The discipline of Natural Design

If we define design work as those cognitive and practical things to which designers give their valuable effort, then our Natural Design framework allows the recording and replaying of design work. Natural Design provides a meta-structural framework that has developed through our observations of engineering design in safety and mission critical industries, such as aircraft design. Our previous work has produced parametrisable models of design work for software intensive systems, and we now look to make an initial assessment of our natural design framework for its fit to the more creative design practices. In this paper we briefly sketch the framework and subsequently attempt to locate ‘creativity’ in it. We find that, although there are good strong hooks for what the designer does, we are forced to find a role for the community of the designer in the creative process in our framework, something that was only implicit in our previous work. Keywords: Natural design; Engineering design; Creativity</p

Developing systems thinking in a Project-Based Learning environment

As science and engineering projects are becoming increasingly more complex, sophisticated, comprehensive and multidisciplinary, there is a growing need for systems thinking skills to ensure successful project management. Systems thinking plays a major role in the initiation, effective management, and in facilitating inter-organizational tasks. This research assesses the capacity for engineering systems thinking and its contribution in carrying out a multidisciplinary project. The research also reviews the cognitive process through which systems thinking skill is acquired. The study focused on a group of students who have completed their senior design projects in high-tech industry, while their plans were being integrated into existing larger projects in the respective industrial sites. The systems thinking skill of the students was examined according to a questionnaire for assessing the Capacity for Engineering Systems Thinking (CEST). Statistical analysis shows significant differences in the students capacity for systems thinking at the beginning and end of the work (p<0.001). This research demonstrates that systems thinking skills can be improved through awareness and involvement in multidisciplinary projects

Characterizing High School Students\u27 Systems Thinking in Engineering Design Through the Function-Behavior-Structure (FBS) Framework

The aim of this research study was to examine high school students\u27 systems thinking when engaged in an engineering design challenge. This study included 12 high school students that were paired into teams of two to work through an engineering design challenge. These dyads were given one hour in their classrooms with access to a computer and engineering sketching paper to complete the design. Immediately following the design challenge, the students participated in a post hoc reflective group interview. The methodology of this study was informed by and derived from cognitive science\u27s verbal protocol analysis. Multiple forms of data were gathered and triangulated for analysis. These forms included audio and video recordings of the design challenge and the interview, computer tracking, and student-generated sketches. The data were coded using Gero\u27s FBS framework. These coded data were analyzed using descriptive statistics. The transitions were further analyzed using measures of centrality. Additionally, qualitative analysis techniques were used to understand and interpret systems and engineering design themes and findings. Through the qualitative and quantitative analyses, it was shown that the students demonstrated thinking in terms of systems. The results imply that systems thinking can be part of a high school engineering curriculum. The students considered and explored multiple interconnected variables, both technical as well as nontechnical in nature. The students showed further systems thinking by optimizing their design through balancing trade-offs of nonlinear interconnected variables. Sketching played an integral part in the students\u27 design process, as it was used to generate, develop, and communicate their designs. Although many of the students recognized their own lack of drawing abilities, they understood the role sketching played in engineering design. Therefore, graphical visualization through sketching is a skill that educators may want to include in their curricula. The qualitative analysis also shed light on analogical reasoning. The students drew from their personal experience in lieu of professional expertise to better understand and expand their designs. Hence, the implication for educators is to aid the students in using their knowledge, experience, and preexisting schemata to work through an engineering design

Languages for Engineering Design: Empirical Constructs for Representing Objects and Articulating Processes

Design knowledge incorporates knowledge and information about designed objects and their attributes, as well as about methods and means for undertaking the design process. Such design knowledge is articulated in several different representations or languages. This paper presents a typology of the languages of engineering design, emphasizing the representation of designed objects and the articulation and representation of the cognitive processes of design. Design languages include verbal or textual statements, drawings and graphics, formulas, and numbers. Still other design languages follow from computational styles. The languages of design and their computer-based implementations are empirical in origin, since observation reveals that these languages are derived not from an overarching theory, but from our experience in trying to understand what we do when we: talk about designed objects, articulate design processes, and teach computers how to do these things as well. Next to presenting a typology of the languages of engineering design, and discussing the role of these languages in design activity, the paper also discusses the possibility of automating design activity through the design and manufacture of expert systems for product design. We will be looking at one of the most advanced systems of this sort, the PRIDE system, and use our study of PRIDE to discuss the possibilities and limits of automating design through the use of expert systems

