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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.

Hazard-intense applications of cyber-physical systems (CPSs), such as the evacuation of a building on fire, require personalized informing on the basis of a real-time assessment of dynamic context. In this paper, a context-dependent message construction mechanism (CD-MCM) is proposed with the objectives (i) to inform people about the emergence and development of a situation unsafe for them, and (ii) to instruct them what they have to do according to an adaptively computed action plan. To achieve this, the concepts of 'situation' and 'impact indicator' have been introduced in order to facilitate the computation of personalized action plans and to send messages about the level of danger and the requested actions. In both activities, the inferred implications of situations are used as the basis of informing the involved people. The messages are adapted to actual situations. In addition, the concept of 'relevance indicator' was utilized to assess the significance of the standing situations for the concerned people in a quasi-real-time manner. The level of danger was evaluated for each person by totaling the values of the situation-related relevance indicators. This was also used to select the proper message templates from the predefined alternatives in the process of message construction. The personalized messages were generated based on the chosen message template and the various message components describing concerned situations or providing instructions. The CD-MCM was validated in a simulated indoor fire evacuation guiding application. In the practical evaluation of the quality of the generated messages, a sample of test people was involved. The results of the evaluation show that the messages generated by the proposed CD-MCM lead to more effective messaging about the personal context and the expected actions than the messages constructed by using static context information only. The reason is that the proposed template-based message construction mechanism facilitates the appropriateness as well as the articulation of the contents of context-sensitive personalized messages.

The aim of this section is to provide an overview on the state of the current research, the exposition of the challenges faced in various fields of knowledge formalisation and representation (KFR),...

Smart CPSs (S-CPSs) have been evolving beyond what was identified by the traditional definitions of CPSs. The objective of our research is to investigate the concepts and implementations of reasoning processes for S-CPSs, and more specifically, the frameworks proposed for the fuzzy front end of their reasoning mechanisms. The objectives of the paper are: (i) to analyze the framework concepts and implementations of CPS, (ii) to review the literature concerning system-level reasoning and its enablers from the points of view of the processed knowledge, building awareness, reasoning mechanisms, decision making, and adaptation. Our findings are: (i) awareness and adaptation behaviors are considered as system-level smartness of S-CPSs that are not achieved by traditional design approaches; (ii) model-based and composability approaches insufficiently support the development of reasoning mechanisms for S-CPSs; (iii) frameworks for development of reasoning in S-CPS should support compositional design. Based on the conclusions above, we argue that coping with the challenges of compositionality requires both software-level integration and holistic fusion of knowledge by means of semantic transformations. This entails the need for a multi aspect framework that is able to capture at least conceptual, functional, architectural, informational, interoperation, and behavioral aspects. It needs further investigation if a compositionality enabling framework should appear in the form of a meta-framework (abstract) or in the form of a semantically integrated (concrete) framework. Highlights Smartness in CPSs is a holistic and synergistic behavioral characteristic. Complex mental representations are compositional. Compositionality is necessary for smart CPSs. Without a rigorous unifying framework, designing synthesis reasoning remains ad hoc.

Owing to the results of research in system science, artificial intelligence, and cognitive engineering, engineered systems are becoming more and more powered by knowledge. Complementing common-sense and scientific knowledge, system knowledge is maturing into a crucial productive asset. However, an overall theory of the knowledge of intellectualized systems does not exist. Some researchers suggest that time has come to establish a philosophically underpinned theoretical framework. This motion is seconded by the on-going intelligence revolution, in which artificial intelligence becomes a productive power, enabler of smart systems, and a strong transformer of the social life. The goal of this paper is to propose a skeleton of the needed generic theory of system knowledge (and a possible new branch of philosophical studies). The major assumption is that a significant part of the synthetic system knowledge (SSK) is &ldquo, symp&eacute, rasma&rdquo, that is, knowledge conjectured, inferred, constructed, or otherwise derived during the operation of systems. This part will become even more dominant in the future. Starting out from the above term, the paper suggests calling this theory &ldquo, rasmology&rdquo, Some specific domains of &ldquo, rasmological&rdquo, studies, such as (i) manifestations of SSK, (ii) mechanisms of generating SSK, (iii) dependability of SSK, (iv) operational power of SSK, (v) composability of SSK, and (vi) advancement of SSK, are identified. It is understood that the essence and status of SSK cannot be investigated without considering the related cognitive processes and technological enablers. The paper presents a number of open questions relevant for follow-up discussions.

Nautical traffic management in The Netherlands is shifting from local traffic control to corridor traffic management. Current traffic management systems do not sufficiently support operators in perceptual and cognitive process to interpret and understand the large amounts of information needed for corridor traffic management. Newly developed user interface concepts aim to overcome deficiencies of current interface designs that insufficiently support situation awareness assessment. The effects of these new user interfaces, however, are insufficiently known due to the intricate relations between situation awareness, task performance, and workload. The objective of this study is to evaluate the effects of the three previously developed user interface concepts on operators’ situation awareness, task performance, and workload to gain better insights into the benefits and limitations of the user interface design concepts. The effects were tested in a simulator environment. The results show that user interface features of an integrated user interface allowed operators to apply more effective information processing, which resulted in better task performance. Features of a context-dependent adaptable user interface triggered proactive behavior of operators, which resulted in better task performance for tasks in which operators require insight into future activities of the elements in the environment.

