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Author: Unver, Hakki OzgurScopus Q: Q2

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    Review
    Citation - WoS: 58
    Citation - Scopus: 65
    Application of Minimum Quantity Lubrication Techniques in Machining Process of Titanium Alloy for Sustainability: a Review
    (Springer London Ltd, 2019) Osman, Khaled Ali; Unver, Hakki Ozgur; Seker, Ulvi
    Recently, the manufacturing sector is increasingly keen to apply sustainability at all levels of sustainability from system to products and processes. At the processes level, cutting fluids (CFs) are among the most unsustainable materials and need to be addressed properly in accordance with three main and decisive aspects, also known as the triple bottom line: ecology, society, and economics. Minimum quantity lubrication (MQL) is a promising technique that minimizes the use of CFs, thus improving sustainability. This paper presents a review of the literature available on the use of the MQL technique during different machining processes involving titanium alloys (Ti-6Al-4V). To carry out the study, four search engines were used to focus on the most cited articles published over a span of 17years from 2000 to 2016. The performance and drawbacks are compiled for each eco-friendly technique: dry, MQL, and cryogenics with combinations of MQL and cryogenics, critically considering machining parameters such as cutting speed, feed rate, and output measures, namely surface roughness, tool life, and cutting temperature. After drawing conclusions from critical evaluation of research body, future research avenues in the field are proposed for the academics and industry.
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    Conference Object
    Citation - WoS: 5
    Citation - Scopus: 10
    Design of a Customer's Type Based Algorithm for Partner Selection Problem of Virtual Enterprise
    (Elsevier Science Bv, 2016) Nikghadam, Shahrzad; Ozbayoglu, Ahmet Murat; Unver, Hakki Ozgur; Kilic, Sadik Engin
    Virtual Enterprise (VE) is a temporary platform for individual enterprises to collaborate with each other, sharing their core competencies to fulfill a customer demand. In order to improve the customer satisfaction, the most successful VEs select their consortium's members based on customer's preferences. There is quite extensive literature in the field of partner selection in VE, each proposing a new approach to evaluate and select the most appropriate partners among pool of enterprises. However, none of the studies in literature recommend which partner selection methodology should be used in each project with a particular customer attitude. In this study an algorithm is proposed which classifies the customers into three categories; passive, standard and assertive. Three different approaches; Fuzzy Logic-FAHP TOPSIS and Goal programming are used for each customer type respectively. This classification is beneficial since the problem's characteristics; such as vagueness of data, change as the customer's attitude varies. The results certify that, adopting this algorithm not only helps the VE to select the most appropriate partners based on customer preferences, but also the model adapts itself to each customer's attitude. As a result, the overall system flexibility is significantly improved. (C) 2016 The Authors. Published by Elsevier B.V.
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    Article
    Citation - WoS: 15
    Citation - Scopus: 20
    A Survey of Partner Selection Methodologies for Virtual Enterprises and Development of a Goal Programming-Based Approach
    (Springer London Ltd, 2016) Nikghadam, Shahrzad; Sadigh, Bahram Lotfi; Ozbayoglu, Ahmet Murat; Unver, Hakki Ozgur; Kilic, Sadik Engin
    A virtual enterprise (VE) is a platform that enables dynamic collaboration among manufacturers and service providers with complementary capabilities in order to enhance their market competitiveness. The performance of a VE as a system depends highly on the performance of its partner enterprises. Hence, choosing an appropriate methodology for evaluating and selecting partners is a crucial step toward creating a successful VE. In this paper, we begin by presenting an extensive review of articles that address the VE partner selection problem. To fill a significant research gap, we develop a new goal programming (GP)-based approach that can be applied in extreme bidding conditions such as tight delivery timelines for large demand volumes. In this technique, fuzzy analytic hierarchy process (F-AHP) is used to determine customer preferences for four main criteria: proposed unit price, on-time delivery reliability, enterprises' past performance, and service quality. These weights are then incorporated into the GP model to evaluate bidders based on customers' preferences and goals. We present a case study in which we implement the F-AHP-GP technique and verify the model's applicability, as it provides a more flexible platform for matching customers' preferences.