Ebook: Transdisciplinarity and the Future of Engineering

This book of proceedings contains peer-reviewed papers that were presented at the 29th ISTE International Conference on Transdisciplinary Engineering (TE2022), organized by System Design and Management (SDM) at the Massachusetts Institute of Technology in Cambridge, MA, United States from July 5–8, 2022.

TE2022 brought together a diverse global community of scholars and practitioners in dialogue and reflection on unmapped: underline engineering itself. Engineering is changing rapidly. The connectedness of the world’s most critical systems along with rapid advancement of methods push us to ask “How will we teach, research, and practice engineering?”

The recent decade has shown an ongoing shift towards model-based design, instrumented products and teams, data-driven analytics, rapid prototyping, and continuous delivery. These changes are enabled on digital and physical platforms driven by distributed teams and open interfaces. Transformations are underway in several industrial sectors, including energy, agriculture, health, and transportation.

It is an exciting time to be an engineer.

We recognize the insufficiency of boundary management and occasional border crossing amongst traditional technical domains, as engineers move beyond disciplinary norms established in the mid to late 20th century. Today engineers are called to address systems in their context across a lifecycle, to collaborate with a myriad of stakeholders and non-engineering experts, and – for these most valuable and daunting challenges – to generate new engineering disciplines.

Yet what is transdisciplinary engineering, and why might we make a distinction? After all, engineering and other practical professionals by their nature have required the collaboration of many disciplines. Would not other labels, for example multi-disciplinary or cross-functional, be the same? A fair question.

Please allow me to share why I believe a transdisciplinary engineering lens is different. I was inspired as an undergraduate engineering student by Don Schon, a mentor who is well known for his remarkable contributions on reflective practice. Schon, a philosopher who worked closely with urban planning, policy, and architecture, was very interested also in engineering and design. When I met him, he was fascinated by the ways that visual and computational models might lead to improved “conversation with the materials” and further improved dialogue amongst stakeholders. My talks with Don stuck with me, and I have often thought about what it means for engineers to be in conversation with the world around us.

Since then, during three decades of industrial work on engineering projects, his deep observations continued to resonate. I’ve seen it many times myself: great engineering to solve tough problems includes and exceeds the disciplinary know-how of specific engineering specialties.

Today’s complex problems, especially those with significant impact on nature and society, require a problem-solving approach which engages significantly beyond traditional engineering.

An exposure to a broader set of requirements, dimensions of performance, and stakeholders pushes specialists and integrators to adjust, apply, and learn in ways that can defy well-accepted assumptions and norms. Disciplinary abstractions are tested in the face of natural complexity. Successful engineers are not only conversant in their own field, but also prepared and proactive to engage with a range of disciplines, technical and social, especially user and practitioner communities. These engineers talk with users, communities, sociologists, economists, artists, scientists, and (even!) lawyers. Engineering for complex sociotechnical system challenges stretches one beyond the assembly of the work of specialists.

Of course, such transdisciplinary practice itself is not new. If fact, if we examine some of the greatest engineering teams in our histories, we can see that their trandisciplinarity helped them to outperform, to face unexpected challenges, to recognize emergent risks and opportunities, to learn and innovate. Similarly, some of the most saddening engineering failures are driven by engineering teams’ inability to see beyond their narrow specializations and their lack of “conversation” with society and nature.

The International Society of Transdisciplinary Engineering (ISTE) aims to explore the evolution of engineering including transdisciplinary practices. We explore how engineers of the future may be better prepared for design, production, and operational decisions that lead to sustainable benefits and costs shared equitably across society and nature.

Engineers in a “conversation with the materials”, conversation with one another, and conversation with nature.