Conventionally, a technical system is defined in the design phase and considers all important requirements and aspects. The expected operations and the circumstances of operations are to be known in advance. If these are known, then the designed system can even be validated before it is produced or launched on the market. Validation is typically based on predictive analyses or simulations. However, these do not apply completely in the case of smart systems such as smart cyber-physical systems (S-CPSs) which self-manage their operation, or at least a part of it. Being able to adapt during run-time and evolve over time, S-CPSs cannot be validated using conventional deterministic approaches. Typical examples of these self-managing systems are S-CPSs already used as instrumentation in the medical field. The above circumscribed situation stimulated our background research, the results of which are concisely summarized and critically concluded in this paper. The literature has been found fairly narrow in terms of novel validation approaches for self-managing systems. The literature proposes to share the tasks of operational and behavioral validation among the system designers and the technical systems themselves. While designers need prognostic approaches to validate system operation, systems need to construct validation plans and execute them at run-time. This requires additional, validation-specific functionalities and context-dependent mechanisms such as run-time validation frameworks or meta-models, objective-sensitive self-monitoring mechanisms, self-constraining and self-supporting mechanisms, and other enablers. Extensive foundational research and system prototype testing are deemed to be indispensable. To make the first small step in this direction, this paper proposes a concept for the validation of smart medical CPSs. This relies on the following hypothesis: If a system has the freedom for self-adaptation, then it should also be equipped with a self-control mechanism, meta-knowledge, and a supervisory controller. These additional resources enable purpose- and context-dependent semantic reasoning about the operational objectives and behavioral states. This paper suggests a number of topics for future research towards a run-time validation engine.

Cyber-physical systems (CPSs) have sophisticated control mechanisms that help achieve optimal system operations and services. These mechanisms, imply considering multiple signal inputs in parallel, to timely respond to varying working conditions. Despite the advantages that control mechanisms convey, they bring new challenges in terms of failure prevention. The compensatory action the control exerts cause a fault masking effect, hampering fault diagnosis. Likewise, the multiple information inputs CPSs have to process can affect the timely system response to faults. This article proposes a failure prognosis method, which combines time series-based forecasting methods with statistically based classification techniques in order to investigate system degradation and failure forming on system levels. This method utilizes a new approach based on the concept of the system operation mode (SOM) that offers a novel perspective for health management that allows monitoring the system behavior, through the frequency and duration of SOMs. Validation of this method was conducted by systematically injecting faults in a cyber-physical greenhouse testbed. The obtained results demonstrate that the degradation and fault forming process can be monitored by analyzing the changes of the frequency and duration of SOMs. These indicators made possible to estimate the time to failure caused by various failures in the conducted experiments.

Continuous enhancements of connected products make them able to generate and communicate a huge amounts of middle-of-life data streams to their producers. This affordance also creates a challenge for current data analytics tools unable to keep up with the heterogeneous nature and characteristics of these type of data. Accordingly, a function able to combine data from multiple data streams and analyze them as one source of information is definitely needed in a next-generation data analytics toolbox to support product enhancements by designers. As a result of a recent Ph.D. project, this paper presents the conceptualization and the implementation of a novel function of merging middle-of-life data streams. The implemented computational mechanism (i) acquires middle-of-life data streams, (ii) pre-processes them individually, (iii) merges information from the concerned streams, (iv) derives recommendation based on the merged information, and (v) send a recommendation as a message to the designer. The performance of the computational implementation was tested in an application case of data steaming and management to white goods designers for enhancing a connected washing machine. From a computational point of view, the testing proved that the set of proprietary algorithms designed for the realization of computational merging, together with the existing ones taken from the literature, were able to efficiently perform the subtasks. The advantages of merges were: (i) it provides more information than the one obtained by processing sensors' data individually, (ii) it reflects the condition of the product with a higher fidelity, (iii) it communicates information about the product while it is in use by the customer, (iv) it reduces the sensors analyses time and effort, and (v) it provides recommendation as an action plan concerning the product at hand. The outcomes of this study will be used in a follow up research to develop a comprehensive smart data analytics toolbox to support product designers in product innovation.

Complementing our previous publications, this paper presents the information schema constructs (ISCs) that underpin the programming of specific system manifestation feature (SMF) orientated information management and composing system models. First, we briefly present (1) the general process of pre-embodiment design with SMFs, (2) the procedures of creating genotypes and phenotypes of SMFs, (3) the specific procedure of instantiation of phenotypes of SMFs, and (4) the procedure of system model management and processing. Then, the chunks of information needed for instantiation of phenotypes of SMFs are discussed, and the ISCs designed for instantiation presented. Afterwards, the information management aspects of system modeling are addressed. Methodologically, system modeling involves (1) placement of phenotypes of SMF in the modeling space, (2) combining them towards the desired architecture and operation, (3) assigning values to the parameters and checking the satisfaction of constraints, and (4) storing the system model in the SMFs-based warehouse database. The final objective of the reported research is to develop an SMFs-based toolbox to support modeling of cyber-physical systems (CPSs).

