Modelling decision support systems using conceptual constraints: linking process systems engineering and decision making models

This paper presents the use of a Conceptual Constraint (CC) Domain to systematize the construction of Decision Making Models (DMMs). The modelling systematics include the integration between the CC Domain and production systems as well as an identification procedure which contains some steps aimed at constraint identification using the CC Domain. The CC Domain consists of different modelling elements such as Conceptual Constraints (generic constraint types), Conceptual Components (pieces of a constraint), and Conceptual Component Elements (pieces of a conceptual component that may be connected to production systems). In this instance, the CC Domain is integrated with the Process Systems Engineering (PSE) Domain as a production system domain. The PSE Domain contains information from the multi-level functional hierarchical in an enterprise and it will be used to cover a wide range of scenarios related to hierarchical integration of DMMs. In addition, an integration step between the CC and PSE Domains is illustrated. The focus of the work is to show how these models should be developed in order to be properly integrated, and how they are used by different functionalities with an identification procedure.Postprint (author's final draft

A rolling horizon optimization framework for the simultaneous energy supply and demand planning in microgrids

This work focuses on the development of optimization-based scheduling strategies for the coordination of microgrids. The main novelty of this work is the simultaneous management of energy production and energy demand within a reactive scheduling approach to deal with the presence of uncertainty associated to production and consumption. Delays in the nominal energy demands are allowed under associated penalty costs to tackle flexible and fluctuating demand profiles. In this study, the basic microgrid structure consists of renewable energy systems (photovoltaic panels, wind turbines) and energy storage units. Consequently, a Mixed Integer Linear Programming (MILP) formulation is presented and used within a rolling horizon scheme that periodically updates input data information

Integrated game-theory modelling for multi enterprise-wide coordination and collaboration under uncertain competitive environment

In this work, an integrated Game Theory (GT) approach is developed for the coordination of multi-enterprise Supply Chains (SCs) in a competitive uncertain environment. The conflicting goals of the different participants are solved through coordination contracts using a non-cooperative non-zero-sum Stackelberg game under the leadership of the manufacturer. The Stackelberg payoff matrix is built under the nominal conditions, and then evaluated under different probable uncertain scenarios using a Monte-Carlo simulation. The competition between the Stackelberg game players and the third parties is solved through a Nash Equilibrium game. A novel way to analyze the game outcome is proposed based on a win–win Stackelberg set of “Pareto-frontiers”. The benefits of the resulting MINLP tactical models are illustrated by a case study with different vendors around a client SC. The results show that the coordinated decisions lead to higher expected payoffs compared to the standalone case, while also leading to uncertainty reduction.Peer ReviewedPostprint (author's final draft

