Volume 9, Issue 3 - Special Issue: Selected Papers from the Workshop on Modelling and Simulation of Food Processing and Operations of the MAS 2012 Conference (Wien, September 19–21, 2012), Guest Editors: Eleonora Bottani, Andrea Grassi, Roberto Montanari, Giuseppe Vignali

: This article proposes an advanced java-based simulation tool developed in order to support decision making in a manufacturing system operating in the hazelnuts industry sector. By providing the user with high flexibility in terms of manufacturing scenarios definition, the simulation tool can be used as an advanced decision-making tool to understand the dynamic interactions between multiple performance measures (that include both production lines and inventory system performances) and a set of user-defined factors (the latter defined by the production manager according to his/her needs in terms of manufacturing scenarios investigation). To understand how the simulation model can be used as decision-making tool and for testing the tool effectiveness, simulation results analyses and analytical meta-models are provided for different manufacturing scenarios.

This work focuses on applying dynamic simulation to explore operating conditions of a packed batch distillation column for reducing the relative concentration of methanol in the distillate. Based on trial-and-error, we studied different cooling rate trajectories of the partial condenser, which has a direct impact on the reflux and distillate rates. Simulations showed that higher cooling rates and smaller cut times achieved lower relative concentrations of methanol in the distillate. Our study suggests that the best operating strategy cannot reduce the relative methanol concentration in the distillate more than 25% compared with the relative methanol concentration in the wine.

The global environment, where many companies compete for their survival, requires a continuous adaptation to changes in the market and to other environment variables. Food industry, agriculture in particular, is a field where the companies are especially sensitive to modifications in regulations and market requirements. It is very convenient to provide the companies of this sector with a theoretical basis, as well as with practical tools for developing an efficient management that may guarantee not only their survival but also their success. In this area, decision-support systems based on the simulation of models, developed by means of the paradigm of the Petri nets, can offer a significant help for improving the efficiency of farming companies, based on the appropriate decision making. In this article, a methodology for decision making, supported by artificial intelligence, is applied to the farming field and an application case is analyzed for better understanding of the advantages and drawbacks of this approach. In particular, a decision-making methodology for improving the management of the operation and redesign of traditional companies in the farming industry is applied to the wine sector in the region of La Rioja (Spain).

This article presents a case study of general ergonomic and operational improvement of the on board process in factory ships. The process includes several lines with automatic and manual operations for processing caught fish as different products. It is a complex system with a great variety of operation possibilities. An exploratory simulation model of the plant and the human tasks is developed as a way to identify improvement opportunities. A combined simulation approach has been adopted for the characterization and improvement of the process comprising (i) a Discrete Event Simulation (DES) to develop the analysis of the production system and experiment with operational rules and (ii) a DHM-based study to analyse the present ergonomic conditions on the manual operations and to propose alternative workstation designs that could lead to effective and ergonomic improvement. As a result, we could characterize the process efficiency in different production scenarios, the organizational effects in the packing workstation and the ergonomic and operational assessment of the packing operations.

Direct steam injection is a sterilization technique which is often used for high-viscosity fluid food, when the preservation of the quality characteristics and energy efficiency are the priority. In this work, an apparatus for the sterilization of tomato concentrate has been analyzed by means of a 3D computational fluid dynamics (CFD) model, in order to optimize the exchanger performance in terms of temperature distribution inside the product. A multidimensional two-phase model of steam injection inside a non-Newtonian pseudoplastic fluid was adopted to evaluate the thermal history of the product and the condensation rate of the steam injected in the heat exchanger during the thermal process. Subsequently, the CFD analysis has been extended to examine the effects of the different process parameters (sterilization temperature, steam flow rate, radial and axial temperature profiles and nozzle geometry) on the resulting product. Results obtained allowed to understand the effects of process parameters on the behavior of the condensing steam and obtain better performance of the exchanger in terms of temperature distribution of the treated product.

This work focuses on discontinuous (batch) vertical fluid mixing systems for food fluids with particles. A properly designed mixing process has to provide two main results: a satisfactory homogeneity of the product and the preservation of the integrity of the solid particles. The main problem in the design of a mixer for fluid–solid suspensions is to identify the operating levers which act in order to optimize the performance of the process, while preserving the integrity of the pieces. The purpose of this work is to identify some structural and physical parameters that have the strongest influence on the performance of the mixing process, in order to obtain useful indications for the design of mixing systems. Different mixer designs were thus analyzed thanks to computational fluid dynamics simulations, from which some key performance indicators (KPIs) related to the effectiveness of the mixing process were obtained. An analysis of variance and a residual analysis were then performed in order to assess the significance of the influence of each input parameter (position of the rotor, fluid viscosity, and aspect ratio), on the individual KPIs and on the global performance of the mixer. From these analyses, some conclusions useful to choose an appropriate design solution for fluid mixers were derived.

This work aims to analyze and predict the thermal pasteurization process for two types of fresh pasta, by means of computational fluid dynamic (CFD) simulation. The types of pasta considered are “ravioli” filled of meat and “orecchiette”, without filling. Thanks to many studies on pasta properties, some parameters, such as thermal conductivity and heat capacity, are previously determined for both products. CFD simulations are, thus, performed using ANSYS CFX code version 14.5 in a transient state (after 150 s for ravioli and after 45 s for orecchiette), to evaluate the pasteurization temperature and the P -value reached on the surface of the orecchiette and at the core of the ravioli, as a function of the process time. The heat exchange takes place in a pasteurization tunnel by means of water vapor at ~371 K. Experimental tests are finally performed to validate the simulation model of heat exchange. Results show a good agreement between the simulated results and the real pasteurization process and confirm the potential usefulness of the simulation model to evaluate the process performance.