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

Smart cyber-physical systems (S-CPSs) are complex engineered systems empowered by cyber-physical computing and equipped with the capability of reasoning, learning, adapting, and evolving. As an outcome of data-driven dynamic computing, reasoning capabilities, and the run-time obtained own knowledge, nonlinear and emergent behavior of S-CPSs whilst in operation is an open issue, not experienced in the case of conventional technical systems. This paper analyzes the technical issues of run-time operation and emergent behavior of S-CPSs, reviews the current understanding and state of advancement in designing S-CPSs for run-time, explores the paradox, and issues of designing for run-time adaptation, and synthesizes some general principles that can be taken into consideration when addressing the challenges, first of all, in the context of advanced manufacturing systems. This paper introduces four levels of CPSs according to reasoning capabilities and adaptation freedom of systems, and recognizes the paradox that a system with a higher level of freedom requires a higher level of self-control and resource management according to the overall objective of operation. Specific and common design principles are presented and critically assessed for each advancement level of CPSs. The principles synthesized by the authors provide only a partial fulfillment of the generic need. The planned future research addresses these issues and proposes (largely implementation and application independent) genuine principles for system developers.

To be able to provide appropriate services in social and human application contexts, smart cyber-physical systems (S-CPSs) need ampliative reasoning and decision-making (ARDM) mechanisms. As one option, procedural abduction (PA) is suggested for self-managing S-CPSs. PA is a knowledge-based computation and learning mechanism. The objective of this article is to provide a comprehensive description of the computational framework proposed for PA. Towards this end, first the essence of smart cyber-physical systems is discussed. Then, the main recent research results related to computational abduction and ampliative reasoning are discussed. PA facilitates beliefs-driven contemplation of the momentary performance of S-CPSs, including a ‘best option’-based setting of the servicing objective and realization of any demanded adaptation. The computational framework of PA includes eight clusters of computational activities: (i) run-time extraction of signals and data by sensing, (ii) recognition of events, (iii) inferring about existing situations, (iv) building awareness of the state and circumstances of operation, (v) devising alternative performance enhancement strategies, (vi) deciding on the best system adaptation, (vii) devising and scheduling the implied interventions, and (viii) actuating effectors and controls. Several cognitive algorithms and computational actions are used to implement PA in a compositional manner. PA necessitates not only a synergic interoperation of the algorithms, but also an objective-dependent fusion of the pre-programmed and the run time acquired chunks of knowledge. A fully fledged implementation of PA is underway, which will make verification and validation possible in the context of various smart CPSs.

Our long-term objective is to develop a software toolbox for pre-embodiment design of complex and heterogeneous systems, such as cyber-physical systems. The novelty of this toolbox is that it uses system manifestation features (SMFs) for transdisciplinary modeling of these systems. The main challenges of implementation of the toolbox are functional design- and language-independent computational realization of the warehouses, and systematic development and management of the various evolving implements of SMFs (genotypes, phenotypes, and instances). Therefore, an information schema construct (ISC) based approach is proposed to create the schemata of the associated warehouse databases and the above-mentioned SMF implements. ISCs logically arrange the data contents of SMFs in a set of relational tables of varying semantics. In this article we present the ISCs necessary for creation of genotypes and phenotypes. They increase the efficiency of the database development process and make the data relationships transparent. Our follow-up research focuses on the elaboration of the SMF instances based system modeling methodology.

Maintaining and enhancing engagement of patients during stroke rehabilitation exercises are in the focus of current research. There have been various methods and computer supported tools developed for this purpose, which try to avoid mundane exercising that is prone to become a routine or even boring for the patients and leads to ineffective training. This paper proposes a strategy bundle-based smart learning mechanism (SLM) to increase the efficiency of rehabilitation exercises. The underpinning strategy considers motor, perceptive, cognitive and emotional aspects of engagement. Part of a cyber-physical stroke rehabilitation system (CP-SRS), the proposed SLM is able to learn the relationship between the actual engagement levels and applied stimulations. From a computational point of view, the SLM is based on multiplexed signal processing and a machine learning agent. The paper presents the mathematical concepts of signal processing, the reasoning algorithms, and the overall embedding of the SLM in the CP-SRS. Regression and classification are two possible solutions for this learning mechanism. Computer simulation is conducted to investigate the limitations of the proposed learning mechanism and compare the results of different machine learning methods. We simulate regression with artificial neural network (ANN), and classification with ANN and Naive Bayes (NB). Results show that classification with NB is more promising in practice since it is less sensitive to the deviations in the inputs than the applied version of ANN.

