An official website of the United States government
Systems engineering processes (SEPs) coordinate the effort of different individuals to generate a product satisfying certain requirements. As the involved engineers are self-interested agents, the goals at different levels of the systems engineering hierarchy may deviate from the system-level goals, which may cause budget and schedule overruns. Therefore, there is a need of a systems engineering theory that accounts for the human behavior in systems design. As experience in the physical sciences shows, a lot of knowledge can be generated by studying simple hypothetical scenarios, which nevertheless retain some aspects of the original problem. To this end, the objective of this article is to study the simplest conceivable SEP, a principalagent model of a one-shot, shallow SEP. We assume that the systems engineer (SE) maximizes the expected utility of the system, while the subsystem engineers (sSE) seek to maximize their expected utilities. Furthermore, the SE is unable to monitor the effort of the sSE and may not have complete information about their types. However, the SE can incentivize the sSE by proposing specific contracts. To obtain an optimal incentive, we pose and solve numerically a bilevel optimization problem. Through extensive simulations, we study the optimal incentives arising from different system-level value functions under various combinations of effort costs, problem-solving skills, and task complexities. Our numerical examples show that, the passed-down requirements to the agents increase as the task complexity and uncertainty grow and they decrease with increasing the agents' costs.
more »
« less
Understanding the Effect of Task Complexity and Problem-Solving Skills on the Design Performance of Agents in Systems Engineering
Systems engineering processes coordinate the efforts of many individuals to design a complex system. However, the goals of the involved individuals do not necessarily align with the system-level goals. Everyone, including managers, systems engineers, subsystem engineers, component designers, and contractors, is self-interested. It is not currently understood how this discrepancy between organizational and personal goals affects the outcome of complex systems engineering processes. To answer this question, we need a systems engineering theory that accounts for human behavior. Such a theory can be ideally expressed as a dynamic hierarchical network game of incomplete information. The nodes of this network represent individual agents and the edges the transfer of information and incentives. All agents decide independently on how much effort they should devote to a delegated task by maximizing their expected utility; the expectation is over their beliefs about the actions of all other individuals and the moves of nature. An essential component of such a model is the quality function, defined as the map between an agent’s effort and the quality of their job outcome. In the economics literature, the quality function is assumed to be a linear function of effort with additive Gaussian noise. This simplistic assumption ignores two critical factors relevant to systems engineering: (1) the complexity of the design task, and (2) the problem-solving skills of the agent. Systems engineers establish their beliefs about these two factors through years of job experience. In this paper, we encode these beliefs in clear mathematical statements about the form of the quality function. Our approach proceeds in two steps: (1) we construct a generative stochastic model of the delegated task, and (2) we develop a reduced order representation suitable for use in a more extensive game-theoretic model of a systems engineering process. Focusing on the early design stages of a systems engineering process, we model the design task as a function maximization problem and, thus, we associate the systems engineer’s beliefs about the complexity of the task with their beliefs about the complexity of the function being maximized. Furthermore, we associate an agent’s problem solving-skills with the strategy they use to solve the underlying function maximization problem. We identify two agent types: “naïve” (follows a random search strategy) and “skillful” (follows a Bayesian global optimization strategy). Through an extensive simulation study, we show that the assumption of the linear quality function is only valid for small effort levels. In general, the quality function is an increasing, concave function with derivative and curvature that depend on the problem complexity and agent’s skills.
