The Digital Thread Framework for Implementing Intelligent Machining Applications

Abstract

The digital transformation of manufacturing industry has led to vast amounts of data, making effective data utilization and analysis crucial for gaining a competitive advantage. However, the diverse formats and complex structures of manufacturing data pose significant challenges to data integration and interoperability. This paper presents a digital thread framework for intelligent machining applications based on a common process planning data model derived from the ISO 14649 standard. The framework integrates various data used in the process planning stage and enables contextual connection of data generated at each stage of the machining process, including virtual machining, machining monitoring, and geometric dimensioning and tolerancing (GD&T). The common data model is constructed by parsing the EXPRESS data model from ISO 14649-1/11 into an OpenAPI Specification JSON format and generating classes in individual programming languages. The digital thread focuses on connecting and restoring the context of operation data, extending the ISO 14649 data model to incorporate tool and equipment information for various applications. The monitoring data is synchronized with the virtual machining data, and the monitoring reference information is mapped to the digital thread project data. The effectiveness of the proposed framework is demonstrated through a reference chattering application, which utilizes parameters from the stability lobe diagram (SLD), machine tool, and virtual machining data. The framework facilitates data analysis and utilization by contextually connecting data generated at each stage of the machining process, ultimately supporting the development of intelligent applications based on monitoring data.