This paper analyses the multi-faceted development process of system paradigm-driven disciplines (SPDDs) and interprets its drivers, stages, offerings, and impacts of the disciplinary shifts. Due to the extreme broadness of the field, the authors could not consider all pertinent scholarly domains. Instead, they placed mechatronics into the focus of their study, collected evidence from this wide-ranging and highly integrative field of engineering, and used it to underpin their reasoning and propositions. After introducing the topic, goals, and approach, the paper includes an interpretational intermezzo to reduce the conceptual and linguistic Babel associated with modern system science, particularly artificial intelligence in systems. As major drivers behind the observable scholarly changes, the trends of (i) scientific convergence and divergence, (ii) technology integration and synthesis, (iii) paradigmatic nearing of engineered systems, (iv) growing level of cognitive abilities, and (v) multi-faceted socio-ecological embedding have been identified. The authors propose that specific stages and offerings can be found in the development process of most SPDDs (in particular, in mechatronics). Their position is that all implications of the disciplinary shifts can hardly be considered due to the wide variety of the application fields and the diverse functionalities. The authors propose a novel reasoning model concerning the scholarly fields enabling SPDDs. Based on transdisciplinary epistemology, this model identifies the operational knowledge spaces and their relationships that characterize, among many others, mechatronics, cyber-physical systems, and artificial intelligence-based problem-solving systems.

Engineering education is an evergreen challenge. It is supposed to follow the scientific progression, aggregation of knowledge, development of technologies, industrial demands, social trends, personal interests, affordances of computerization, evolution of educational practices, and so forth. From time to time, it must renew itself to comply with the changing situations, growing complexities, and quality expectations. The presented work was driven by the conjecture that next-generation engineering education (NG-EE) cannot be designed and implemented without understanding it as a holistic problematics. Therefore, this article attempts to consider the whole of engineering education and make propositions concerning its probable future based on a survey of the current literature and the author's long-term experiences. It is structured according to five fundamental questions: (i) Why is innovation in engineering education a challenging problematics (again)?; (ii) What are the currently typical approaches to engineering education?; (iii) What can be utilized as enablers for NG-EE?; (iv) What can we expect from the offerings of generative artificial intelligence tools?; and (v) What sort of new mind-set is needed for NG-EE? The main findings of the literature survey are discussed in detail, and propositional answers are formulated to these questions. It is advocated that NG-EE (i) is becoming increasingly transdisciplinary, (ii) needs novel conceptual models, methodological frameworks, and management scenarios, (iii) should impose a holistic rather than a reductionist view on systems, (iv) should consider increased diversification of engineering jobs, (v) should equip with the competencies of autonomous learning, and (vi) should offer a constructive but critical attitude to using artificial intelligence technologies.

As a continuation of the work previously published in two papers in this journal, this paper addresses the problem of systematically constructing sharable transdisciplinary research models (TRMs) for definitive research problematics (DRPs). The paper discusses the underpinning fundamentals and proposes a practical methodics that is underpinned by intuitive reasoning rather than by proven theories but relies on a lucid procedural framework. The main activities are discussed through a demonstrative example designated as ‘avoidance of frequent vehicle accidents at suburban road crossings'. First, a concise overview of the literature related to research models is provided and the work reported in this paper is placed in this context. Then, the operational aspects of the transdisciplinary research model development methodics are discussed. As a starting point, the proposed methodics assumes the availability of a comprehensive specification of the DRP. The conversion process includes six steps: (i) exploring research concepts by content analysis of the DRP, (ii) finding pertinent research concepts and combining them into a semantic map, (iii) selecting the most influential concepts and relations for parameterization, (iv) choosing multi-view research concept descriptor constructs and parameters (indicators, variables, and constants) for study, (v) creating sharable multi-modal representations of the research model, and (vi) external validation of the content by researchers and stakeholders. An adapted version of the validation square approach is used in then last assessment. The approved TRM is the starting point of the development of supradisciplinary research designs – this is however not addressed here due to page limitations.