Stakeholder-assisted modeling and policy design for engineering systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology, Management, and Policy Program, 2005.Page 462 blank.Includes bibliographical references.There is a growing realization that stakeholder involvement in decision-making for large- scale engineering systems is necessary and crucial, both from an ethical perspective, as well as for improving the chances of success for an engineering systems project. Traditionally however, stakeholders have only been involved after decision-makers and experts have completed the initial decision-making process with little or no input from stakeholders. This has resulted in conflict and delays for engineering systems with brilliant technical designs that do not address the larger context of the broader social goals. One of the fears of experts is that the involvement of stakeholders will result in technical solutions that are of poor quality. The hypothesis of this research is that an effective involvement of stakeholders in the decision-making process for engineering systems from the problem definition stage through the system representation can produce a system representation that is superior to representations produced in an expert-centered process. This dissertation proposes a Stakeholder-Assisted Modeling and Policy Design (SAM-PD) process for effectively involving stakeholders in engineering systems with wide-ranging social and environmental impact. The SAM-PD process is designed based on insights from existing engineering systems methodologies and alternative dispute resolution literature. Starting with a comprehensive analysis of engineering systems methodologies, the role of experts in engineering systems decision-making and existing stakeholder involvement mechanisms, this research explores the role of cognitive biases of engineering systems representation through actual experiments,(cont.) and concludes that the process of defining a system through its boundaries, components and linkages is quite subjective, and prone to implicit value judgments of those participating in the system representation process. Therefore to account for stakeholder interests, concerns and knowledge in engineering systems decision-making, it is important to have a collaborative process that enables stakeholders to jointly shape the problem definition and model outputs necessary for decision-making. Based on insights from the literature, this research developed a collaborative process for engineering systems decision-making, and explored its merits and drawbacks in applying it to the Cape Wind offshore wind energy project involving actual stakeholders in the system representation process. It further explored the potential application of such a process to the Mexico City transportation/air pollution system and the Cape and Islands Renewable Energy Planning project. The Cape Wind case study showed that a stakeholder-assisted system representation was superior to the equivalent expert-centered system representation used by the permitting agency as a basis for decision-making, in that it served as a thought expander for stakeholders, captured some effects that the expert-centered representation could not capture, better took into account social, economic and political feasibility and was more useful in suggesting better alternative strategies for the system. The case studies also highlighted the importance of the convening organization, institutional readiness for collaborative processes, the importance of stakeholder selection and process facilitation, the potentials of system representation as a basis for stakeholder dialogue and the importance of quantification versus evaluation of system representations.(cont.) The basic implication of this research is that it would be myopic of engineering systems professionals to shift the burden of stakeholder involvement to decision-makers, and keep the analysis a merely expert-centered process. Due to the many subjective choices that have to be made with regards to system boundaries, choice of components, inclusion of linkages, nature of outputs and performance metrics and assumptions about data and relationships, system analysts are in fact not producing the analysis that will help the decision-making process. The best airport designs done with multi-tradeoff analysis and intricate options analysis may lead to nowhere if stakeholders affected by the project do not see their interests reflected in the analysis. The notion is that a good systems analysis is not one that impresses other engineering systems professionals with its complexity, but one that can actually address the problems at hand.by Ali Mostashari.Ph.D

Socio-Cognitive and Affective Computing

Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing

Implementation challenges of annotated 3D models in collaborative design environments

Recent studies in the area of collaborative design have proposed the use of 3D annotations as a tool to make design information explicitly available within the 3D model, so that different stakeholders can share information throughout the product lifecycle. Annotation practices defined by the latest digital definition standards have formalized the presentation of information and facilitated the implementation of annotation tools in CAD systems. In this paper, we review the latest studies in annotation methods and technologies and explore their expected benefits in the context of collaborative design. Next, we analyze the implementation challenges of different annotation approaches, focusing specifically on design intent annotations. 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Socio-cognitive analysis of engineering systems design : shared knowledge, process, and product

