Design Automation Lab

Knowledge Based Engineering (KBE) is a popular method applied to enable design automation of repetitive CAD operations. KBE defines a wide range of methods and processes. We define KBE as:

Automating non-creative design tasks by utilizing object-oriented programming.

At Design Automation Laboratory we have developed a new way to efficiently automate design with geometry primitives called High Level CAD templates (HLCt), namely:

• Generic CAD model can be placed and automatically adapted to various geometrical shapes without needing to manipulate any parameter.
• The method is generic and not specifically designed for 1 or 2 specific CAD tools.
• Designers start from a blank sheet and configure component by component, like a virtual LEGO system. Add new LEGO bricks to your library whenever you want and thus your design options are unlimited.

Multidisciplinary optimization (MDO) is defined by Giesing et al. (1998), as

A method for designing complex technical systems and subsystems that consistently exploits synergies between interrelated phenomena

A classic example with two domains is the strength and aerodynamics of an aircraft wing which, for reasons of strength, should be rough, but slim due to aerodynamics. In practice, however, more disciplines must be taken into account and also more compromises must be handled. MDO today has a relatively small distribution in Swedish industry and is often not really multidisciplinary.

MDO has many advantages, but a practical problem is that MDO is a numerical process with many computationally demanding iterations. To address this, effective methods are being developed within the research group.

Since different subsystems generally have conflicting optimal solutions, a holistic perspective is necessary to achieve an optimal design from a holistic perspective. In addition, there are always several and conflicting requirements for the product, which is why the so-called Multi-objective optimization (MOO) is an attractive way to tackle the problem, as even a large number of so-called Pareto optimal solutions are generated. One way of dealing with conflicting requirements and a changing set of requirements from customers is to simultaneously adopt a development strategy based on modularization and product families.

Complex engineering products are connected to their operational environment as well as with each other, and nowadays, it is often observed that most real-world applications are based on a synergetic approach of several interconnected systems. What is more, complex products can have long development and production times, and thus, a further challenge is to be able to account for uncertainties like the introduction of a new technology or future market changes. Lastly, the envisioned role of a complex product may easily change within its life cycle, and hence, the new operating conditions can lead to an underperforming or even unusable system. By looking a yet-to-be-designed product as part of System of Systems (SoS), the development team can identify critical design factors early in the process where there is still time to make decisions, while overall, designers can also ensure a better performance and a customized product according to a set of customer-specific needs.

Compared to the traditional Systems Engineering (SE) approach where the requirements are fixed, System of Systems Engineering (SoSE) is based on exploring a much larger design space and it is expected to lead to solutions that can provide better resilience to constantly changing requirements. More specifically, the consideration of the system’s participation in a larger ensemble, allows analysts to identify several SoS constellations that can deliver the desired capabilities, and therefore, this makes it possible to relax or even remove some of the initial system requirements. Accordingly, an SoSE approach enables manufacturers to align a product with their business strategy, product portfolio, technology, and competence development plans, while in general, it can also help them adjust the same product for the needs of more than one customer.