H
Harry Martin
Researcher at Open University
Publications - 18
Citations - 676
Harry Martin is an academic researcher from Open University. The author has contributed to research in topics: Supply chain & Multiple-criteria decision analysis. The author has an hindex of 6, co-authored 15 publications receiving 574 citations. Previous affiliations of Harry Martin include Open University in the Netherlands.
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Development of maintenance function performance measurement framework and indicators
TL;DR: A conceptual framework that provide guidelines for choosing maintenance function performance indicators is proposed and seeks to align maintenance objectives with manufacturing and corporate objectives, and provides a link between the maintenance objectives, maintenance process/efforts and maintenance results.
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The impact of (low) trust on knowledge sharing
TL;DR: The differences in the level of knowledge sharing between co-workers in high versus low trust situations, for cognition- based trust and for affect-based trust as well as implicit and explicit knowledge are examined.
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Empirical analysis of maintenance performance measurement in Belgian industries
TL;DR: In this paper, an industrial survey was carried out to explore the use of performance measurement in maintenance management, and the results showed that maintenance performance measurement is dominated by lagging indicators (equipment, maintenance cost and safety performance).
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Integrating the spare parts supply chain: an inter‐disciplinary account
TL;DR: In this article, the authors argue for the sharing of appropriately balanced combination of quantitative and qualitative information that is currently hidden, or exists in isolation, within supply chains, and argue that such information sharing may potentially generate substantial benefits for all players within a given supply chain.
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Modelling maintenance effects on manufacturing equipment performance: results from simulation analysis
TL;DR: In this paper, an approach of linking maintenance with equipment performance is developed using simulation modelling, which involves defining probabilistic models and assumptions affecting system performance, such as the initial failure rate/intensity of the equipment; the probablity model for the system deterioration and corresponding effect; the Probabilistic model for a random times of corrective maintenance (CM) and preventive maintenance (PM) that takes into the account the types of maintenance plans/policies and the potential dependency between CM and PM times; and the probabilistically model for random effects of the CM and preventive