Ontoloji tabanlı çok-etmenli sanal fabrika sisteminin tasarımı ve geliştirilmesi.

Major developments in computers and information technologies, enable industrial and mechanical engineers to establish new net based, virtual collaboration platforms for enterprises. Benefiting from virtual enterprise platform enterprises will be able to combine their resources and capabilities on project based collaborations meanwhile protect their independent mainstream policies and secure their secret information. This concept is called virtual enterprise(VE). 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 Enterprises (SME) and industry parks containing multiple SMEs that have different vertical competencies. One of the main targets of this research is to create an Ontology based Multi Agent Virtual Enterprise (OMAVE) System to prepare an appropriate platform for collaboration between technology start-ups in techno-parks and SMEs in Organized Industrial Zones in order to produce high value added high-tech products. OMAVE aims to help SMEs to shift from classic trend of manufacturing part pieces towards high-tech, innovative and research based products. In this way and to reach this goal a new semantic data infrastructure to enhance Re-Configurability and Flexibility of virtual enterprise systems has been developed. In order to support flexibility in Virtual Enterprise business processes and enhance its integration to enterprises' available manufacturing systems (e.g. MRP) an ontology based domain model of VE system has been established. OWL DL semantic data structure of VE by defining concepts, axioms, rules and functions in VE system has been developed. TDB data store to keep VE data and information in form of triples developed. SPARQL semantic RDF query language is used to handle and manipulate data on developed system data store. This architecture supports structure flexibility for developed VE infrastructure and improve reusability of data and knowledge in VE life cycle. To establish a multi agent based partner selection platform different agent types have been developed. These agents collaborate and compete with each other to select the most appropriate partner for the forthcoming VE project consortium. The agent based auctioning platform is coupled with a Fuzzy-AHP-TOPSIS multi criteria decision making algorithm to evaluate incoming bids from agents and rank proposals in each iteration. It is also important to notice that here, agents interaction's semantic is provided by an agent ontology. This agent ontology provides concepts, properties and all message formats for agents to settle a common language in interactions between agents. Implementing concurrent engineering, collaborative design and Product Life Cycle Management (PLM) concepts by integrating Dassault systems web based CATIA/ENOVIA V6 design and PLM tools to OMAVE system. To test and verify these achievements a case study to produce a test product by using developed OMAVE tools is established. This test product manufactured by contributions of SMEs from OSTIM organized Industrial Zone Aviation and Defense Cluster.Ph.D. - Doctoral Progra

Value-driven partner search for <i>Energy from Waste</i> projects

Energy from Waste (EfW) projects require complex value chains to operate effectively. To identify business partners, plant operators need to network with organisations whose strategic objectives are aligned with their own. Supplier organisations need to work out where they fit in the value chain. Our aim is to support people in identifying potential business partners, based on their organisation’s interpretation of value. Value for an organisation should reflect its strategy and may be interpreted using key priorities and KPIs (key performance indicators). KPIs may comprise any or all of knowledge, operational, economic, social and convenience indicators. This paper presents an ontology for modelling and prioritising connections within the business environment, and in the process provides means for defining value and mapping these to corresponding KPIs. The ontology is used to guide the design of a visual representation of the environment to aid partner search

Tools for enterprises collaboration in virtual enterprises

Virtual Enterprise (VE) is an organizational collaboration concept which provides a competitive edge in the globalized business environment. The life cycle of a VE consists of four stages i.e. opportunity identification (Pre-Creation), partner selection (Creation), operation and dissolution. The success of VEs depends upon the efficient execution of their VE-lifecycles along with knowledge enhancement for the partner enterprises to facilitate the future formation of efficient VEs. This research aims to study the different issues which occur in the VE lifecycle and provides a platform for the formation of high performance enterprises and VEs. In the pre-creation stage, enterprises look for suitable partners to create their VE and to exploit a market opportunity. This phase requires explicit and implicit information extraction from enterprise data bases (ECOS-ontology) for the identification of suitable partners. A description logic (DL) based query system is developed to extract explicit and implicit information and to identify potential partners for the creation of the VE. In the creation phase, the identified partners are analysed using different risks paradigms and a cooperative game theoretic approach is used to develop a revenue sharing mechanism based on enterprises inputs and risk minimization for optimal partner selection. In the operation phases, interoperability remains a key issue for seamless transfer of knowledge information and data. DL-based ontology mapping is applied in this research to provide interoperability in the VE between enterprises with different domains of expertise. In the dissolution stage, knowledge acquired in the VE lifecycle needs to be disseminated among the enterprises to enhance their competitiveness. A DL-based ontology merging approach is provided to accommodate new knowledge with existing data bases with logical consistency. Finally, the proposed methodologies are validated using the case study. The results obtained in the case study illustrate the applicability and effectiveness of proposed methodologies in each stage of the VE life cycle

A Novel Partner Selection Method in Virtual Enterprise Based on the Ontology and SOA and AHPmodel

Partner selection is a key problem in virtual enterprise. This paper researches on selecting the dynamic, Competitive and compatible partners, which is the key link in the establishment of virtual enterprise. this paper presented a method have two main steps , first step is detecting candidate partner using semantic concept and second step is selecting proper partner using competency and quality of service in AHP method . The advantage of this method scrutiny of partner selection problem , and partner selection in this method occur dynamic and automation

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Role of Semantic web in the changing context of Enterprise Collaboration

In order to compete with the global giants, enterprises are concentrating on their core competencies and collaborating with organizations that compliment their skills and core activities. The current trend is to develop temporary alliances of independent enterprises, in which companies can come together to share skills, core competencies and resources. However, knowledge sharing and communication among multidiscipline companies is a complex and challenging problem. In a collaborative environment, the meaning of knowledge is drastically affected by the context in which it is viewed and interpreted; thus necessitating the treatment of structure as well as semantics of the data stored in enterprise repositories. Keeping the present market and technological scenario in mind, this research aims to propose tools and techniques that can enable companies to assimilate distributed information resources and achieve their business goals

Interpretive structural modelling of risk sources in a virtual organisation

International audienceSpeedier network decision making together with shorter time to bring items to market together with lower network operating costs all result from enhanced knowledge sharing. In addition re-use of enterprise and network knowledge resulting from improved capture means that any risk of repeating earlier project work is limited, repetition of past mistakes is reduced. Decisions are made with greater awareness of any risks involved and therefore there is likely to be a reduction in costs arising from faulty decisions and failed collaborations. While there are many advantages attaching to the use of virtual organizations (VOs) there are also challenges, including risks that have become apparent through undertaking a review of the literature. In total 13 sources of risk were found stemming from the network related risks in a VO, where the emphasis of the study was placed,. This paper contains a thorough study that will identify these threats as well as gaining a sound understanding of them by examining them one by one as they have been identified by the literature and previous studies. Subsequently, their relative importance will be analysed through the use of Structural Modeling (ISM) using information gathered in a questionnaire