Wingquist Laboratory was a VINN Excellence Centre 2007–2017. This is a description of Stage 4.
Centre research profile for Stage 4 (year 9-10)
During Stage 2, research was organized in five cross-disciplinary projects that evolved in an overlapping way in the end of Stage 2. Therefore, in Stage 3, research in the centre was organized in three broader cross-disciplinary themes. Under each theme a number of topics and research questions were formulated in collaboration with the industrial partners. The change from five narrow projects to three broader themes was a way to open up for wider collaboration, enhance for marketing of the centre and its results and thereby also for implementation of results in new companies and business areas. The theme leaders were all younger researchers with pronounced industrial experience.
The research themes turned out to be most functional. They provided good arenas for collaboration, both internally between the research groups as well as externally with industry and between industrial partners. They served as incubators for new ideas. From a marketing point of view, visualizing the focus of the centre, they were on a good abstraction level. Therefore, the themes were kept for Stage 4.
The research in the themes were conducted based on the idea of formulating and answering a number of research questions. In the same way as earlier, when reaching the end of a period, some research questions may have been answered, some may still be valid and some turned out to be wrongly formulated. Refinement and updates of the research focus and potential research questions for Stage 4 are presented in each theme.
Platform-based Development
Platform-based development and production is a widely adopted strategy for balancing reuse and customization. The aim of the research proposed within this theme was to significantly contribute to a new object oriented approach for platform based development, in line with the German initiative “Industry 4.0”.
Theme Leader
This new approach provide a ground for reuse of assets in all product and production system development phases from early knowledge elicitation to detail system design and preparation for production of variants. This includes development of the platform itself as well as use of the platform to generate configured system variants. Supported activities include synthesis, modeling, configuration, analysis, simulation and optimization.
Examples of research areas in Stage 4:
- Set-based design methods and models for configurable system platforms
- Robust and configurable geometrical platform system interfaces
- Knowledge management
- Configurable integrated product and production platform models
- Production process and system platform integration
This approach builds on systems theory and object orientation, and it is similar to how SW systems are developed and described. The German vision Industry 4.0, has adopted the same basic ideas. This vision foresees that future complex multi-technological systems, as well as their containing sub-systems and parts, need to be designed and described in a way that they can carry all relevant knowledge about themselves across their life cycle.
They should thereby be able to communicate this knowledge to interacting systems, e.g. govern their own production or their use in supply chain development collaboration. Expected results are more effective and efficient ways for the industrial partners to reuse their knowledge about their core technologies, products, production facilities and processes in the realization of future products.
Research questions addressed during Stage 4:
- RQ1: How can stakeholder values and system requirements be mapped in a configurable system platform?
- RQ2: How can large non-geometrical data sets be defined and structured in order to facilitate downstream visualization automation in a platform context?
- RQ3: How can knowledge be evaluated before reuse to minimize risk?
- RQ4: How can lean methods be used to trigger knowledge creation, capture and reuse?
- RQ5: How can knowledge be modeled and maintained for reusability?
- RQ6: How can set-based design principles be applied in pre-embodiment architecture design, embodiment design and detail design of configurable system platforms?
- RQ7: How can product and production system platforms be integrated in a PLM environment with CAX tools in order to enable efficient and effective platform synthesis, analysis, simulation and optimization?
- RQ8: How can the geometry of configurable platform system interfaces be assured and optimized for member variants in a product family?
- RQ9: How can interactions and interfaces between product and production systems be modelled and co-configured?
- RQ10: How can manufacture process (e.g. assembly, spot-welding, welding) models be integrated in system platforms in order to support process configuration, simulation and optimization (cost, performance)?
During Stage 4 we offered free training courses in CCM software for object oriented platform modelling.
Perceived Quality
Customer perception of product quality is a key factor in creating successful products. Perceived Quality (PQ) represents all aspects that create a feeling of good quality of a product. The producer’s ability to predict engineering execution that forms a basis for high PQ is related to both simulation and interpretation.
Important research areas
- Customer demands and requirement for improved PQ
- Simulation and visualization of visual PQ
- Squeek & Rattle (S&R) simulation
The main focus was customer understanding due to similar needs from the industrial partners. This is a very important area of the research, since customer demands diverge between markets and for different segments and products. During several research phases, the base has been established to create a new method to understand the customer value of PQ during all phases of a product development project.
Since PQ became a research theme within the centre, the industrial demands increased rapidly. There is a need to shorten project development time and to dramatically reduce dependency on product verifying test series. This means that both efficiency and virtual capability need to increase. Accordingly, all main enablers stated above need to be improved, regarding time and availability of test series.
Research questions
- RQ1: How can different products on a global market be balanced and executed in order to optimize customer experience regarding Perceived Quality?
- RQ2: How can weight factors based on customer insight be defined and structured in order to summarize Perceived Quality?
- RQ3: How can knowledge be collected and reused in order to simulate and evaluate Perceived Quality in early development phases?
- RQ4: How can simulation results be extracted and incorporated in high-end visualizations for evaluation of Perceived Quality?
- RQ5: How can evaluation of Perceived Quality appearance requirements be automated?
- RQ6: How can virtual environments be configured and evaluation processes be adjusted in order to represent details?
- RQ7: What are the limits for using results from a linear squeak & rattle simulation to assess a non-linear phenomenon?
- RQ8: How can one “worst case” load for S&R simulation be defined?
- RQ9: What is the impact of the temperature on the S&R simulation?
- RQ10: How can the critical S&R interface be identified in an efficient way?