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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Author: search.filters.author.Nagi, R.Subject: search.filters.subject.manufacturing

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    Design of Material Flow Networks in Manufacturing Facilities
    (1994) Herrmann, Jeffrey W.; Ioannou, George; Minis, Ioannis; Nagi, R.; Proth, J.M.; ISR
    In this paper we consider the design of material handling flow paths in a discrete parts manufacturing facility. A fixed-charge capacitated network design model is presented and two efficient heuristics are proposed to determine near-optimal solutions to the resulting NP- hard problem. The heuristics are tested against an implicit enumeration scheme used to obtain optimal solutions for small examples. For more realistic cases, the solutions of the heuristics are compared to lower bounds obtained by either the linear programming relaxation of the mixed integer program, or an iterative dual ascent algorithm. The results obtained indicate that the heuristics provide good solutions in reasonable time on the average. The proposed methodology is applied to design the flow paths of an existing manufacturing facility. The role of the flow path network problem in the integrated shop design is also discussed.
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    Manufacturing Cell Formation Under Random Product Demand
    (1993) Harhalakis, George; Minis, Ioannis; Nagi, R.; ISR
    The 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.
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    A Class of Conflict Free Petri Nets Used for Controlling Manufacturing Systems
    (1992) Harhalakis, George; Levantopoulos, Marios M.; Lin, Chang-Pin; Nagi, R.; Proth, J.M.; ISR
    This paper is devoted to the behavior, evaluation and management of non-cyclic discrete systems in general and manufacturing systems in particular. We introduce a special type of Petri nets called CFIOs (Conflict-Free nets with Input and Output transitions). It is shown that CFIOs are live, reversible if consistent, and can be kept bounded under certain conditions. We also develop reduction rules which facilitate the computation of the t-invariants of CFIOs. We then take advantage of the qualitative properties of CFIOs to perform planning in manufacturing systems. Numerical examples illustrate these approaches
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    Hierarchical Modeling Approach for Production Planning
    (1992) Harhalakis, George; Nagi, R.; Proth, J.M.; ISR
    Production 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.