Design automation can be used to support efficient information handling and knowledge processing in computer-based product modelling, as well as make possible new design exploration and optimisation capabilities. To be able to utilise and manage design automation systems over time, it is important to understand how the disciplinary methods and models are dependent on each other through the product model constituents and then how these relations should be built to support maintenance, leveraging and future reuse. Awareness of the concrete representation of relations could support the system's traceability and transparency, and depending on the chosen technique, comprehension and extendability can be affected. This paper presents a conceptual framework for how a set of product model constituents are, can and to some extent, should be extended to define relations in multidisciplinary design automation systems.

The use of a product platform has been acknowledged as a strategic enabler for product family development and mass customisation. However, many companies struggle with adopting the common platform approach building upon pre-defined modules and components as it constrains the fulfilment of unique customer requirements and a rapid introduction of new technologies. These are the conditions under which manufacturing companies acting as suppliers operates, where unique solutions are delivered to different business customers, market segments or brands. This work reports the results from case studies of platform development conducted in collaboration with five product developing and manufacturing companies. The focus of this paper is on their initial states; including how they work with their product concept before a development project is started, the character of requirements and the adoption of product platforms. The main contribution of this work is a presentation of criteria on, and identification of, new platform elements termed design assets. These are introduced as a means to enable diverse types of resources to be reused in a company and a pragmatic way to bridge the gap between the physical products and the knowledge, tools and methods needed to realise these.

Design automation systems are implemented by many manufacturing companies to automate the repetitive and time-consuming design tasks. By automating such tasks, the designers have more time to focus on creativity and offer more customized solutions to the customers.

To automate a design task, first, the design knowledge should be captured from designers. This type of knowledge which is usually understandable by humans should be structured and formalized. Next, computer codes and scripts (that are mostly understandable by computers/expert persons) are created to execute the knowledge and provide the desired output.

To support maintenance of computer codes and scripts in a design automation system, it is necessary to know what, how and why about that piece of code/script. In order to support maintenance of the systems, we represent the system’s knowledge in form of knowledge objects. Knowledge objects are executed in run time and consist of two parts: computer readable and human readable. The focus in this paper is on the human readable which we call it “design description”. A MOKA-based framework is provided to create design descriptions for the computer readable parts. The design descriptions help engineers to understand and if needed update the computer readable parts, which in a wider aspect support maintenance of the whole system. E-books were used as a way to represent the design descriptions and a case study is provided to explore the results of the research.

Knowledge objects are used to automate engineering processes in a flexible and scalable way. The focus of knowledge objects has been the automation of engineering design. However, in this paper we present a way to integrate knowledge objects into e-books so that formalized engineering knowledge can be read by any stakeholder and still be automatically applied by the system from the same file. The paper shows how different stakeholders throughout the life-cycle of a design automation system benefit from the knowledge object and e-book integration, how the integration is done and an example where the integration was applied. The example is a real example from industry.

Mass customization and product individualization are driving factors behind design automation, which in turn are enabled through the formalization and automation of engineering work. The goal is to offer customers optimized solutions to their needs timely and as profitable as possible. The path to achieve such a remarkable goal can be very winding and tricky for many companies, or even non-existing at the moment being. To succeed requires three essential parts: formally represented product knowledge, facilities to automatically apply the product knowledge, and optimization algorithms. This paper shows how these three parts can be supported in engineer-to-order businesses through the concept of knowledge objects. Knowledge Objects are human readable descriptions of formalized knowledge bundled with corresponding computer routines for the automation of that knowledge. One case example is given at the end of the paper to demonstrate the use of knowledge objects. © 2019, Springer International Publishing AG, part of Springer Nature.

In this paper a method is introduced that supports reuse and maintenance of design information. The method allows sharing design information in different levels of details tailored for the stakeholders according to their needs. In addition, it is possible to share the information in multiple formats to suite different purposes. The results are demonstrated in an industrial partner which is a supplier of tooling for manufacturing industry.

A rapidly growing strategy in product design and manufacture, with great potential to improve customer value, is mass-customization. The main idea is to divide the product into modules that can be shared among different product variants. This will support a wide range of options for the end customer to select among, while an internal efficiency, similar to mass-production, can be achieved. This has been a success for many companies acting on the consumer market. However, many manufacturing companies are engineer-to-order (ETO) oriented, such as original equipment suppliers (OES). They design a unique solution, often in close collaboration with other companies. The solution can then be manufactured in different quantities depending on the client’s need. For these companies, there is a strategic need for developing high quality engineering support to further utilize and exploit the information and knowledge produced during product development and to succeed with a strategy influenced by the principles of mass-customization. This has to include the implementation and management of systems enabling highly custom-engineered products to be efficiently designed and manufactured. One challenge when introducing such flexible support is to enable traceability of decisions taken, tasks executed, knowledge used and artefacts developed throughout the whole lifecycle of an individual product. In this chapter, it is shown that traceability can be achieved by introducing support for capturing, structuring and mapping between decisions and resulting outputs, such as geometrical building blocks, knowledge implemented as rules, and the argumentation for the selection, design and specification of these. Three examples are presented where the concept Design Description has been modelled based on an item-oriented, a task-oriented, and a decision-oriented perspective which show the generality of the Design Description concept. The three examples demonstrate how to use the Design Description to enable traceability in platform design, product design, and manufacturing development processes.

This paper aims to present a methodology to predict the anisotropic and non-linear behaviour of glass fibre reinforced plastics using finite element methods. A material model is implemented in order to remedy the need of multiple material definitions, and to control the local plastic behaviour as a function of the fibre orientation. Injection moulding simulations traditionally provide second order orientation tensors, which are considered together with a homogenization scheme to compute local material properties. However, in the present study, fourth order tensors are used in combination with traditional methods to provide more accurate material properties. The elastic and plastic response of the material model is optimized to fit experimental test data, until simulations and experiments overlap. The proposed material model can support design engineers in making more informed decisions, allowing them to create smarter products without the need of excessive safety factors, leading to reduced component weight and environmental impact. 

Product platform development is a well-established approach for reusing product knowledge in the form of geometry and its configuration rules and constraints. Explicitly defining all platform components is not always possible however. This is why a product platform approach where the processes of realising platform components also are supported is needed, instead of exclusively relying on their results. The work presented here works toward this, with a focus on automated tool development enabled by extending design assets from different tools.

During the casting process and solidification of ductile iron castings, a heterogeneous microstructure is formed throughout the casting. This distribution is strongly influenced by the item geometry and the process related factors, as chemical composition and local solidification conditions. Geometrical changes to the geometry of the casting thus alters the local mechanical behavior and properties, as well as the distribution of stresses and strains when the casting is subjected to load. In order to find an optimal geometry, e.g. with reduced weight and increased load-bearing capacity, this interdependency between geometry and local material behavior needs to be considered and integrated into the optimization method. In this contribution, recent developments in the multidisciplinary integration of casting process simulation, solidification and microstructure modelling, microstructure-based material characterization, finite element structural analyses with local material behavior and structural optimization techniques are presented and discussed. The effect and relevance of considering the local material behavior in shape optimization of ductile iron castings is discussed and evidenced by an industrial application. It is shown that by adopting a multidisciplinary optimization approach by integration of casting simulation and local material behavior into shape optimization, the potential of the casting process to obtain components with high performance and reliability can be enabled and utilized.