Machine-interpretable Engineering Design Standards for Valve Specification

TL;DR

The paper tackles the challenge of converting paper and PDF-based engineering standards into machine-interpretable content to automate valve-design and equipment-selection workflows. It introduces a modular ontological framework aligned with the ISO Industrial Data Ontology (IDO) top level, employing OTTR modelling patterns, OWL representations, and SHACL validation to enable automated reasoning about VDS compliance. Using a valve use case, the authors demonstrate how standard-derived modules (ASME B16.34, API 6D/602, piping and materials ontologies) can instantiate asset models, reason about design-rule conformance, and verify product suitability and completeness. The work highlights provenance tracking, reusability across standards, and practical steps for standards bodies to digitize content, offering a concrete path toward SMART, machine-interpretable standards in high-hazard process industries.

Abstract

Engineering design processes use technical specifications and must comply with standards. Product specifications, product type data sheets, and design standards are still mainly document-centric despite the ambition to digitalize industrial work. In this paper, we demonstrate how to transform information held in engineering design standards into modular, reusable, machine-interpretable ontologies and use the ontologies in quality assurance of the plant design and equipment selection process. We use modelling patterns to create modular ontologies for knowledge captured in the text and in frequently referenced tables in International Standards for piping, material and valve design. These modules are exchangeable, as stored in a W3C compliant format, and interoperable as they are aligned with the top-level ontology ISO DIS 23726-3: Industrial Data Ontology (IDO). We test these ontologies, created based on international material and piping standards and industry norms, on a valve selection process. Valves are instantiated in semantic asset models as individuals along with a semantic representation of the environmental condition at their location on the asset. We create "functional location tags" as OWL individuals that become instances of OWL class Valve Data Sheet (VDS) specified valves. Similarly we create instances of manufacturer product type. Our approach enables automated validation that a specific VDS is compliant with relevant industry standards. Using semantic reasoning and executable design rules, we also determine whether the product type meets the valve specification. Creation of shared, reusable IDO-based modular ontologies for design standards enables semantic reasoning to be applied to equipment selection processes and demonstrates the potential of this approach for Standards Bodies wanting to transition to digitized Smart Standards.

Figures (11)

• Figure 1: Part of ASME B16.34 Table 2-2.2 showing Group 2.2 materials and acceptable pressure and temperature ranges. Reprinted from ASME B16.34 Valves Flanged, Threaded and Welding End, Edition year 2020 by permission of The American Society of Mechanical Engineers. All rights reserved
• Figure 2: Levels in the ISO/IEC SMART standards hierarchy
• Figure 3: Example of a typical valve data sheet for full bore floating ball valve, class rating CL 150, with raised face flange connection and soft seat design showing design data and references to International API, ASME and ASTM standards
• Figure 4: Industrial ontology design pyramid
• Figure 5: Classes and object properties for the BCAS302R Floating Full Bore Valve whose datasheet is shown in Figure \ref{['fig:BCAS302R']}. Colours are used for different ontology classes as follows: green for valve parts and light green for the use case. Black lines with open arrows represent subclass relations and red lines are object properties with labels in grey boxes.