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Advances in manufacturing systems include attempts to create collaborative networks for enterprise integration and information interoperability. To achieve collaboration and sharing effectively, various networking technologies have been proposed in the literature. The web has emerged as a basic entity for interconnecting man and machine and almost all parts of the enterprise community are being reshaped to exploit the opportunities that it offers. Apart from web technology, there are various other tools and techniques that have attracted research communities for representing data in ways that both machines and humans can understand. Semantic web, the second-generation web technology, is enriched by machine-processable information to support the users in their tasks. This paper presents the vision of the semantic web and describes ontologies and associated metadata as the building blocks of the semantic web. It reviews the literature dealing with the application of the semantic web and ontology in the broad domain of manufacturing. First, brief details about key enablers, i.e. web services, semantic web, semantic services, and ontology, are presented. Then the implementation of these approaches in different sectors of manufacturing is discussed. A knowledge base for all the information resources concerned with the manufacturing domain is also built up in this paper. An ontology model for a knowledge base of information resources is designed in Prot eg e software, which can be used for storing and searching information about authors, journals, blogs, newspapers, and many other sources of information.

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Modelling and analysis of complex and co-ordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain. © 2011 Taylor & Francis

Corporate memory is the total body of data, information and knowledge required to deliver the strategic aims and objectives of an organization. In the current market, the rapidly increasing volume of unstructured documents in the enterprises has brought the challenge of building an autonomic framework to acquire, represent, learn and maintain corporate memory, and efficiently reason from it to aid in knowledge discovery and reuse. The concept of semantic web is being introduced in the enterprises to structure information in a machine readable way and enhance the understandability of the disparate information. Due to the continual popularity of the semantic web, this paper develops a framework for corporate memory management on the semantic web. The proposed approach gleans information from the documents, converts into a semantic web resource using RDF and RDF Schema and then identifies relations among them using Latent Semantic Analysis (LSA) technique. The efficacy of the proposed approach is demonstrated through empirical experiments conducted on two case studies.