Control vector parameterization with sensitivity based refinement applied to baking optimization

In bakery production, product quality attributes as crispness, brownness, crumb and water content are developed by the transformations that occur during baking and which are initiated by heating. A quality driven procedure requires process optimization to improve bakery production and to find operational procedures for new products. Control vector parameterization (CVP) is an effective method for the optimization procedure. However, for accurate optimization with a large number of parameters CVP optimization takes a long computation time. In this work, an improved method for direct dynamic optimization using CVP is presented. The method uses a sensitivity based step size refinement for the selection of control input parameters. The optimization starts with a coarse discretization level for the control input in time. In successive iterations the step size was refined for the parameters for which the performance index has a sensitivity value above a threshold value.With this selection, optimization is continued for a selected group of input parameters while the other nonsensitive parameters (below threshold) are kept constant. Increasing the threshold value lowers the computation time, however the obtained performance index becomes less. A threshold value in the range of 10–20% of the mean sensitivity satisfies well. The method gives a better solution for a lower computation effort than single run optimization with a large number of parameters or refinement procedures without selection

Product quality driven design of bakery operations using dynamic optimization

Quality driven design uses specified product qualities as a starting point for process design. By backward reasoning the required process conditions and processing system were found. In this work dynamic optimization was used as a tool to generate processing solutions for baking processes by calculating optimal operation strategies which give a basis for process and unit operation design. Two different approaches for dynamic optimization had been applied: calculation of continuous trajectories based on the calculus of variations (1) and calculation of switching trajectories by using control vector parameterization (2). Optimization of bakery processes was performed for different product specifications and by using different heating sources: convective, microwave and radiation heating. Moreover, effects of variations in dough properties on the optimal processing system were also evaluated. The results showed that dynamic optimization procedures were versatile tools to achieve a better and a more flexible design by generating a number of solutions from the specified final product qualities. Furthermore, the results underpinned the well known empirical fact that different final product speci- fications require different baking strategies. It was also shown that the initial dough properties have significant effect on baking procedures, and that combining several heating inputs improved the flexibility of the process operation. In addition, optimization for continuous trajectories gave overall a better result than using the switching trajectories

Quality prediction of bakery products in the initial phase of process design

The development of food production processes is facilitated by tools which explore the interaction between process design, operation conditions and product characteristics. In this work an approach how to set-up a simulation model is presented for the phenomena and transformations which occur during baking and which fix the product quality. The simulation model has three consecutive parts: mass and heat transport in the product, transformations concerning starch state transition and color, and the formation of quality attributes (color, softness, crispness and staling). The model for mass and heat transfer is based on laws of conservation and expressed in partial differential equations for spatial products. The starch state transition and color formation are a mixture of qualitative and quantitative information, while the product quality model is mainly based on qualitative information. The model is applied to three bakery products: bread, biscuit and a cake-type. The results show that the model estimates the product quality and its transformations as a function of dough composition, baking and storage condition. The results fit well to observed changes of properties and product quality during baking

Elektrificatie drogers inspireert industrie Bulk

Vanuit het ISPT1-project ‘GRIP op drogers’, in samenwerking met de NWGD2, is deze zomer een expertmeeting gehouden over het thema elektrificatie. De gastheer was mattenfabrikant Rinos, waar gasgestookte droogovens voor de ‘curing’ van de matten zijn vervangen door elektrische ovens. De experts doordachten hoe ook bij andere bedrijven droogprocessen succesvol kunnen worden geëlektrificeerd