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Zahid Usman

Researcher at Coventry University

Publications -  25
Citations -  782

Zahid Usman is an academic researcher from Coventry University. The author has contributed to research in topics: Ontology (information science) & Knowledge sharing. The author has an hindex of 10, co-authored 24 publications receiving 559 citations. Previous affiliations of Zahid Usman include Rolls-Royce Holdings & Rolls-Royce Motor Cars.

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Journal ArticleDOI

Cobot programming for collaborative industrial tasks: An overview

TL;DR: An overview of collaborative industrial scenarios and programming requirements for cobots to implement effective collaboration is given, and detailed reviews on cobot programming, which are categorised into communication, optimisation, and learning are conducted.
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A model-driven ontology approach for manufacturing system interoperability and knowledge sharing

TL;DR: This article presents a novel concept, based on the Model Driven Architecture (MDA), implemented under the Interoperable Manufacturing Knowledge Systems (IMKS) project in order to understand the extent to which manufacturing system interoperability can be supported using radically new methods of knowledge sharing.
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CPS data streams analytics based on machine learning for Cloud and Fog computing: a survey

TL;DR: This paper is the first to systematically study machine learning techniques for CPS data stream analytics from various perspectives, especially from a perspective that leads to the discussion and guidance of how the CPS machine learning methods should be deployed in a Cloud and Fog architecture.
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Towards a formal manufacturing reference ontology

TL;DR: The research work reported in this paper contributes to the development of formal reference ontology for manufacturing, which is envisaged as a key component in future interoperable manufacturing systems.
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Towards the ontology-based consolidation of production-centric standards

TL;DR: This article explores the specification of well-defined core concepts that can be used as a basis for capturing tailored semantic definitions and finds that a CL-based method represents a favoured contender for scoped and facts-driven manufacturing applications.