BACKGROUND: The enzymatic hydrolysis of steam‐exploded wheat straw using commercial enzyme complexes has been studied. A cellulase enzyme complex (Accellerase 1500), along with specific xylanase complements (Accellerase‐XC and Accellerase‐XY) provided by Genencor, have been used to enhance glucose and xylose recovery. A systematic study with response surface methodology (RSM) was used to check the effect of the operating conditions: pH (4–5), temperature (50–60 °C) and enzyme/substrate ratio (0.1–0.5 mL gcellulose−1) on the enzymatic hydrolysis with Acellerase 1500 to maximize the sugar yield. Xylanases were used as complements to increase the release of xylose. RESULT: Statistical results from ANOVA analysis demonstrated that the enzymatic hydrolysis was clearly improved by temperature and enzyme/substrate ratio. The optimum conditions for higher glucose and xylose releases were obtained with the higher enzyme dosage ratio (0.5 mL g−1cellulose), 50 °C and pH 4. CONCLUSION: Model validation at optimum operating conditions showed good agreement between the experimental results and the predicted responses for a confidence level of 95%. The use of the xylanase complements, Accellerase‐XY (accessory xylanase enzyme complex) and Accellerase‐XC (accessory xylanase/cellulase enzyme complex), increases the conversion of hemicellulose. Accellerase‐XC supplementation was more effective, obtaining an increase in yields of glucose and xylose of 11.8% and 23.6%, respectively, using a dosage of 0.125 mL g−1cellulose. © 2012 Society of Chemical Industry

This work aims to optimise the operation of an evaporation network with shared resources in real time. The goal is minimising the resource utilisation (live steam and cooling water) while satisfying a set of operational constrains. Hence, problems of optimal load allocation of feeds to plants and cooling-water distribution among them arise. The work bases on plants surrogate models, experimentally obtained, and analyses different formulation alternatives of the optimisation from the practical point of view: centralised vs distributed approaches. In particular for the distributed approach, we propose a problem decomposition which allows us to solve the problem in two iterative ways: 1) as two independent optimisations or 2) via price-coordination schemes.

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This work deals with the problem of distribution of cooling water in an evaporation process. The aim is to develop a Real-Time Optimisation (RTO) tool which improves the resource efficiency by supplying the optimal water distribution within a surface-condensers network for a given production demand. The approach includes experimental models and the automatic update of fouling factor. The problem is formulated and solved via nonlinear programming. Production constraints and concerns about the practical implementation are also taken into account in the design of the RTO tool.

En este trabajo se describe el desarrollo e implementación de un sistema de control de una planta piloto química. Dicha planta piloto tiene la característica de que el componente principal del proceso, la reacción exotérmica, está siendo simulado. Antes de configurar el sistema SCADA, se ha modelado y simulado el proceso, y definido el sistema de control que se llevará a cabo. Destacar que el sistema SCADA además de proporcionar una interfaz gráfica de visualización del sistema, conecta la tarjeta de adquisición de datos de la planta con diferentes módulos externos accesibles como servidores OPC con diferentes funcionalidades: cuatro capaces de realizar cálculos PID y que de forma conjunta constituyen el sistema de control, y uno que funciona como un bloque calculador.

This work discusses what should be the desirable path and correct tools for the optimal re-design and operation of processes in the Industry 4.0 framework, as illustrated in a challenging case study corresponding to a complex network of evaporation plants in a viscose-fiber factory. The goal is to integrate optimal design, to improve the existing cooling systems, together with the optimal operation of the whole network, balancing the initial investment with the potentially achievable savings. A rigorous mathematical model for such optimization purpose has been built. The model explicitly considers different structural alternatives as a superstructure for the incorporation of new equipment into the network. The uncertainty associated to future operating conditions is also considered by using a two-stage stochastic formulation. Furthermore, the model is also the base from which a deterministic real-time optimization (RTO) builds upon to support the daily management of the future network operation. The RTO tool suggests the allocation of different products to evaporation plants, the distribution of the cooling water and the suitable number of heat pumps to switch on for optimal economic operation. Design and operation problems are formulated and solved via mixed-integer non-linear programming and the results have been tested with historical plant data.

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