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With its roots in the 1960s, e-collaboration has dramatically evolved and expanded over the past decades and became a globally adopted practice of teamwork. On the other hand, despite the development of e-collaboration technologies, the lack of true collaboration remains one of the main reasons for teamwork failures. However, traditional approaches to improving collaboration due to time-consuming, complicated, and expensive procedures do not meet the modern setup's requirements. This paper presents a new fast, simple, and low-cost method to improve e-collaboration through active engagement measures by analyzing data logs. The authors designed and ran a feedback system to mirror the participants' engagement during a collaborative engineering design course. The results of two case studies, including nine teams, suggest meaningful positive impacts of the method. The presented approach is applicable in upgrading e-collaboration platforms and further investigation on improving web-based collaborative learning and teamwork through monitoring dashboards and feedback systems.

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.

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.

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.

In recent years, the engineering community realized the potential of additive manufacturing (AM) technology to be a game changer in product development and manufacturing. The capability of AM to build tailored products within short lead-time can make it a key contributor to Industry 4.0 in a lean manufacturing perspective.

In global recession, outsourcing becomes a question of survival for most executives who need to restore profitability and growth. One of the critical challenges faced by such decisions is the potential risk of leaking confidential information through shared suppliers and partners. In this paper, a new approach is proposed to decompose a product into several sub-components for mitigating the risk of Intellectual Property (IP) leakage caused by inferences in supply chains. A design structure matrix is employed to study the potential risk of IP leakage considering different types of interactions between product components. Based on such a matrix, a clustering algorithm is developed to decompose and allocate the product components regarding IP protection issue. This methodology can be considered as a decision support tool to help the manufacturer select a set of optimal suppliers while minimizing the information leakage risk and the manufacturing cost.

This paper presents a new approach for the development of best practices in the aerospace industry through social media. A survey and semi-structured interviews used on a smaller sample suggest that integrating social media to formal organizational structures around a community of practice could indeed be employed to facilitate knowledge and experience sharing between established experts and participants. Finally, this paper also explores the extension of this framework to complement more formal and structured information processes typically managed by PLM solutions to better support the development of best practices via communities of practice. In this case, a complementary link between best practices under development in a community of practice and the design solution being developed in the Digital Mock-Up is presented.

A prototype results from the need to verify various qualities of the product at different stages of its development. In set-based design, multiplying prototypes is particularly critical to enable a broad exploration of the design space before committing to a solution. The exploration targets the choice of the best of all viable concepts on one hand but on the other hand also focuses on documenting them to better orient the search during the next attempts. This ultimately contributes to gradually improving the company’s engineering knowledge. According to current aerospace industry practices and considering the set based development paradigm in Lean thinking, an approach to handle multiple prototypes information with Digital Mock-Up (DMU) technologies is forwarded in this paper. This approach postulates that prototyping and testing activities may be supported by a Manufacturing Process Management (MPM) solution with a special use of three key functionalities, namely: Product Data Management (PDM) and MPM instantiation, MPM links, and Configuration Management (CM). These aspects are essential when handling multiple prototyping sets along with their test results.

In Canada, engineering programs will soon have to show that: i. graduates possess specific attributes, ii. outcomes are assessed in their context, iii. results are used to improve the program. This paper presents a model to meet all three criteria, and provides curriculum control options to fulfil CEAB conditions. It defines proficiency levels and information flow, from stakeholders’ surveys to the fusion of data. Control modules, pre-graduation work experience and post-graduation reviews gather internal and external observations. Coverage of the CEAB attributes by the CDIO Syllabus is summarised. Its utility for meeting objectives about the 12 attributes is clarified. An XML tool upholds coherence between learning objectives and targeted proficiency levels. More than merely instructive, this model displays the characteristics of a convincing demonstration for the CEAB.

The modern perspective on product life cycle and the rapid evolution of Information and Communication Technologies in general have opened a new era in product representation and product information sharing between participants, both inside and outside the enterprise and throughout the product life. In particular, the Product Development Process relies on cross-functional activities involving different domains of expertise that each have their own dedicated tools. This has generated new challenges in terms of collaboration and dissemination of information at large between companies or even within the same organization. Within this context, the work reported in this paper focuses on a specific stakeholder within product development activities — the testing department. Its business is typically related to the planning and building of prototypes in order to perform specific tests on the future product or one of its sub-assemblies. This research project aims at investigating how results from testing activities can efficiently interface with other departments, in particular to offer relevant information feedback to designers. As a first step, a study based on an open source initiative is described to show how two natively disparate PLM tools can dialogue to merge information in a central environment. The principles applied in the study are then transposed to introduce a framework where information from prototyping and testing activities could be mapped and merged with design activities to match needs in a cross-functional setting.Copyright © 2010 by ASME

The 3D analysis of tolerances is one of the critical functional requirements of solid-modelling systems which is most lacking at the present time. 3D tolerance analysis is most difficult to carry out by hand when it involves geometrical tolerances. A computerized 3D tolerance analysis is therefore needed, and an appropriate tolerancing model must be devised. The paper first acknowledges the kinematic nature of tolerance-chain analysis. A kinematic formulation of full 3D dimensional and geometrical tolerances is then proposed. The scheme represents all tolerances within a kinematic model, which is compatible with existing standards such as ansi y14.5m . The semantics of tolerances is respected, as tolerances are automatically interpreted to yield tolerance zones and datum reference frames. A tolerance chain is modelled as a kinematic chain, thus enabling multiple tolerances to be manipulated to solve 3D tolerance-chain analysis problems. The implementation of the modelling concept on an exact solid modeller is described. An application of the tolerancing model to the visualization of tolerance zones is also shown.

DSMs and related matrices are commonly used to represent system interfaces, which is closely associated with a need to decompose systems into their elements. However, besides the importance of managing the decomposed elements of systems, the systems engineer should also possess a capability to manage other systems’ relationships. In this paper we are focusing on the DSM capability to represent three fundamental system entities and four structural relationships, as they are defined in the Object-Process Methodology. We argue that DSM is an appropriate tool to facilitate a systematic approach to digital transformation of objects and processes through the different stages of the design process. We use a coffee maker as a case study demonstrating how each entity flows from an abstract environment to a more detailed one following specific structural relationships.