Bryan R. Moser

August 2, 2022

Massachusetts Institute of Technology

Cambridge, MA USA

The specification of interfaces is critical in modularization and product architecture development. Literature defines product architecture as (1) the arrangement of functional elements, (2) the mapping from functional elements to physical components (3) the specification of the interfaces between interacting physical components. However, other scholars state that interfaces should include more than physical components, such as spatial, material, energy, and information exchange. This view has been extended to include attachment, transfer, control and communication, power, spatial, field, and environmental interfaces. However, to use interfaces through the product lifecycle and reuse them between product architectures and generations, there must be an approach to handle applicable interfaces in a company. This research contributes by presenting a way to operationalize (investigate an abstract concept, it’s essential to make it measurable and tangible) interfaces by introducing interface requirements that are definable, measurable, definable, and testable properties as a part of the interface development process and interface description. The method is illustrated by applying it in an industrial case study.

In the last decade, the field of Human-Robot Collaboration (HRC) has received much attention from both research institutions and industries. Robot technologies are in fact deployed in many different areas (e.g., industrial processes, people assistance) to support an effective collaboration between humans and robots. In this transdisciplinary context, User eXperience (UX) has inevitably to be considered to achieve an effective HRC, namely to allow the robots to better respond to the users’ needs and thus improve the interaction quality. The present paper reviews the evaluation scales used in HRC scenarios, focusing on the application context and evaluated aspects. In particular, a systematic review was conducted based on the following questions: (RQ1) which evaluation scales are adopted within the HRI scenario with collaborative tasks?, and (RQ2) how the UX and user satisfaction are assessed?. The records analysis highlighted that the UX aspects are not sufficiently examined in the current HRC design practice, particularly in the industrial field. This is most likely due to a lack of standardized scales. To respond to this recognized need, a set of dimensions to be considered in a new UX evaluation scale were proposed.

The introduction of product platforms has been acknowledged as a strategic enabler for increased business competitiveness. A vast body of research has described different aspects of platforms, but little work has been done on defining or delimiting the different types of elements that may build up a platform. Design assets include platform elements that are not commonly considered as a part of a platform. Previous research has suggested the introduction of formalized design assets to systematically extend an items-based platform with intangible elements. These are transdisciplinary objects, specifically prepared for reuse between projects to provide support for a wide range of engineering activities: specialized CAD geometry, working methods, spread sheets, function models or different types of knowledge representations, among others. The presented research is part of a larger project seeking to improve the collaboration between product development and manufacturing. This paper focuses on the use of potential and formal design assets at a development department of a global manufacturer of consumer products. The results show that the application of formal design assets depends on several factors, such as the level of professional experience and individual working styles. The contribution of the paper is a description of which formal and informal design assets that are used and a discussion on how the formal assets can be better utilized.

Improved resource efficiency, in industry and throughout the product life cycle, is a challenge and potentially, integrated product and production platforms can act as support. The aim of this study is to explore the current state of the technical platform in two industrialized housebuilding (IHB) companies from a mixed product architecture perspective. The study is part of a collaboration also involving three manufacturing companies and one IT provider. The research is crossing borders by means of interactive research and transdisciplinary engineering, and more than 50 practitioners and 13 researchers with competences in product management, engineering design, computational engineering, software development, production development, testing, quality, sourcing, and project management have been involved. Product platforms have been introduced in IHB to better control mixed product architectures and allow mass customization. Commonly, there is a technical platform for product architecture management, and a process platform for production management. High customization levels have resulted in an increasing number of variants not efficiently utilizing the technical platform. The results show that strong clients have negative influence on the technical platform while offering multiple products may facilitate simpler management of the technical platform but makes it more difficult to make changes and improvements.

In the era of Industry 4.0 and digital transformation (DT), the way the manufacturing industry provides value has shifted from selling products to directly creating value for customers. The synergy between business and information technology is the most important criterium for DT. This study proposed an object-oriented ontology-based enterprise architecture (OOOEA) framework, based on the unified modeling language (UML), to connect and integrate all databases and modules of the enterprise’s existing information system (or ERP). The enterprise domain knowledge must be depicted to achieve business-IT alignment. This research starts from the physical and philosophical views of object-oriented ontology (OOO), pays attention to the essence of all things observed or understood in business operations, and constructs the core ideas of the OOOEA framework. The contribution comes from three aspects. One is to provide guidance for the first step of DT, the other is to propose a concise and applicable methodology as the basis for communication between employees at all levels, and the third is to verify the feasibility and effectiveness of the framework proposed in this research through a practical case study.

