approach to R-D project selection problem and a solution proposal: UTA method

Binici¹,

Aksakal²

2020

Pamukkale J Eng Sci

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Küreselleşmenin hızla arttığı günümüzde rekabet edebilirliğin temeli bilgiye dayanmaktadır. Bilgi, Ar-Ge çalışmaları ile sistematik hale getirilerek bilim ve teknolojiye dönüşür. Bir ülkenin kalkınması katma değer üretmesi, istihdam sağlayabilmesi, üretimlerini sürekli artırarak devam ettirebilmesi ancak bilgi birikiminin artması ve artan bilginin bilim ve teknolojiye dönüştürülmesi ile mümkündür. Ürün ve hizmet çeşitliliğinin çok fazla olduğu göz önüne alındığında ülkelerin ve üreticilerin bu faaliyetlerini sürdürebilmeleri ve rekabet edebilmeleri için yenilikler ortaya koyması gerekmektedir. Bu konuda araştırma ve geliştirme (Ar-Ge) büyük önem taşımaktadır. Ar-Ge, hali hazırda bulunan bilgilerden yeni ürün, yeni üretim yöntemlerinin geliştirilmesi veya yeni teknolojilerin, ürünlerin, üretim yöntemlerinin elde edilmesi olarak tanımlanabilir. Diğer ülkelerde olduğu gibi ülkemiz de Ar-Ge yatırımlarını teşvik etmekte ve Ar-Ge yatırımlarına destek vermektedir. Bu kapsamda birçok kurum ve kuruluş girişimcilerin, firmaların, akademisyenlerin Ar-Ge projelerini sağladığı katma değer oranında desteklemektedir. Ar-ge boyutunda desteğin belirlenmesinde etkin olacak katma değer ise fayda olarak değerlendirilebilir. Bu amaçla desteklerin etkin bir şekilde kullanılması göz önüne alınarak, çalışmamızda Ar-Ge projelerinin seçiminin yapıldığı bir yarışmada projelerin değerlendirme süreci ele alınmıştır. UTA yöntemi marjinal faydayı dikkate alan yapısı ve doğrusal programlama yaklaşımını içermesi nedeniyle tercih edilmiştir. Yöntemin çözüm aşamasında elde edilen matematiksel modelin çözümü için de GAMS Programından yararlanılmıştır. Bulunan çözümün fayda temelli olmasından dolayı projelerin daha etkin ve doğru şekilde sıralanmasına destek sağlayabileceği gösterilmeye çalışılmıştır. Anahtar kelimeler: UTA Yöntemi, Ar-Ge proje seçimi, Çok kriterli karar verme yöntemi

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A Dynamic MAUT Decision Model for R&D Project Selection

Cited by 7 publications

References 10 publications

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Multicriteria Decision-Making to Determine the Optimal Energy Management Strategy of Hybrid PV–Diesel Battery-Based Desalination System

A new approach to R-D project selection problem and a solution proposal: UTA method

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