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Deadlocks are critical events in Flexible Manufacturing Cells (FMC) that result from circular waits among a set of resources. Circular waits happen when a set of resources with finite capacity are in a permanent hold due to wait state to admit new jobs. Past literature examines the deadlock-free scheduling in FMCs considering many types of resources and techniques. This thesis proposes a new resource-oriented deadlock-free approach using a robot equipped with dual-grippers serving as a material handler in a FMC. The proposed methodology uses Constraint Programming (CP). The system performance is analyzed using different buffer configurations. Many test problems are generated to validate the developed models. The finding demonstrates that the proposed dual-gripper robot (DGR) can outperform the single-gripper robot (SGR) in many settings for FMCs. Likewise, the experience with the CP for the modeling and solving approach proposed in this research consolidates its application to FMC deadlock-free scheduling problems.

Transient Liquid Phase bonding under Temperature Gradient (TG-TLP bonding) is a relatively new process of TLP diffusion bonding family for joining difficult-to-weld aerospace materials. Earlier studies have suggested that in contrast to the conventional TLP bonding process, liquid state diffusion drives joint solidification in TG-TLP bonding process. In the present work, a mass conservative numerical model that considers asymmetry in joint solidification is developed using finite element method to properly study the TG-TLP bonding process. The numerical results, which are experimentally verified, show that unlike what has been previously reported, solid state diffusion plays a major role in controlling the solidification behavior during TG-TLP bonding process. The newly developed model provides a vital tool for further elucidation of the TG-TLP bonding process.

Transient Liquid Phase bonding under Temperature Gradient (TG-TLP bonding) is a relatively new process of TLP diffusion bonding family for joining difficult-to-weld aerospace materials. Earlier studies have suggested that in contrast to the conventional TLP bonding process, liquid state diffusion drives joint solidification in TG-TLP bonding process. In the present work, a mass conservative numerical model that considers asymmetry in joint solidification is developed using finite element method to properly study the TG-TLP bonding process. The numerical results, which are experimentally verified, show that unlike what has been previously reported, solid state diffusion plays a major role in controlling the solidification behavior during TG-TLP bonding process. The newly developed model provides a vital tool for further elucidation of the TG-TLP bonding process.

Deadlocks are critical events in Flexible Manufacturing Cells (FMC) that result from circular waits among a set of resources. Circular waits happen when a set of resources with finite capacity are in a permanent hold due to wait state to admit new jobs. Past literature examines the deadlock-free scheduling in FMCs considering many types of resources and techniques. This thesis proposes a new resource-oriented deadlock-free approach using a robot equipped with dual-grippers serving as a material handler in a FMC. The proposed methodology uses Constraint Programming (CP). The system performance is analyzed using different buffer configurations. Many test problems are generated to validate the developed models. The finding demonstrates that the proposed dual-gripper robot (DGR) can outperform the single-gripper robot (SGR) in many settings for FMCs. Likewise, the experience with the CP for the modeling and solving approach proposed in this research consolidates its application to FMC deadlock-free scheduling problems.

In this thesis, a two-dimensional (2D) finite element (FE) model was developed from the patient’s hip DXA image to evaluate osteoporotic fracture risk. The loading configuration was designed to simulate a lateral fall onto the greater trochanter. Bone inhomogeneous mechanical properties (e.g. Young’s modulus) assigned to the FE model were correlated to bone mineral density captured in DXA image using empirical functions. In-house MATLAB codes were developed to investigate the effects of different factors such as bone mineral density, femoral neck length, neck diameter, neck angle and patient’s body weight on fracture risk. The 2D FE model constructed from DXA image was able to de-termine the factors which affect fracture risk to a greater extent based on the location of femur. The model developed here can be considered as a first attempt for investigating the effects of different parameters on fracture risk using patient specific 2D FE method.

This research aims to improve the performance of the service of a Chemotherapy Treatment Unit by reducing the waiting time of patients within the unit. In order to fulfill the objective, initially, the chemotherapy treatment unit is deduced as an identical parallel machines scheduling problem with unequal release time and single resource. A mathematical model is developed to generate the optimum schedule. Afterwards, a Tabu search (TS) algorithm is developed. The performance of the TS algorithm is evaluated by comparing results with the mathematical model and the best results of benchmark problems reported in the literature. Later on, an additional resource is considered which converted the problem into a dual resources scheduling problem. Three approaches are proposed to solve this problem; namely, heuristics, a Tabu search algorithm with heuristic (TSHu), and Tabu search algorithm for dual resources (TSD).

