A decision model for making decisions under epistemic uncertainty and its application to select materials

Shahinur, Sweety; Ullah, Aman; Noor-E-Alam, Muhammad; Haniu, Hiroyuki; Kubo, Akihiko

doi:10.1017/s0890060417000191

Cited by 13 publications

(6 citation statements)

References 48 publications

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“…One challenge is the epistemic uncertainty, i.e., the lack of knowledge on how to interpret the results and how to design further steps, e.g., simulation experiments, and also the imprecise and coarsedata and information for the modeling and parameterization of simulation models. Decision models can help here [59].…”

Section: Discussionmentioning

confidence: 99%

Simulation of Energy and Media Demand of Beverage Bottling Plants by Automatic Model Generation

et al. 2021

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Facing environmental challenges, high energy costs and a growing public awareness, the global brewing industry is increasingly publishing ambitious targets toward a more sustainable production. Small and medium-sized enterprises of the brewing and beverage industry cannot ensure energy and media efficiency mainly due to capital and knowledge inadequacy. This article addresses this problem and presents a pragmatic method to determine the energy and media demand. Accordingly, a modeling editor as well as a standardized data structure and automatic simulation parameter determination tools were developed to implement the method. A given production plant can be modeled with adequate details using the presented editor. Based on a configuration file, a holistic simulation model can be generated automatically in a simulation environment. A beverage bottling plant was studied, and the necessary datasets were obtained for implementing the proposed editor and, thereby, the method. It was confirmed that the simulated values of electrical energy and compressed air consumption match the measured empirical data. The measures to increase energy and media efficiency were also found effective. Using the presented method, enterprises of the brewing and beverage industry can easily uncover avenues for potential savings, test the effectiveness of optimization strategies, and substantiate possible investment decisions.

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Section: Discussionmentioning

confidence: 99%

Simulation of Energy and Media Demand of Beverage Bottling Plants by Automatic Model Generation

et al. 2021

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“…Purpose Techniques Yazdani [36] Material selection AHP, FARE * and WASPAS * Shahinur et al [37] Material selection DSS and fuzzy analysis Jadid [38] Material selection DSS Venkata and Davim [39] Material selection AHP and TOPSIS * Sefair et. al.…”

Section: Referencesmentioning

confidence: 99%

A Framework of Selecting Building Flooring Finishing Materials by Using Building Information Modeling (BIM)

Orabi

Al-Gahtani

2022

Advances in Civil Engineering

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Building materials selection is a critical process affected by many complicated factors. Due to the specific function of elements, alternatives to materials must be appropriately chosen as they differ in quality, performance, and cost. Implementing a Value Engineering (VE) process is challenging as it requires effort and several workshops. Thus, this study proposes a framework to automate the VE process of selecting building flooring material. The framework identified selected agreed criteria of flooring finishing materials measured based on agreed standard tests. The developed framework is distinguished from other current research using a combination of Analytic Hierarchy Process (AHP), Pairwise, and Function Analysis System Technique (FAST) methods to define the criteria ranking weight and include the building function. Furthermore, the framework is integrated with Building Information Modeling (BIM) that has been widely used in the Architecture, Engineering, and Construction industry (AEC). Finally, a case study of a residential house in Saudi Arabia was used to demonstrate the framework. The proposed framework was verified by using two questioners and expert consultations.

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“…The sole attention of this paper is about the MADM framework. MADM approaches are already well demonstrated that addresses the uncertainty by considering a set of alternatives with uncertain values for the attributes or criteria of the alternatives (Wallenius et al ., 2008; Shahinur et al ., 2017). The basic steps in all MADM approaches are generally considered as: Decision matrix is the discrete decision space where a finite set of alternatives is expressed by its performance ratings in multiple attribute or criteria. Weightage or priority is assigned to each criterion according to the design requirements to satisfy the customer's demands and desires.…”

Section: Materials Selectionmentioning

confidence: 99%

“…Shahinur et al . (2017) judiciously introduced the fuzzy logic to select the material for vehicle body and the aluminum alloys are chosen as the best materials. Cryogenic storage tank materials are analyzed by WPM (Dehghan-Manshadi et al ., 2007), TOPSIS (Jahan et al ., 2012a), MOORA (Karande and Chakraborty, 2012), Fuzzy logic (Khabbaz et al ., 2009), and the preeminent material is considered as Austenitic steel (SS 301-FH).…”

Section: Materials Selectionmentioning

confidence: 99%

Material selection in engineering design based on nearest neighbor search under uncertainty: a spatial approach by harmonizing the Euclidean and Taxicab geometry

Das

Bhattacharya

Sarkar

2018

AIEDAM

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Material selection is a fundamental step in mechanical design that has to meet all the functional requirements of the component. Multiple-attributed decision-making (MADM) processes are already well established to choose the preeminent alternative from the finite set of alternatives, but there is some lack of geometrical evidence if the alternatives are considered as multi-dimensional points. In this paper, a fresh spatial approach is proposed based on nearest neighbor search (NNS) in which the nearness parameter is considered as a Manhattan norm (Taxicab geometry) in turn which is a function of the Euclidean norm and cosine similarity to raise a preeminent alternative under the MADM framework. Cryogenic storage tank and flywheel are considered as two case studies to check the validity of the proposed spatial approach based on NNS in material selection. The result shows the right choice for the cryogenic storage tank is the austenitic steel (SS 301 FH), and for the flywheel, it is a composite material (Kevler 49-epoxy FRP) those are consistent with the real-world practice and the results are compared with other MADM methods of previous works.

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A decision model for making decisions under epistemic uncertainty and its application to select materials

Cited by 13 publications

References 48 publications

Simulation of Energy and Media Demand of Beverage Bottling Plants by Automatic Model Generation

Simulation of Energy and Media Demand of Beverage Bottling Plants by Automatic Model Generation

A Framework of Selecting Building Flooring Finishing Materials by Using Building Information Modeling (BIM)

Material selection in engineering design based on nearest neighbor search under uncertainty: a spatial approach by harmonizing the Euclidean and Taxicab geometry

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