A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

Design Prototypes: A Knowledge Representation Schema for Design

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Digital Twin in manufacturing: A categorical literature review and classification

House of Quality

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security.

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Continuous maintenance and the future – Foundations and technological challenges

Development and operation of Digital Twins for technical systems and services

Innovations in digital modelling for next generation manufacturing system design

The product architecture has a significant influence on all phases of the product life cycle. Many literature sources claim modular product design offers a large range of advantages for addressing this influence. For example, it enables mass customisation, allows environmentally friendly end-of-life strategies, reduces development costs and allows efficient work in loosely coupled organisations. However, the generally low level of justification of these advantages together with the lack of commonly accepted theoretical references leads to a rather scattered view of the potential of modularisation. Moreover, the diversity of methodological approaches and the lack of common vocabulary represent a challenge for standardisation of practices and may hinder systematic implementation in product development. In particular, more guidance may be required to allow product development teams to choose the right modularisation approach that fits in with their objectives. This article summarises published literature in ...

Rainer Stark

Papers

Continuous maintenance and the future – Foundations and technological challenges

Development and operation of Digital Twins for technical systems and services

Innovations in digital modelling for next generation manufacturing system design

A systematic literature review on modular product design

Development capabilities for smart products