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Typescript (photocopy). / Digitized by Kansas Correctional Industries / Department: Computer Science.

The presented thesis describes the development of an automation design procedure for structural design of concrete slab bridges and how it can be used to conduct a set-based structural design. The automation procedure integrated finite element modelling, analysis and structural related verification (verifications in geometry, ULS and SLS) together and realised automatic implementation of the two processes. By employing the automation design procedure and the set-based design methodology, a case study is performed based on an existed bridge. In contrast with a traditional point-based design process, the set-based structural design considers a wide range of possible design solutions, called design space, which are combinations of possible choices of different design parameters. In the case study, the design parameters like structural dimensions and reinforcement layout are considered and constitutes the design space. The design space is first narrowed by structural related constraints and further narrowed by multiple criteria which are material cost, material mass and global warming impact (equivalent CO2 emission) until reaching an optimal solution considering the three criteria. The results of the case study reveal the potential of set-based design by using the automation design procedure in obtaining optimal design solutions on the three mentioned criteria. Meanwhile, a rough time estimation shows the automatic procedure helps improve the design efficiency. It also suggests that the evaluation and decision of the finally chosen solution should be the trade-offs between material cost and environmental impact.

A methodology for the design of operational control aspects of an Automatic Guided Vehicle (AGV) based material handling system is presented. The methodology, which is composed of an integrated model of an AGV based system, was implemented using simulation techniques. The model views a manufacturing function as consisting of machining, queueing, and moving of parts in a shop and that these components of manufacturing must be integrated and coordinated if the production objectives of an enterprise are to be realized. A machining center is modeled as a physical region of a plant and it consists of machines for part processing and capacitated queues in which inbound and outbound parts reside, queueing for machining or handling resources. Automatic guided vehicles provide the transport mechanism required to interface the machining centers. A network approach is employed to represent the layout of the facility, including the location of departments, input and output queues in each department, and the layout of the guidance system on which the AGVs operate. The network approach, along with the coordinate system are employed for modeling the actual translation of vehicles and parts through the shop. The travel time of vehicles and parts between points depends on vehicle speed and the prevailing traffic condition along the path of travel. Several shop control strategies in the application of AGVs have been modeled, implemented, and their effects on shop performance demonstrated. Among these factors are vehicle dispatching, vehicle routing, unit load size selection, job sequencing, shop loading, queue constraints, and capacity constraints due to vehicles and machines. A job in the shop is considered to consist of one or more parts grouped in portable unit load sizes. Therefore, it is unit loads rather than jobs that make the flow transitions. The results of the simulation experiments conducted indicated vital control elements in the design of AGV systems. Through a series of output statistics on system performance, the model provides an easy to use tool to analyze, evaluate, and design of AGV based manufacturing system. / Ph. D.

The overall purpose of this research is to develop a real-time ultrasound based system for controlling robotic weld quality by monitoring the weld pool. The concept of real-time weld quality control is quite broad, and this work focuses on weld penetration depth monitoring and control with laser ultrasonics. The weld penetration depth is one of the most important geometric parameters that define the weld quality, hence remains a key control quantity. This research focuses on the implementation and optimization of the laser phased array generation unit and the development of signal analysis algorithms to extract the weld penetration depth information from the received ultrasonic signals. The system developed is based on using the phased array technique to generate ultrasound, and an Electro-Magnetic Acoustic Transducer (EMAT) as a receiver. The generated ultrasound propagates through the weld pool and is picked up by the EMAT. A transient FE model is built to predict the temperature distribution during welding. An analytical model is developed to understand the propagation of ultrasound during real-time welding and the curved rays are numerically traced. The cross-correlation technique has been applied to estimate the Time-of-Flight (ToF) of the ultrasound. The ToF is then correlated to the measured weld penetration depth. The analytical relationship between the ToF and penetration depth, obtained by a ray-tracing algorithm and geometric analysis, matches the experimental results. The real-time weld sensing technique developed is efficient and can readily be deployed for commercial applications. The successful completion of this research will remove the major obstacle to a fully automated robotic welding process. An on-line welding monitoring and control system will facilitate mass production characterized by consistency, high quality, and low costs. Such a system will increase the precision of the welding process, resulting in quality control of the weld beads. Moreover, in-process control will relieve human operators of tedious, repetitive, and hazardous welding tasks, thus reducing welding-related injures.

The effects of in-vehicle automation and driving assistant systems on the mental workload and situation awareness of drivers have been the interest of many studies; some of the implications of automation in such man-machine systems have been identified. Due to the introduction of advanced automated systems in agricultural machinery, farmers are currently working with semi-autonomous vehicles. A human factors perspective on the design of these systems will ensure safe and efficient operation of such man-machine systems. In this study, a systematic approach was utilized to address human factors issues associated with operating a semi-autonomous agricultural vehicle, and to provide design recommendations. The study was carried out in three stages. First, a task analysis was used to identify tasks associated with operating an agricultural vehicle and to select appropriate experimental variables. Next, a preliminary experiment was performed to validate the test procedure and measurement techniques. Finally, the main experiment was administered. Experiments were conducted using the Tractor Driving Simulator located in the Agricultural Ergonomics Laboratory at the University of Manitoba. Thirty young experienced tractor drivers participated in this study. The experiment investigated the effects of i) vehicle steering task automation (VSTA) and ii) implement control and monitoring task automation (ICMTA) on mental workload and situation awareness of drivers. It was found that ICMTA significantly affected situation awareness (and its underlying components) of the operator. The situation awareness of drivers increased as the automation support level increased, but the highest level of automation, where the participants were out of the task loop, resulted in low situation awareness, similar to the condition with no automation support. VSTA only reduced the attentional demand of the situation, one of the three components of the situation awareness, which had negative effect on overall situation awareness. Based on the results from a subjective mental workload measure, moderate levels of mental workload were reported when the participants were involved in the implement control and monitoring task loop. The highest level of ICMTA reduced the average mental workload by 18%. Reaction time of drivers and number of errors committed by drivers both decreased as the automation level increased. / October 2015