Various system-engineering frameworks (SEFs) have been developed for composable systems, whose overall operation is the sum of the operations of their components. However, smart cyber-physical systems (S-CPSs) are compositional in nature. Their reasoning capability and system knowledge assume an ‘ampliative’ (inter)operation of all hardware, software, or cyberware components. The need for SEFs that support synthesis, modeling, analysis, simulation, verification, and validation of S-CPSs is recognized in the literature. The objective of this paper is a critically review the state of development of compositionality enabling frameworks. Both quantitative and qualitative literature studies were conducted in combination with critical system thinking. The reasoning model used in the qualitative analysis was derived based on the findings of the quantitative analysis. The major observations are: (i) the notion of compositionality is not studied extensively in the context of S-CPSs that do not obey the principle of reductionism, (ii) methodological support of implementation of compositional CPSs seems to be in its infancy, (iii) SEFs may play a crucial role in synthesis, modeling and implementation of S-CPSs, and (iv) SEFs for compositional system design may be realized using the principles of semantic knowledge fusion or meta-synthesis. Our follow up research targets a formal definition and computational implementation of a testable prototype of a specific SEF tool supporting compositional design of reasoning mechanisms.Copyright © 2018 by ASME

There has been intense foundational research in complex technical systems (CTSs) over the last half century. These systems are exemplified by advanced mechatronics systems, embedded control systems, real-time systems, agent-based smart systems, distributed software systems, internet of things systems, and cyber-physical systems. The objective of this paper is to offer an initial cataloguing of the various research domains and to identify the major research issues. The paper has an ontological flavour, because it concentrates on what research has been and is being done, rather than on why and how research is done. The underpinning study has been done in three stages: (i) intuition-driven exploration of a reference set of related academic publications, (ii) evidence-based specification of a categorization of the domains and subdomains of research, and (iii) refinement and validation of the proposed classification based on a control set of related academic publications. The proposed reasoning model identifies three categories of research domains. The ‘intellectualizations’ category includes research domains such as: (i) philosophy, (ii) ontology, and (iii) epistemology of CTSs. The research domains included in the ‘realizations’ category are: (iv) methodology, and (v) creation of CTSs. The domains considered in the ‘influences’ category are: (vi) manifestations, and (vii) axiology of CTSs. Based on the proposed reasoning model a landscape of foundational research in CTSs is proposed for public debate. Our follow-up study focuses on the extension of the proposed classification to other families of complex engineered systems such as sociotechnical systems and social ecosystems.

As a novel computational approach, ubiquitous computing was emerging at the beginning of the 1980s and has reached a rather mature level by now. It assumes that computing can be available anywhere, anytime and in any context due to technological developments, social demands and calm implementations. Over the years, the opportunities of this computing paradigm have been explored and the benefits have been exploited successfully in many application fields. This survey paper addresses ubiquitous computing from the perspective of enabling computer aided design. The specific objectives of the reported survey are to: (i) give an overall account of the current status of ubiquitous computing and technologies, (ii) cast light on how ubiquitous computing has influenced the development of CAD systems, tools, and methods, and (iii) critically investigate future development opportunities of ubiquitous computing enabled computer aided design. First, the paper discusses the principles and typical technologies of ubiquitous computing. Then, the development and spectrum of the so-called standard computer aided design tasks are analyzed from a computational point of view. Afterwards, the already implemented design enabling functionalities are discussed and some additional functional possibilities are considered. The literature provides evidence that ubiquitous computing has not managed to revolutionize the methodologies or the systems of computer aided design so far, though many researchers intensively studied the affordances and the application possibilities of ubiquitous technologies. One reason is that ubiquitous computing technologies had in the last two decades to compete with other kinds of computational technologies, such as high-capacity computing, high-speed networking, immersive virtual reality, knowledge ontologies, smart software agents, mobile communication, etc., which had a much stronger influence on the development of computer aided design methods and systems. In combination with the rather conservative and conventionalist industrial practice of CAD system development and application, this may explain why the ubiquitous computing revolution remained weak in computer aided design. The literature clearly indicates that application of ubiquitous technologies did not lead to radically new functionalities that could have been exploited by the concerned industries. Consequently, it seems to be possible that computer aided design simply steps over the paradigm of ubiquitous computing and expects new functionalities from the emerging new computing paradigms, such as brain-computer interfacing, cyber-physical computing, biological computing, or quantum computing. An overall account of the status of ubiquitous computing and technologies in CAD.Penetration of ubiquitous computing remained insignificant in most applications.Application of ubiquitous technologies did not lead to radically new functionalities.Computer aided design steps over the paradigm of ubiquitous computing.New CAD functionalities expected from the emerging new computer paradigms.