more »
« less
- Award ID(s):
- 1728165
- PAR ID:
- 10105617
- Date Published:
- Journal Name:
- ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
- Volume:
- 2A
- Page Range / eLocation ID:
- V02AT03A060
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
As the world becomes increasingly complicated, systems thinking continues to gain recognition as an important and necessary skill for future engineers. Systems thinking does not replace traditional technical skills required of engineers; rather, it provides a complementary skillset to help better navigate complex systems and their corresponding problems. The increasing complexity of U.S. industries demands that universities train and educate future engineers with systems-thinking skills to solve the range of interconnected problems companies may face. Many factors have the potentials to impact systems-thinking skills. This paper aims to identify the effects of potential impacting factors on the systems-thinking skillset. Current college engineering students were the target population of the study. Structural Equation Modeling was performed to quantify the relationship between systems-thinking skills and potential impacting factors. The results of this study indicated that employment status would affect the overall systems-thinking skills of the engineering students and the engineering students with outside job experience will score higher than students without outside job experience in the systems-thinking skills.more » « less
-
Service-learning (SL) is a promising way to engage and support local communities, educate students as holistic citizens and professionals, and strengthen the connection between higher education and society. However, within engineering education, SL as a pedagogy often falls short of reaching its full potential as a transformational pedagogy. To further our understanding of why SL, in the context of engineering, remains limited, this research characterizes: 1) implicit beliefs about engineering in students’ descriptions of their SL experiences, and 2) the ways in which students’ beliefs manifest within the context of SL in engineering. Our data include rich, contextual descriptions of SL experiences, which enabled us to generate insight into students’ implicit beliefs about engineering and how they manifest in SL contexts. We used an inductive, qualitative approach to analyze focus group and interview data. We found that students predominantly draw on three implicit beliefs about engineering when engaged in SL experiences: (1) Engineering is predominantly technical, (2) Engineering requires deliverables or tangible products, and (3) Engineers are the best problem solvers. These beliefs often manifested problematically, such that they promote university-centered and apolitical SL practice, while reinforcing social hierarchy, leading to community exploitation in support of student development. This study produces empirical evidence that such implicit beliefs are a mechanism that limits the potential of SL by hindering community-centric and justice-oriented practice. However, some students demonstrated their ability to disrupt these beliefs, thereby showing the potential for SL as a pedagogy in engineering to surface implicit and counterproductive beliefs about engineering and achieve SL goals. The beliefs that are salient in SL and the concrete ways in which they manifest for students have implications for how SL is practiced in engineering and the experiences of both students and partner communities. These beliefs impact the extent to which the socio-political elements of the service are addressed, the extent to which SL is university- versus community-centric, and the quality and extent to which the engineering solution is aligned with social justice. The implications of these findings lead to recommendations for future research on how engineering educators might explicitly design SL curricula to identify, address, and dismantle problematic beliefs before they manifest in problematic ways in SL contexts.more » « less
-
This project explores the collaborative skills occurring within engineering education and practice. While technical competence is crucial, collaborative skills are paramount in engineering enterprises, and current evidence suggests working in teams does not ensure the development of effective collaboration behaviors among engineers. Yet, lifelong learning requires engineers to navigate complex interactions within diverse design teams, emphasizing the need for a nuanced understanding of collaboration. To address this gap, our study aims to identify the least-performed effective collaboration behaviors in engineering capstone teams and explore the reasons behind this occurrence. This investigation is part of a larger study that employs the Reasoned Action Approach where we seek to uncover individual beliefs and factors influencing the performance of target behaviors. These insights serve as tools for engineers, students, educators, and managers to assess and enhance collaboration skills, fostering effective teamwork in engineering settings. Ultimately, this overarching goal of advancing professional formation in engineering distills into the key question: Why do individuals exhibit variations in performing effective collaboration behaviors in engineering teams?more » « less
-
This project explores the collaborative skills occurring within engineering education and practice. While technical competence is crucial, collaborative skills are paramount in engineering enterprises, and current evidence suggests working in teams does not ensure the development of effective collaboration behaviors among engineers. Yet, lifelong learning requires engineers to navigate complex interactions within diverse design teams, emphasizing the need for a nuanced understanding of collaboration. To address this gap, our study aims to identify the least-performed effective collaboration behaviors in engineering capstone teams and explore the reasons behind this occurrence. This investigation is part of a larger study that employs the Reasoned Action Approach1 where we seek to uncover individual beliefs and factors influencing the performance of target behaviors. These insights serve as tools for engineers, students, educators, and managers to assess and enhance collaboration skills, fostering effective teamwork in engineering settings. Ultimately, this overarching goal of advancing professional formation in engineering distills into the key question: Why do individuals exhibit variations in performing effective collaboration behaviors in engineering teams?more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1115/DETC2018-85941
