Systems Engineering Process Enhancement: Requirements Verification Methodology using Natural Language Processing (NLP) for Automotive Industry

2023-36-0117

01/08/2024

Features
Event
SAE Brasil 2023 Congress
Authors Abstract
Content
More sophisticated vehicle features to improve user experience and safety in the Automotive Industry applications have significantly increased the number of Electronic Control Units (ECUs) over the years. These changes were followed by the increased complexity in technical solutions for Embedded Software and interfaces among the ECUs. In this context, Systems Engineering (SE) plays a key role to achieve robustness on definition and implementation of complex systems.
The overall system is broken down into lower functions associated to a specific use case, considering user’s input and the expected outputs, in three different abstraction levels – Concept, Logic and Technology. Those functions are described with structure and behavior diagrams and requirements using SysML (Systems Modelling Language), which enables the entire system simulation and validation before being cascaded to ECUs Software implementation team during the Product Development process through Model-Based Systems Engineering (MBSE) tools.
On this scope, the requirements have a vital role inside Systems Engineering methodology because it is the statement which defines the system required functionalities, performance, constraints, and other characteristics that satisfy stakeholders and costumers needs. The SysML diagrams are built based on the defined system requirements and many times this is a very iterative process, time-consuming and error-prone task until satisfying every required function logic and conditions. When the requirements are poorly defined, these can lead to project failure. Therefore, requirements must be unambiguous, verifiable, and traceable through Systems Engineering lifecycle. By using Easy Approach to Requirements Syntax (EARS) template, Systems Engineers have specific words to standardize the requirements, accomplishing with EARS requests such as “When,” “While,” “Where,” “If” to mention the stimulus or pre-conditions, “Then” to call the function/product and “shall” representing the action to be taken. In addition, by using the rules proposed by the International Council on Systems Engineering (INCOSE), Systems Engineers can improve the robustness of the requirement by avoiding, for example, words that may be misinterpreted during the system modeling and development process. In this context, Natural Language Processing (NLP) can be used to improve process flow by automating requirement verification. NLP techniques will be responsible for mapping and processing the text data in the system requirements based on actions, preconditions, functions, and triggers to improve the quality and robustness of the developed requirements.
By Applying NLP algorithms, this paper aims to consolidate a more robust methodology to verify the system requirements, based on EARS template and INCOSE rules, prior to SysML diagrams development, which improves the final overall system implementation to satisfy the stakeholders and customer needs.
Meta TagsDetails
DOI
https://doi.org/10.4271/2023-36-0117
Pages
12
Citation
Júnior, F., Reis, P., Cavalcante, M., and de Oliveira, A., "Systems Engineering Process Enhancement: Requirements Verification Methodology using Natural Language Processing (NLP) for Automotive Industry," SAE Technical Paper 2023-36-0117, 2024, https://doi.org/10.4271/2023-36-0117.
Additional Details
Publisher
Published
Jan 08
Product Code
2023-36-0117
Content Type
Technical Paper
Language
English