Globalization, powered by digitization, is increasing technology growth and knowledge transfer rates to levels not seen in the previous 3500 years, obscuring absolute truth and accelerating rates of innovation and production. Competing, or remaining competitive, in this global marketplace requires a learning organization adopt a method of capture, retention, and reuse for demonstrated tacit knowledge to accelerate the development of increasingly complex systems of high quality at a reasonable cost. The architectural theory of Patterns and Pattern Language is a validated methodology for mining tacit domain knowledge from a proven system. This work applies architectural theory to a multi-year development experiment and captures exposed knowledge as a design pattern in a model based systems engineering tool, demonstrating applicability of digital engineering initiatives in the description and reuse of expert design knowledge. By creating and archiving model based expressions of expert knowledge, a learning organization can improve practical decision making and avoid uninformed concept phase decision making.

Integration of data from multiple sources into a single, project wide view is a necessity to keep up with increasing complexity and transdisciplinary considerations in engineering projects. Semantic Web Technologies (SWT) provide a unique way of linking and reasoning upon data from disparate sources to gain insights on the data viewed as a whole. By ingesting project data into a tool-agnostic repository and applying targeted reasoning, SWT can be used to perform system level verification tasks, such as providing a Key Performance Indicator (KPI) of completeness that gives project design and status insights to key stakeholders. This paper reports research creating a Semantic System Verification Layer (SSVL) as an extension to an existing Digital Engineering framework that utilizes SWT. This process and procedure are applied to a relevant use case to demonstrate and clarify the functions.

This research conducts integrated patent landscape analyses based on the landmark cases of patent infringement disputes between VLSI Technology and Intel. Complex multidisciplinary semiconductor knowledge ontology and taxonomy are derived from the landmark cases. Since Intellectual property (IP) and patent legal right protections defensively and offensively are critically important to high-tech companies for remaining globally competitive, the analysis of the patent portfolio consisting of the multiple technology innovations is the major challenge of this research. First, the patent search based on keywords of the patents under dispute. Afterward, the patenting trends of top assignees in the semiconductor industry, ranked in top International Patent Classification (IPC) codes, are analyzed. Further, this research performs topic clustering, a form of non-supervised learning, to divide all domain patents into unique topic groups. The ontology schema, based on the topic clustering results, builds the critical domain knowledge map, which can be used to highlight transdisciplinary technologies and their IPs. The research ensures newly granted patents, which focus on the disputed technical topics with literally or equally similar claims, must be cautious about the rist of potential infringement disputes. In the future, this transdisciplinary approach can be applied to various industries for IP protection.

Since service has evolved as a third factor that customers consider besides quality and price when making buying decisions, design for ease of service has been proposed in pursuing service excellence and gaining customer loyalty. Its approach includes a service performance assessment in which service time and complexity of service delivery have been considered to form a service index to reflect the service supportability of a design. To make service operations easier, not only should the complexity and time be taken into account, but the quality of timely service delivery is also critical. This paper presents the integration of the quality aspect of service into the index to ensure service supportability. This integration is built around the idea that poor service performance almost always results in customer dissatisfaction; therefore, a design should ensure customers will not be dissatisfied with service delivery. For each service activity, potential causes of poor service performance and their effects on customer dissatisfaction are identified and assessed. A Reverse Kano model is applied to determine how customers perceive the potential causes. The information gathered is incorporated into the index in the form of a no dissatisfaction factor. The proposed index was applied to assess window frame installation for illustration.

