The emerging technology of 4D printing combines additive manufacturing and active materials under energy stimulation to create objects with shape and/or property-changing capacities. De-signing such structures requires careful consideration of the transformation’s specifications, shape and structure, stimulation strategy, and materials selection, thereby integrating multiple perspectives constraints and knowledge. The long-term objective aims to develop a computational design synthesis for 4D printing framework that comprises generative, evaluation, and recom-mendation procedures. However, these procedures require a suitable information backbone aligned with the involved stakeholders and the design progress. This paper proposes a multi-view and multi-representation system in a computer-aided design (CAD) environment to support di-vergent and convergent creation while ensuring automation and the streamline of design intents. An implementation is made through an add-on into a commercial CAD environment , and a case study is introduced to demonstrate its applicability.

As the need for speed in conception is ever-growing, computer-aided design (CAD) stayed confined in the PLM paradigm, letting only a single user access and modifying a CAD document at a time. To overcome this statement, a new way of CAD emerged: the collaborative CAD. By letting multiple users access the same document simultaneously, task can be parallelized with much more ease. Two main currents exist in collaborative CAD. The first one is synchronous work, where users can work on the same document simultaneously. The second one is asynchronous work, where a document can be opened by different users, and then the work of all users has to be merged at the end. This paper compares the workflow of the PLM approach and the collaborative CAD with a concrete example. Then the capabilities and limitations of the current collaborative CAD solutions are shown and analyzed. Finally, perspectives regarding the in work research is presented.

[Context] At the cusp of Industry 4.0 and against a backdrop of fierce competition, manufacturing companies must design and manufacture increas-ingly complex and cost-effective products. PLM software are now widely used to manage products throughout their lifecycle. The knowledge of de-signers using these softwares is critical and valuable for the company. Human resources must therefore preserve and maintain their knowledge and the intel-lectual heritage of their experts.

[Problem] In the next few years, there will be a lack of skilled resources in the manufacturing industry due to retirements. Let's also mention the turno-ver of consultants working within these companies. It is essential to imple-ment solutions today in order to protect the intellectual heritage of tomorrow. This paper ambition to answer to how can the knowledge of these experts be captured and used, and how knowledge graph could be a suitable tool to achieve this objective.

[Proposal] This article proposes a methodology for implementing KBE (Knowledge Based Engineering) solutions. This methodology called KARMEN (Knowledge Access Request for Manufacturing and Engineering by Network graph) is based on an FBS type ontology (Function, Behavior, Structure) as well as on the exploitation of Knowledge Graphs.

A use case of redesigning a mechanical part for metal additive manufactur-ing will be presented. Besides, an experimental protocol will be specified to capture the knowledge of business experts within a graph-oriented database built on Neo4J.

Finally, it will demonstrate that navigation within a knowledge graph can be a powerful tool for knowledge transfer and support in designing novice profile.