Browsing by Author "Brennan, Robert William"

Now showing 1 - 8 of 8
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    Appropriate control architectures for automated manufacturing systems
    (1996) Brennan, Robert William; Rogers, Paul
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    Beyond Service Learning: Towards an Understanding of Engineering Student Development of Social Responsibility
    (2018-09-26) Jatana, Lauren Shawna; Eggermont, Marjan J.; Brennan, Robert William; Li, Simon; Nygren, Anders
    More than ever, engineering students must be prepared for social responsibility. The 20th-century saw unprecedented social and technical advancement, leading to population growth and depleting natural resources. As a result, engineering educators have been called upon to prepare students for these professional social responsibilities. However, social responsibility is more discretionary and interpretive than legal and ethical responsibilities, and educators lack clarity on what exactly social responsibility entails and how to design effective learning experiences for it. This thesis explores the relationship between student participation in various engineering learning experiences and social responsibility. Results of this study show that fourth- year students were likely to have higher social responsibility measures than first-year students, especially in a professional capacity. Participation in certain learning experiences corresponded to increased social responsibility measures, while others did not. Lastly, the results show that social responsibility measures could be correlated with three professional graduate attributes.
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    Development of a Scalable Self-Regulation Intervention in Support of Lifelong Learning for First-year Engineering Students
    (2019-09-18) Sullivan, Monique; Brennan, Robert William; Sun, Qiao; Rosehart, William Daniel; Li, Simon; Weinhardt, Justin M.
    Lifelong learning is a Canadian Engineering Accreditation Board (CEAB) graduate attribute and thus a fundamental component of engineering education, and yet, unlike many core engineering concepts such as thermodynamics or heat transfer, there is no agreed upon approach to teach it to students. This work narrows in on the self-regulation component of lifelong learning and draws on research from the learning sciences, motivation theory, and psychology to develop a scalable intervention for first-year engineering students. Several research-based instructional strategies were modified into four workshops and sets of reminders, each with an emphasis on higher purpose, learning strategies, metacognition, or growth mindset. They were offered to first-year engineering students during the winter term and impact on student performance and beliefs were measured. This thesis presents the details of the workshops, results from their first implementations, two frameworks to evaluate the learning intervention, and suggestions for future work. While this thesis cannot provide conclusive results, it does provide evidence and support that self-regulation can and should be explicitly taught to engineering students.
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    Embedded Multi-Agent Systems Based Wireless Control Networks for Cyber-Physical Systems
    (2019-05-29) Taboun, Mohammed Salem; Brennan, Robert William; Kremer, Rob C.; Li, Simon; Far, Behrouz Homayoun; Shen, Weiming
    With the emergence of cyber-physical systems, there has been a growing interest in network-connected cyber-physical devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. As the capabilities of low processing power devices increase, there is also a growing interest in wireless control networks. As the capabilities of wireless control networks are extended to reconfigurable systems, the bandwidth requirements are drastically increasing. To remain reconfigurable, an intelligent entity needs to process all of this data. Intelligent models are typically deployed in a cloud environment, and required data (typically sensory and reconfiguration data) is passed through a series of network protocols (eg. wireless sensor network and internet protocols) where it is then aggregated and processed by a model, which then returns reconfiguration data and control instructions. For large-scale industrial networks however, the limit on bandwidth produces a challenge for employing intelligent cloud-based models. In this thesis, embedded intelligence in wireless control networks by means of embedded software agents is proposed. Through the use of wireless sensor communication protocols based off of hardware protocols such as ZigBee, the embedded agents are proposed to maintain intelligence while reducing the bandwidth requirements of the wireless control network. Architectures for both cloud-based and embedded agents are compared through an experiment and simulation, which shows the embedded agents are still able to maintain the same quality of service while reducing the bandwidth usage. As the goal of embedding agents is to maintain the intelligence of the wireless control network in a more distributed fashion, new wireless protocols need to be developed. In harsh industrial environments, the wireless control network is subject to blockages, such as interference from welding machines. In this thesis, two prescriptive reconfiguration protocols to overcome such harshness are proposed. The first reconfiguration protocol aims to overcome blockage between the individual sensing/acting nodes and the sink, which is responsible for aggregating and transmitting data to a data acquisition system. The second reconfiguration protocols are meant to overcome blockage between sensor nodes and actor nodes handling the same process. Both reconfiguration protocols are detailed, and tested in an experimental simulation. The results of the experiment show that when there is either type of blockage, the quality of service remains the same. The only significant effect is seen on process-level metrics when there is blockage between the sensor and actor nodes of the same process.
