The Experts below are selected from a list of 189 Experts worldwide ranked by ideXlab platform

Katie Lawton - One of the best experts on this subject based on the ideXlab platform.

Michel-alexandre Cardin - One of the best experts on this subject based on the ideXlab platform.

  • An approach based on robust optimization and decision rules for analyzing real options in Engineering Systems Design
    IISE Transactions, 2017
    Co-Authors: Aakil M. Caunhye, Michel-alexandre Cardin
    Abstract:

    ABSTRACTIn this article, a novel approach to analyze flexibility and real options in Engineering Systems Design is proposed based on robust optimization and decision rules. A semi-infinite robust counterpart is formulated for a worst-case non-flexible Generation Expansion Planning (GEP) problem taken as a demonstration application. An exact solution methodology is proven by converting the model into an explicit mixed-integer programming model. Strategic capacity expansion flexibility—also referred to as real options—is analyzed in the GEP problem formulation and a multi-stage finite adaptability decision rule is developed to solve the resulting model. Finite adaptability relies on uncertainty set partitions, and in order to avoid arbitrary choices of partitions, a novel heuristic partitioning methodology is developed based on upper-bound paths to guide the partitioning of uncertainty sets. The modeling approach and heuristic partitioning methodology are applied to analyze a realistic GEP problem using dat...

  • an approach for analyzing and managing flexibility in Engineering Systems Design based on decision rules and multistage stochastic programming
    Iie Transactions, 2017
    Co-Authors: Michel-alexandre Cardin, Qihui Xie, Shuming Wang
    Abstract:

    ABSTRACTThis article introduces an approach to assess the value and manage flexibility in Engineering Systems Design based on decision rules and stochastic programming. The approach differs from standard Real Options Analysis (ROA) that relies on dynamic programming in that it parameterizes the decision variables used to Design and manage the flexible system in operations. Decision rules are based on heuristic-triggering mechanisms that are used by Decision Makers (DMs) to determine when it is appropriate to exercise the flexibility. They can be treated similarly as, and combined with, physical Design variables, and optimal values can be determined using multistage stochastic programming techniques. The proposed approach is applied as demonstration to the analysis of a flexible hybrid waste-to-energy system with two independent flexibility strategies under two independent uncertainty drivers in an urban environment subject to growing waste generation. Results show that the proposed approach recognizes the...

  • analyzing the tradeoffs between economies of scale time value of money and flexibility in Design under uncertainty study of centralized versus decentralized waste to energy Systems
    Journal of Mechanical Design, 2016
    Co-Authors: Michel-alexandre Cardin, Junfei Hu
    Abstract:

    This paper presents and applies a simulation-based methodology to assess the value of flexible decentralized Engineering Systems Design (i.e., the ability to flexibly expand the capacity in multiple sites over time and space) under uncertainty. This work differs from others by analyzing explicitly the tradeoffs between economies of scale (EoS)—which favors Designing large capacity upfront to reduce unit cost and accommodate high anticipated demand—and the time value of money—which favors deferring capacity investments to the future and deploying smaller modules to reduce unit cost. The study aims to identify the best strategies to Design and deploy the capacity of complex engineered Systems over time and improve their economic lifecycle performance in the face of uncertainty by exploiting the idea of flexibility. This study is illustrated using a waste-to-energy (WTE) system operated in Singapore. The results show that a decentralized Design with the real option to expand the capacity in different locations and times improves the expected net present value (ENPV) by more than 30% under the condition of EoS α = 0.8 and discount rate λ = 8%, as compared to a fixed centralized Design. The results also indicate that a flexible decentralized Design outperforms other rigid Designs under certain circumstances since it not only reduces transportation costs but also takes advantage of flexibility, such as deferring investment and avoiding unnecessary capacity deployment. The modeling framework and results help Designers and managers better compare centralized and decentralized Design alternatives facing significant uncertainty. The proposed method helps them analyze the value of flexibility (VOF) in small-scale urban environments, while considering explicitly the tradeoffs between EoS and the time-value of money.