We live in an age in which new things are emerging faster than their deep understanding. This statement, in particular, applies to doing research and educating university students concerning next-generation cyber-physical systems (NG-CPSs). The fast evolution of this system paradigm would have expected a rapid and comprehensive paradigmatic change in research and education concerning this family of systems. However, this has not happened yet. Seeking a sufficient explanation, this paper reviews the current literature and attempts to cast light on the most significant recent developments in the field of NG-CPSs. The main assumptions of the authors are that research and education should appear in harmony in academic knowledge acquisition and distribution processes and that the academic education of NG-CPSs should be organized and conducted according to a defendable future vision. Combining the results of a broadly based study of the literature with prognostic critical thinking and personal experiences, this review-based position paper first discusses the current sociotechno-scientific environment, the involved stakeholders, and the demands and two approaches of truly systems-oriented education. Then, it concentrates on (i) the recognized limitations of mono- and interdisciplinary research, (ii) supradisciplinary organization of research, and (iii) transdisciplinary knowledge generation for NG-CPSs. As main contributions, the paper (i) identifies and analyzes the latest theoretical, engineering, and technological developments, (ii) reveals the major trends and their presumably significant implications, and (iii) presents several thought-provoking findings and makes propositions about the desirable actions.

This second Part of the paper (i) develops a detailed procedural model for handling complicated research problematics, (ii) transfers the procedural framework into a scenario of processing steps, (iii) demonstrates the deployment of the procedural scenario in a sample case, and (iv) addresses some important issues of research model development for supradisciplinary research. First, the framework called Holistic Systematic Combinatorial Scoping (HSCS) is introduced that comprises 21 subsequent activity steps. To illustrate the practical application of the HSCS framework, a demonstrative case study of preventing frequently occurring accidents at an uncontrolled intersection is presented. This case-study explains how the HSCS framework can facilitate (i) semantic capturing and rendering of complicated research problematics, (ii) scoping the overall research problematics and constructing definitive research problematics, and (iii) deriving a manageable research model of definitive research problematics. Further research intends to test the methodology by transdisciplinary research collectives and other CPSs related problematics.

Application-specific reasoning mechanisms (ASRMs) development is a rapidly growing domain of systems engineering. A demonstrative implementation of an active recommender system (ARS) was realized to support designing ASRMs and to circumvent procedural obstacles by providing context-sensitive recommendations. The specific problem for the research presented in this paper was the development of a synthetic validation agent (SVA) to simulate the decisional behaviour of designers and to generate data about the usefulness of the recommendations. The fact of the matter is that the need for the SVA was raised by the pandemic, which prevented involving groups of human designers in the recommendation testing process. The reported research had three practical goals: (i) development of the logical fundamentals for the SVA, (ii) computational implementation of the SVA, and (iii) application of the SVA in data generation for the evaluation of usefulness of recommendation. The SVA is based on a probabilistic decisional model that quantifies decisional options according to the assumed decisional tendencies. The three key concepts underlying the SVA are (i) decisional logic, (ii) decisional knowledge, and (iii) decisional probability. These together enable generation of reliable data about the decisional behaviours of human designers concerning the obtained recommendations. The completed tests proved the above assumption.

There are many large-scale, transdisciplinary research problematics associated with next-generation cyber-physical systems, which are difficult to capture, analyze, and transfer into sharable research models. This two-part paper is intended to contribute to a better understanding and to provide a systematic approach to describing, scoping, and specifying manageable contents for transdisciplinary research models. Part 1 of the paper analyzes the essence and the interplays of the most important current trends, and creates a robust theoretical and methodological foundation for capturing and scoping research problematics associated with the evolving paradigm of cyber-physical systems. The elaboration and deployment of the proposed approach are discussed in detail in Part 2. Besides the overall procedural framework of the proposed holistic systematic combinational breakdown, all steps are explained and exemplified in an illustrative real-life example. The discussion in both Parts concludes with a number of propositions and further research opportunities concerning the theoretical and methodological foundations.

System knowledge and reasoning mechanisms are essential means for intellectualization of cyber-physical systems (CPSs). As enablers of system intelligence, they make such systems able to solve application problems and to maintain their efficient operation. Normally, system intelligence has a human-created initial part and a system-produced (extending) part, called synthetic system intelligence (SSI). This position paper claims that SSI can be converted to a new industrial asset and utilized as such. Unfortunately, no overall theory of SSI exists and its conceptual framework, management strategy, and computational methodologies are still in a premature stage. This is the main reason why no significant progress has been achieved in this field, contrary to the latent potentials. This paper intends to contribute to: (i) understanding the nature and fundamentals of SSI, (ii) systematizing the elicitation and transfer of SSI, (iii) exploration of analogical approaches to utilization of SSI, and (iv) road-mapping and scenario development for the exploitation of SSI as an industrial asset. First, the state of the art is surveyed and the major findings are presented. Then, four families of analogical approaches to SSI transfer are analyzed. These are: (i) knowledge transfer based on repositories, (ii) transfer among agents, (iii) transfer of learning resources, and (iv) transfer by emerging approaches. A procedural framework is proposed that identifies the generic functionalities needed for a quasi-autonomous handling of SSI as an industrial asset. The last section casts light on some important open issues and necessary follow-up research and development activities.