Authors belonging to different institutions (‘schools’) of cyber-physical systems (CPSs) research and development report on largely different objectives, underpin their work with different theories and methodologies, and target characteristics which can actually better characterize other categories and families of engineered systems. This has resulted in an ontological chaos. Therefore, our research addressed the question: What exists in the form of past, current and future CPSs? Our hypothesis has been that we can have an ordered picture on the landscape of CPSs by introducing the notion of system generation. Generation is a structural term defined as a ‘technological/engineering cohort’ of different individual manifestation of systems that reflect genotypic features of ancestor systems belonging to the same category, but deviates from them with regards to their phenotypic features. Based on our literature findings, we have defined five generations of CPSs, which could be differentiated based on: (i) the level of self-intelligence, and (ii) the level of self-organization. The zeroth generation includes look-alikes and partial implementations of CPS. The 1G-CPSs include systems with self-regulation and self-tuning capabilities, while the 2G-CPSs are capable to operationalize self-awareness and self-adaptation. The 3G-CPSs are equipped with the capabilities of self-cognizance and self-evolution. According to our reasoning model, only the fourth generation of CPSs is supposed to achieve self-consciousness and self-reproduction in the form of system of systems. The paper analyses the major paradigmatic characteristics of these generations. It also provides an outlook to the trends that may have strong influence on the introduced generations of CPSs.

Some sort of ‘intellectual’ mechanisms are needed for second generation cyber-physical systems (CPSs) to be self-aware and self-adaptive. This paper (i) proposes procedural abduction (PA) as one possible mechanism for enabling smart reasoning, (ii) introduces the fundamental concepts and the computational procedure, and (iii) argues for their practical utility. PA includes eight cluster of activities: (i) run-time extraction of signals and data by sensing, (ii) recognition of events, (iii) inferring about existing situations, (iv) building awareness about the performance of the system at attaining of objectives of operation/servicing, (v) devising alternative performance enhancement strategies, (vi) designing adaptation of the parts and the system as a whole, (vii) planning the implied interventions, and (viii) actuating effectors and controls. As a computational approach, PA facilitates believes-driven contemplation of the momentary performance of a system with regards to the most relevant objective of servicing and ‘best option’-based realization of adaptiveness. Computational realization of PA necessitates a combination of a large number of conventional and specific artificial intelligence algorithms. A fully fledged implementation of PA is underway, which will make verification and validation in the context of various smart CPSs possible.

There has been an increase in the amount and complexity of traffic on Dutch inland waterways. Traffic management shifted from local traffic control to corridor traffic management. Due to these changes, operators in nautical traffic management centers experience difficulty to gain and maintain sufficient situation awareness. In our previous research, three groups of deficiencies of current situation awareness support have been identified. To overcome these deficiencies, a theoretical framework for information engineering user interface concepts was developed and used for designing three interface concepts. A coherent, an integrated and a context-dependent adaptable user interface were designed and implemented as testable prototypes. To support the process of information engineering, we combined user-centered design techniques with the formalism of set theory, directed graphs and semantic networks. From a methodological point of view, these proved to be useful both in conceptualization and implementation of the concepts. The usability of these concepts was tested in a simulator environment. The results show that the implemented prototypes represent an important improvement compared to the traditional interface solutions currently used by nautical traffic management operators. However, it was recognized that the coherent user interface implementation still suffered from a number of deficiencies. The context-dependent adaptable user interface was evaluated most positively.

Motor interaction in virtual sculpting, dance trainings, and physiological rehabilitation requires close virtual proximity of users, which may be hindered by low resolution of images and system latency. This paper reports on the results of our investigation aiming to explore the pros and cons of using ultrahigh 4K resolution displays (4096 × 2160 pixels) in remote motor interaction. 4K displays are able to overcome the problem of visible pixels and they are able to show more accurate image details on the level of textures, shadows, and reflections. It was our assumption that such image details can not only satisfy visual comfort of the users, but also provide detailed visual cues and improve the reaction time of users in motor interaction. To validate this hypothesis, we explored the relationships between the reaction time of subjects responding to a series of action-reaction type of games and resolution of the image used in an experiment. The results of our experiment showed that the subjects’ reaction time is significantly shorter in 4K images than in HD or VGA images in motor interaction with small motion envelope.

There are many real-life processes whose smart control requires processing context information. Though processing time-varied context information is addressed in the literature, domain-independent solutions for reasoning about time-varying process scenarios are scarce. This paper proposes a method for dynamic context computation concerning spatial and attributive information. Context is interpreted as a body of information dynamically created by a pattern of entities and relationships over a history of situations. Time is conceived as a causative force capable of changing situations and acting on people and objects. The invariant and variant spatial information is captured by a two-dimensional spatial feature representation matrix (SFR-matrix). The time-dependent changes in the context information are computed based on a dynamic context information (DCI) management hyper-matrix. This humble but powerful representation lends itself to a quasi-real time computing and is able to provide information about foreseeable happenings over multiple situations. Based on this, the reasoning mechanism proposed in this paper is able to provide informative instructions for users who needed to be informed in a dynamically changing situation. This paper uses the practical case of evacuation of a building in fire both as an explorative case for conceptualization of the functionality of the computational mechanism and as a demonstrative and testing application. Our intention is to use the dynamic context computation mechanism as a kernel component of a reasoning platform for informing cyber-physical systems (I-CPSs). Our future research will address the issue of context information management for multiple interrelated spaces.