This study consists of two projects related to Tissue Engineering: Engineering biomimetic scaffolds for bone regeneration and ear reconstruction, and bioreactor design for ex-vivo bioengineered scaffold. The co-electrospinning method was used to produce composite membranes with different layers from gelatin and polycaprolactone (PCL) nanofibers, followed by paper-stacking cell seeded membranes to mimic the twisted plywood structure found in lobster cuticles. 3D laser scanner was used to capture the precise shape of a human ear model; and the negative molds were fabricated to compress scaffolds into the shape of human ear. Design for assembly (DFA) method was used to analyze and improve the design of the current bioreactor. A new design is proposed to ease operation, save time and increase the application efficiency. The proposed solution is evaluated in a virtual environment using 3D assembly modeling and simulation.

Shear strength of precast/prestressed hollow-core (PHC) slabs subjected to concentrated or line loads, especially near supports, may be critical and usually is the governing criteria in the design. This study presents the second phase of a research program, undergoing at the University of Manitoba, to calibrate the shear equations in the Canadian code for predicting the shear capacity of PHC slabs. This phase includes both experimental and numerical investigations using a finite element analysis (FEA) software package. The length of bearing, void shape and size, level of prestressing and shear span-to-depth ratio were investigated. The experimental results were compared to the predictions of the Canadian, American and European codes. It was concluded that the Canadian code is unduly conservative. However, the special European code for PHC slabs resulted in better and more consistent predictions. The FEA suggested that the adequate prestressing reinforcement ratio to obtain highest shear capacity ranges between 0.7% and 1.1%.

This research aims to improve the performance of the service of a Chemotherapy Treatment Unit by reducing the waiting time of patients within the unit. In order to fulfill the objective, initially, the chemotherapy treatment unit is deduced as an identical parallel machines scheduling problem with unequal release time and single resource. A mathematical model is developed to generate the optimum schedule. Afterwards, a Tabu search (TS) algorithm is developed. The performance of the TS algorithm is evaluated by comparing results with the mathematical model and the best results of benchmark problems reported in the literature. Later on, an additional resource is considered which converted the problem into a dual resources scheduling problem. Three approaches are proposed to solve this problem; namely, heuristics, a Tabu search algorithm with heuristic (TSHu), and Tabu search algorithm for dual resources (TSD).

This study consists of two projects related to Tissue Engineering: Engineering biomimetic scaffolds for bone regeneration and ear reconstruction, and bioreactor design for ex-vivo bioengineered scaffold. The co-electrospinning method was used to produce composite membranes with different layers from gelatin and polycaprolactone (PCL) nanofibers, followed by paper-stacking cell seeded membranes to mimic the twisted plywood structure found in lobster cuticles. 3D laser scanner was used to capture the precise shape of a human ear model; and the negative molds were fabricated to compress scaffolds into the shape of human ear. Design for assembly (DFA) method was used to analyze and improve the design of the current bioreactor. A new design is proposed to ease operation, save time and increase the application efficiency. The proposed solution is evaluated in a virtual environment using 3D assembly modeling and simulation.

Shear strength of precast/prestressed hollow-core (PHC) slabs subjected to concentrated or line loads, especially near supports, may be critical and usually is the governing criteria in the design. This study presents the second phase of a research program, undergoing at the University of Manitoba, to calibrate the shear equations in the Canadian code for predicting the shear capacity of PHC slabs. This phase includes both experimental and numerical investigations using a finite element analysis (FEA) software package. The length of bearing, void shape and size, level of prestressing and shear span-to-depth ratio were investigated. The experimental results were compared to the predictions of the Canadian, American and European codes. It was concluded that the Canadian code is unduly conservative. However, the special European code for PHC slabs resulted in better and more consistent predictions. The FEA suggested that the adequate prestressing reinforcement ratio to obtain highest shear capacity ranges between 0.7% and 1.1%.

The Winnipeg Children’s Hospital encounters delays within the surgical patient flow and cancellations due to a lack of available resources in the Pediatric Intensive Care Unit (PICU). Applying the concepts of lean thinking and the practices of simulation and statistical analysis, these problems were better understood and solutions were developed. Improvement projects were performed centralized on lean concepts and utilizing the tools of value-stream mapping and 7 forms of waste. Building and running a simulation model provided a capacity versus demand measure for the overall performance of the PICU. Simulation allowed for the study of hypothetical situations such as varying department resources and fluctuating patient levels. Statistical calculations were used to create a prediction tool to determine the probability of a PICU bed being available. This would enable a reduction in last-minute cancellations of surgical cases requiring a PICU bed.