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 213-222).This research is based on the well-known but seldom stated premise that the design of complex engineered systems is done by people -- each with their own knowledge, thoughts, and views about the system being designed. To understand the implications of this social dimension, the Integrated Concurrent Engineering (ICE) environment, a real-world setting for conceptual space mission design, is examined from technical and social perspectives. An integrated analysis demonstrates a relationship among shared knowledge, process, and product. The design process is analyzed using a parameter-based Design Structure Matrix (DSM). This model, consisting of 682 dependencies among 172 parameters, is partitioned (reordered) to reveal a tightly coupled design process. Further analysis shows that making starting assumptions about design budgets leads to a straightforward process of well-defined and sequentially executed design iterations. To analyze the social aspects, a network-based model of shared knowledge is proposed. By quantifying team members' common views of design drivers, a network of shared mental models is built to reveal the structure of shared knowledge at a snapshot in time. A structural comparison of pre-session and post-session networks is used to compute a metric of change in shared knowledge. Based on survey data from 12 design sessions, a correlation is found between change in shared knowledge and each of several system attributes, including technological maturity, development time, mass, and cost. Integrated analysis of design process and shared knowledge yields three interdisciplinary insights.(cont.) First, certain features of the system serve a central role both in the design process and in the development of shared knowledge. Second, change in shared knowledge is related to the design product. Finally, change in shared knowledge and team coordination (agreement between expected and reported interactions) are positively correlated. The thesis contributes to the literature on product development, human factors engineering, and organizational and social psychology. It proposes a rigorous means of incorporating the socio cognitive aspects of design into the practice of systems engineering. Finally, the thesis offers a set of recommendations for the formation and management of ICE design facilities and discusses the applicability of the proposed methodology to the full-scale development of complex engineered systems.by Mark Sean Avnet.Ph.D

From Human-Systems Integration to Human-Systems Inclusion for Use-Centred Inclusive Manufacturing Control Systems

The paper discusses about human-systems inclusion as a new way to take into account human factors on systems engineering. This process applies not only principles from human-supported by automation but also those on automation-supported by human to improve autonomy between humans and machines and autonomy between people. The main concern of human-systems integration is the consideration of a low number of future users in the design process or of the feedback of a majority of users in the evaluation process. Human-system inclusion considers that the system has to take into account and adapt to all users whatever their social, economic, physical or cognitive state, or disability. The concept of “human in the loop” or of “human touch” is usually limited to the definition of the role of humans and machines. It does not consider dynamic variability of users and systems abilities, and anticipate the feasible development of autonomous machines by reducing progressively human engagement in the control and supervisory loop. The paper presents both integration and inclusion concepts for Industry 4.0, and then suggests some challenging perspectives for use-centred inclusive manufacturing control systems in terms of opportunities and threats

Human agency in disaster planning: a systems approach

This is the final version of the article. Available from Wiley via the DOI in this record.Current approaches to risk management place insufficient emphasis on the system knowledge available to the assessor, particularly in respect of the dynamic behaviour of the system under threat, the role of human agents and the knowledge availability to those agents. In this paper, we address the second of these issues. We are concerned with a class of systems containing human agents playing a variety of roles as significant system elements - as decision makers, cognitive agents or implementers. i.e. Human Activity Systems (Checkland, 1999). Within this family of HASs we focus upon safety and mission critical systems, referring to this sub-class as critical human activity systems or CHASs. Identification of the role and contribution of these human elements to a system is a nontrivial problem whether in an engineering context, or, as is the case here, in a wider social and public context. Frequently they are treated as standing apart from the system in design or policy terms. Regardless of the process of policy definition followed, analysis of the risk and threats to such a CHAS requires a holistic approach, since the effect of undesirable, uninformed or erroneous actions on the part of the human elements is both potentially significant to the system output and inextricably bound together with the non-human elements of the system. We present a procedure for identifying the potential threats and risks emerging from the role(s) and activity of those human agents, using the 2014 flooding in SW England and the Thames Valley as a contemporary example.The project was partially supported the EU-CIRCLE (A pan-European framework for strengthening critical infrastructure resilience) project, funded by the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No 653824)