Cross-Domain Impact Analysis made easy with System Engineering

By Andreas Trautheim-Hofmann

The joint project ImPaKT funded by the German Federal Ministry of Education and Research (BMBF) has come to a successful conclusion after three years. As part of this project, PROSTEP developed and tested a reference process for cross-domain impact analyses and a reference model for linking the required information. The information to be linked was prepared using artificial intelligence (AI).

The technical and financial impact of product changes is often difficult to assess. This is especially true when it comes to complex, mechatronic products whose development involves different domains that are spread across several organizations. The aim of the ImPaKT project was to develop and implement a model-based and AI-supported solution that makes impact analyses simpler and faster.

The ImPaKT project involved the Heinz Nixdorf Institute at Paderborn University as the consortium leader, along with the Institute for Machine Elements and System Development at RWTH Aachen University, the service providers CONTACT Software, Itemis, and PROSTEP, plus several industrial partners. The main task of the industrial partners was to define the requirements from the development processes and to the validate the suitability of the pilot applications using various examples from practice. PROSTEP contributed its many years of expertise in system modeling, the development of reference architectures, data exchange and integration to the project.

One aim and result of the project was also to find a solution approach that is suitable for assessing, for example, the effects of a new requirement or the associated changes if the information is still managed on a document basis and is not linked to each other. Knowledge about object relationships is stored in textual descriptions that cannot be accurately analyzed by machines.

Model-based systems engineering (MBSE) methods were applied and expanded to model the reference architecture. MBSE has advantages in the interdisciplinary development of complex, mechatronic products because a small change to the requirements can sometimes have unexpected effects on function, mechanics, electrics/electronics (E/E), software, or even processes and organizational aspects. For this reason, a tailoring guide has been developed which supports companies with a gradual, practical introduction.

The entire project was geared towards specific application examples from industry partners. It quickly became apparent that the changes extend into the production processes, bringing the cost/benefit question of a change even more to the fore. In impact analyses, it is important to find out as quickly as possible where the greatest risks and costs of a change are lying.

The ImPaKT reference architecture for impact analyses consists of two levels. One level is the impact analysis process, i.e. the consideration of the IT systems that carry out this process. We have developed a coordinated process model for this. The second level is the reference model of the so-called parameter space (PARS) to be analyzed with this process. It is the blueprint or template for how information is related.

The reference model is described in the MBSE modeling language SysML. It is based on the requirements and experience of the project partners as well as the long-term sustainable concepts and flexible structures of the standardized STEP data models. However, this information model contains the essential know-how about the interdisciplinary networking of requirements, functions, logic or solutions, components, documents, models, and process artifacts in a much more condensed form. It is a generic model in that it is not limited to mechanical engineering but can map all types of products consisting of mechanics, E/E, software, and services.

In contrast to existing approaches, only the information relevant for impact analyses is made available as a linked data structure in one or several cascaded parameter spaces, which ensures good performance even in the most complex environments. Much of this information is already stored digitally, but it must first be made available across departments and systems, i.e. integrated and linked in an MBSE architecture. As mentioned above, a lot of information is still stored in documents or distributed across different authoring and management systems.

One of the AI use cases that promised particularly high potential and which PROSTEP developed further is the preparation of information for complex impact analyses. We ran through this using the example of Excel lists with hundreds of requirements described in text form. These texts were analyzed using NLP (Natural Language Processing) methods to identify similarities and correlations and convert them into a MBSE-compliant requirements model. It can then be made available in the parameter space and, if required, linked to component information, function, and product structures and/or test activities and their results.

The transformation of the requirements list into a structured model did not work automatically. The AI made suggestions for possible correlations based on the determined weightings, which were then evaluated by experts, resulting in a very high-quality requirements model..

With the whole supply chain in mind, the project partners have made the solution flexible and modular. As a result, the companies do not have to model their products completely with MBSE methods but can fill the parameter space with content bit by bit, e.g. by extracting and linking the essential information from the product structure and documents in the first step. They can then use AI, for example, to build a requirements model and link it to the existing structures and nodes, and so on.

The reference model for the parameter space is one of the key results of the project. PROSTEP has continuously validated, adapted, and expanded it together with the partners based on their practical application examples. In addition, we validated the model with our Mars Rover testbed and then imported it into OpenCLM so that we can fill the template with the know-how from the connected data pots or link to them. This iterative process has enabled the model to achieve a high level of maturity in terms of completeness, semantic precision, and flexibility.

The reference architecture and models for impact analyses can be used by companies of all sizes in almost all industries as blueprints for their MBSE landscape. Companies can gradually develop their company-specific parameter space as a knowledge base for impact analyses. “According to initial estimates, this can save up to 80% of resources and time when carrying out impact analyses for changes or new developments”, says Dr. Martin Holland, Director Strategy & Business Development, and continues: “Our digital thread solution OpenCLM enables companies to analyze cross-domain dependencies between artefacts in different source systems and assess the impact of changes on affected artefacts, for example. On this basis, companies can make more informed decisions.”

For detailed information on the project results and the reference architecture please feel free to contact me directly: andreas.trautheim@prostep.com

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