The interconnectedness of knowledge implies the need for a transdisciplinary attitude between humans and computers. This paper proposes a method for requirements and BOMs engineering and their chaining toward CAD models. Agents and multi-agent systems are considered and modelled as transdisciplinary concepts. The cooperative and agent-based platform F-EGEON (Fuzzy Engineering desiGn sEmantics elabOration and applicatioN) is developed for requirements and BOMs engineering. F-EGEON agents structure data into fuzzy BOMs: Fuzzy Requirement BOM (r-BOM), Fuzzy Function BOM (f-BOM), Fuzzy Component (c-BOM) and Fuzzy Parameters BOM (t-BOM). Then, a specific F-EGEON agent generates the Fuzzy cad-BOM to be transmitted to the CAD models. The prospect of equipping intelligent requirements engineering with systems like F-EGEON should not only aim to represent designer proposals, but also to support positive actions or behaviors in the design environment. An intelligent requirement engineering system must be capable of identifying (and even analyzing) false (even imprecise, incomplete, contradictory) statements and biased representations.

System stakeholders from multiple disciplines increasingly interact with computer models and simulations to make critical decisions. Advanced digital models have transformed how engineers interact, analyze requirements, develop and verify system elements, and test them to validate that they meet stakeholder needs. However, these models are often developed by a specific discipline for its own purposes. Convincing other stakeholders to accept the results of these tools can be a challenge, and indeed, the adoption of models and simulations at the level of system development still lags the pace of the underlying computational and application advances. The acceptance of models and simulations remains largely a function of the subjective preferences of engineers and other stakeholders. In this paper, we investigate the social and technical factors that contribute to the acceptance and effectiveness of models and simulations, what we refer to as model confidence. We combine a literature review with practitioner interviews to identify constructs and attributes influencing model confidence. Model confidence results from the interplay of model-related, modeler-related and stakeholder-related constructs. The constructs identified in this study populate a model confidence framework currently being developed. They highlight important considerations for future research and practice to enable improved and increased use of models and simulations in multidisciplinary settings.

When developing new products there are a multitude of requirements from different domains to consider making it a multidisciplinary activity. It involves stakeholders from the company and from the broader society. Requirements come from for example the customers, the production facility, suppliers, and governmental agencies placing safety and environmental regulations on the product. To manage all these heterogeneous requirements, a need of formalization and support emerges. The requirements can be managed using IT support. This functionality is often provided in contemporary PLM-systems. In this paper, it is investigated how a large industrial company with in-house design and manufacturing of consumer products formalize the requirements and handles them through the product development stages. The study involves corporate documents and interviewing staff from several departments of the company. Results show that while some aspects such as compliance with health and safety regulations are well supported, others are being addressed differently in each project with little formalization and IT support. This increases the risk of extra iterations in the development process. The paper discusses how to mitigate those risks and highlights some areas of possible improvement of the practices and IT support in product – as well as in production development.

Electric vehicles (EVs) are becoming a viable alternative to eliminate emissions, reduce dependence on fossil fuels, and gradually replace vehicles with an internal combustion engine (ICE). The traction battery of these vehicles has the primary function of supplying the energy necessary for the electric motor to work. Its design is complex and represents one of the most significant difficulties in reducing the cost of vehicular electrification. This article describes the challenges faced by a transdisciplinary team in designing a lithium-ion battery pack with a battery management system (BMS) applied to a small urban vehicle developed in the context of the “Program Route 2030”. Through the case study approach, we will present the interaction between 29 researchers from three Brazilian Science and Technology Institutions (ICT) (UTFPR-PG; UTFPR-CT; SENAI-PR) and two subsidiaries of multinationals (Renault; Clarios) in the automotive sector also based in Brazil. Preliminary results show the importance of transdisciplinary work in leveling the team’s knowledge about the product, determining target specifications through applying the House of Quality (HoQ) tool, specifying cell chemistry, proposing the modules’ physical arrangement, and developing the BMS.

