ABSTRACT

Solution spaces are sets of designs that meet all quantitative requirements of a given design problem, aiding requirement management. In previous works, ways of calculating subsets of the complete solution space as hyper-boxes, corresponding to a collection of permissible intervals for design variables, were developed. These intervals can be used to formulate independent component requirements with built-in tolerance. However, these works did not take physical feasibility into account, which has two disadvantages: first, solution spaces may be useless, when the included designs cannot be realized. Second, bad designs that are not physically feasible unnecessarily restrict the design space that can be used for requirement formulation.

In this paper, we present the new concept of a requirement space that is defined as the largest set of designs that (1) allows for decomposition (e.g., into intervals when it is box-shaped), (2) maximizes the useful design space (good and physically feasible), and (3) excludes the non-acceptable design space (bad and physically feasible). A small example from robot design illustrates that requirement spaces can be significantly larger than solution spaces and thus improve requirement decomposition.

Dual ontological products are a physical construction and an emotional construction. Multitude of human factors must be considering when designing dual ontological products. To increase the product's impact and reach, designers should also understand the requirements of potential users. A design stage conflict exists between the emotional construction and the physical construction of a product when considering human factors. Designers find it difficult to achieve the right compromise between these constructions and hence, the balancing of the two is crucial. This research therefore contributes a novel harmonistic knowledge-based framework which makes designers aware of design stage conflicts and consequences of commitments made on human factors in the use-phase of the artefact. This approach was implemented in a machine learning based computational tool which exploits harmonistic knowledge and information collected from potential users to proactively assist, guide, and motivate product designers. This paper also presents a descriptive study for the evaluation of the framework and its implementation as a computer-based prototype tool. Results show the necessity and beneficial use of the tool for design engineering practice.

This article aims to contribute to the knowledge on product/service system (PSS) design practice as follows. First, a new rationale for why PSS design in practice often does not exploit its full potential is given based on a theory on inseparability of services. Second, a representation of the dependencies between product design parameters (DPs) and service DPs in a form of potential-dependency knowledge base is proposed as a remedy. Third, reusability of the knowledge captured from product-service integration across sectorial borders is shown with PSS design at a complex product manufacturer.

Digitalisation is making significant inroads into society at the same time as the general commercial trend is to able to personalise the product one acquires. The field of digital product representation, and the techniques for adopting a particular product in accordance with the customer's expectations, have become very important corporate assets. From a company's perspective these assets can be leveraged both for internal efficiency and also for different types of external customer interactions. In this article, the standpoint is that product geometry forms the foundation for digital product representation. It is from this perspective that the geometrical ecosystem comes into focus. Geometry creation and geometry consumption, in combination with geometrical configuration management, are high-value areas that must be mastered. A research-based 20-year industrial perspective building up such capabilities serves as an example. The article concludes with a forward-looking perspective on potential areas for continued exploration on this journey.

As product, production systems and material strongly influence each other, an integrated view on these domains offers huge potentials during development in order to adjust characteristics being mutually dependent. Considering manufacturing aspects within the design process certainly constitute a widespread approach to make sure that the products can be produced to predefined costs and quality.

As product characteristics are realised through material characteristics and manufacturing processes, material aspects need to be integrated into this view. Moreover, different geometries have to be assembled in order to create particular structures, why joints devote a special attention.

For this reason, a definition approach that integrates product, production systems, material plus joints and considers the ecological performance apart from the regular technical and economic aspects offers a huge potential for successful future solutions. This paper reviews relevant development approaches as well as supporting IT tools in the different domains. As a result, an extendedly integrated view is introduced and a method that supports the integrated selection of solutions regarding a technical, economic and ecological performance is introduced.

Additive manufacturing (AM), which was first applied for rapid prototyping, is now becoming a real option for small-batch production of final products. Further expansion of AM is closely correlated to production costs. AM can only become competitive to traditional manufacturing methods if a product is designed for AM already from the beginning as it is an expensive technology that should only be applied if it adds enough value to the product. The aim of this paper is to increase cost awareness in the conceptual design phase and to support product developers in doing AM cost estimation and process selection. The proposed model integrates design for AM and costs calculation. The input data to the process is preliminary design and design requirements. The main contribution of this paper is the multi-criteria AM function, which enables concurrent consideration of different technical and economical criteria. The multi-criteria AM function helps to compare how AM processing and product design parameters influence the product cost. The holistic overview of different options increases the solution space and enables product optimization in several iterations.

Whilst Concurrent Conceptual Design (CCD) has been performed for many years at facilities such as: the Concurrent Design Facility at ESA and the Project Design Center at JPL-NASA, the sequencing know-how resides in their communities of practice. This paper strives to explain how a sequencing algorithm based on Design Structure Matrices can be used as an instrument to facilitate the interaction between disciplines during CCD studies for Model-Based systems exemplified with two case studies.

Although well researched and praised in academic publications, function modelling (FM) does not have gained much traction in industrial application. To investigate into possible reasons for this, this publication researches literature of nine different projects where enhanced function-means modelling has been applied. The projects are analysed for their purpose of FM-use, applied benefits and discovered challenges of the FM approach. From this, the main challenges for FM application are the abstraction level of the modelling language as well as the lack of an interface to CAD modelling.