Yazar "Kazancoglu, Y." seçeneğine göre listele

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    Investigating barriers to circular supply chain in the textile industry from Stakeholders’ perspective
    (Taylor and Francis Ltd., 2020) Kazancoglu, I.; Kazancoglu, Y.; Kahraman, A.; Yarimoglu, E.; Soni, G.
    The objectives of this study are to understand the circular supply chain barriers for textile companies to implement the circular economy. Main contributions of the study were to propose a specific framework that reveals circular supply chain barriers in transition to circular economy with holistic view by encompassing all stakeholders, to reveal causal relationships among the circular supply chain barriers within textile industry. Causal relationships between the proposed circular supply chain barriers were identified by Fuzzy-Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The barriers are classified under cause and effect groups and related implications are proposed. The findings of this study are lack of collecting, sorting and recycling, reluctance for acceptance of CE model, and problems related to uniformity and standardisation are revealed as the most important barriers, respectively. Moreover, lack of technical knowledge is the most influencing factor, whereas, challenges in product design is the most influenced factor. © 2020 Informa UK Limited, trading as Taylor & Francis Group.
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    Scheduling jobs through multiple parallel channels using an expert system
    (Taylor & Francis Ltd, 2007) Soyuer, H.; Kocamaz, M.; Kazancoglu, Y.
    In recent years, as a result of global competition, the efficiency and effectiveness of business processes are becoming much more critical than ever. Information technology constitutes a critical role as a strategic competitive tool in the global business market. In the previous paradigm, the holistic view was missing and ultimately did not contain real life constraints. The new paradigm is based on the systems approach and represents the real life circumstances of production with applicable and sufficient models. This study is based on an expert system for the scheduling of a manufacturing system. The expert system works with a unique algorithm, which has been developed in this paper. The aim is to develop an expert scheduling system which is realistic and applicable to real life situations. Job specification, machine competence, due date, earliest completion and minimum set up time are the factors which have been taken into account to achieve this aim. As a result, the algorithm achieves both applicability and optimality in solution.