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Understanding emergence is an important goal of system thinking, as it can express both desirable and negative properties of products and systems. Emergence has also a special importance as it has a direct link to the performance of products and systems, and thus has a direct relationship with the quality of life and thus sustainability in our societies. Emergence and system thinking are closely related to engineering design methodologies. In our paper, we develop a more precise definition of emergence through the core principles of systems complementarity that are similarity, irreducibility and sophisticated relationships expressed through the interfaces between systems, subsystems or product components.We demonstrate the utility of the approach based on an aircraft pylon case study by presenting a detailed definition of an interface design matrix and analyse how pylon subsystems influence emergence. The results have shown that the product can be perfectly represented by a model-based approach supporting interface management and the assessment of system complementarity. In turn, this approach allows to go beyond a qualitative definition of emergence, as it proposes a quantitative approach through the assessment of complementarity.

Engineering design teams, particularly in academic courses, were no exception to the consequences of the unknown virus and the global pandemic. Forced online teaching has influenced the way of using communication technologies. The information flow architecture of engineering design is also transforming due to the remote activities and the dominancy of web-based technologies. This transformation creates different patterns of distributed cognition within design teams. In the course of full remote teaching, we studied the entire information flow of a small and dispersed engineering team through the early stages of design for one month using the ethnographic method and Distributed Cognition analysis techniques. Our analysis, of the interdisciplinary design team during a rocket engineering project and system engineering teaching, shows the considerable role of different online data sharing and communications technology platforms in distributed cognition and collaborative problem solving within the team. These new trends create new challenges and opportunities, and in order to enhance collaborative design, these emerged out of the box trends require more attention and updating of existing strategies.

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.

Additive Manufacturing (AM) — one of several core digital technologies in “Industry 4.0” — is increasingly being deployed in industrial-scale contexts. The successful serial production of end-use polymer and metal components has demonstrated the possibility of AM as a primary production process in several applications. However, one of the principal challenges to greater adoption is a lack of organizational mastery over AM’s implementation in production contexts, and, more specifically, the absence of clear decision-making tools to facilitate exploration of implementation scenarios. To this end, this work proposes the use of a discrete-event simulation-based software modelling tool to investigate the influences of different facility-level planning decisions on techno-economic characteristics of serial production by AM. By changing key parameters, this tool enables users to observe variation in part cost, identify the contributions of individual system elements to part cost, and assess overall system throughput. The tool enables users to identify locally optimal solutions and make corresponding planning decisions, and to explore limiting cases of cost and lead time. In conclusion, we identify the limitations in the current modeling approach, and propose additional directions for future study.

Manufacturing companies nowadays face difficulties due to inefficient change management in domains as engineering, manufacturing, logistics, etc. Even though there are powerful software solutions and process-based methods available, it is uncertain how to efficiently react in an integrated manner to interdisciplinary changes. Whereas learning factories show great results for manufacturing education, change management is still uninvestigated in this context. Therefore, this work presents the basic infrastructure and use case for a demonstration and teaching environment that is currently being developed at Skoltech in collaboration with TUM. The results are derived from an integrated process for engineering and manufacturing change management.

This paper reviews the information available on specifics of the design decision-making process for the case of disruptive technological innovations associated with new products and systems. It defines the term “disruptive technological innovation,” provides with the explanation of decision-making methodology peculiarities for this type of innovation, and describes currently existing techniques and tools to support design decision making in case of disruptive technological innovations. The current paper relates to decision making in systems engineering and design, and therefore deals with the design decision making. The terms “disruptive technologies” and “disruptive innovations” appeared at the end of the 1990s. Researchers frequently mention disruptive innovations and technologies in the description of technical products for different industries: aircraft, automotive, food, petroleum, etc. A disruptive technological innovation is defined as a combination of disruptive technology and disruptive innovation. A new product can be relatively a simple device like an unmanned aerial vehicle and a smartphone, or a complex system like a modern aerospace vehicle or a space information network. Being an innovative developed product, it possesses peculiarities influencing the product development phase of the product lifecycle design decision-making process and accompanying supporting techniques and tools. This review investigates the specifics of design decision making of disruptive technologically innovative products that influence different stages of the product development phase in their product lifecycles. The paper combines aspects of systems engineering with innovation theory, key elements of the design of complex systems, and highlights the product development phase of the product lifecycle design decision-making process.

The paper discusses the principles of human-centered design applied to the development of a medical wearable electrocardiogram (ECG) patch-like system. The following design issues are taken under consideration. Firstly, how to design wearable suitable for people of different size, gender and age. Secondly, how to ensure proper signal detection, both tactile and visual. Thirdly, how to provide reliable physical connections between the element of the hardware piece (electronics, adhesive base, housing). Fourthly, how to reach intuitiveness of the user-system interface. Fifthly, how to achieve appearance more of a consumer product rather than a medical device, as many people prefer such systems to be small, convenient, comfortable and give no indications about its actual function. Design decisions throughout the development cycle are based on analysis of several available sensors with analogous purpose.

Increasing product complexity and the growing importance of software components poses challenges for PLM systems in modern companies and extended enterprises. Today product behavior and its processes drive product value, so companies use sophisticated software to accurately predict it before its manufacture. In this work we argue that states are a natural atomic part of any product, system or process. Then we briefly review and compare current methods for behavior and state representations in domain engineering and systems engineering practices. We show that the support provided to the engineer by PLM systems in managing and sharing behavioral and state product properties across an extended enterprise is insufficient in comparison to their significance for successful product development and its complete life cycle.

