Browsing by Subject "Industrial Engineering"

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    An Assessment and Simulation Methodology of Sustainability in Manufacturing System
    (2018-06) Islam, Md
    This thesis work presents a new integrated framework to connect the economic, environmental and social factors, and to analyze sustainability performance of the system by balancing these factors. Sustainable manufacturing systems should be profitable and environmentally friendly while being safe both physically and socially for everyone in the system. This thesis work highlights the main aspects and requirements of sustainability, which are related to manufacturing systems, demonstrating that there are other aspects of sustainability in general that are not reflective on manufacturing. This work also highlights many useful assessment indices of manufacturing sustainability, which makes quantification, and then comparison and optimization of system performance possible. A comparative study on the existing sustainability assessment tools is performed to classify these tools based on appropriateness to manufacturing systems and limitations by reviewing the significant research work in system modeling for assessing and optimizing manufacturing sustainability. The review has revealed that the triple bottom line TBL factors, economic, social and environmental, are difficult to evaluate and optimize simultaneously due to the complex nature of manufacturing systems and the wide variety of processes and type of the system. Furthermore, the review has demonstrated that there is significant research gap in considering social sustainability for overall sustainability characterization. The consideration and the integration of social sustainability with other factors make this framework unique and more functional. Three case studies have been conducted to understand the applicability of this novel framework. The first case study reveals the difficulties associated with achieving social sustainability as most of the parameters in social sustainability are intangible in nature that’s why it is difficult to optimize the parameters associated with social sustainability. The last two case studies are analyzed to evaluate the sustainability in oil and gas industry with the help of fuzzy interference modelling. Fuzzy interference modelling is the core unit of decision making and mathematical reasoning of the sustainability assessment simulation, when the outcomes are uncertain. The modelling is built with the help of triangle membership functions to fuzzify the variables. Fuzzy rules like ‘IF THEN’ along with operators “OR” or “AND” then come into play for generating necessary decision rules. In this work, these decision rules aggregately simulate and generate the overall sustainability assessment results for case studies 2 and 3. All case studies strongly demonstrate the pragmatic and facile application of the proposed framework to assess the overall sustainability in continuous manufacturing context. Finally, the scope of future research work is also presented for the proposed novel framework.
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    Essays in operations and inventory management.
    (2009-08) Yu, Yimin
    This thesis consists of two essays. The first essay is on capacity pooling and cost sharing among independent firms in the presence of congestion. We analyze the benefit of production/service capacity sharing for a set of independent firms. Firms have the choice of either operating their own production/service facilities or investing in a facility that is shared. Facilities are modeled as queueing systems with finite service rates. Firms decide on capacity levels (the service rate) to minimize delay costs and capacity investment costs possibly subject to service level constraints. If firms decide to operate a shared facility they must also decide on a scheme for sharing the costs. We formulate the problem as a cooperative game and identify a cost allocation that is in the core. The allocation rule charges every firm the cost of capacity for which it is directly responsible, its own delay cost, and a fraction of buffer capacity cost that is consistent with its contribution to this cost. In settings where unit delay costs are private information, the cooperative capacity sharing game becomes embedded with a non-cooperative information reporting game. We show how a cost allocation rule can be designed to induce all firms to report truthfully this information. Moreover, we show that, under this allocation rule, truth telling is a dominant strategy, with each firm reporting truthfully its private information regardless of the reporting decisions of other firms. The second essay is on a customer-item decomposition approach to inventory problems. We consider inventory systems with periodic review, correlated, non-stationary stochastic demand and correlated, non-stationary stochastic and sequential leadtimes. We treat systems with both single and multiple stages. We use the customer-item decomposition approach to decompose the associated inventory control problem into sub-problems, each involving a single customer-item pair. We then formulate each subproblem as an optimal stopping problem. We use properties that arise from this formulation to show that the optimal policy is a state-dependent base-stock policy and to show, for the case of positive demand, that the optimal policy can be obtained via an algorithm whose complexity is polynomial in the length of the planning horizon. We also use the formulation to construct myopic heuristics which lead to explicit solutions for the optimal policy in the form of a critical fractile. We characterize conditions under which the myopic heuristics are optimal. We show how the results can be extended to systems with advance demand information and batch ordering.