Applying graph matching techniques to enhance reuse of plant design information

TL;DR

This paper explores how graph matching algorithms can be adapted and applied to process plant design data to improve the reuse of existing design information, supported by empirical evaluation on industrial data.

Contribution

It proposes a methodology combining graph simplification and node similarity measures for applying graph matching in plant design, validated on real industrial cases.

Findings

Effective graph matching approach for plant design data

Improved reuse of previous plant designs

Validated methodology on industrial pulp and paper plants

Abstract

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.