Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Integrating Human Performance Models into Early Design Stages to Support Accessibility(2021) Knisely, Benjamin Martin; Vaughn-Cooke, Monifa; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Humans have heterogeneous physical and cognitive capabilities. Engineers must cater to this heterogeneity to minimize opportunities for user error and system failure. Human factors considerations are typically evaluated late in the design process, risking expensive redesign when new human concerns become apparent. Evaluating user capability earlier could mitigate this risk. One critical early-stage design decision is function allocation – assigning system functions to humans and machines. Automating functions can eliminate the need for users to perform risky tasks but increases resource requirements. Engineers require guidance to evaluate and optimize function allocation that acknowledges the trade-offs between user accommodation and system complexity. In this dissertation, a multi-stage design methodology is proposed to facilitate the efficient allocation of system functions to humans and machines in heterogeneous user populations. The first stage of the methodology introduces a process to model population user groups to guide product customization. User characteristics that drive performance of generalized product interaction tasks are identified and corresponding variables from a national population database are clustered. In stage two, expert elicitation is proposed as a cost-effective means to quantify risk of user error for the user group models. Probabilistic estimates of user group performance are elicited from internal medicine physicians for generalized product interaction tasks. In the final stage, the data (user groups, performance estimations) are integrated into a multi-objective optimization model to allocate functions in a product family when considering user accommodation and system complexity. The methodology was demonstrated on a design case study involving self-management technology use by diabetes patients, a heterogeneous population in a safety-critical domain. The population modeling approach produced quantitatively and qualitatively validated clusters. For the expert elicitation, experts provided internally validated, distinct estimates for each user group-task pair. To validate the utility of the proposed method (acquired data, optimization model), engineering students (n=16) performed the function allocation task manually. Results indicated that participants were unable to allocate functions as efficiently as the model despite indicating user capability and cost were priorities. This research demonstrated that the proposed methodology can provide engineers valuable information regarding user capability and system functionality to drive accessible early-stage design decisions.Item Strategic Product Design for Retail Channel Acceptance under Uncertainty and Competition(2007-11-05) Williams, Nathan Adam; Azarm, Shapour; Kannan, P.K.; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Significant recent research has focused on the marriage of consumer preferences and engineering design in order to improve profitability. However, in many markets, the profitability of new products for manufacturers is also a significant function of the retail channel structure through which the new products reach the ultimate customer. At the crux of the issue is the fact that channel dominating retailers, like Home Depot, Toys R' Us, Wal-Mart have significant power arising from their hundreds of billions of dollars of sales revenue and have the ability to unilaterally control a manufacturer's access to the customers. A product design methodology is proposed that accounts for this new and important power asymmetry. Manufacturer's product success as defined by profit is affected by pricing at the retail and wholesale levels which in turn is dependent on the channel structure, i.e., retailer monopoly or duopoly. These channel structures are explored in this dissertation under an econometric or game theoretic framework and the results are shown to have important implications for designers. Additional non-traditional considerations for engineering product design such as bundling and exclusive contracts which are typical for retail channels are also explored by integrating marketing models with a design optimization structure. Lastly, some design methods for mitigating uncertainty in the strategic landscape of retailer dominated channels are developed. The dissertation has three research thrusts. Research Thrust 1 is devoted to developing a product design optimization approach with retailer acceptance as a probabilistic constraint on candidate designs. Slotting allowances are considered in concert with engineering design as complimentary approaches to achieving access to consumer markets. The retailer's decision framework and the design optimization approach of Thrust 1 are extended in Thrust 2 to include competitive pricing responses from both competing manufacturers and channel controlling retailers. In Thrust 2 the implications for product design when manufacturers face monopolistic and duopolistic retail channels is explored as well as the design implications of an exclusive manufacturer/retailer relationship. Finally, in Thrust 3 the prior thrusts are implemented for multiple product categories and product bundles in order to consider synergy and competition amongst multiple complementary designs. Under this final Thrust 3, an approach to mitigating the risk of uncertainty in competitor design attributes is also developed.