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    Multi-Agent Modelling of Industrial Cyber-Physical Systems for IEC 61499 Based Distributed Intelligent Automation
    (2023-07-21) Lyu, Guolin; Brennan, Robert William; Li, Simon; Tu, Yiliu (Paul); Bisheban, Mahdis; Dankers, Arne; Kadera, Petr
    Traditional industrial automation systems developed under IEC 61131-3 in centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. Major challenges are that these systems designed under traditional engineering techniques and running on legacy automation platforms are unable to automatically discover alternative solutions, flexibly coordinate reconfigurable modules, and actively deploy corresponding functions, to quickly respond to frequent changes and intelligently adapt to evolving requirements in dynamic environments. The core objective of this research is to explore the design of multi-layer automation architectures to enable real-time adaptation at the device level and run-time intelligence throughout the whole system under a well-integrated modelling framework. Central to this goal is the research on the integration of multi-agent modelling and IEC 61499 function block modelling to form a new automation infrastructure for industrial cyber-physical systems. Multi-agent modelling uses autonomous and cooperative agents to achieve run-time intelligence in system design and module reconfiguration. IEC 61499 function block modelling applies object-oriented and event-driven function blocks to realize real-time adaption of automation logic and control algorithms. In this thesis, the design focuses on a two-layer self-manageable architecture modelling: a) the high-level cyber module designed as multi-agent computing model consisting of Monitoring Agent, Analysis Agent, Self-Learning Agent, Planning Agent, Execution Agent, and Knowledge Agent; and b) the low-level physical module designed as agent-embedded IEC 61499 function block model with Self-Manageable Service Execution Agent, Self-Configuration Agent, Self-Healing Agent, Self-Optimization Agent, and Self-Protection Agent. The design results in a new computing module for high-level multi-agent based automation architectures and a new design pattern for low-level function block modelled control solutions. The architecture modelling framework is demonstrated through various tests on the multi-agent simulation model developed in the agent modelling environment NetLogo and the experimental testbed designed on the Jetson Nano and Raspberry Pi platforms. The performance evaluation of regular execution time and adaptation time in two typical conditions for systems designed under three different architectures are also analyzed. The results demonstrate the ability of the proposed architecture to respond to major challenges in Industry 4.0.
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    Queueing analysis of two healthcare systems where physician activity is offloaded to supporting health professionals
    (2020-06-30) Tagimacruz, Maria Antonieta; Bischak, Diane P.; Marshall, Deborah A.; Bijvank, Marco; Brennan, Robert William; da Silveira, Giovani J. C.; Willoughby, K. A.
    Patient waiting time to see a specialist and specialist utilization are vital aspects of providing musculoskeletal (MSK) healthcare service. Long waiting times not only subject patients to physical pain and suffering but also detrimentally impacts society. This dissertation uses queuing theory to analyze three models for rheumatologists consultation involving an alternative care provider, osteoarthritis consultation involving a musculoskeletal screener, and a central intake referral system for osteoarthritis patients. The second chapter presents a queueing and simulation approach to analyze the impact of an alternative care provider in a rheumatologist consultation system on waiting time and specialist utilization. Using a multi-class closed queueing network, we look into the boundaries for workload allocation within which performance improvements are realized. Chapter three compares an osteoarthritis consultation system with and without an MSK screener modeled as a network of queues. In addition to the impact of the addition of the MSK screener, we also investigate the impact of the surgical threshold of the screener relative to that of the surgeon to the patient waiting time and surgeon’s utilization. Finally, in the fourth chapter, we model an osteoarthritis referral central intake system and explore the impact of the deterministic and probabilistic routing decisions at the central intake on surgical patient waiting time and surgeon’s utilization.
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    Towards an Understanding of the Influence of Student Leadership Development on Early-Career Engineers
    (2018-04-23) Paul, Robyn Mae; Cowe Falls, Lynne G.; Hayley, Jocelyn; Brennan, Robert William
    New engineering graduates must be equipped with diverse skillsets beyond their technical foundations to help solve the challenges of the twenty-first century. Among these skills includes an increasing recognition of the importance of engineering leadership. As a developing field of research, there is limited clarity on what is engineering leadership and the influence of leadership development on early-career engineers. The Schulich School of Engineering launched the Maier Student Leadership Program in 2006 to help engineers reach their full career potential. This thesis presents the reflections on this program and moves towards an understanding of its influence on early-career engineers. The most influential factors were found to be: humility, empathy, and curiosity. These three constructs, which were fostered through the Maier Program, provide alumni with valuable skillsets in the first 5-10 years of their career. Additionally, this thesis presents a proposed definition of engineering leadership to provide clarity on the concept.
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    Transfer Lines of Multi-State Geometric Machines: Modelling, Performance Analysis, and Control
    (2018-11-21) Zeng, Zhigang; Brennan, Robert William; Enns, Silvanus Theodore; Pieper, Jeffrey Kurt
    A serial stage line is a typical pattern in manufacturing systems, but its modelling, analysis, and control during transients remain mostly unexplored. This type of manufacturing system consists of multiple serial stages. In each stage, each of which may have multiple machines, the system allows multiple independent machines to work concurrently. A major problem associated with system scheduling and dynamic capacity planning in serial stage lines is the uncertainty inherent to part delivery services, which may disrupt the original plan and result in higher production costs. Another problem relates to handling a lack of synchronization while coupling the stages into a system. A multi-state geometric machine is employed to describe one-part completion probability for all machines in a stage. The different states enable uncertain processing time to be modelled probatilistic distribution. Within a framework of serial stage lines with multi-state geometric machines and finite virtual buffers, Markov chain models of two- and three-stage transfer lines are proposed to describe the cascade effects of upstream and downstream resources, respectively. Based on the Markov model, a recursion model of the transition matrix is considered to be a state space. A predictive control model is then built to obtain the optimal admission policy for short-term scheduling, which can guide production managers in their decision-making. The proposed methodology is presented through different study cases. This model, combined with empirical studies of historical data, answers decision-making questions like, “How should parts be dynamically scheduled throughout a workday to minimize time-related production costs based on a fixed workload?” and, “If the original plan is interrupted by an emergency order or extraordinary duration processing, how should the rest of a day be rescheduled to minimize time-related cost based on a fixed workload?”