8 resultados para Changeover

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

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In this paper, we are concerned about the short-term scheduling of industrial make-and-pack production processes. The planning problem consists in minimizing the production makespan while meeting given end-product demands. Sequence-dependent changeover times, multi-purpose storage units with finite capacities, quarantine times, batch splitting, partial equipment connectivity, material transfer times, and a large number of operations contribute to the complexity of the problem. Known MILP formulations cover all technological constraints of such production processes, but only small problem instances can be solved in reasonable CPU times. In this paper, we develop a heuristic in order to tackle large instances. Under this heuristic, groups of batches are scheduled iteratively using a novel MILP formulation; the assignment of the batches to the groups and the scheduling sequence of the groups are determined using a priority rule. We demonstrate the applicability by means of a real-world production process.

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We investigate numerically the effects of nozzle-exit flow conditions on the jet-flow development and the near-field sound at a diameter-based Reynolds number of Re D = 18 100 and Mach number Ma = 0.9. Our computational setup features the inclusion of a cylindrical nozzle which allows to establish a physical nozzle-exit flow and therefore well-defined initial jet-flow conditions. Within the nozzle, the flow is modeled by a potential flow core and a laminar, transitional, or developing turbulent boundary layer. The goal is to document and to compare the effects of the different jet inflows on the jet flow development and the sound radiation. For laminar and transitional boundary layers, transition to turbulence in the jet shear layer is governed by the development of Kelvin-Helmholtz instabilities. With the turbulent nozzle boundary layer, the jet flow development is characterized by a rapid changeover to a turbulent free shear layer within about one nozzle diameter. Sound pressure levels are strongly enhanced for laminar and transitional exit conditions compared to the turbulent case. However, a frequency and frequency-wavenumber analysis of the near-field pressure indicates that the dominant sound radiation characteristics remain largely unaffected. By applying a recently developed scaling procedure, we obtain a close match of the scaled near-field sound spectra for all nozzle-exit turbulence levels and also a reasonable agreement with experimental far-field data.