Abstract The Systems Engineering Experience Accelerator (SEEA) project created a new approach to developing the systems engineering workforce which augments traditional, in-class education methods with educational technologies aimed at accelerating skills and experience with immersive simulated learning situations that engage learners with problems to be solved. Although educational technology is used in a variety of domains to support learning, the SEEA is one of the few such technologies that supports development of the systems engineering workforce. While the existing technology infrastructure and experience content is useful, it is limited in its ability to support a community of educators and developers. The SEEA was developed with a goal of transitioning to an open-source sustainment model which will provide long-term support for a community of educators and learners in creating learning exercises to address their specific needs. Currently, it is difficult to design and develop educational content without significant knowledge of the SEEA design. This research task is focused on developing a set of tools specifically for educators and developers outside the SEEA research and development team, to support their designing and developing learning modules for their use. It concentrates on a subset of possible tools prioritized by the likelihood of having the most impact on facilitating module development. The tools development efforts fall into four major categories – simulation tools for building and testing simulation models that mimic the behavior and results of programs that focus on system design and development, experience building tools that provide the structure for such system engineering experiences and the events that occur in them, learning assessment tools to measure the efficacy of the experience, and EA infrastructure changes to support this work. This paper describes the capabilities of these tools and provides an evaluation of their capabilities in the update of an existing experience and the development of a number of new educational experiences. In addition, their use is learning assessment is discussed. The paper concludes with a description of our future directions.
Abstract : The Design and Development Tools for the Systems Engineering Experience Accelerator (SEEA) tools development efforts fall into four major categories simulation tools for building and testing simulation models that mimic the behavior and results of acquisition programs, experience building tools that provide the structure for such system engineering experiences, learning assessment tools to measure the efficacy, and EA infrastructure changes to support this work. The simulation and experience building development projects achieved completion of the requirements and use cases, a review of existing tools to leverage, the development of a Prototype Sim Builder with GUI for model building and Phase Editor, Event Editor, Artifact Integrator respectively. Included capability was the manipulation of sub-models for modularity purposes and model archiving/curation and the development of a Prototype Sim Tuner that allows testing of model behavior drilled down to variables of interest. The tools are now at the stage where they are ready to be evaluated by external users for their use in Experience and Simulation development. An iterative development approach was quite successful at providing incremental functionality that was reviewed with its potential users throughout the research effort, prioritizing the most important features and delivering working prototypes throughout the effort.
A well-designed graphical environment that supports model specification has the potential of enabling the modeler to make better use of the modeling constructs and architecture. We describe on-going research in creating a graphical environment that supports model specification in OOSIM (Object-Oriented Simulation in Manufacturing), a high fidelity manufacturing system simulator.< >
Object-oriented programming (OOP) has been revolutionizing software development and maintenance. When applied to simulation of manufacturing systems, OOP also provides an opportunity for developing new ways of thinking and modeling. In this paper, we identify existing large-scale, persistent OOP-based research efforts focusing on manufacturing system simulation, and present an integrating framework for discussing the associated modeling abstractions, implementation strategies, common themes, and distinctive features. The goal is to identify the fundamental research and application issues, assess the current state of the art, and identify key research needs.
Abstract Investigating an Innovative Approach for Developing Systems Engineering Curriculum: The Systems Engineering Experience Accelerator Traditional systems engineering education, training, and experience are not adequate tomeet the emerging challenges posed by ever increasing systems complexity and societaldemands, the workforce called upon to meet the challenges, and the timeframe in which thesechallenges need to be addressed. In response to this fundamental issue, the systems engineeringExperience Accelerator research project was initiated to leverage technology to create anexperiential, emotional state in the learner coupled with reflective learning so that time iseffectively compressed and the learning process of a systems engineer can be significantlyaccelerated as compared to the rate at which learning would occur naturally on the job. Thepurpose of the research project is to develop a simulator prototype of the Experience Acceleratorfocused on a small set of systems engineering competencies to evaluate the theoreticalcapabilities of the developed system. In the process of developing the research prototype, theExperience Accelerator team defined an approach that can be leveraged in the development ofexperiential-based systems engineering curriculum. This approach leverages a competencytaxonomy, a collection of ‘Aha’ moments, and a learner profile coupled with a series ofsimulated challenges and land mines. The systems engineering competency taxonomy is basedon a combination of systems and critical thinking, systems engineering technical leadership,systems engineering implementation, technical and program management, and other broad-basedprofessional competencies; and was built from existing models and systems thinking research.The ‘Aha’ moments were gathered from ongoing interviews of systems engineering experts whowere asked to recall specific moments in their past experiences where they had a definingmoment that helped mature their systems engineering expertise. The events that surroundedthose moments were collected as examples of the conditions under which the learning or ‘Aha’moments occurred. These events, combined with collected learner profile information, willshape the inclusion of challenges and land mines in the simulation to create an environment ripefor the learning experience. An understanding of the Experience Accelerator approach can guidecurriculum development in attempting to recreate on-the-job experiential learning in an artificialsetting. Case studies can be leveraged to develop new learning scenarios that could be added tothe planned open source version of the Experience Accelerator simulator. These and otherapproaches for experience-focused systems curriculum development are discussed in the paper.
Abstract : Acquisition programs are under pressure to deliver increasingly complex capability to the field without the cost growth associated with recent programs. Evolutionary acquisition was adopted to help reduce system cost (through the use of mature technologies) and to improve system performance (through faster deployment of incremental capability). While the ultimate verdict is not yet in on this decision, our previous simulation-based results have demonstrated that evolutionary acquisition can deliver improved capability more quickly than traditional acquisition, but that cost may actually increase over that of traditional acquisition. This is due to the overhead resulting from more frequent system deployment and update cycles. Are there other factors that can help reduce the cost of evolutionary acquisition? This paper investigates the role of system modularity and production level in the cost of evolutionary acquisition. Modularity typically imposes upfront costs in design and development, but may result in downstream savings in production and sustainment (including deployment of evolutionary new capability). A simulation experiment is conducted to determine under which conditions cost increases are minimized. The presentation includes 26 briefing charts.
Advanced mechatronic systems increasingly are finding application in modern manufacturing, as high-tech production requirements dictate high levels of machine precision, automation and integration. A high-tech factory typically contains a variety of flexibly automated processing and material handling systems. Working together, these systems are capable of executing complex operations to produce sophisticated end products. At the same time, such systems must operate in a logically correct and efficient manner to help justify their capital cost. This requirement points to the importance of system-level control to coordinate shop floor equipment and activities. In the paper, we present a generic control architecture designed to promote logically correct and efficient system behavior. The architecture and its associated control logic are based on a discrete-event systems representation. We also briefly outline future plans to use the architecture as the basis for simulation-based prototyping.
