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Now showing 1 - 6 of 6
  • Conference Object
    Citation - WoS: 19
    Citation - Scopus: 23
    An Experimental Study on Surface Quality of Al6061-T6 in Ultrasonic Vibration-Assisted Milling with Minimum Quantity Lubrication
    (Elsevier Science BV, 2022) Namlu, Ramazan Hakki; Yilmaz, Okan Deniz; Lotfisadigh, Bahram; Kilic, S. Engin
    Al6061-T6 is frequently used in the automotive and aerospace industries, where milling is an essential process, due to its high strength-to-weight ratio. In order to achieve improved surface quality in milling, Ultrasonic Vibration-Assisted Milling (UVAM) has been introduced recently. Besides, Minimum Quantity Lubrication (MQL) is another advanced method to enhance the surface properties of the cutting by improving the coolant performance. However, the effects of simultaneous implementation of UVAM and MQL methods has not yet been studied sufficiently. This paper investigates the effects of applying UVAM in tandem with MQL in cutting of Al6061-T6. The results showed that surface quality enhanced with this combination. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
  • Article
    Citation - WoS: 77
    Citation - Scopus: 101
    An Intelligent Process Planning System for Prismatic Parts Using Step Features
    (Springer London Ltd, 2007) Amaitik, Saleh M.; Kilic, S. Engin
    This paper presents an intelligent process planning system using STEP features (ST-FeatCAPP) for prismatic parts. The system maps a STEP AP224 XML data file, without using a complex feature recognition process, and produces the corresponding machining operations to generate the process plan and corresponding STEP-NC in XML format. It carries out several stages of process planning such as operations selection, tool selection, machining parameters determination, machine tools selection and setup planning. A hybrid approach of most recent techniques ( neural networks, fuzzy logic and rule-based) of artificial intelligence is used as the inference engine of the developed system. An object-oriented approach is used in the definition and implementation of the system. An example part is tested and the corresponding process plan is presented to demonstrate and verify the proposed CAPP system. The paper thus suggests a new feature-based intelligent CAPP system for avoiding complex feature recognition and knowledge acquisition problems.
  • Article
    Citation - WoS: 10
    Citation - Scopus: 14
    A Neural Network Model for the Assessment of Partners' Performance in Virtual Enterprises
    (Springer London Ltd, 2007) Sari, Burak; Amaitik, Saleh; Kilic, S. Engin
    In response to increasing international competition, enterprises have been investigating new ways of cooperating with each other to cope with today's unpredictable market behaviour. Advanced developments in information & communication technology (ICT) enabled reliable and fast cooperation to support real-time alliances. In this context, the virtual enterprise (VE) represents an appropriate cooperation alternative and competitive advantage for the enterprises. VE is a temporary network of independent companies or enterprises that can quickly bring together a set of core competencies to take advantage of market opportunity. In this emerging business model of VE, the key to enhancing the quality of decision making in the partner companies' performance evaluation function is to take advantage of the powerful computer-related concepts, tools and technique that have become available in the last few years. This paper attempts to introduce a neural network model, which is able to contribute to the extrapolation of the probable outcomes based on available pattern of events in a virtual enterprise. Quality, delivery and progress were selected as determinant factors effecting the performance assessment. Considering the features of partner performance assessment and neural network models, a back-propagation neural network that includes a two hidden layers was used to evaluate the partner performance.
  • Article
    Citation - WoS: 12
    Citation - Scopus: 19
    An 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. Engin
    New 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: 1
    Citation - Scopus: 1
    EFFECT OF THE MQL TECHNIQUE ON CUTTING FORCE AND SURFACE QUALITY DURING THE SLOT MILLING OF TITANIUM ALLOY
    (inst Za Kovinske Materiale I in Tehnologie, 2022) Osman, Khaled Ali; Yilmaz, Volkan; Unver, Hakki Ozgur; Seker, Ulvi; Kilic, S. Engin
    In this study, the effects of four control parameters, i.e., the cutting speed (v(c)), feed per tooth (f), depth of cut (a(p)), and flow rate of the cutting fluid (Q), on the surface roughness (R-a) and cutting force (F-c) were investigated in the slot milling of titanium alloys (Ti-6A1-4V). The effects of the control parameters were determined by a statistical analysis. In addition, RSM models for R-a and F-c during machining under three cooling/lubrication conditions, i.e., dry, flood, and minimum quantity lubrication (MQL), were obtained. The results revealed that both R-a and F-c are sensitive to changes in f, a(p) and Q. It was found that the MQL condition generates lower values of R-a where the surface roughness value is 0.227 mu m. By contrast. F-c values under the MQL condition were close to those of the flood condition and at times even better. The machining performance at a cutting-fluid flow rate of 36 mL/h under the MQL condition was found to be the best under certain machining conditions. MQL was found to be an effective alternative technique for conventional conditions when machining Ti-6Al-4V.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 12
    An 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. Engin
    A 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.