Contribución al estudio de plantas químicas multiproducto de proceso discontínuo

La operación de plantas discontinuas multiproducto a niveles óptimos de capacidad de producción requiere un análisis detallado y selectivo entre las diferentes alternativas viables para la fabricación de cada uno de los productos, teniendo en cuenta las características específicas de la propia planta y las restricciones de producción asociadas a cada situación concreta. Por ello es necesario que en la etapa de concepción de la planta se hayan efectuado los estudios de diseño adecuados (síntesis y cálculo de capacidades), a fin de obtener una planta que permita la flexibilidad necesaria para obtener niveles de producción óptimos en las diferentes situaciones que pueden presentarse durante el ciclo de vida de las instalaciones y en un entorno de mercado cambiante.En la presente tesis se ha planteado la resolución de algunos problemas de estrategia (tanto de diseño como de fabricación, y su interrelación) que se presentan en una planta multiproducto trabajando por lotes. Para ello se han desarrollado:· Una estrategia de diseño eficiente, basada en las formulaciones habituales del problema, que permite una reducción sustancial en el número global de variables y restricciones.· Un método de optimización aplicable a la estrategia de diseño anterior, basado en procedimientos de cálculo de gradientes y que incluye ciertas modificaciones heurísticas, que permite una reducción importante en el tiempo de cálculo necesario para llegar a la solución de los problemas planteados.· Un modelo de planta de proceso discontinuo orientado a cubrir los requerimientos de simulación de planes de producción, que considera las fases básicas de toda operación discontinua y las restricciones que se pueden establecer entre ellas.El modelo puede ser fácilmente manipulado para incorporar restricciones de funcionamiento propias de casos específicos.· Una serie de procedimientos de planificación de la producción y secuenciación de tareas que, utilizando el modelo anterior, permiten simular situaciones y analizar fácilmente las respuestas de una determinada planta en diferentes escenarios de mercado.· Un sistema de relación entre los procedimientos de diseño y de planificación, de forma que las conclusiones sobre el funcionamiento de la planta en determinados escenarios de trabajo permitan corregir adecuadamente los resultados de un diseño preliminar.Estos procedimientos se han aplicado al estudio de diversos casos, extraídos tanto de la literatura existente sobre el tema como de diferentes aplicaciones sobre situaciones industriales reales, donde se contemplan tareas discontinuas y semicontinuas en un amplio rango de condiciones de trabajo, de número y clases de equipos, de número de productos y de restricciones de producción y diseño, analizándose también problemas de remodelación.Al estudiar situaciones industriales reales, la necesidad de adaptarse a un entorno muy complejo y cambiante, con una serie de características propias que difícilmente pueden introducirse en un modelo matemático sencillo (por ejemplo, políticas de empresa), suele llevar a situaciones inabordables a través de las formulaciones y los procedimientos de cálculo que habitualmente se aplican a diferentes problemas de optimización. Por otra parte, la utilización de modelos simplificados suele ser en detrimento del rigor necesario, dando lugar a soluciones incorrectas o incluso irrealizables. En consecuencia, para conseguir resultados aceptables será necesario utilizar procedimientos basados en el conocimiento específico de cada caso concreto

Towards automatic construction of domain ontologies: Application to ISA88 and assessment

Process Systems Engineering has shown a growing interest on ontologies to develop knowledge models, organize information, and produce software accordingly. Although software tools supporting the structure of ontologies exist, developing a PSE ontology is a creative procedure to be performed by human experts from each specific domain. This work explores the opportunities for automatic construction of domain ontologies. Specialised documentation can be selected and automatically parsed; next pattern recognition methods can be used to extract concepts and relations; finally, supervision is required to validate the automatic outcome, as well as to complete the task. The bulk of the development of an ontology is expected to result from the application of systematic procedures, thus the development time will be significantly reduced. Automatic methods were prepared and applied to the development of an ontology for batch processing based on the ISA88 standard. Methods are described and commented, and results are discussed from the comparison with a previous ontology for the same domain manually developed.Postprint (published version

Improving automation standards via semantic modelling: Application to ISA88

Standardization is essential for automation. Extensibility, scalability, and reusability are important features for automation software that rely in the efficient modelling of the addressed systems. The work presented here is from the ongoing development of a methodology for semi-automatic ontology construction methodology from technical documents. The main aim of this work is to systematically check the consistency of technical documents and support the improvement of technical document consistency. The formalization of conceptual models and the subsequent writing of technical standards are simultaneously analyzed, and guidelines proposed for application to future technical standards. Three paradigms are discussed for the development of domain ontologies from technical documents, starting from the current state of the art, continuing with the intermediate method presented and used in this paper, and ending with the suggested paradigm for the future. The ISA88 Standard is taken as a representative case study. Linguistic techniques from the semi-automatic ontology construction methodology is applied to the ISA88 Standard and different modelling and standardization aspects that are worth sharing with the automation community is addressed. This study discusses different paradigms for developing and sharing conceptual models for the subsequent development of automation software, along with presenting the systematic consistency checking methodPeer ReviewedPostprint (author's final draft

Optimal management of bio-based energy supply chains under parametric uncertainty through a data-driven decision-support framework