Changing customer requirements, regulations, technology and regulations, shift to automated assembly and product variety are common challenges faced by many manufacturing industries and alignment between product and production system is critical for business success. Design engineers should be aware of production constraints and capabilities to ensure efficient manufacture and assembly of products that are developed. This requires different and detailed support to guide the work, evaluate different design solutions, enable continuous and concurrent work with design for producibility and production preparation. A study was conducted in three companies to understand alignment and integration of product development and production preparation processes. Also, utilization of production requirements, design for manufacture and assembly (DFMA) and failure modes and effect analysis (FMEA) to support design for producibility (DFP) was studied. Currently, production preparation is done through discussions between design and production engineers. Production preparation and work with DFMA and FMEA is skill and experience dependent. Definition, structuring and sharing of production requirements on different system levels, from production and product perspectives are identified as critical to supporting design for producibility and production preparation. The work with FMEA and DFMA can be developed and improved with systematic and structured way of working with production requirements.

Evaluating the initial impact of a large-scale disaster can be difficult and misdiagnosing the breadth and severity of an event may lead to a misallocation of response resources. During natural disaster response preparation, multiple classes of distributional and deep uncertainty affect decision making, increasing the range of effects influencing strategic and tactical resource allocation plans. Planning tools for humanitarian aid and disaster response (HADR) centers must address robustness of operations despite these “fog of uncertainty” factors, rather than calculate an efficient point estimate. This paper addresses needs to identify and improve issues affecting HADR response, including mechanisms to increase the robustness of HADR plans and response capabilities. It is not necessary nor viable to eliminate all uncertainty in response allocation decisions. Instead, an exogenous uncertainties, policy levers, relationships, and measures (XLRM) chart would serve as a useful decision-support tool to identify highly impactful variables which most significantly influence uncertainty while supporting risk management and decision-making when planning or executing a response. Furthermore, such considerations would mitigate some of the fog of uncertainty associated with coordinating an initial response to a disaster. The authors address changing tempo and decision/action cycles ranging from strategic planning to tactical response in HADR centers, focusing on XLRM examination and implementation.

In the context of the increasing aging population, design for the elderly has become more and more important. Many products have taken into consideration the elder-friendly design. However, the actual usability in real practice has not been sufficiently investigated. This study aims to tackle the problem and examine the practical usability of such a design through an experimental way. In particular, the Alipay app was selected as the target product to test. Its normal mode and elder-friendly mode were compared. For this purpose, we designed a set of experiments with 16 participants who are older than 45 years old and randomly divided them into two groups. One group used the normal mode, and the other used the elder-friendly mode. The eye tracker of Tobii Pro Glasses 2 was employed to collect participants’ eye movement data on these interfaces. Moreover, user interviews, user behavior observation, and System Usability Scale were jointly adopted to collect related user behavior information and subjective experience evaluation. Based on the qualitative and quantitative data, the differences between the two modes in the dimensions of information architecture, interface design, and task flow were identified. The results show that the current elder-friendly design cannot effectively facilitate usability for elderly users. Furthermore, the corresponding transdisciplinary design strategies were proposed to help with the improvement in design for the elderly.

Food loss and waste has become a major social problem all over the world. To reduce “Food loss and waste,” laws have been put in place to turn it into animal feed and fertilizers, relax delivery deadlines, and reduce serving sizes of meals. In addition, there are other activities promoted by the government, such as the use of food banks. However, even if all these activities are utilized, food loss and waste can never be reduced to zero. Another way to reduce food loss, other than these laws and activities, is to provide food materials to restaurants that provide inexpensive meals in the city, called “Kodomo-Shokudo.” By using food that would otherwise be wasted at the “Kodomo-Shokudo,” we can contribute to reducing food loss and lowering the operating costs of the these restaurants. Our aim is to clarify the difference between the food bank and “Kodomo-Shokudo” and create a route model that supplies food losses to the “Kodomo-Shokudo.” Kodomo-Shokudo is a community place where local residents or NPOs take the initiative to provide meals to children for free or at a low cost. Consequently, Monte Carlo simulations show that the resulting transportation costs could be significantly reduced.