This study is undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput of the clinic and reducing the average patients’ waiting time. In order to achieve this objective, a simulation model of this system is built and several scenarios that target matching the arrival pattern of the patients and resources availability are designed and evaluated. After performing detailed analysis, one scenario proves to provide the best system’s performance. The best scenario determines a rational arrival pattern of the patient matching with the nurses’ availability and can serve 22.5% more patients daily. Although the simulation study shows the way to serve more patients daily, it does not explain how to sequence them properly to minimize the average patients’ waiting time. Therefore, an efficient scheduling algorithm was developed to build a scheduling template that minimizes the total flow time of the system.

Flexible job-shop scheduling problem (FJSP) is a generalization of the classical job-shop scheduling problem (JSP). It takes shape when alternative production routing is allowed in the classical job-shop. However, production scheduling becomes very complex as the number of jobs, operations, parts and machines increases. Until recently, scheduling problems were studied assuming that all of the problem parameters are known beforehand. However, such assumption does not reflect the reality as accidents and unforeseen incidents happen in real manufacturing systems. Thus, an optimal schedule that is produced based on deterministic measures may result in a degraded system performance when released to the job-shop. For this reason more emphasis is put towards producing schedules that can handle uncertainties caused by random disruptions. The current research work addresses solving the deterministic FJSP using evolutionary algorithm and then modifying that method so that robust and/or stable schedules for the FJSP with the presence of disruptions are obtained. Evolutionary computation is used to develop a hybridized genetic algorithm (hGA) specifically designed for the deterministic FJSP. Its performance is evaluated by comparison to performances of previous approaches with the aid of an extensive computational study on 184 benchmark problems with the objective of minimizing the makespan. After that, the previously developed hGA is modified to find schedules that are quality robust and/or stable in face of random machine breakdowns. Consequently, a two-stage hGA is proposed to generate the predictive schedule. Furthermore, the effectiveness of the proposed method is compared against three other methods; two are taken from literature and the third is a combination of the former two methods. Subsequently, the hGA is modified to consider FJSP when processing times of some operations are represented by or subjected to small-to-medium uncertainty. The work compares two genetic ap

With the increased complexity of modern power systems, it may be required more than one platform to do an intended study efficiently and accurately. This research was carried out to investigate the use of co-simulation in an application of power system. A back-to-back Voltage Source Converter (VSC) transmission system was modeled in PSCAD/EMTDC which is an Electro-Magnetic Type (EMT) software. Results were analyzed for some operating points of the system. Then the control system of the above system was modelled in MATLAB/SIMULINK while the rest of the system was modeled in PSCAD/EMTDC. Both of these systems were interfaced to obtain the complete system and results were analyzed under same operating points as the original PSCAD case.

No-wait scheduling problem refers to the set of problems in which a number of jobs are available for processing on a number of machines with the added constraint that there should be no waiting time between consecutive operations of the jobs. It is well-known that most of the no-wait scheduling problems are strongly NP-hard. Moreover, no-wait scheduling problems have numerous real-life applications. This thesis studies a wide range of no-wait scheduling problems, along with side constraints that make such problems more applicable. First, 2-machine no-wait flow shop problem is studied. Afterwards, setup times and single server constraints are added to this problem in order to make it more applicable. Then, job shop version of this problem is further researched. Analytical results for both of these problems are presented; moreover, efficient algorithms are developed and applied to large instances of these problems. Afterward, general no-wait flow shop problem (NWFS) is the focus of the thesis. First, the NWFS is studied; mathematical models as well as metaheuristics are developed for NWFS. Then, setup times are added to NWFS in order to make the problem more applicable. Finally, the case of sequence dependent setup times is further researched. Efficient algorithms are developed for both problems. Finally, no-wait job shop (NWJS) problem is studied. Literature has proposed different methods to solve NWJS; the most successful approaches decompose the problem into a timetabling sub-problem and a sequencing sub-problem. Different sequencing and timetabling algorithms are developed to solve NWJS. This thesis provides insight to several no-wait scheduling problems. A number of theorems are discussed and proved in order to find the optimum solution of no-wait problems with special characteristics. For the problems without such characteristics, mathematical models are developed. Metaheuristics are utilized to deal with large-instances of NP-hard problems. Computational result