  • Empirical evaluation of procedures to generate flexibility in Engineering Systems and improve lifecycle performance
    Research in Engineering Design, 2013
    Co-Authors: Michel-alexandre Cardin, Daniel D. Frey, Richard De Neufville, Olivier Ladislas De Weck, Gwendolyn L Kolfschoten, David M. Geltner
    Abstract:

    The Design of Engineering Systems like airports, communication infrastructures, and real estate projects today is growing in complexity. Designers need to consider socio-technical uncertainties, intricacies, and processes in the long-term strategic deployment and operations of these Systems. Flexibility in Engineering Design provides ways to deal with this complexity. It enables Engineering Systems to change in the face of uncertainty to reduce impacts from downside scenarios (e.g., unfavorable market conditions) while capitalizing on upside opportunities (e.g., new technology). Many case studies have shown that flexibility can improve anticipated lifecycle performance (e.g., expected economic value) compared to current Design and evaluation approaches. It is a difficult process requiring guidance and must be done at an early conceptual stage. The literature offers little guidance on procedures helping Designers do this systematically in a collaborative context. This study investigated the effects of two educational training procedures on flexibility (current vs. explicit) and two ideation procedures (free undirected brainstorming vs. prompting) to guide this process and improve anticipated lifecycle performance. Controlled experiments were conducted with ninety participants working on a simplified Engineering Systems Design problem. Results suggest that a prompting mechanism for flexibility can help generate more flexible Design concepts than free undirected brainstorming. These concepts can improve performance significantly (by up to 36 %) compared to a benchmark Design—even though users did not expect improved quality of results. Explicit training on flexibility can improve user satisfaction with the process, results, and results quality in comparison with current Engineering and Design training on flexibility. These findings give insights into the crafting and application of simple, intuitive, and efficient procedures to improve lifecycle performance by means of flexibility and performance that may be left aside with existing Design approaches. The experimental results are promising toward further evaluation in a real-world setting.

  • An integrated screening framework to analyze flexibility in Engineering Systems Design
    2013
    Co-Authors: Mehdi Ranjbar Bourani, Michel-alexandre Cardin, Wen Sin Chong, Ravindu Atapattu, Kok Seng Foo
    Abstract:

    This paper presents ongoing development for a novel integrated screening framework for flexibility analysis considering multi-domain uncertainty sources and multi-criteria for Designing complex Engineering Systems. The proposed methodology aims to address two main issues in the Design process for flexibility: 1) the complexity of exploring exhaustively flexible Design strategies under multiple uncertainty sources, and 2) the multiple and possibly conflicting criteria inherent to Design decision-making. The proposed screening framework is applied to a real-world capital-intensive project in the oil and gas industry. Current results indicate that the screening model offers better performance than a full exhaustive search of the Design space in terms of the number of evaluations and simulation runtime, while providing good Design solutions in terms of lifecycle performance. The work provides insights on how to analyze flexibility in the conceptual Design of complex Systems, especially when computational resources are limited, and Design needs to consider multiple decision-making criteria.

Jeffrey W. Baur - One of the best experts on this subject based on the ideXlab platform.

  • Performance assessment of a multi-objective parametric optimization algorithm with application to a multi-physical Engineering system
    Structural and Multidisciplinary Optimization, 2018
    Co-Authors: Edgar Galván, Richard J. Malak, Darren J. Hartl, Jeffrey W. Baur
    Abstract:

    Engineers routinely perform parameter studies to investigate how system response changes over a range of parameter values. This can provide Engineering insight into the importance of an exogenous variable, the robustness of a Design alternative, or even the validity of simulation models. Parametric optimization is an extension of this concept in which one investigates how the solution to an optimization or equilibrium problem changes over a range of parameter values. It has been applied in economics, process Engineering and Engineering Systems Design. Recent work has yielded a general-purpose algorithm for parametric multi-objective optimization, the Predicted Parametric Pareto Genetic Algorithm (P3GA), and demonstrated it on Engineering examples. This article advances understanding about the capabilities of P3GA through a suite of test problems of varying scale and application to a multiphysical engineered system: a magnetohydrodynamic thermal transport (MTT) system. We also compare P3GA to iterated application of an established multi-objective optimization algorithm, NSGA-II. Results indicate P3GA outperforms the iterative approach, underscoring the importance of using an algorithm tailored to parametric optimization.