Donald Stokes developed a paradigm that categorizes research into three quadrants based on two dimensions: the pursuit of basic understanding and consideration of utility. His ultimate goal was to create synergy between science and technology for economic advancement. Academics working on basic research fall into the Bohr quadrant; engineers fall into Edison’s quadrant of applied research. Pasteur’s quadrant, use-inspired basic research, is largely occupied by government agencies and societal input into setting their research priorities is indirect. Community labs are organizations that enable community members to perform research. Yet their utility as scientific organizations is unclear; understanding where they fall within the quadrant paradigm may enable their role to be better defined and may help their contributions to the scientific endeavor to be more fully realized. We use interviews with participants, review of literature, and review of lab and project websites to understand the nature of community lab projects and participants’ motivations. We show that the role of community labs falls most frequently into Pasteur’s quadrant. Community labs’ ability to integrate diverse expertise, pivot between basic and applied work quickly, support collaboration, and focus on local priorities makes them valuable additions to this quadrant and to the scientific research community.

Meeting the UK’s net-zero greenhouse gases target by 2050 requires transdisciplinary engineering, it requires efficient exchange and collaboration between engineering and social science, between engineers and policy makers within the national government. Based on ethnographic fieldwork conducted within the UK’s department for Business, Energy and Industrial Strategy (BEIS), this paper explores how technical and policy expertise were mobilized and combined in a recent change in utility-scale solar policy. Taking a model developed by BEIS’ engineering advice team in collaboration with the established renewable policy team, this paper looks at what it means to give and receive engineering advice in the context of utility-scale solar regulation. Looking at the model design process from both the engineer’s and policy advisor’s perspectives highlights how concepts of expertise, disciplinarity compatibility and opposition impact policy and outcomes. The modelling process was successful in helping the negotiation and reconciliation of technical and social concerns to enable a change in utility-scale solar regulation satisfactory to industry and constituents. By drawing on this case, this paper ends on a wider discussion about how the generation of mutual trust and development of interactional knowledge between engineers and policy advisers enables TE in policy practice.

The establishment of development pipelines for innovative technologies is a familiar aspect of digital transformation within the energy industry. One variant relies on innovation teams to rapidly prototype ideas as Proofs-of-Concept (POC) that, when successful, are matured and commercialized as new technical solutions within product lines. However, as the number of ideas grows, diversity of in-scope energy systems broadens, and resources remain constrained, identifying the highest-value ideas aligned with innovation goals and enterprise strategy has become paramount. We outline a prioritization and selection (PAS) approach founded on systems engineering (SE) to manage the work progressed within an innovation team. Specifically, we adapt the tradespace methodology for design selection when stakeholder needs and project constraints create a multi-objective optimization problem. The assessment combines a rigorous stakeholder analysis and surveys to characterize a multi-attribute utility function measuring POC benefit. POC resources are estimated from anticipated duration, development needs, validation requirements, and process change required by the technical solutions. These metrics characterize cost-benefit trade-offs, complemented by innovation measures associated with each POC. The final end-to-end workflow enables innovation idea comparisons with a dashboard to guide POC selection, portfolio shaping, and work prioritization across multiple energy disciplines and industry asset classes.

In order to reduce carbon dioxide emissions from international shipping, the International Maritime Organization (IMO) is discussing the future strengthening of EEDI/EEXI and the introduction of subsidies and carbon taxes. However, the stakes in international shipping are so complex that it is difficult for the IMO to predict how regulations will affect shipping companies’ decisions and markets in the future, making it difficult to determine effective regulations.In this study, we develop an agent simulator that simulates the decision-making process of actual shipping companies, and propose a method to quantitatively evaluate the response of international shipping to various regulations, thereby supporting the decision-making process of policy makers. The developed simulator outputs simulation results from 2023 to 2050 when the EEDI/EEXI reduction rate, subsidy rate, and carbon tax rate are input.In this study, we conducted simulations for 100 different regulatory proposals and plotted the results of all the proposals on a scatter plot of total carbon dioxide emissions and total benefits to support the decision making of regulatory decision makers. Furthermore, we were able to support effective regulatory decisions even when the assumptions were that the carbon emission reduction targets set by the IMO would be met and that carbon tax revenues would exceed subsidy expenditures.