Computational mechanisms (complex structures of functionally connected algorithms) are developed very frequently by both the academia and the industry for specific applications, but the transferability to other applications is seldom addressed and systematically tested. This raises the need for application validity of constructive computational methodologies (CCMs). First, this background research paper clarifies the fundamental concepts related to application validation. Applicability validation focusses on the indicators of appropriateness with regards to a particular purpose. Then, it surveys the various approaches of application validation based on the publications available in contemporary literature. Its main finding is that applicability validation of CCMs seems to be a stepchild of academic research. The same applies to the industrial exploration of the applicability of CCMs tailored to a narrow family of applications to a wider range of applications.

Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.

There are many real life processes whose smart control requires processing context information. Though the issue of processing varying context information has been addressed in the literature, domain independent solutions that can support reasoning and decision making according to time-varying process scenarios in multiple application fields are scarce. This paper proposes a method for dynamic context computation concerning spatial and attributive information. Context is interpreted as a body of information dynamically created by a pattern of entities and relationships over a history of situations. Time is conceived as a causative force capable of changing situations, and acting on people and objects. The invariant and variant spatial information is captured by a two-dimensional spatial feature representation matrix. The time-dependent changes in the context information are computed based on a dynamic context information management hyper-matrix. This humble but powerful representation lends itself to a quasi-real time computing and is able to provide information about foreseeable happenings over multiple situations. The paper uses the practical case of evacuation of a building in fire both as an explorative case for conceptualization of the functionality of the computational mechanism and as a demonstrative and testing application. Our intention is to use the dynamic context computation mechanism as a kernel component of a reasoning platform for informing cyber physical systems.

Brain signal and eye tracking technology have been intensively applied in cognitive science in order to study reading, listening and learning processes. Though promising results have been found in laboratory experiments, there are no smart reading aids that are capable to estimate difficulty during normal reading. This paper presents a new concept that aims to tackle this challenge. Based on a literature study and an experiment, we have identified several indicators for characterizing word processing difficulty by interpreting electroencelography (EEG) and electrooculography (EOG) signals. We have defined a computational model based on fuzzy set theory, which estimates the probability of word processing and comprehension difficulty during normal reading. The paper also presents a concept and functional prototype of a smart reading aid, which is used to demonstrate the feasibility of our solution. The results of our research proves that it is possible to implement a smart reading aid that is capable to detect reading difficulty in real time. We show that the most reliable indicators are related to eye movement (i.e. fixation and regression), while brain signals are less dependable sources for indicating word processing difficulty during continuous reading.

Speeding because of time pressure is a leading contributor to traffic accidents. Previous research indicates that people respond to time pressure through increased physiological activity and by adapting their task strategy in order to mitigate task demands. In the present driving simulator study, we investigated effects of time pressure on measures of eye movement, pupil diameter, cardiovascular and respiratory activity, driving performance, vehicle control, limb movement, head position, and self-reported state. Based on existing theories of human behavior under time pressure, we distinguished three categories of results: (1) driving speed, (2) physiological measures, and (3) driving strategies. Fifty-four participants drove a 6.9-km urban track with overtaking, car following, and intersection scenarios, first with no time pressure (NTP) and subsequently with time pressure (TP) induced by a time constraint and a virtual passenger urging to hurry up. The results showed that under TP in comparison to NTP, participants (1) drove significantly faster, an effect that was also reflected in auxiliary measures such as maximum brake position, throttle activity, and lane keeping precision, (2) exhibited increased physiological activity, such as increased heart rate, increased respiration rate, increased pupil diameter, and reduced blink rate, and (3) adopted scenario-specific strategies for effective task completion, such as driving to the left of the lane during car following, and early visual lookout when approaching intersections. The effects of TP relative to NTP were generally large and statistically significant. However, individual differences in absolute values were large. Hence, we recommend that real-time driver feedback technologies use relative instead of absolute criteria for assessing the driver’s state.

This article presents a new methodology that enables designers to include in simulations not only the physics aspects of artifact behavior, but also human actions. The motivation for this research came from the fact that none of the conventional approaches to engineering simulations includes manipulative control of products by users as foreseen by designers. By implementing control over physics simulations, changes in parameters can be introduced that alter the course of the simulated process. As a means to do this, we propose to use scenario bundles, with which designers can operationalize their conjectures of how human users interact with products as a series of interconnected simulations. For the imaginary use process described in a scenario bundle, the designer can specify various product designs, user characteristics, and environments, which may in each case lead to different concatenations of simulation actions. The proposal facilitates the exploration of possible mismatches and anomalies in use processes. In this article, we describe the theoretical fundamentals and the overall concept of the proposed methodology, as well as its realization as a proof-of-concept implementation. This implementation can be used as a tool to specify scenario bundles and to perform controlled simulations of human-product interaction. The use of the tool is demonstrated through a practical example. Although the implementation has proven to be successful in terms of executing scenario bundles, two bottlenecks need further attention: (i) devising stable algorithms for large deformations in physical interaction simulation and (ii) incorporation of already existing algorithms for simulation of low-level human motion control.