Jitesh H. Panchal - One of the best experts on this subject based on the ideXlab platform.

  • Designing Representative Model Worlds to Study Socio-Technical Phenomena: A Case Study of Communication Patterns in Engineering Systems Design
    Journal of Mechanical Design, 2020
    Co-Authors: Ashish M. Chaudhari, Paul T. Grogan, Erica Gralla, Zoe Szajnfarber, Jitesh H. Panchal
    Abstract:

    Abstract The Engineering of complex Systems, such as aircraft and spacecraft, involves large number of individuals within multiple organizations spanning multiple years. Since it is challenging to perform empirical studies directly on real organizations at scale, some researchers in Systems Engineering and Design have begun relying on abstracted model worlds that aim to be representative of the reference socio-technical system, but only preserve some aspects of it. However, there is a lack of corresponding knowledge on how to Design representative model worlds for socio-technical research. Our objective is to create such knowledge through a reflective case study of the development of a model world. This “inner” study examines how two factors influence interdisciplinary communication during a concurrent Design process. The reference real world system is a mission Design laboratory (MDL) at NASA, and the model world is a simplified engine Design problem in an undergraduate classroom environment. Our analysis focuses on the thought process followed, the key model world Design decisions made, and a critical assessment of the extent to which communication phenomena in the model world (engine experiment) are representative of the real world (NASA’s MDL). We find that the engine experiment preserves some but not all of the communication patterns of interest, and we present case-specific lessons learned for achieving and increasing representativeness in this type of study. More generally, we find that representativeness depends not on matching subjects, tasks, and context separately, but rather on the behavior that emerges from the interplay of these three dimensions.

  • Secure Collaboration in Engineering Systems Design
    Journal of Computing and Information Science in Engineering, 2017
    Co-Authors: Shumiao Wang, Jitesh H. Panchal, Siddharth Bhandari, Mikhail J. Atallah, Siva Chaitanya Chaduvula, Karthik Ramani
    Abstract:

    The goal in this paper is to enable collaboration in the coDesign of Engineering artifacts when participants are reluctant to share their Design-related confidential and proprietary information with other coDesigners, even though such information is needed to analyze and validate the overall Design. We demonstrate the viability of coDesign by multiple entities who view the parameters of their contributions to the joint Design to be confidential. In addition to satisfying this confidentiality requirement, an online coDesign process must result in a Design that is of the same quality as if full sharing of information had taken place between the coDesigners. We present online coDesign protocols that satisfy both requirements and demonstrate their practicality using a simple example of coDesign of an automotive suspension system and the tires. Our protocols do not use any cryptographic primitives—they only use the kinds of mathematical operations that are currently used in single-Designer situations. The participants in the online Design protocols include the coDesigners, and a cloud server that facilitates the process while learning nothing about the participants' confidential information or about the characteristics of the coDesigned system. The only assumption made about this cloud server is that it does not collude with some participants against other participants. We do not assume that the server does not, on its own, attempt to compute as much information as it can about the confidential inputs and outputs of the coDesign process: It can make a transcript of the protocol and later attempt to infer all possible information from it, so it is a feature of our protocols the cloud server can infer nothing from such a transcript.

  • USING CONTESTS FOR Engineering Systems Design: A STUDY OF AUCTIONS AND FIXED-PRIZE TOURNAMENTS
    2016
    Co-Authors: Ashish M. Chaudhari, Joseph Thekinen, Jitesh H. Panchal
    Abstract:

    With the increasing interest in using open innovation and crowdsourcing contests for Engineering Design, there is a need for understanding how different types of contests affect the outcomes. While contests have been studied in the economics literature, the analytical models are based on various simplifying assumptions. There is a lack of critical analysis of these assumptions, which is necessary before utilizing the insights from the models in a Design context. In this paper, we address this gap by critically analyzing contest models for Engineering Design scenarios.

