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Technological advancements have led to the transition of manufacturing industries to Smart Manufacturing and Industry 4.0. Promising concepts such as Digital Twin and Digital Thread could help speed up the transition. One benefit of using digital twins is to enable continuity of lifecycle information. However, currently, most digital-twin implementations focus on modeling a particular lifecycle stage of a physical element in “silos”. This makes companies missing out on up to 65% of possible value of digital twin investments. This also results in it challenging to incorporate diverse data streams from different lifecycle stages. Digital thread has been used to represent information flow along the product lifecycle. Using information across product lifecycle stages will facilitate interoperability and reusability of digital twins. Because data from each lifecycle stage could be accessed and managed systematically, this will ensure the value and the credibility of the digital twin. A lot of confusion still remains in industry about what are digital twin and digital thread as well as their relationships. Using lifecycle data from a digital thread for digital twin implementation is complex because of the heterogeneity of standards and technologies involved. In this paper, we provide definitions of both digital twin and digital thread; we highlight the benefit of using them for interoperability and reusability of a digital twin for product lifecycle management and analysis; we propose a methodology for implementing digital twins using lifecycle data supported by a digital thread. Finally, we showcase the proposed methodology by providing an example of integrating digital twins with a digital thread.

ontostep is a method to translate the STandard for the Exchange of Product Model Data (STEP) schema and its instances to an ontology and knowledge graphs represented in the web ontology language (owl). ontostep models can be integrated with any owl models to enrich their semantics. However, the current implementation has several limitations, mainly in (1) supporting the latest International Organization for Standardization (ISO) 10303 schemas and (2) generating various representation types depending on the purpose of use. We present an improved implementation of ontostep to overcome these limitations. In this article, we demonstrate that the new implementation can successfully translate STEP schemas and instances in a faster and more flexible way, thus furthering the adoption of the full capabilities of ISO 10303. By encoding STEP entities in owl, we facilitate integration with other standards through knowledge graphs.

Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF), has garnered significant attention as it can bring quality information into the digital thread. Implementing more automated methods for product quality assurance is challenging due to the lack of unified information models from design to inspection. To this end, we propose an approach to fuse as-designed data represented in STEP and as-inspected data represented in QIF in a standards-based digital thread based on ontology with knowledge graphs. Specifically, we present an automated pipeline for generating knowledge graphs representing STEP and QIF data, a mapping implementation to integrate STEP and QIF knowledge graphs, and rules and queries to demonstrate the integration’s potential for better decision making with respect to product quality assurance.