A new open access article co-authored with Prof. Martin Törngren of KTH Royal Institute of Technology appears in a special issue of Designs on Challenges and Directions Forward for Dealing with the Complexity of Future Smart Cyber-Physical Systems.
How to Deal with the Complexity of Future Cyber-Physical Systems?
Martin Törngren and Paul T. Grogan
Abstract: Cyber-Physical Systems (CPS) integrate computation, networking and physical processes to produce products that are autonomous, intelligent, connected and collaborative. Resulting Cyber-Physical Systems of Systems (CPSoS) have unprecedented capabilities but also unprecedented corresponding technological complexity. This paper aims to improve understanding, awareness and methods to deal with the increasing complexity by calling for the establishment of new foundations, knowledge and methodologies. We describe causes and effects of complexity, both in general and specific to CPS, consider the evolution of complexity, and identify limitations of current methodologies and organizations for dealing with future CPS. The lack of a systematic treatment of uncertain complex environments and “composability”, i.e., to integrate components of a CPS without negative side effects, represent overarching limitations of existing methodologies. Dealing with future CPSoS requires: (i) increased awareness of complexity, its impact and best practices for how to deal with it, (ii) research to establish new knowledge, methods and tools for CPS engineering, and (iii) research into organizational approaches and processes to adopt new methodologies and permit efficient collaboration within and across large teams of humans supported by increasingly automated computer aided engineering systems.
A new open access data article appears in Data in Brief to provide open access to a data set collected from a human designer experiment:
Data on multi-actor parameter design tasks by engineering students with variable problem size, coupling, and team size
Paul T. Grogan
Abstract: The experiment studies the effect of technical and social sources of complexity on effort required to complete abstracted design tasks. Parameter design tasks define a set of input design parameters and functional requirements modeled with a linear coupling matrix. Selecting design variables to meet all functional requirements within error limits completes a task. Technical complexity arises from the number and degree of coupling between design parameters. Social complexity arises from the number of designers involved in a task. The experiment includes 10 sessions with between 19 and 24 rounds of randomly generated parameter design tasks each having between two and six design variables and one, two, or three designers. Designers completed individual tasks in parallel during rounds. This article contains raw and post-processed data from 374 completed tasks ranging in effort from a few seconds for simple tasks to more than 15 min for complex ones.
Two papers were presented this week at the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE) in Quebec City, Canada.
Toward a Model-based Experimental Approach to Assessing Collective Systems Design Processes
A. Valencia Romero and P.T. Grogan in Design Theory Methodology (DTM)
Abstract: This work presents a conceptual model of collective decision-making processes in engineering systems design to understand the tradeoffs, risks, and dynamics between autonomous but interacting design actors. The proposed approach combines value-driven design, game theory, and simulation experimentation to study how technical and social factors of a design decision-making process facilitate or inhibit collective action. The collective systems design model considers two levels of decision-making: 1) lower-level design value exploration; and 2) upper-level design strategy selection. At the first level, the actors concurrently explore two strategy-specific value spaces with coupled design decision variables. Each collective decision is mapped to an individual scalar measure of preference (design value) that each actor seeks to maximize. At the second level, each of the actor’s design values from the two lower-level design exploration tasks is assigned to one diagonal entry of a normal-form game, with off-diagonal elements calculated in function of the “sucker’s” and “temptation-to-defect” payoffs in a classical strategy game scenario. The model helps generate synthetic design problems with specific strategy dynamics between autonomous actors. Results from a preliminary multi-agent simulation study assess the validity of proposed design spaces and generate hypotheses for subsequent studies using human subjects.
Operational and Strategic Decisions in Engineering Design Games
P.T. Grogan and A.E. Bayrak in Design Automation Conference (DAC)
Abstract: Engineering design games model decision-making activities by incorporating human participants in an entertaining platform. This article distinguishes between design decisions at operational and strategic timescales as important features of engineering design games. Operational decisions consider static and short-term dynamic decisions to establish a player’s situation awareness and initial entertainment. Strategic decisions consider longer-term dynamic decisions subject to large uncertainties to retain player engagement. However, constraints on cognitive load limit the ability to simultaneously address both lower-level operational design decisions and higher-level strategic decisions such as collaboration or sustainability. Partial automation can be introduced to reduce cognitive load for operational decisions and focus additional effort on strategic decisions. To illustrate tradeoffs between operational and strategic decisions, this paper discusses example cases for two existing games: Orbital Federates and EcoRacer. Discussion highlights the role of automation and entertainment in engaging human participants in engineering design games and makes recommendations for design of future engineering design games.
A new article appears in Systems Engineering Early View today as a contribution to a special issue from the CESUN 2016 symposium:
Gaming Methods in Engineering Systems Research
Paul T. Grogan and Sebastiaan A. Meijer
Abstract: Recent interest in applications of games and gaming methods has stimulated discussion of their use in engineering systems research. Simulation games or gaming simulations are interactive environments which simultaneously model a technical system through simulation and a social system with role-play participants. Their boundary-spanning nature aligns with challenges in engineering systems to consider both technical and social factors in design. This paper outlines a class of gaming methods for research in engineering systems. Key contributions synthesize diverse bodies of literature to classify gaming applications as generating generalizable and contextual knowledge to benefit participants and principals, identify intellectual foundations in related social sciences, and describe the dual purpose of games as a research method for analytical or design science objectives. Conclusions highlight opportunities and challenges for gaming research methods to accommodate social science research in design-centric activities.