  • Behavioral Experimentation and Game Theory in Engineering Systems Design
    Journal of Mechanical Design, 2015
    Co-Authors: Zhenghui Sha, Karthik Kannan, Jitesh H. Panchal
    Abstract:

    Game-theoretic models have been used to analyze Design problems ranging from multi-objective Design optimization to decentralized Design and from Design for market Systems (DFMS) to policy Design. However, existing studies are primarily analytical in nature, which start with a number of assumptions about the individual decisions, the information available to the players, and the solution concept (generally, the Nash equilibrium). There is a lack of studies related to Engineering Design, which rigorously evaluate the validity of these assumptions or that of the predictions from the models. Hence, the usefulness of these models to realistic Engineering Systems Design has been severely limited. In this paper, we take a step toward addressing this gap. Using an example of crowdsourcing for Engineering Design, we illustrate how the analytical game-theoretic models and behavioral experimentation can be synergistically used to gain a better understanding of Design situations. Analytical models describe what players with assumed behaviors and cognitive capabilities would do under specified conditions, and the behavioral experiments shed light on how individuals actually behave. The paper contributes to the Design literature in multiple ways. First, to the best of our knowledge, it is a first attempt at integrated theoretical and experimental game-theoretic analysis in Design. We illustrate how the analytical models can be used to Design behavioral experiments, which, in turn, can be used to estimate parameters, refine models, and inform further development of the theory. Second, we present a simple experiment to understand behaviors of individuals in a Design crowdsourcing problem. The results of the experiment show new insights on using crowdsourcing contests for Design.

  • USING CROWDS IN Engineering Design – TOWARDS A HOLISTIC FRAMEWORK
    2015
    Co-Authors: Jitesh H. Panchal
    Abstract:

    Product development organizations are increasingly using crowdsourcing for Design-related activities such as idea generation and evaluation, and solving difficult problems. In order to effectively use crowdsourcing within Engineering Systems Design, it is important to systematically Design these initiatives by considering conflicting goals such as maximizing participation and the quality of outcoMES within cost constraints. There is currently a lack of holistic frameworks that help Design engineers in Designing crowd-based initiatives, specifically, framing problems, choosing the right type of crowdsourcing mechanisms, and Designing incentives. This paper is an attempt towards such a holistic framework which consists of three phases. The first phase involves selecting from the four classes of crowdsourcing initiatives. The second phase involves making structural, problem-related and evaluation decisions about the crowdsourcing initiative. The third phase involves Designing appropriate reward structures. An analytical modeling framework based on the theory of contests is presented, followed by a discussion of specific issues related to Engineering Systems Design.

Edgar Galván - One of the best experts on this subject based on the ideXlab platform.

  • Performance assessment of a multi-objective parametric optimization algorithm with application to a multi-physical Engineering system
    Structural and Multidisciplinary Optimization, 2018
    Co-Authors: Edgar Galván, Richard J. Malak, Darren J. Hartl, Jeffrey W. Baur
    Abstract:

    Engineers routinely perform parameter studies to investigate how system response changes over a range of parameter values. This can provide Engineering insight into the importance of an exogenous variable, the robustness of a Design alternative, or even the validity of simulation models. Parametric optimization is an extension of this concept in which one investigates how the solution to an optimization or equilibrium problem changes over a range of parameter values. It has been applied in economics, process Engineering and Engineering Systems Design. Recent work has yielded a general-purpose algorithm for parametric multi-objective optimization, the Predicted Parametric Pareto Genetic Algorithm (P3GA), and demonstrated it on Engineering examples. This article advances understanding about the capabilities of P3GA through a suite of test problems of varying scale and application to a multiphysical engineered system: a magnetohydrodynamic thermal transport (MTT) system. We also compare P3GA to iterated application of an established multi-objective optimization algorithm, NSGA-II. Results indicate P3GA outperforms the iterative approach, underscoring the importance of using an algorithm tailored to parametric optimization.