This paper addresses the optimal management of a multi-objective bio-based energy supply chain network subjected to multiple sources of uncertainty. The complexity to obtain an optimal solution using traditional uncertainty management methods dramatically increases with the number of uncertain factors considered. Such a complexity produces that, if tractable, the problem is solved after a large computational effort. Therefore, in this work a data-driven decision-making framework is proposed to address this issue. Such a framework exploits machine learning techniques to efficiently approximate the optimal management decisions considering a set of uncertain parameters that continuously influence the process behavior as an input. A design of computer experiments technique is used in order to combine these parameters and produce a matrix of representative information. These data are used to optimize the deterministic multi-objective bio-based energy network problem through conventional optimization methods, leading to a detailed (but elementary) map of the optimal management decisions based on the uncertain parameters. Afterwards, the detailed data-driven relations are described/identified using an Ordinary Kriging meta-model. The result exhibits a very high accuracy of the parametric meta-models for predicting the optimal decision variables in comparison with the traditional stochastic approach. Besides, and more importantly, a dramatic reduction of the computational effort required to obtain these optimal values in response to the change of the uncertain parameters is achieved. Thus the use of the proposed data-driven decision tool promotes a time-effective optimal decision making, which represents a step forward to use data-driven strategy in large-scale/complex industrial problems.Peer ReviewedPostprint (published version

Application of industrial symbiosis principles to the management of utility networks

Utility exchanges between different plants have shown to produce large energy savings, extending the potential advantages of Energy/Process Integration through Industrial Symbiosis principles. Systematic approaches to determine such exchanges in industrial networks have been already proposed, although some of them are only applicable to specific situations and some others introduce the figure of a central authority. However, assuming such a figure in non-cooperative situations may restrict the economic benefit of some companies involved, thus discouraging their participation and preventing eventual agreements. The aim of this work is to develop an optimization model that allows analyzing the different symbiosis alternatives in different conflicting situations, even without the presence of any authority. Scenarios inspired by Game Theory have been considered. The problem has been modelled using a Mixed Integer Linear Programming (MILP) formulation and its capacities are illustrated through a particular case from the literature. Results show that the method allows establishing utility exchanges between different plants, which can improve the energetic, economic and environmental efficiency of all of them, as well as the whole set. Considering cooperative scenarios may allow determining solutions producing total energy savings and cost reductions, but without taking the specific interests of individual companies into account. On the other hand, considering non-cooperative scenarios ensures desirable outcomes from the eventual agreements for each company. Furthermore, the model is able to identify the economic barriers of the companies for participating, thus, being a useful and applicable tool that may improve decision-making support for managing utility networks in such situations.Peer ReviewedPostprint (published version

Scenario-based dynamic negotiation for the coordination of multi-enterprise supply chains under uncertainty

A novel scenario-based dynamic negotiation approach is proposed for the coordination of decentralized supply chains under uncertainty. The relations between the involved organizations (client, provider and third parties) and their respective conflicting objectives are captured through a non-zero-sum and non symmetric roles SBDN negotiation. The client (leader) designs coordination agreements considering the uncertain reaction of the provider (follower) resulting from the uncertain nature of the third parties, which is modeled as a probability of acceptance function. Different negotiation scenarios are studied: (i) cooperative, and (ii) non-cooperative and (iii) standalone cases. The use of the resulting models is illustrated through a case study with different vendors around aPeer ReviewedPostprint (author's final draft

Targeting economic and environmental benefits associated with the integration of regeneration units in water systems

Water treatment is traditionally seen as an "end-of-pipe" solution to deal with contaminated water satisfying discharge regulations at a minimum expense. However, the reuse of treated water as regenerated water is a promising strategy to counteract water scarcity. This approach to transform waste into resources is motivated by the circular economy paradigm. This study presents a mathematical programming approach to target both the environmental and economic benefits of water systems by introducing additional regeneration units to close the loop. In addition to water users and authorities, the approach also considers operators and dealers, which are revealed as key stakeholders. Hence, the feasible region of the regeneration units design specifications is determined and visualized through a multi-objective optimization approach targeting the systems operating cost and freshwater consumption. Its application is demonstrated on a benchmark case study from the literature, revealing a potential economic benefit of 37.5% and a freshwater reduction of 80.9% over the case without regeneration units. Furthermore, we show that a cooperative exchange strategy leads to higher benefits compared to the solutions presented in the literature. Finally, we demonstrate how the barrier plots introduced in this work can be used by different stakeholders in the water market to support their decision-making.Peer ReviewedPostprint (published version