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Article Citation - WoS: 12Citation - Scopus: 19An Ontology-Based Multi-Agent Virtual Enterprise System (omave): Part 1: Domain Modelling and Rule Management(Taylor & Francis Ltd, 2017) Sadigh, Bahram Lotfi; Unver, Hakki Ozgur; Nikghadam, Shahrzad; Dogdu, Erdogan; Ozbayoglu, A. Murat; Kilic, S. EnginNew advancements in computers and information technologies have yielded novel ideas to create more effective virtual collaboration platforms for multiple enterprises. Virtual enterprise (VE) is a collaboration model between multiple independent business partners in a value chain and is particularly suited to small and medium-sized enterprises (SMEs). The most challenging problem in implementing VE systems is ineffcient and inFLexible data storage and management techniques for VE systems. In this research, an ontology-based multi-agent virtual enterprise (OMAVE) system is proposed to help SMEs shift from the classical trend of manufacturing part pieces to producing high-value-added, high-tech, innovative products. OMAVE targets improvement in the FLexibility of VE business processes in order to enhance integration with available enterprise resource planning (ERP) systems. The architecture of OMAVE supports the requisite FLexibility and enhances the reusability of the data and knowledge created in a VE system. In this article, a detailed description of system features along with the rule-based reasoning and decision support capabilities of OMAVE system are presented. To test and verify the functionality and operation of this system, a sample product was manufactured using OMAVE applications and tools with the contribution of three SMEs.Article Citation - WoS: 37Citation - Scopus: 43Slot milling of titanium alloy with hexagonal boron nitride and minimum quantity lubrication and multi-objective process optimization for energy efficiency(Elsevier Sci Ltd, 2020) Osman, Khaled Ali; Yilmaz, Volkan; Unver, Hakki Ozgur; Seker, Ulvi; Kilic, Sadik EnginThe implementation of sustainable manufacturing techniques to make machining processes more eco-friendly is a challenging topic that has attracted significant attention from the industrial sector for many years. As one of the dominant manufacturing processes, machining can have a considerable impact in terms of ecology, society, and economics. In certain areas, this impact is a result of using certain cutting fluids, especially during the machining of difficult-to-cut alloys such as titanium, where a large amount of cutting fluid is wasted to ease the cutting process. In such scenarios, identifying suitable machining conditions to supply cutting fluids using eco-friendly techniques is currently a major focus of academic and industrial sector research. In this study, effects of minimum quantity lubrication with different concentrations of hexagonal boron nitride nanoparticles on the surface roughness and cutting force of slot-milled titanium alloy is investigated using analysis of variance and response surface methodology. The results reveal that all responses are sensitive to changes in the feed per tooth, cutting depth, and cutting fluid flow rate. The regression functions generated were combined with particle swarm optimization in order to improve energy-efficiency, as well. Possible sectorial scenarios were generated for wider industrial adoption. With this study, it was proven that utilizing minimum quantity lubrication with hexagonal boron nitride nanoparticles can reduce both cutting force and surface roughness, which makes it to be a promising alternative as a nanoparticle augmented minimum quantity lubrication method for machining titanium alloys. (C) 2020 Elsevier Ltd. All rights reserved.Article Citation - WoS: 19Citation - Scopus: 20A Framework for Energy Reduction in Manufacturing Process Chains (e-Mpc) and a Case Study From the Turkish Household Appliance Industry(Elsevier Sci Ltd, 2016) Uluer, Muhtar Ural; Unver, Hakki Ozgur; Gok, Gozde; Fescioglu-Unver, Nilgun; Kilic, Sadik EnginEnergy is a major input in the manufacturing sector. Its security and efficiency are of supreme importance to a nation's industrial activities. Energy consumption also has serious environmental impacts in terms of Greenhouse Gas (GHG) emissions. In order to use energy more efficiently, simply designing parts and planning manufacturing processes with an energy-aware mindset is insufficient; it is also necessary to model and assess the energy efficiency of a process chain from a holistic point of view. In this work, we propose an integrated energy reduction framework and the internal methods to implement it. Our framework builds on three pillars. Creating an energy profile of a process chain is the first step in characterizing a manufacturing system in terms of energy demand. Energy-aware part designs and process plans are based on ISO/STEP 10303 AP224 standards in order to estimate the embodied energy of a mechanical part. Finally, using discrete event simulation methods, the energy consumption of a process chain is assessed and reduction scenarios are generated based on design or operational alternatives. A data collection and analytics system visualizing measures and key performance indicators (KPIs) also must be implemented in order to measure real consumption values and track improvement results over time. The energy reduction in manufacturing process chains (E-MPC) framework is unique in that it provides a structured method which enables the embodied energy of a part to be estimated during early design stages and further enables the evaluation of design impacts on process chains, thereby recognizing the dynamic nature of systems. A pilot case study of the framework was implemented at the largest household appliance manufacturer in Turkey, Arcelik A.S. In order to evaluate its usefulness and validity, we performed a detailed implementation on a fully automated crankshaft manufacturing line in Arcelilc's refrigerator compressor plant. The results reveal that design improvements estimated gains would reach 2%, whereas operational improvements yield up to 10% energy savings per produced part. (C) 2015 Elsevier Ltd. All rights reserved.Article Citation - WoS: 7Citation - Scopus: 12An Ontology-Based Multi-Agent Virtual Enterprise System (omave): Part 2: Partner Selection(Taylor & Francis Ltd, 2017) Sadigh, Bahram Lotfi; Nikghadam, Shahrzad; Ozbayoglu, A. Murat; Unver, Hakki Ozgur; Dogdu, Erdogan; Kilic, S. EnginA virtual enterprise (VE) is a collaboration model between multiple business partners in a value chain. The VE model is particularly feasible and appropriate for small- and medium-sized enterprises (SMEs) and industrial parks containing multiple SMEs that have different vertical competencies. The VE consortium's success highly depends on its members. Therefore, it is crucial to select the most appropriate enterprises when forming a VE consortium. In this study, a new multi-agent hybrid partner selection algorithm is developed for application in the development of an ontology-based multi-agent virtual enterprise (OMAVE) system. In this platform, the agent's interactions are supported by agent ontology, which provides concepts, properties and all message formats for the agents. Different types of agents collaborate and compete with each other so that unqualified or inefficient enterprises are eliminated from the enterprise pool. Only the remaining enterprises would be allowed to enter the negotiation process and propose in the bidding. The agent-based auctioning platform is coupled with a fuzzy-AHP-TOPSIS algorithm to evaluate partners based on their proposals and background. Accordingly, the winning enterprise for each task is identified and the whole project can be accomplished by assigning tasks to the responsible partners. To test and verify the functionality of the developed OMAVE system, a sample module using OMAVE applications and tools was manufactured. The last section of this paper presents the results of this case study, which validate the applicability of the proposed technique.
