Institute for Systems Research Technical Reports
Permanent URI for this collectionhttp://hdl.handle.net/1903/4376
This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.
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Item A Practical Method for Design of Hybrid-Type Production Facilities(1994) Harhalakis, George; Lu, Thomas C.; Minis, Ioannis; Nagi, R.; ISRA comprehensive methodology for the design of hybrid-type production shops that comprise both manufacturing cells and individual workcenters is presented. It targets the minimization of the material handling effort within the shop and comprises four basic steps: (1) identification of candidate manufacturing cells, (2) evaluation and selection of the cells to be implemented, (3) determination of the intra-cell layout, and (4) determination of the shop layout. For the cell formation step the ICTMM technique has been enhanced to cater for important practical issues. The layout of each significant cell is determined by a simulated annealing (SA)-based algorithm. Once the sizes and shapes of the selected cells are known, the shop layout is determined by a similar algorithm. The resulting hybrid shop consists of the selected cells and the remaining machines. The methodology has been implemented in an integrated software system and has been applied to redesign the shop of a large manufacturer of radar antennas.Item Manufacturing Cell Formation Under Random Product Demand(1993) Harhalakis, George; Minis, Ioannis; Nagi, R.; ISRThe performance of cellular manufacturing systems is intrinsically sensitive to demand variations and machine breakdowns. A cell formation methodology that addresses, during the shop design stage, system robustness with respect to product demand variation is proposed. The system resources are aggregated into cells in a manner that minimizes the expected inter-cell material handling cost. The statistical characteristics of the independent demand and the capacity of the system resources are explicitly considered. In the first step of the proposed approach the expected value of the feasible production volumes, which respect resource capacities, are determined. Subsequently, the shop partition that results in near optimal inter cell part traffic is found. The applicability of the proposed approach is illustrated through a comprehensive examples.Item Hierarchical Modeling Approach for Production Planning(1992) Harhalakis, George; Nagi, R.; Proth, J.M.; ISRProduction management problems are complex owing to large dimensionality, wide variety of decisions of varying scope, focus and time-horizon, and disturbances. A hierarchical approach to these problems is a way to address this complexity, wherein the global problem is decomposed into a series of top-down sub- problems. We advocate that a single planning architecture cannot be employed for all planning problems. We propose a multi-layer hierarchical decomposition which is dependent on the complexity of the problem, and identify the factors influencing complexity. A systematic stepwise design approach for the construction of the hierarchy and inputs required are presented. The subsequent operation of the hierarchy in an unreliable environment is also explained. Aggregation schemes for model reduction have been developed and blended with a time-scale decomposition of activities to provide the theoretical foundation of the architecture. It is also hoped that this methodology can be applied to other such large-scale complex decision making problems.Item Design and Operation of Hierarchical Production Management Systems(1991) Nagi, R.; Harhalakis, G.; ISRProduction Planning Management and Control of a production system subject to random events are challenging problems. A multi-layer hierarchical approach to tactical and aggregate production planning problems is proposed, wherein the architecture is strongly based on the specific physical system, applicable controls and the complexity of the decision making problem at hand. We address the design and operation of such Hierarchical production Management Systems (HPMS). Regarding the design aspect, we start by developing schemes for product, machine and temporal aggregation; consistency and controllability issues in the hierarchy have been addressed in the aggregation/disaggregation schemes. These three aggregation schemes for model reduction have been developed and incorporated to the time-scale decomposition of activities, in order to provide a solid theoretical foundation of the architecture. We then proceed to a systematic stepwise design approach for the construction of the hierarchy. It provides the appropriate number of layers and an associated Model as well as Decision Making Problem (DMP) at each level. A model is defined by entities, attributes, links and domains, while a DMP is defined by a set of possible controls (decisions), constraints, and optimality criteria to be optimized over a planning horizon. The operation of the hierarchy consists of a topdown computation of controls, which calls for the resolution of an optimization problem at each level of the hierarchy. The solution of any problem in sequence determines some parameters in the subsequent problem. We detail the mechanism for top-down constraint propagation, which is important in ensuring consistency of criteria and feasibility. The execution then involves the bottom-up feedbacks, and a revision in the plan is carried out if necessary. In particular, the rolling horizon mechanism, and the reaction of the hierarchy to random events has been detailed. A generic job-shop example has been employed to present the design and operation of the HPMS. It is hoped that this methodology can be applied to other types of large-scale complex decision making problems.