The Winnipeg Children’s Hospital encounters delays within the surgical patient flow and cancellations due to a lack of available resources in the Pediatric Intensive Care Unit (PICU). Applying the concepts of lean thinking and the practices of simulation and statistical analysis, these problems were better understood and solutions were developed. Improvement projects were performed centralized on lean concepts and utilizing the tools of value-stream mapping and 7 forms of waste. Building and running a simulation model provided a capacity versus demand measure for the overall performance of the PICU. Simulation allowed for the study of hypothetical situations such as varying department resources and fluctuating patient levels. Statistical calculations were used to create a prediction tool to determine the probability of a PICU bed being available. This would enable a reduction in last-minute cancellations of surgical cases requiring a PICU bed.

This study is undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput of the clinic and reducing the average patients’ waiting time. In order to achieve this objective, a simulation model of this system is built and several scenarios that target matching the arrival pattern of the patients and resources availability are designed and evaluated. After performing detailed analysis, one scenario proves to provide the best system’s performance. The best scenario determines a rational arrival pattern of the patient matching with the nurses’ availability and can serve 22.5% more patients daily. Although the simulation study shows the way to serve more patients daily, it does not explain how to sequence them properly to minimize the average patients’ waiting time. Therefore, an efficient scheduling algorithm was developed to build a scheduling template that minimizes the total flow time of the system.

With the increased complexity of modern power systems, it may be required more than one platform to do an intended study efficiently and accurately. This research was carried out to investigate the use of co-simulation in an application of power system. A back-to-back Voltage Source Converter (VSC) transmission system was modeled in PSCAD/EMTDC which is an Electro-Magnetic Type (EMT) software. Results were analyzed for some operating points of the system. Then the control system of the above system was modelled in MATLAB/SIMULINK while the rest of the system was modeled in PSCAD/EMTDC. Both of these systems were interfaced to obtain the complete system and results were analyzed under same operating points as the original PSCAD case.

Flexible job-shop scheduling problem (FJSP) is a generalization of the classical job-shop scheduling problem (JSP). It takes shape when alternative production routing is allowed in the classical job-shop. However, production scheduling becomes very complex as the number of jobs, operations, parts and machines increases. Until recently, scheduling problems were studied assuming that all of the problem parameters are known beforehand. However, such assumption does not reflect the reality as accidents and unforeseen incidents happen in real manufacturing systems. Thus, an optimal schedule that is produced based on deterministic measures may result in a degraded system performance when released to the job-shop. For this reason more emphasis is put towards producing schedules that can handle uncertainties caused by random disruptions. The current research work addresses solving the deterministic FJSP using evolutionary algorithm and then modifying that method so that robust and/or stable schedules for the FJSP with the presence of disruptions are obtained. Evolutionary computation is used to develop a hybridized genetic algorithm (hGA) specifically designed for the deterministic FJSP. Its performance is evaluated by comparison to performances of previous approaches with the aid of an extensive computational study on 184 benchmark problems with the objective of minimizing the makespan. After that, the previously developed hGA is modified to find schedules that are quality robust and/or stable in face of random machine breakdowns. Consequently, a two-stage hGA is proposed to generate the predictive schedule. Furthermore, the effectiveness of the proposed method is compared against three other methods; two are taken from literature and the third is a combination of the former two methods. Subsequently, the hGA is modified to consider FJSP when processing times of some operations are represented by or subjected to small-to-medium uncertainty. The work compares two genetic ap

The Winnipeg Children’s Hospital encounters delays within the surgical patient flow and cancellations due to a lack of available resources in the Pediatric Intensive Care Unit (PICU). Applying the concepts of lean thinking and the practices of simulation and statistical analysis, these problems were better understood and solutions were developed. Improvement projects were performed centralized on lean concepts and utilizing the tools of value-stream mapping and 7 forms of waste. Building and running a simulation model provided a capacity versus demand measure for the overall performance of the PICU. Simulation allowed for the study of hypothetical situations such as varying department resources and fluctuating patient levels. Statistical calculations were used to create a prediction tool to determine the probability of a PICU bed being available. This would enable a reduction in last-minute cancellations of surgical cases requiring a PICU bed.