COllaborative DEsign in Virtual Environment (CODEVE) is a teaching methodology developed within the European Global Product Realization (EGPR) course over a number of years. Today’s products are global and our students engage in their early professional practice facing challenges of working within distributed organisations to develop global products. Following early research on methods and tools in educating students for such challenges, the Global Product realisation course was initiated at the dawn of 21st Century and was performed since then as a collaboration between European Universities. Each year, an Academic Virtual Enterprise of participating Universities and an Industrial partner is formed in which students are distributed in international teams formed from multiple partner Universities. Educational activities and the project tasks are primarily communicated through video-conferencing and other synchronous and asynchronous means of communication. The design process model applied in CODEVE originates from the model of Pahl and Beitz, but is extended and adapted to suit the fuzzy front end of design projects performed in academic virtual enterprises. The extensions are related to creating a vision and implementing design research methodologies at the start of the project, blending phases of embodiment and detail design as well as bringing students for the first time in the final workshop which is aimed to culminate with the working prototype and public presentations of the products. The CODEVE methodology was tested on projects which include design of consumer products, service driven products and industrial machinery. The evaluation of the methodology was supported by the Erasmus + funded project called Networked Activities for Realization of Innovative Products (NARIP) from 2015–2017.

The CODEVE teaching methodology enables students to work on an industrial project, it encourages them to understand and explore methods from other disciplines and helps them to overcome barriers of distributed environment. Similarly, they realise that communication style, relationships with teammates, and the availability and clarity of shared information play a crucial role in the realisation of the project.

The CODEVE methodology has been implemented in academic institutions in Europe and tested in both European and transatlantic projects with Universities from Europe and America. This chapter outlines advantages and challenges in conducting this type of educational projects including the influence of the selection of product, industrial partners, marketing, implementation etc.

Cyber-physical systems (CPSs) are seen as one of the tangible results of the convergence of advanced information technology, nanotechnology, biotechnology, cognitive science, and social science in addition to conventional systems science, engineering, and technologies. Designing next-generation cyber-physical systems (NG-CPSs) is a challenging matter for abundant reasons. It is not possible to consider all reasons and to address their interplays simultaneously in one paper. Therefore, this position paper elaborates only on a selected number of topical issues and influential factors. The author claims that the shift of the paradigm of CPSs and the uncertainty related to the paradigmatic systems features of NG-CPSs are among the primary reasons. Since the future of CPSs will be influenced strongly by their intellectualization, adaptation/evolution, and automation, these aspects are also addressed. It is argued that interaction and cooperation with NG-CPSs should be seen from a multi-dimensional perspective and that socialization of NG-CPSs needs more attention in research. The need for aggregation, management, and exploitation of the growing amount of synthetic systems knowledge produced by smart CPSs is seen by the author as an important emerging concern.

Conceptualization and design of intellectualized, socialized, and personalized cyber-physical systems (CPSs) need integration of existing knowledge across the involved disciplines, as well as exploration and synthesis of novel knowledge beyond disciplinary boundaries. The latter needs a combined use of interdisciplinary, multidisciplinary, and transdisciplinary research. Supradisciplinary research has emerged as a new doctrine of combining these research approaches from epistemological, methodological, and procedural perspectives. However, no methodology can be found in the literature that could facilitate the practical execution of supradisciplinary research programs. This position paper proposes a conceptual framework that can be used as a blueprint for operationalization of such undertakings. The framework rests on six generic pillars: (i) problematics, (ii) infrastructure, (iii) method, (iv) stakeholders, (v) operations, and (vi) knowledge. It specifies the major concerns that have to be taken into consideration in a systematic manner in developing executional scenarios for supradisciplinary research. The framework facilitates (i) management of research organization tasks, (ii) joint formation of shared research infrastructure, (ii) setting up concrete research program, (iii) academic partnering and public stakeholder involvement, (iv) process flow management and capacity/competence allocation, (v) a holistic knowledge synthesis, assessment, and consolidation, and (vi) development of tools supporting the preparation and execution of large-scale supradisciplinary research. In its current form, it does not cover the specific societal and personal issues of a successful organization of the inquiry at individual researchers, research teams, and research community levels. A community-based follow-up research may focus on the practical application and testing of the framework in concrete cases-a task that an individual researcher cannot address.

