Advancing Industry 4.0 concepts by mapping the product of the automotive industry on the spectrum of Cyber Physical Systems, we immediately recognise the convoluted processes involved in the design of new generation vehicles. New technologies developed around the communication core (IoT) enable novel interactions with data. Our framework employs previously untapped data from vehicles in the field for intelligent vehicle health management and knowledge integration into design. Firstly, the concept of an inter-disciplinary artefact is introduced to support the dynamic alignment of disparate functions, so that cyber variables change when physical variables change. Secondly, the axiomatic categorisation (AC) framework simulates functional transformations from artefact to artefact, to monitor and control automotive systems rather than components. Herein, an artefact is defined as a triad of the physical and engineered component, the information processing entity, and communication devices at their interface. Variable changes are modelled using AC, in conjunction with the artefacts, to aggregate functional transformations within the conceptual boundary of a physical system of systems.

The proposed methodological framework concerns axiomatic theory fusion (ATF) of non-additive engineering design theories. ATF includes seven steps: (i) semantic discretization of the composite theories, (ii) deriving epistemological entities by logical/semantic analysis, (iii) establishing and representation of relations among all relevant epistemological entities, (iv) combining the inter- theoretical epistemological entities of the component theories, (v) deriving propositions based on the combined set of epistemological entities, (vi) transcription of the epistemological entities and propositions into a textual/visual theory description, and (vii) validation of the resultant theory in application contexts. The proposed framework makes ATF an effective, content independent methodology for fusing component theories, no matter if they are descriptive, explanatory, predictive or controlling in nature. ATF methodology requires professional comprehension and rigor from the researchers. It is necessary to justify the logical correctness and practical validity of the target theory in the specific application context.

The challenges related to product structures, which go hand in hand with megatrends such as individualization, can be met with the modularity of product structures. With the help of various modularization methods, modular product structures are created with regard to different goals. There are many references to the effects of modular product structures on life phases and economic targets in the literature. These effects were collected in previous research in a generic impact model. Since there is a lot of information about the effects, such models become very comprehensive and thereby difficult to handle. For this reason, the impact model is consistently generated using SysML. The adaptation to company scenarios is possible through the use of simulations with which, for example, company-related and product-related boundary conditions can be controlled by means of a User Interface.

Pipe inspection robots have been developed to reduce the cost and time required for gas pipe inspection. However, these robots have been developed using a scrap and build method and are not used in practice. In this paper, we propose a method of virtual pipe inspection simulation to clarify the parameters that are important in increasing the robot's ease of use. This paper presents the results obtained by a feasibility study with regard to pipe simulation. We developed a virtual pipe by simulating eight actual turns of an external gas pipe, and a robot equipped with camera at the tip. In the experiments, three individuals working in the field of gas inspection carried out the operation. We obtained questionnaire, time, and brain activity data. The results revealed various important points that must be considered in practical simulation and robot design. In conclusion, the virtual pipe simulation can be useful in developing the design of a pipe inspection robot.

System design at the early stage of design plays an important role in design process. Model based systems engineering is seen as a prominent approach for this challenge. System design can be explored by means of system simulation. However, as the system is a complex system, system model tends to have high level of abstraction. Therefore, the models cannot depict every details of the system, which makes optimization unreasonable.

Furthermore, at the early stage of design, there are many uncertainties such as success of technological developments. By properly incorporating uncertain factors in system design, the system can be tolerant. Currently system design is conducted by experienced experts. However, for more complex system, it would be difficult to continue the current practice. Therefore, a method to support design team to make decision in system design is needed.

This paper proposes a computational support for the system design. Design constraints, which seems the core information that design team wants at system design, are modeled. By visualizing constraints quantitatively and intuitively, the proposed method can support design team to conduct system design and design study.

In today's highly competitive market, product success is determined by two critical factors - innovation and sustainability. While innovation looks to rampantly satisfy the consumers' ever growing requirements with creative solutions, sustainability attempts to rationalise the precarious demands of desired requirements on economy, society and environment.

InDeaTe - Innovation Design database and Template, a web-based, design process guidance tool, supports design of sustainable systems by incorporating sustainability requirements into the design process. This paper investigates the potential of the tool to improve the usefulness of a design, one of the indicators of the creativity of the solutions, apart from its novelty. Comparative studies are conducted to assess the improvement of ‘requirement-satisfaction’,a proxy measure for usefulness. Upon introduction of the tool into the design process, significant improvements are reported, thereby reflecting the ability of InDeaTe to increase the usefulness of solutions and foster creativity in design.