International audience; The paper proposes a new methodology to interactively simulate grasping of virtual product prototypes with the goal to evaluate the contact forces between the grasping hand and product as well as the load on the human arm. Interaction between product concepts and the users happens in a virtual environment, in which the user controls a virtual hand interactively. The contact between the virtual hand and the grasped product is simulated and visual feedback is provided to the user. Controlling the virtual hand interactively in real time holds many challenges. One of the challenges is mapping the motion of the user to contact forces, which then results in stable grasping of objects. In this paper we present a new methodology to convert and map the measured position of the real hand into contact forces so that the contact between the virtual hand and the object remains stable. Our approach applies a multi-objective optimization that takes into account the posture and anthropometric properties of grasping hand, as well as the penetration of the hand in the grasped virtual object in order to find the optimal arrangement of contact forces. The paper reports on the principle of our grasping control methodology as well as presents some test cases to show the advantages and disadvantages of the proposed approach.

The main statement of this paper is that synergetic modeling and co-design of the hardware, software and cyberware parts of complex cyber-physical systems (CPSs) are yet not solved, even from the perspective of an underpinning transdisciplinary theory. CPSs contain functionally tightly connected analog and digital hardware, control, and application software, and knowledge, data, and media contents as cyberware. The lack of a unified theoretical framework and an all-inclusive system conceptualization methodology can be traced back to professional, methodological and cultural differences between the abovementioned domains of development. The objective of our research is to make a step towards a theoretical framework that can support transdisciplinary modeling of CPSs. Architectural and operational modeling have been identified as two principal and interrelated dimensions of system modeling, and a mereo-operandi theory (MOT) has been identified as target. Mereotopology has been considered as the basis of architectural modeling. Operational modeling has been based on parameterized representation of the underlying physical principles, the morphological characteristics, the operation elements, and the overall operation flows. A demonstrative case study is presented to evidence the practical feasibility and utility of the proposed MOT. Our follow up research will focus on using this as a conceptual framework and computational basis for specification of system manifestation features and on a computational implementation to support embedded customization.Copyright © 2015 by ASME

Interaction with cyber-physical systems (CPSs) is a new challenge for system developers and human-system interaction designers, and but also for end-users. Due to the lack of proper insights, there are many unknowns, open issues, and eventually new challenges. For this reason, there is a need for a comprehensive theory that considers all aspects of interaction with CPSs, provides a reasoning framework, and facilitates the implementation of highly interactive CPSs. The research presented in this paper tries to make the first steps in this direction. We are aware of the fact that, in the case of CPSs, system-human interaction and system-system interaction are to be considered besides human-system interaction. Human-system interaction influenced by: (i) the level of interaction, (ii) the intellectual domains of interaction, (iii) the contexts of interaction, and (iv) the modalities of interaction. The proposed theory decomposes these into various constituents and captures the relations among them. Physical, syntactic, semantic, semantic, pragmatic and apobetic levels of interaction are considered in combination with four domains of interaction (perceptive, cognitive, motor, and emotional). In addition to the common human interaction modalities (visual, audio, haptic, etc.), the theory also considers system communication channels. It is claimed that interaction is also influenced by the implicit context implied by the specific objectives of interaction, i.e., cooperation, coordination, collaboration of coadunation, and not only by the explicit context provided by narrower and broader embedding environments of CPSs. The theory establishes explicit relationships between the above mentioned influencing factors, which are important at specifying wishful interaction profiles. The advantages that the proposed comprehensive theory offers in comparison with the traditional interaction design approaches are shown through the example of a smart bathroom.Copyright © 2015 by ASME

In this special issue a selection of recent articles is presented that report on improving and/or facilitating collaboration in product design and development by deploying technologies. The article...

This paper summarizes the results of an empirical study concerning the use of hand motions as one of the input mechanisms of a multi-modal interface of computer aided conceptual design systems for initial shape design of consumer durables. A hand motion language (HML) has been developed and used in designed experiments to describe simple, compound and hybrid shapes. The subjects were asked to reconstruct the presented shapes by sketching on paper. Comprehension of the hand motion language has been evaluated in terms of fidelity and efficiency. The results clearly indicate the potentials of a HML in shape conceptualization. In addition, the experiments revealed several new issues related to the application of the hand motion language in a multi-modal interface.

Demand from the industry motivated software vendors to address the issue of supporting collaborative conceptual design by software tools. Considering the fact that a vast number of software tools have been developed to support a mixture of design activities of collaborative conceptual design (i.e. idea generation, presentation, reasoning, and modeling) from various aspects (e.g. functionality, shape, structure, behavior, sustainability, and service), selecting the most appropriate tools is a challenging task. One of the key problems is that there are no objective techniques and procedures to compare the tools and make a decision. We propose a new quantitative approach, which evaluates shape modelers by taking into consideration the cognitive aspects of collaborative conceptual design. Conceptual design is of a dynamic nature that originates in fast idea generation and modeling, evolving concepts, and coexistence of alternative solutions. On the other hand, collaborative aspect should be supported ...