This Extended Editorial has been compiled by the members of the Editorial Board to celebrate the 25th anniversary of the establishment of the Journal of Integrated Design and Process Science, which operates as the Transactions of the Society for Process and Design Science. The paper divides in three parts. The first part provides a detailed overview of the preliminaries, the objectives, and the periods of operation. It also includes a summary of the current application-orientated professional fields of interests, which are: (i) convergence mechanisms of creative scientific disciplines, (ii) convergence of artificial intelligence, team and health science, (iii) convergence concerning next-generation cyber-physical systems, and (iv) convergence in design and engineering education. The second part includes invited papers, which exemplify domains within the four fields of interest, and also represent good examples of science communication. Short synopses of the contents of these representative papers are included. The third part takes the major changes in scientific research and the academic publication arena into consideration, circumscribes the mission and vision as formulated by the current Editorial Board, and elaborates on the planned strategic exploration and utilization domains of interest.

Machlup, F. used the words alpha, beta, and gamma to identify humanities, science, and social science as three distinct fields of academic learning and knowing, in addition to general knowledge. Gilles, W. and Paquet, G. identified a fourth type of disciplinary knowledge and labelled it as delta. This includes the knowledge of creative disciplines such as design, law, and economy. Since the time of these road-paving works, a lot has changed. In the last two decades, various concepts and manifestations of intellectualized engineered systems have appeared. A paradigmatic feature ofthese systems, exemplified by smart cyber-physical systems, is that they collect, infer, or extract massive amount of synthetic system knowledge (M-SSK) based on some pre-programmed human knowledge. The amount of this type of knowledge grows continuously. It can be aggregated on system level as well as on system of systems level. This paper argues that this aggregated M-SSK is not covered by the abovementioned four genres of knowledge. In fact, it represents a new genre. The conducted literature study underpins this claim. Therefore, the paper suggests dealing with it as a new genre, called epsilon-knowledge. Artificial intelligence, system engineering, cyber-physical systems, and knowledge engineering are the disciplines dealing with epsilon-knowledge. The paper refers to sympérasmology as the proper conceptual framework of studying this genre of knowledge.

The special issue of the Journal of Integrated Design and Process Science (JIDPS) discusses inventive approaches to competitive systems engineering, including any new developments in the area. It focuses on how inventiveness can be achieved in such a conventional domain as general systems engineering and how researchers see milestones of invention such as a steam engine, a transformer, a transistor, a television, a computer, and the like in the current days. It investigates whether the published inventions and patent proposals based on the results of the ongoing ground-braking scientific inquiry and learning, or do they involve only small steps and low risk of adaptation. This special issue is designed to cast light on some inventive approaches to competitive systems engineering. The motivation has come from the outcome of the abovementioned effort to get deeper insights in resources of non-traditional system engineering as well as in the interest of the journal concerning the phenomenon and manifestation of convergence in the creative and inventive practices.

Machlup used the words alpha, beta, and gamma to identify humanities, science, and social science as three distinct fields of academic learning and knowing, in addition to general knowledge. Gilles and Paquet identified a fourth type of disciplinary knowledge and labeled it as delta. This includes the knowledge of creative disciplines such as design, law, and economy. Since the time of these road-paving works, a lot has changed. In the last two decades, various concepts and manifestations of intellectualized engineered systems have appeared. A paradigmatic feature of these systems, exemplified by smart cyber-physical systems, is that they collect, infer, or extract massive amount of synthetic system knowledge (M-SSK) based on some pre-programmed human knowledge. The amount of this type of knowledge grows continuously. It can be aggregated on system level and on system of systems level. This paper argues that this aggregated M-SSK is not covered by the abovementioned four genres of knowledge. In fact, it represents a new genre. The conducted literature study underpins this claim. Therefore, the paper suggests dealing with it as a new genre, called epsilon-knowledge. Artificial intelligence, system engineering, cyber-physical systems, and knowledge engineering are the disciplines dealing with epsilon-knowledge. The paper refers to sympérasmology as the proper conceptual framework of studying this genre of knowledge.

