An efficient and simplified solution to the predesign problem of multiproduct plants

̃a, A. Espun; Zaro, Marco; ́nez, J.M. Marti; Puigjaner, Luís

doi:10.1016/0098-1354(89)89015-5

Cited by 15 publications

(5 citation statements)

References 6 publications

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“…They consider that the total production is achieved in only one time and neglect short-term production problems. Others 8 consider successive long-term monoproduct campaigns providing the production level of several products. Another approach commonly used in the literature concerns the simultaneous manufacturing of several products under the condition that they do not share equipment, the so-called multiproduct campaigns.…”

Section: A Discrete-event Simulation Model For Design Purposesmentioning

confidence: 99%

Multiobjective Batch Plant Design: A Two-Stage Methodology. 1. Development of a Design-Oriented Discrete-Event Simulation Model

Bernal-Haro

Azzaro‐Pantel

Pibouleau

et al. 2002

Ind. Eng. Chem. Res.

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This work reports development of a two-stage methodology for multiobjective batch plant design, which may be viewed as an alternative to traditional approaches based on mathematical programming techniques: (1) At the upper level, a genetic algorithm (GA) has been developed for solving the problem of design and proposing several plant structures. This kind of algorithm has proven previously its efficiency for the treatment of combinatorial problems. ( 2) At the inner level, a discrete-event simulation model (DES) tests the technical feasibility of the generated configurations. Part 1 of this series of papers is devoted to the implementation of the DES model whereas part 2 will tackle the development of the GA. The basic principles of the development of the design-oriented DES model are first recalled, and then the various potential uses of the simulator are presented. A detailed account of model assumptions for design purpose is also given. The formalism is illustrated by a typical example serving as a test bench in part 2.

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Section: A Discrete-event Simulation Model For Design Purposesmentioning

confidence: 99%

Multiobjective Batch Plant Design: A Two-Stage Methodology. 1. Development of a Design-Oriented Discrete-Event Simulation Model

Bernal-Haro

Azzaro‐Pantel

Pibouleau

et al. 2002

Ind. Eng. Chem. Res.

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“…This kind of plants produces a number of related products using the same equipment in the same operation sequence. Mainly, approaches with constant time and size factors are the most used in the modeling of such plants 2–11. Similar approaches using constant factors have also been presented in the field of multipurpose batch plant design 12–16.…”

Section: Introductionmentioning

confidence: 99%

Multiproduct batch plants design using linear process performance models

Moreno

Montagna

2010

AIChE Journal

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In this contribution, a novel linear generalized disjunctive programming (LGDP) model is developed for the design of multiproduct batch plants optimizing both process variables and the structure of the plant through the use of process performance models. These models describe unit operations using explicit expressions for the size and time factors as functions of the process variables with the highest impact. To attain a linear formulation, values of the process variables as well as unit sizes are selected from a set of meaningful discrete values provided by the designer. Regarding structural alternatives, both kinds of unit duplications in series and in parallel are considered in this approach. The inclusion of the duplication in series requires different detailed models that depend on the structure selected. Thus, in a new approach for the multiproduct batch plant design, a set of potential structural alternatives for the plant is defined. V V C 2010 American Institute of Chemical Engineers AIChE J, 57: 122-135, 2011 Keywords:LGDP, performance models, multiproduct batch plants, duplication in series IntroductionA large number of optimization models for the design of multiproduct batch plants have been developed over the last decades.1 This kind of plants produces a number of related products using the same equipment in the same operation sequence. Mainly, approaches with constant time and size factors are the most used in the modeling of such plants. [2][3][4][5][6][7][8][9][10][11] Similar approaches using constant factors have also been presented in the field of multipurpose batch plant design. [12][13][14][15][16] However, these models fix the process variables to get a determined process recipe avoiding the evaluation of various economic trade-offs involved in the design decisions. To attain more detailed formulations, process performance models have been included into the design of multiproduct batch plants. The performance models describe size and time factors as a function of the process decision variables (i.e., variables with the highest economic impact on the process) selected for the optimization. Several contributions [17][18][19][20][21][22][23] have tackled performance models instead of fixed recipes to incorporate information about the production process in the plant design. Specifically, the performance models entail additional algebraic equations obtained from mass balances and simplified kinetic equations that describe every unit operation in the process. They may be constant values, an equation, or even a system of equations in accordance with the selected level of detail.In all of the aforementioned problem formulations, the final model is nonlinear and, generally, depending on the proposed representation for the unit operations, nonconvex.Correspondence concerning this article should be addressed to M. S. Moreno at smoreno@santafe-conicet.gov.ar. 122AIChE Journal January 2011 Vol. 57, No. 1 Typically, the most common approach used to solve this problem has been to formulate it as a mixe...

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“…In 1979 and 1982, Grossman and Sargent, Knopf et al, and Takamastsu et al improved the MP methods and applied them to the design problem. Moreover, in 1989, Espuña and Puigjaner used an efficient optimization strategy based on gradient calculation, with the advantage of reducing the computing time, to solve the problem . In 1994, Barbosa-Póvga and Macchietto constructed the model, including very general constraints and objective functions and permitting both capital costs of equipment units and pipework and operating costs and revenues to be taken into account.…”

Section: Introductionmentioning

confidence: 99%

Ants Foraging Mechanism in the Design of Multiproduct Batch Chemical Process

Wang

Zhao

2002

Ind. Eng. Chem. Res.

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In this paper, a novel evolutionary approach, the ants foraging mechanism (AFM), that effectively overcomes local optima is presented for the solution of the optimal design of multiproduct batch chemical processes. To demonstrate the effectiveness of AFM in solving the proposed problem, four examples adopted from the literature are presented, together with the computation results. Satisfactory results are obtained in comparison with the results of mathematical programming (MP), tabu search (TS), genetic algorithm (GA), and simulated annealing (SA) algorithm.

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An efficient and simplified solution to the predesign problem of multiproduct plants

Cited by 15 publications

References 6 publications

Multiobjective Batch Plant Design: A Two-Stage Methodology. 1. Development of a Design-Oriented Discrete-Event Simulation Model

Multiobjective Batch Plant Design: A Two-Stage Methodology. 1. Development of a Design-Oriented Discrete-Event Simulation Model

Multiproduct batch plants design using linear process performance models

Ants Foraging Mechanism in the Design of Multiproduct Batch Chemical Process

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