This article investigates how graph matching can be applied to process plant design data in order to support the reuse of previous designs. A literature review of existing graph matching algorithms is performed, and a group of algorithms is chosen for further testing. A use case from early phase plant design is presented. A methodology for addressing the use case is proposed, including graph simplification algorithms and node similarity measures, so that existing graph matching algorithms can be applied in the process plant domain. The proposed methodology is evaluated empirically on an industrial case consisting of design data from several pulp and paper plants.
The benefits of the use of modeling and simulation in engineering are acknowledged widely. It has proven its advantages e.g., in virtual prototyping i.e., simulation aided design and testing as well as in training and R&D. It is recognized to be a tool for modern decision making. However, there are still reasons that slow down the wider utilization of modeling and simulation in companies. Modeling and simulation tools are separate and are not an integrated part of the other engineering information management in the company networks. They do not integrate well enough into the used CAD, PLM/PDM and control systems. The co-use of the simulation tools themselves is poor and the whole modeling process is considered often to be too laborious. In this article we introduce an integration solution for modeling and simulation based on the semantic data modeling approach. Semantic data modeling and ontology mapping techniques have been used in database system integration, but the novelty of this work is in utilizing these techniques in the domain of modeling and simulation. The benefits and drawbacks of the chosen approach are discussed. Furthermore, we describe real industrial project cases where this new approach has been applied.
Private, public, and not-for-profit organizations come together in cross-sector alliance projects and programmes (CSA) to bring about large-scale changes. CSA can often face determined competition from other alliances that oppose large-scale change or propose alterative large-scale changes. Competition can be related to people's deeply held beliefs arising from their ideologies, cultures, and/or other sources of entrenched preconceptions. In previous CSA research, there has been little consideration of competition between CSA involving people's deeply held beliefs. Accordingly, in this paper, a conceptual framework for better understanding CSA competition is introduced. This encompasses the influence of people's beliefs and related underlying determinants. This is necessary because there are many large-scale challenges that involve private, public, and not-for-profit organizations working together in projects and programmes against competition.
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