Before implementing a product data management system within a company, the internal processes of product and process development and the information handled herein should be organized well. To enable this organization, one should be able to see the bottlenecks. Therefore, the working methods and the documents involved should be made transparent. That is why the development processes of three automotive suppliers have been analyzed and documented in three representations, formatted according to a generic scheme, to gain transparency of the processes. Based on these representations, a so-called induced model of product and process development is created. In this paper, which is an extension of Vroom RW et al. (2002. In PAKM 2002, LNAI 2596, Karagiannis D, Reimer U (eds). Springer: Berlin; 347–358), the format of the representations will be explained briefly, the application method for the realization of the representations will be described and some of the results will be illustrated. Also, the problems that came up during the research will be described. Copyright © 2003 John Wiley & Sons, Ltd.

In this paper, we review the state of the art and practice in the development and quality assurance of design support software (DSS) products. We first study and analyze the processes of development of DSS products, and then review risk-reducing techniques employed in their development. Based on the analysis and the reviews, we propose a comprehensive methodology for pre-implementation testing of DSS, and concisely present its main elements. One of the distinct characteristics of the processes of development of DSS is that they are heavily research oriented. They typically involve formulation of specification requirements, selection or creation of theories, formulation of methods, designing of algorithms, and writing codes for pilot implementations. Often the problems are unclear and the solution concepts are unknown. Usually the conventional software development models and testing techniques are used in the development of DSS. The problem is that they cover only a subset of the DSS development activities and they do not scale to exactly match the needs in these processes. Almost all software development concepts or mental models demand the developers to prepare specifications, then design software and finally write codes. Even tests and reviews are conducted to exclusively ensure consistency and completeness of requirement specifications, designs and codes. A more robust methodology is required to ensure effective development and testing of DSS. What is needed is systematic development and testing of all early implementations and various stakeholders must also be systematically involved in this.

An intense shift from traditional mechatronics systems to cyber-physical systems has been taking place over the last two decades. The former systems, which integrate mechanical, electronics, computing, control and situated reasoning components, are typically implemented as closed, predefined, controlled and deterministic systems. The latter systems are characterized by open system boundaries, large functional and structural complexities, self-learning and -reasoning capabilities, partial autonomy, context-driven adaptability, and decentralized decision making. As the latest trend, they are getting more extensively embedded in the fabric of society. There exists no dedicated design theory that would explain how to conceptualize, design and realize this family of non-linear systems. In this paper, concentrating on the changing place and role of information, first an overview of the milestones of the overall physical, biological, social and technological evolution is given. Then, the distinguishing characteristics of cyber-physical systems are analysed, the current transition towards social-cyber-physical systems is considered, and the need for a comprehensive design theory for this family of systems is explained. As examples of the aspects which the design theory of social-cyber-physical systems should describe, explain, and predict, the phenomenon of: (a) aggregative complexity, (b) emergent attributes/behaviour, (c) compositional synergy, (d) multi-abstraction-based specification, (e) dynamic scalability, (f) multi-modal prototyping, and (g) integrity verification and behaviour validation are discussed and the issues of handling them in design are addressed. The main proposition is that there is an urgent need for a multi-disciplinary research in this novel domain of interest in order to facilitate a deeper disciplinary understanding and to allow the development of specific design methodologies and computational support tools.

Vague discrete modeling is a flexible and adaptable means for designers to express and shape ideas in a collaborative environment.

This paper describes the design and results of an explorative experiment done in the field of industrial design engineering. It extends the Wizard of Oz test technique by using clay as a feedback medium. The subject communicates with speech and gestures, the result is shown on a video screen. The experiment included 4 senior engineering students, each had to model four existing objects and then received a design assignment. The conclusions are that the method is applicable for simulating a multimodal design system, although there are some limitations regarding the direct manipulation of the artefact.

The communication of design model data between participants of an engineering team is a fundamental subprocess in concur rent engineering (CE). The problems encountered in data transfer are abundant. It is understood that data transfer should be enhanced to ward knowledge transfer. Although it is possible to define what knowledge transfer is in general terms, it is crucial to specify it at the subprocess level; only then loss-less data communication can be implemented in practice. We, therefore, need to specify the conditions for successful data transfer subprocesses. In this paper we investigate which conditions are specific for CE. They are then formulated using the finite automaton formalism. From these conditions it can be concluded which measures should be taken in order to avoid data exchange problems and hence to support knowledge sharing. Examples are provided and an outlook to further applications is discussed.

Research in computer support to industrial design typically involves much experimentation. Proposals for new modeling methods are commonly evaluated using pilot software implementations. The experimentation tends to be lengthy and therefore expensive. We propose a faster way to evaluate the functionality of design tools. This evaluation method, called abstract prototyping, can be used in a very early stage of the development of a computer tool, prior to any software implementation. The evaluation focuses on how potential users appreciate new modeling functions by simulating their basic properties. The method aims at decreasing the risk of building a useless tool. We have applied abstract prototyping to make a selection among different candidate shape modeling techniques. The method proved to be feasible, fast and inexpensive