IT²EC 2022 - previous agenda


Creating a Digital Thread with Competencies

09 September 2021
Technologies and Architectures

“Model Based Product Support” (MBPS) is a logistics informatics approach to transforming supply and maintenance practices that requires a product's components, structure, description, parts, and maintenance tasks to be represented as digital data. This presents significant opportunities for improving training and performance. Specifically, (1) using digital representations to develop and manage technical training can reduce the time it takes to propagate engineering changes through training programs; (2) linking training to authoritative system data reduces the risk of disconnects between training and operations; and (3) tying performance back to training can help prevent major accidents by identifying missing competencies before they cause serious problems.

These benefits motivated a US Navy effort called “Acquisition Requirements for Training Transformation” (ARTT) that is prototyping the ability to create a “digital thread” linking product specifications, training development, and shipboard performance. The data carried along this thread is expressed in terms of competencies (knowledge, skills, and abilities) required for maintenance tasks. In the ARTT vision, competencies are extracted from standardized product data and fed forward into tools used for training analysis, design, and development. When changes are made in the product specification, they create alerts that cause training to be updated. Meanwhile, data from maintenance logs is tied back to the competencies addressed in training and used to indicate which competencies have or have not been successfully trained. This informs the nature and frequency of the training and supports a machine-aided change management process.

Technical Approach and Innovations

Three ingredients combine to create the “digital thread” and to enable the successful execution of a project that involves multiple collaborations and that relies on technologies that are being developed in parallel. The first ingredient is the competency and skills system (CaSS). CaSS is an open source DoD system that (a) enables competencies to be managed and maintained as shareable linked open data, and (b) can collect performance data from systems using mechanisms such as the experience API (xAPI). CaSS enables product data, training, and performance to be expressed and exchanged in a common language. The second ingredient is the development of a new standard, S6000T, that incorporates training analysis into data models for product definition and maintenance. This standard is providing a common data model and guiding OEM-generated documentation so that the needed data on maintenance tasks comes as part of an acquisition. The third ingredient is AI, in the form of Natural Language Processing (NLP) and Machine Learning. AI is used to write competencies based on task data and training analysis. Eventually, AI will be used to analyze performance data and provide feedback concerning training effectiveness and optimal training frequency and, beyond that, to optimize staffing and create personalized training programs.


Paper/Presentation Content

This paper details our technical approach, describes a current implementation with the U.S. Navy, and showcases the feasibility and benefits of blending model-based product support with a competency-based “digital thread”. It concludes with a discussion of broader applications of an AI-powered competency-based approach to semi-automate training design and evaluation.

Sanjay Khetia, Director, Strategic Alliances - PLEXSYS
Robby Robson, CEO - Eduworks Corporation