Browsing by Author "Sadigh, Bahram Lotfi"
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Article Citation Count: 6Cutting force prediction in ultrasonic-assisted milling of Ti-6Al-4V with different machining conditions using artificial neural network(Cambridge Univ Press, 2021) Namlu, Ramazan Hakkı; Turhan, Cihan; Turhan, Cihan; Kilic, S. Engin; Lotfısadıgh, Bahram; Kılıç, Sadık Engin; Energy Systems Engineering; Mechanical Engineering; Manufacturing EngineeringTi-6Al-4V alloy has superior material properties such as high strength-to-weight ratio, good corrosion resistance, and excellent fracture toughness. Therefore, it is widely used in aerospace, medical, and automotive industries where machining is an essential process for these industries. However, machining of Ti-6Al-4V is a material with extremely low machinability characteristics; thus, conventional machining methods are not appropriate to machine such materials. Ultrasonic-assisted machining (UAM) is a novel hybrid machining method which has numerous advantages over conventional machining processes. In addition, minimum quantity lubrication (MQL) is an alternative type of metal cutting fluid application that is being used instead of conventional lubrication in machining. One of the parameters which could be used to measure the performance of the machining process is the amount of cutting force. Nevertheless, there is a number of limited studies to compare the changes in cutting forces by using UAM and MQL together which are time-consuming and not cost-effective. Artificial neural network (ANN) is an alternative method that may eliminate the limitations mentioned above by estimating the outputs with the limited number of data. In this study, a model was developed and coded in Python programming environment in order to predict cutting forces using ANN. The results showed that experimental cutting forces were estimated with a successful prediction rate of 0.99 with mean absolute percentage error and mean squared error of 1.85% and 13.1, respectively. Moreover, considering too limited experimental data, ANN provided acceptable results in a cost- and time-effective way.Article Citation Count: 10An experimental investigation on the effects of combined application of ultrasonic assisted milling (UAM) and minimum quantity lubrication (MQL) on cutting forces and surface roughness of Ti-6AL-4V(Taylor & Francis inc, 2021) Namlu, Ramazan Hakkı; Kılıç, Sadık Engin; Kilic, Sadik Engin; Lotfısadıgh, Bahram; Mechanical Engineering; Manufacturing EngineeringTi-6Al-4V is widely used in aerospace, medical and defense industries where materials with superior characteristics are needed. However, Ti-6Al-4V is categorized as a difficult-to-cut material, and machining of this alloy is highly challenging. Ultrasonic Assisted Milling (UAM) is a quite recent method to facilitate the machining of difficult-to-cut materials. This method has numerous advantages over the Conventional Milling (CM) method, such as reduced cutting forces and increased surface quality. Besides, Minimum Quantity Lubrication (MQL) is an alternative cooling method to enhance the process efficiency with respect to conventional cooling methods. Cutting force and surface roughness are essential measures to evaluate the cutting performance of a machining process. However, the simultaneous effects of implementing MQL and ultrasonic vibrations in milling operations are not much researched yet. In this study, the combined effects of UAM and MQL on cutting forces and surface roughness during the machining of Ti-6AL-4V are investigated. Results show that the combination of MQL and UAM enhances the cutting forces in rough cutting operations and the surface roughness in both finish and rough cutting operations significantly compared to conventional processes. Consequently, it is concluded that simultaneous implementation of UAM and MQL enhances overall cutting performance in end-milling operation of Ti-6Al-4V.Article Citation Count: 8An ontology-based multi-agent virtual enterprise system (OMAVE): part 1: domain modelling and rule management(Taylor & Francis Ltd, 2017) Lotfısadıgh, Bahram; Unver, Hakki Ozgur; Kılıç, Sadık Engin; Dogdu, Erdogan; Ozbayoglu, A. Murat; Kilic, S. Engin; Manufacturing EngineeringNew 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 Count: 8An ontology-based multi-agent virtual enterprise system (OMAVE): part 2: partner selection(Taylor & Francis Ltd, 2017) Lotfısadıgh, Bahram; Nikghadam, Shahrzad; Kılıç, Sadık Engin; Unver, Hakki Ozgur; Dogdu, Erdogan; Kilic, S. Engin; Manufacturing EngineeringA 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.Article Citation Count: 17A survey of partner selection methodologies for virtual enterprises and development of a goal programming-based approach(Springer London Ltd, 2016) Kılıç, Sadık Engin; Sadigh, Bahram Lotfi; Lotfısadıgh, Bahram; Unver, Hakki Ozgur; Kilic, Sadik Engin; Manufacturing EngineeringA 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.