During the process of product engineering, decisions with uncertain consequences have to be made about future development (Albers et al., 2017a). Customer, user and vendor requirements that are already known and those who are relevant for the future have to be recognized and transferred into consistent projects. Classical approaches like customer surveys or market analyses are only partially useful for anticipating or validating future product requirements since they rather evaluate todays situation. Methods of foresight are preferably applied to make decisions under circumstances of uncertainty and to generate future knowledge. The following work treats thus a system that enables the user to deduce future requirements based on trend analyses. The system which was first mentioned in Albers et al. and further developed in Marthaler et al. will serve as the basis. (Albers et al., 2018a; Marthaler et al., 2019). The goal is to present and evaluate a system based on the analysis and identification of trends that allows to identify robust requirements for future product generations and to transfer them into concrete development agreements in the form of a development road map.

Additive Manufacturing (AM) provides significant opportunities for design and functional integration of parts and assemblies. Compared to conventional processes, the AM principle increases design freedom notably. Additionally, numerous processible materials and hybrid processes enable the implementation in different industries, spanning from aerospace over automobile until medical applications.

However, there are still handicaps to be addressed, arising from the large diversity of AM principles, post-processing and quality assurance issues, partly insufficient user knowledge, and organizational aspects. Coherently, lacking requirements specification hinders a successful consideration of AM in the early stages of development, and its later implementation.

To promote knowledge build-up, this contribution presents a requirements specification framework, which supports developers in determining demands throughout the development process, including those resulting from post-processing and testing operations. By incorporating thorough analyses of general organizational and resort overarching limitations, this contribution promotes a successful implementation of suitable AM strategies.

In today's engineering projects, interdisciplinary work leads to an increase in interfaces between different departments and domains. As each stakeholder pursues different goals and tasks, a heterogeneous model landscape is required. In each domain, a variety of different model and software implementations provide the essential basis for efficient work. On the interfaces, the risk of model inconsistencies increases. To handle occurring inconsistencies, various approaches have been presented. For model-based systems engineering projects, rule-based methods are considered as the most suitable technique. However, said approaches require a high manual effort in identifying model dependencies and establishing consistency rules. Unfortunately, in particular these steps are not well described and supported. Therefore, this paper presents an easily applicable approach for the identification of model dependencies in interdisciplinary projects. The method is supported by a software implementation and is directly integrated in engineering workflows. A first industrial case study has shown positive effects of the approach and revealed further research goals.

This paper demonstrates a concept for a cross-domain strategy for the sustainable processing and dissemination of product information. Important functional product features are explicitly mapped as working surface information in different domain tools with the help of the contact channel method and are integrated using a model-based systems development approach. The approach uses established state of the art design tools and can be integrated into existing product development processes, knowledge based engineering concepts and product (system) lifecycle management strategies.

Complexity of products and systems is increasing through digitalization, interdisciplinarity as well as high technology maturity and new business models. In consequence, new product development (NPD) projects need to manage and satisfy a large number of requirements from a broad range of stakeholders. Yet, NPD projects are often delayed due to requirement changes. In this paper, a new method for analyzing requirement change propagation is presented. The method is based on the assessment of requirement interrelations structured in a requirements structure matrix by a modified page-rank algorithm. By the method, a high number of strongly interrelated requirements can be analyzed in an efficient manner. Additionally, higher-level interrelations as well as the relative weights of requirements are also incorporated in the analysis. Hereby, an efficient holistic approach towards the analysis of requirement change propagation is proposed.

Complex technological artefacts are often decomposed into smaller components to keep their design manageable. The resulting challenge is to coordinate decisions that involve multiple components and to design components such that high-level targets are met. Analytical Target Cascading (ATC) is an analytical coordination method for the optimization of decomposed systems, which we aim to incorporate in systems engineering design process. To this extent, we relate the domain of engineering optimization to the domain of requirements engineering, and propose a method that constructs an ATC problem from functional specifications and requirements written in the newly developed Elephant Specification Language. The proposed method is demonstrated in the two-level design of an automotive powertrain. This contribution is a step towards design automation and is expected to increase the usability of decomposed optimization techniques.

Model-based systems engineering (MBSE) is well-known in gaining the control over the complexity of systems and the development processes, while agile is a project management methodology originally from software development that uses short development cycles to focus on continuous improvement in the development of a product or service. In this paper, we adopt the concept of agile into MBSE and then proposed the new approach - Munich Agile MBSE Concept (MAGIC). The highlights of the MAGIC approach can be concluded as 1) the requirements which have been defined in the first stage will be examined and traced at each following stages; 2) communication between every 2 stages always exists in order to have a close connection during each system development phase; 3) the idea of Industry 4.0 has been included and reflected to achieve automation and data exchange with manufacturing technologies; 4) the concept of IOT (Internet of Things) is also considered when it comes to the usage and service of the system to satisfy the customer's needs; 5) the whole spirit of agile is reflected as the iterative and incremental design and development

The digitalization of the Industry is one of the megatrends taking place, but many companies struggle to follow this trend. The main reason is the absence of simple solutions for the integration of sensory functions, which are applicable to the existing system. Therefore, this paper discusses the aspects of simplicity in the context of integrating sensory functions into existing systems, to support the development of digitalized products.