Applicability testing of constructive computational mechanisms (CCMs) is a new challenge for both the academia and the industry. The overwhelming majority of the existing validation approaches focuses on the internal validity of CCMs (e.g. consistency, bias), while there is a shortage of efficient approaches for assessing the external validity (e.g. applicability, reusability). The objective of this paper is to clarify the concepts and criteria, and to develop an approach for a systematic evaluation of the applicability of a given CCM to cases that were not considered at design time. The approach is adapted from the validation square approach (VSA). The adapted methodology (A-VSA) makes it possible to evaluate CCMs from (a) theoretical structural, (b) empirical structural, (c) theoretical performance, and (d) empirical performance dimensions. Altogether eight indicators are introduced that support the evaluation process. The effectiveness of the A-VSA was confirmed through a case study, in which a specific CCM is considered and the strategy of the A-VSA was operationalized with three completely different application cases. As evidenced by the results, the proposed A-VSA establishes a tight coupling among the enablers embraced by a CCM and the aspects of theoretical and empirical validation, which approves the approach to be an efficient tool for defining the range and/or the extent of applicability. The advantage of the A-VSA is that it offers a way to transfer qualitative applicability evaluation into quantitative applicability assessment, which allows the use of both subjective statements and mathematical modeling in applicability testing. The results of the assessment can guide the adaptation work of a CCM when applied to an out-of-domain application.

Cyber-physical systems (CPSs) represent practical examples of the integration of bits and atoms in human and social contexts and contribute to the integration of neurons and genes into system implementation. Many experts believe that a deeper theoretical understanding of system adaptation will lead to the development of autonomous systems and adjustable autonomy. In terms of the introduction of changes, adaptation can be made during idle time or runtime. In addition, adaptation can be externally initiated and internally initiated. In terms of intentionality indispensable, planned, or self-decided adaptations are distinguished. Adaptations are planned during the design time, runtime, or in both. Internally initiated adaptation is self-adaptation, a form of system operation in which the goals and rules of adaptation are not provided by external controllers. Internally initiated control intertwines the logics of application functions and adaptation functions. This approach is based on programming language features, such as conditional expressions, parameterization, and exceptions in software (SW) systems.

The deposition process of wire and arc additive manufacturing (WAAM) is usually planned based on a bead geometry model (BGM), which represents the relationship between bead geometries (e.g. width, height) and required deposition parameters. However, the actual deposition situation may deviate from the one in which the BGM is built, such as varied heat dissipation conditions, resulting in morphological changes of deposited beads and geometrical errors in the formed parts. In this paper, a novel control mechanism for enhancing the fabrication accuracy of WAAM based on fuzzy-logic inference is proposed. It considers the geometrical errors measured on already deposited layers and deposition context to adjust deposition parameters of beads in the subsequent layer, forming an interlayer closed-loop control (ICLC) mechanism. This paper not only presents the theoretical fundamentals of the ICLC mechanism but also reports the technical details about utilizing this mechanism to control the forming height of multi-layer multi-bead (MLMB) components. A fuzzy-logic inference machine was applied as the core component for calculating speed change of bead deposition based on height error and previously applied change. In terms of validation, the effectiveness of the proposed control mechanism and the implemented controller was investigated through both simulative studies and real-life experiments. The fabricated cuboid blocks showed good accuracy in height with a maximum error of 0.20 mm. The experimental results implied that the proposed ICLC approach facilitates deposition continuity of WAAM, and thus enables process automation for robotic manufacturing.

Though they can be traced back to different roots, both smart design and smart systems have to do with the recent developments of artificial intelligence. There are two major questions related to them: (i) What way are smart design and smart systems enabled by artificial narrow, general, or super intelligence? and (ii) How can smart design be used in the realization of smart systems? and How can smart systems contribute to smart designing? A difficulty is that there are no exact definitions for these novel concepts in the literature. The endeavor to analyze the current situation and to answer the above questions stimulated an exploratory research whose first findings are summarized in this paper. Its first part elaborates on a plausible interpretation of the concept of smartness and provides an overview of the characteristics of smart design as a creative problem solving methodology supported by artificial intelligence. The second part exposes the paradigmatic features and system engineering issues of smart systems, which are equipped with application-specific synthetic system knowledge and reasoning mechanisms. The third part presents and elaborates on a conceptual model of AI-based couplings of smart design and smart systems. The couplings may manifest in various concrete forms in real life that are referred to as "connectors"in this paper. The principal types of connectors are exemplified and discussed. It has been found that smart design tends to manifest as a methodology of blue-printing smart systems and that smart systems will be intellectualized the enablers of implementation of smart design. Understanding the affordances of and creating proper connectors between smart design and smart systems need further explorative research.