Aplicació d'algoritmes genètics en l'optimització dels processos de fabricació del paper

  1. Turon Casalprim, Xavier
Supervised by:
  1. Pere Mutjé Pujol Director
  2. Jalel Labidi Director

Defence university: Universitat de Girona

Fecha de defensa: 19 April 2005

Committee:
  1. Luis Jiménez Alcaide Chair
  2. Jordi Bayer Trías Secretary
  3. Maria Angels Pèlach Serra Committee member
  4. Antonio L. Torres López Committee member
  5. Francisco Sobrón Grañón Committee member

Type: Thesis

Teseo: 128978 DIALNET

Abstract

The growing awareness of the civil society for the environment and the resulting regulations introduced has modified chemical industry production processes. Existing process configuration should be modified to reach an integrated process design. Methodologies are required to support process reconfiguration during the integrated process design. The development of a methodology and its related tools is the goal of the research presented here. The focus lies on the development and application of a process optimization methodology. This optimization methodology starts with an existing process configuration and looks for feasible new configurations according to objectives fixed. The whole methodology has two differentiated parts: a commercial process simulation tool and the process optimization technique. Methodology starts with a validated process simulation reproducing existing process, in this case a non integrated paper mill producing coated high grade printing paper. Then process optimization technique performs a search in domain of possible results, looking for best results satisfying the objectives stated. Optimization technique is based on genetic algorithms as a search tool, coupled with mathematic linear programming. A pool of retained results is introduced into process simulation as process flows redistribution. Process simulation results determine feasibility of each reconfiguration. Objectives of process optimization are defined in an objective function in the optimization technique. Such function rules the search of results. Objective function could contain a single objective or a combination of objectives. In this case, objective function is defined to reach water consumption minimization and material loss minimization. Optimization was carried out under constraints to reach combined goals in a trade-off solution. As a result of optimisation methodology application interesting results were obtained enhancing system closure and raw materials savings while keeping process operability and paper quality.