The Winnipeg Children’s Hospital encounters delays within the surgical patient flow and cancellations due to a lack of available resources in the Pediatric Intensive Care Unit (PICU). Applying the concepts of lean thinking and the practices of simulation and statistical analysis, these problems were better understood and solutions were developed. Improvement projects were performed centralized on lean concepts and utilizing the tools of value-stream mapping and 7 forms of waste. Building and running a simulation model provided a capacity versus demand measure for the overall performance of the PICU. Simulation allowed for the study of hypothetical situations such as varying department resources and fluctuating patient levels. Statistical calculations were used to create a prediction tool to determine the probability of a PICU bed being available. This would enable a reduction in last-minute cancellations of surgical cases requiring a PICU bed.

This research constructs the virtual environment of a multi-floor building and provides some navigation assistance to enhance the navigation experience of users in the virtual environment. Based on the 2D architectural floor plans and photographs of Engineering and Information Technology Complex (EITC), a virtual environment of the multi-floor building is created using visualization modeling. Geometric modeling, texture mapping, and lighting procedures are employed to increase the visual effect. Two navigation assistance functions, walking through and optimal path navigation guiding tour, developed in the virtual environment helps users navigating in the virtual environment. Walking through allows users to navigate freely to obtain the spatial and geographical information of the virtual environment. Optimal path navigation guiding tour function leads users moving from a specified start position to the destination position along the optimal path. An improved shortest path algorithm is used for calculating the optimal path.

Health Sciences Centre (HSC) in Winnipeg is the major healthcare facility serving Manitoba, Northwestern Ontario, and Nunavut. An evaluation of HSC’s adult surgical patient flow revealed that one major barrier to smooth flow was their Operating Room (OR) scheduling system. This thesis presents a new two-stage elective OR scheduling system for HSC, which generates weekly OR schedules that reduce artificial variability in order to facilitate smooth patient flow. The first stage reduces day-to-day variability while the second stage reduces variability occurring within a day. The scheduling processes in both stages are mathematically modelled as multi-objective optimization problems. An attempt was made to solve both models using lexicographic goal programming. However, this proved to be an unacceptable method for the second stage, so a new multi-objective genetic algorithm, Nondominated Sorting Genetic Algorithm II – Operating Room (NSGAII-OR), was developed. Results indicate that if the system is implemented at HSC, their surgical patient flow will likely improve.

Health Sciences Centre (HSC) in Winnipeg is the major healthcare facility serving Manitoba, Northwestern Ontario, and Nunavut. An evaluation of HSC’s adult surgical patient flow revealed that one major barrier to smooth flow was their Operating Room (OR) scheduling system. This thesis presents a new two-stage elective OR scheduling system for HSC, which generates weekly OR schedules that reduce artificial variability in order to facilitate smooth patient flow. The first stage reduces day-to-day variability while the second stage reduces variability occurring within a day. The scheduling processes in both stages are mathematically modelled as multi-objective optimization problems. An attempt was made to solve both models using lexicographic goal programming. However, this proved to be an unacceptable method for the second stage, so a new multi-objective genetic algorithm, Nondominated Sorting Genetic Algorithm II – Operating Room (NSGAII-OR), was developed. Results indicate that if the system is implemented at HSC, their surgical patient flow will likely improve.

Future generation wireless networks are envisioned to provide ubiquitous networking to a wide number of mobile users, promising them the ability to access the various data networks anywhere and anytime. Such networks have motivated the research into efficient management and allocation of the wireless network's limited resources. Heterogeneity also exists amongst the subscribers, i.e. there are those who are willing to spend a little extra on their subscriptions in the prospect of obtaining a better level of service. This work proposes a framework for efficient resource management, while satisfying the heterogeneous QoS demands of the different subscribers. Part of the proposed framework was used to generate mathematical models for the purpose of analyzing the behavior of the system under two different resource management schemes.

Future generation wireless networks are envisioned to provide ubiquitous networking to a wide number of mobile users, promising them the ability to access the various data networks anywhere and anytime. Such networks have motivated the research into efficient management and allocation of the wireless network's limited resources. Heterogeneity also exists amongst the subscribers, i.e. there are those who are willing to spend a little extra on their subscriptions in the prospect of obtaining a better level of service. This work proposes a framework for efficient resource management, while satisfying the heterogeneous QoS demands of the different subscribers. Part of the proposed framework was used to generate mathematical models for the purpose of analyzing the behavior of the system under two different resource management schemes.