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Selection of Waste Lubricant Oil Regenerative Technology Using Entropy-Weighted Risk-Based Fuzzy Axiomatic Design Approach
Volume 29, Issue 1 (2018), pp. 41–74
Pub. online: 1 January 2018      Type: Research Article      Open accessOpen Access
Received
1 August 2017
Accepted
1 January 2018
Published
1 January 2018

Abstract

The selection of waste lubricant oil regenerative technology regarding the complexity of the technologies and financial issues is a complex problem. Some risk factors exist regarding the ratings of technologies on the effective criteria. The current study tackles the selection of the technology based on fuzzy axiomatic design approach considering risk factors. Shannon entropy significance coefficients are computed for criteria. The problem is first solved by considering all criteria and then supplementary solutions are presented by categorizing the criteria to technical and economic groups. Two types of risk factors are identified for the technologies, i.e. general and specific risk factors.

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Biographies

Ijadi Maghsoodi Abteen
Aimaghsoodi@srbiau.ac.ir

A. Ijadi Maghsoodi is a MSc student in industrial engineering at the Islamic Azad University, Science and Research Branch, Tehran, Iran. He has earned a BSc degree in industrial engineering from Islamic Azad University, Qazvin Branch, Qazvin, Iran. He has industrial experience in lubricating oils industry and regenerative waste products at Monad Oil Company in UAE. His research interests are focused on MCDM, intelligent decision support systems, statistical learning, and data-mining.

Hafezalkotob Arian
ar_hafezalkotob@azad.ac.ir

Ar. Hafezalkotob is a lecturer at Islamic Azad University, South Tehran Branch, Iran from 2014–2017. He received a MSc degree in mechanical engineering (applied design), in 2010, and a BSc degree in mechanical engineering (solids design), in 2007, both from Islamic Azad University, Tehran, Iran. He is also a member of young researchers and elite club, South Tehran Branch, Islamic Azad University, Tehran, Iran. He has authored several research papers published in highly-ranked journals including Elsevier’s ASOC, APM, EAAI, and JMAD as well as IOS-Press’s JIFS. His research interests include the fields of MCDM under risk and uncertainty, fuzzy and interval sets, design optimization, material selection, machine selection, composites, biomedical prostheses, buckling, finite element method, and artificial neural networks.

Azizi Ari Iman
Imanazizi65@gmail.com

I. Azizi-Ari received his BSc in industrial engineering from the Islamic Azad University, South Tehran Branch, Tehran, Iran. Currently, he is a MSc student in industrial engineering at the Islamic Azad University, Science and Research Branch, Tehran, Iran. He has a background in quality management systems, supervising and leading projects in the field of quality assurance and control in companies such as Shatel and National Iranian Gas Company. His current research interests are human resource developments, quality assurance, quality control, and MCDM.

Ijadi Maghsoodi Sasan
Sasansim@yahoo.co.uk

S. Ijadi Maghsoodi is the general-manager and CEO of the Monad Oil F.Z.C in UAE and PAK oil company in Kazakhstan. He earned BSc and MSc degrees in civil and construction engineering from the Swansea University, Wales, UK. He has long experience in managing development projects regarding recycling technologies.

Hafezalkotob Ashkan
a_hafez@azad.ac.ir

As. Hafezalkotob is currently an associate professor at the Industrial Engineering College of South Tehran Branch of Islamic Azad University. He received his BSc degree in industrial engineering in 2004, MSc degree in industrial engineering in 2007, and PhD degree in industrial engineering in 2012 from Iran University of Science and Technology, Tehran, Iran. He has authored papers published in highly-ranked journals including TRE, IJPE, JCLP, ASOC, EAAI, CAIE, APM, AMC, JMAD, IJFS, MPE, JMSY, as well as some other journals and conferences proceedings. His research interests include supply chain management, decision-making techniques, game theory, and mathematical modelling.


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Keywords
waste lubricant oil regenerative technology MCDM FAD Shannon entropy risk factors

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