Two general requirements can be formulated for a solution to be applicable simple: The first requirement is affected by the product structure. The solution must affect the least possible amount of modules and must not interfere with the interfaces of the modular platform. The second requirement is affected by the effort to model the behaviour of the desired information and the possible data a sensory function is delivering. The effort to develop a reliable solution has to be compared with the commercial potential of the solution.

To consider the mentioned requirements, the paper explains three approaches to assess the simplicity of solutions on an example of the desired monitoring of the functions of a rotary plug valve.

This paper shows how designers of IoT-enabled products can assess the environmental impacts associated with the user behaviour and the service system around the product. High-quality secondary data and a user-behaviour survey were able to highlight critical aspects of a smart fridge's design. A streamlined LCA looked at just the in-use phase of the product within 4 PSS scenarios. The system included: the effects on the food waste; grocery shopping methods; fridge door openings; and how the users interact with the smart fridge features. The results show that a smart fridge as within a PSS can reduce the impact on the environment (GWP of 21,700 kg CO2-eq within the ‘average PSS scenario’ and GWP of 23,100 kg CO2-eq for the normal fridge with ‘typical scenario’). The product's increased emissions are counteracted by the reduction in GWP due to: reduction in food waste; and shifts from brick-and-mortar grocery shopping to e-commerce. Therefore some of the critical aspects of the product's design that are most influential on the environmental impact of an IoT fridge are: the design of the web-browsing capability; and the use-by date tracking system.

Social robots are in direct communication and interaction with people, thus it is important to design these robots for different needs of individuals or small groups. This has revealed the need to develop design methods for personalized or mass-individualized social robots, which are expected to respond to many different needs of people today and in the future. In this paper, a previously developed 3D DSM model is implemented in the systematic conceptual design of social robot families. The model is independent of any physical elements and based on behavioural elements as perception, cognition and motoric action. The data regarding 45 different social robots from 80 articles in the literature is used to identify these three behaviours of the existing social robots and the mutual relationships among these different behaviours are defined in order to develop a 3D DSM structure to be used as a basis for designing social robot families. The resulting novel 3D DSM is a general-purpose, basic model that can be used to identify behavioural modules to design social robot families.

The high interaction between process and product models in product development and systems engineering (SE) is common sense. However, most research in the field of model based systems engineering (MBSE) focusses of physical systems (hardware and software). The authors claim that this focus is a main reason for the low acceptance and high effort for implementation of SE and MBSE in industrial practice. Thus, this contribution aims at supporting an integrative analysis and synthesis of process and product models by introducing the concept and framework of Model-based Process Engineering. Based on established research this framework introduces three main systems, namely the system of processes, system of product models, and system of tools to describe complex product development. The main contribution of this work is a preliminary concept to structure and link the systems of processes and product models. Besides form the description of the main relations between the systems an integrated modelling concept to represent links between the process and product model system is proposed.

The definition of initial requirements in the early phase of product development is characterised as a decision process under highest uncertainties. Studies show that projects often deviate from their planned goals or even fail due to ill-defined requirements. Despite the importance and criticality of this task, a detailed description and risk-oriented explanation is missing in the product development literature. The goal of this paper is to develop an explanation model/frame which establishes a link between the development context and an appropriate procedure for the initial requirements definition based on general risk treatment strategies. In a first step, risk-driving context factors with high influence on this task are identified. Then two case studies are compared to analyse the interrelations between their context factors and the applied risk treatment strategies that are implemented in their procedures for defining initial requirements.

The use of flexible and autonomous robotics systems is the solution for the automation task of the production and intra-logistics environments. This dynamic context requires the robot to be aware of its surroundings through the whole task, also after accomplishing the gripping action. We present an anomaly detection approach based on unsupervised learning and reconstruction fidelity of image data. We design our method to enhance the dynamic environment perception of robotics systems and apply it in a palletizing robot, in order to perceive and detect changes to its surrounding and process after the gripping step. Our proposed approach achieves the performance targeted by the considered industrial requirements.

Industrial companies today must operate in an increasingly competitive world and need to rethink their organization accordingly. First, industrial strategies concerning technical management need to change and develop. If we consider the specific management of the product design process, managers use indicators during the lifecycle of the product concerning quality, cost and lead-times. For example, some new indicators concerning performance metrics related to cooperation issues among the design team are set up. Secondly, managers increasingly need to integrate the user in the early phases of the design process. The main benefit of this approach is that it allows designers to innovate more rapidly and robustly. The aim of this paper is to introduce a new approach making it possible to calculate a performance indicator concerning use design. The new indicator will help management drive the design process through the integration of use in the product, helping to enhance the usability of the future product, and consequently improve innovation.