Set-based design (SBD), sometimes referred to as set-based concurrent engineering (SBCE), has emerged as an important component of lean product development (LPD) with all researchers describing it as a core enabler of LPD. Research has explored the principles underlying LPD and SBCE, but methodologies for the practical implementation need to be better understood. A review of SBD is performed in this article in order to discover and analyse the key aspects to consider when developing a model and methodology to transition to SBCE. The publications are classified according to a new framework, which allows us to map the topology of the relevant SBD literature from two perspectives: the research paradigms and the coverage of the generic creative design process (Formulation–Synthesis–Analysis–Evaluation–Documentation–Reformulation). It is found that SBD has a relatively low theoretical development, but there is a steady increase in the diversity of contributions. The literature abounds with methods, guidelines and tools to implement SBCE, but they rarely rely on a model that is in the continuum of a design process model, product model or knowledge-based model with the aim of federating the three Ps (People–Product–Process) towards SBCE and LPD in traditional industrial contexts.

Model-Based Systems Engineering (MBSE) approaches guide complex system/product design and development from the very early stages of the product development process. Its full-scale integration into the Product Lifecycle Management (PLM) would allow to facilitate a better data flow from conceptual design to detailed design. In this paper we discuss such data flow focusing on three core models: Object-Process Methodology (OPM), Core product model (CPM), and STEP. We describe core artefacts of these models and those entities in which they overlap, thus we define which data is critical throughout the entire system/product development. We demonstrate that the fundamental problem associated with the integration of MBSE and PLM is due to the fundamental essence of systems, which needs both explicit representations of time and space to represent completely the system form and behavior throughout the product/system life cycle. An analysis for a CubeSat mission is also presented to illustrate the data correspondences between the various models.

Currently the healthcare industry undergoes disruptive changes so that the design of medical products requires much better speed, flexibility and inter-connectivity. Research and development of mobile health products require an intensive collaboration from cross-disciplinary teams. In order to succeed, healthcare product providers should adapt their engineering processes to the fast improving environment. This paper introduces a hybrid Lean-Agile approach for the medical wearable device development process with respect to the learning outcomes and quality management system.

We present the preliminary results of our investigation on the effectiveness of the Serum methodology for Agile development of space hardware. We analyze the development process of a hardware payload that is part of a host nanosatellite mission composed of two 6U CubeSats (30cm x 20cm x 10cm). The host mission is a collaboration with several partners including academia and small and medium enterprises. Scrum is a product development process created as a faster, more effective way of developing software. The goal of our investigation is to understand whether and by how much the same Scrum principles that proved successful in software can be adopted vis-a-vis in hardware projects. We also intend to identify the fundamental challenges in such an approach for space missions. In the host mission, Scrum has been adopted for the development of the payload subject to the investigation. The paper introduces the ongoing development process and identifies Scrum-related challenges internal to the payload development and challenges related to the coordination of the process with partners adopting established development processes. The paper identifies opportunities of future work for the fine tuning of Agile development methodologies in space projects and illustrates key statistics that have been collected throughout the development so far.

Both startups and traditional space industry are exploring new business opportunities and new engineering approaches in what is becoming known now as New Space.

This work builds upon a previous proposal for the use of the extended SAPPhIRE model of causality as a foundation for a PLM system, and more specifically the management of design data at the conceptual design phase. During the conceptual design phase, the product definition is in a state of flux as multiple iterations and options are considered until a suitable baseline design is developed. The role of PLM systems is to manage the people, processes and products involved in developing and sustaining a product in order to increase stakeholder satisfaction and product quality while reducing lifecycle costs. At the conceptual design stage, a balance must be struck between the freedom to iterate and the need to control the design process and capture relevant data.

Currently, MBSE and PLM methods and solutions are not well aligned with each other resulting in excessive complexity and uncertainty. Their full-scale integration would facilitate the development of complex systems. Better data flow from conceptual design to detailed design and feedback from later stages of product development are needed. In this paper, we analyse the MBSE and PLM integration from a system of systems (SoS) perspective and apply some of the methods used in systems engineering to better understand their nature, quantify their epistemic uncertainty and propose possible solutions to reduce their complexity and uncertainty. To achieve these goals, we study systems ontologies, such as the object-process methodology (OPM), the core product model (CPM), and manufacturing process management (MPM), which represent essential elements of a digital engineering solution. We also propose a measure of complexity to better quantify the structure of the interfaces through the design structure matrix (DSM)-based approach.

Engineering change management (ECM) makes up a large portion of overall product development effort and provokes significant uncertainty in planning and executing the product development operations. By enabling better planned ECMs, practitioners can improve overall project management. This work introduces the concept of the digital twin for the ECM process to enable its continuous quantitative assessment and improvement of engineering process planning. For this, we bring forward two key contributions: the concept of the framework for ECM process simulation and analysis, and the approach to refine the ECM modelling parameters using historical data and thus reduce associated uncertainty. This work proposes that by using past information, we can improve the accuracy of ECM modelling and enable more precise predictions on process lead time and its standard deviation. We conclude the article with an outlook for further research pointing at the current limitations and challenges.