A semantic framework for enabling model integration for biorefining

This paper introduces a new paradigm for establishing a framework that enables interoperability between process models and datasets using ontology engineering. Semantics are used to model the knowledge in the domain of biorefining including both tacit and explicit knowledge, which supports registration and instantiation of the models and datasets. Semantic algorithms allow the formation of model integration through input/output matching based on semantic relevance between the models and datasets. In addition, partial matching is employed to facilitate flexibility to broaden the horizon to find opportunities in identifying an appropriate model and/or dataset. The proposed algorithm is implemented as a web service and demonstrated using a case study.The authors wish to acknowledge the financial support by the Marie Curie Initial Training Networks Program, under the RENESENG project (FP7-607415)

Industrial symbiosis and agri-food system: Themes, links, and relationships

Industrial symbiosis is an eco-innovative system concept that is based on a circular economy and industrial ecology ideas. This process comprises the movement of materials, energy, and skills across enterprises located within eco-industrial parks, and strives to provide economic, environmental, and social competitive advantages for all the involved parties. Considering that the agri-food system creates a vast quantity of by-products along the supply chain, it is a sector that has huge potential within material and energy recovery systems and fits well into eco-industrial parks. The current study is a literature review that aims to evaluate the interest exhibited so far by scientific research in the topic of industrial symbiosis in the agri-food sector and to highlight the primary analytical techniques that have been used for this topic. Using the paradigm of multiple correspondence analysis, a content analysis was conducted from which the major themes of the researched phenomena emerged. The results indicate that the topic areas are unrelated and somewhat distant from each other. The analyzed case studies have revealed that the authors had neglected the communicative and collaborative elements among stakeholders, and instead focused on the potential use of some tools and approaches. Furthermore, it has been hypothesized that the hiding of information within a supply chain prevents industrial symbiosis procedures from being implemented. This research suggests the necessity of creating communication and cooperation platforms among stakeholders, which would promote the introduction of new techniques and tools for the development of circular production systems

An investigation of sustainable agricultural residue availability for energy applications

An integrated modeling strategy is developed to determine the potential for sustainable agricultural residue removal potential for bioenergy production. Agricultural residues have been identified as a significant potential resource for bioenergy production, but serious questions remain about the sustainability of harvesting residues. Agricultural residues play an important role in limiting soil erosion from wind and water and in maintaining soil organic carbon. Because of this, multiple factors must be considered when assessing sustainable residue harvest limits. Validated and accepted modeling tools for assessing these impacts include the Revised Universal Soil Loss Equation Version 2 (RUSLE2), the Wind Erosion Prediction System (WEPS), and the Soil Conditioning Index. Currently, these models do not work together as a single integrated model. This dissertation presents an integrated modeling strategy that couples existing datasets with the RUSLE2 water erosion, WEPS wind erosion, and Soil Conditioning Index soil carbon modeling tools to create a single integrated residue removal modeling system. Using this computational tool, a series of studies were performed. The first investigates agricultural residue removal potential for the state of Iowa. The key conclusions of this study are that under current management practices and crop yields nearly 26.5 million Mg of agricultural residue are sustainably accessible in the state of Iowa, and that through the adoption of no till practices residue removal could sustainably approach 40 million Mg. The next study provides a spatially comprehensive assessment of sustainable agricultural residue removal potential across the US. This type of assessment is needed to support development and investment decisions for an emerging bioenergy industry. Earlier assessments determining the quantity of agricultural residue that could be sustainably removed for bioenergy production at the regional and national scale faced a number of computational limitations. These limitations included the number of environmental factors, the number of land management scenarios, and the spatial fidelity and spatial extent of the assessment. The study presented here provides estimates of county average and state totals of sustainably available agricultural. The results of the assessment show that in 2011 over 150 million metric tons of agricultural residues could have been sustainably removed across the US. Projecting crop yields and land management practices out to 2030, the assessment determines that over 207 million metric tons of agricultural residue could be sustainably removed for bioenergy production at that time. The next study develops a computational strategy that utilizes data inputs from multiple spatial scales to investigate how variability within individual fields can impact sustainable residue removal. Increased availability of sub-field scale datasets such as grain yield data, high fidelity digital elevation models, and soil characteristic data provides an opportunity to investigate the impacts of sub-field scale variability on sustainable agricultural residue removal. Using three representative fields in Iowa, this paper contrasts the results of current Natural Resources Conservation Services (NRCS) conservation management planning analysis with sub-field scale analysis for rake and bale removal of agricultural residue. The results of the comparison show that the field average assumptions used in the NRCS conservation management planning may lead to unsustainable residue removal decisions for significant portions of some fields. The final study examines the potential of a conceptual variable rate residue removal equipment configuration capable of on-the-fly residue removal rate adjustments from 0%-80% by modeling residue removal at thirteen removal rate levels: 0% and 25%-80% at 5% increments. Three Iowa fields with diverse soil, slope, and grain yield characteristics were examined, and the sustainable removal rate of agricultural residue using the conceptual variable rate removal equipment was 2.35, 7.69, and 5.62 Mg ha-1. In contrast, the sustainable removal rates using rake and bale removal for the entire field were 0.0, 6.40, and 5.06, respectively

Conceptual modelling for integrated decision-making in process systems

This Thesis addresses the systematic construction of Decision Making Models (DMMs) from the conceptualization stage to its application in specific situations, with special emphasis on !he treatment of scenarios where there is a hierarchy of decision levels, common in the Process Systems (PS). Although the methodologies developed are generic, the scope of this Thesis is limited to the perspective of Process Engineering. The central component required to construct a DMM is the conceptual description of the reality, which supports the system alisation of management procedures . During this description, two different dom ains can be identified: the PS Domain, useful to describe the structure of the process as such (physical reality and the way in which its elements are related), and the Management Domain, identified in this Thesis as associated with the Conceptual Constraints (CC) that describe the restrictions associated with the management of the process . In this way, the PS Domain includes concepts and relationships that appear in the control standards of the process followed by the company: the description of the process to be developed, the description of the physical equipment in which it is developed , and that of its interactions, giving rise to the control of the execution of the procedures; this domain should allow managing the construction, design, operation and control of any manufacturing system. On the other hand, the CC Domain contains the information associated with the concepts and relationships that m ust be fulfilled to ensure a coherent set of decisions, with the purpose of identifying and representing the systematics to follow during the decision-making process, giving rise to the conceptual representation of this system and, finally, the construction of the corresponding DMM. The first challenge addressed in this thesis is associated with the systematisation of conceptual modelling from semantic information, for the construction ofontologies from textual sources and a procedure to verify the interna! coherence of lhese sources. The application of this methodology has been used for the identification of the essential concepts and relationships in the PS Domain, allowing creating a generic, common and shared model, unlike the existing models. In the next step, this PS Domain has been used to solve management problems in systems that comprise multi-level hierarchies. The resulting decision-making process allows integrating the decisions made al each level, ensuring their consistency from an approach that simultaneously considers the management of all available information (data and knowledge). On the other hand, the introduction of the necessary concepts and relationships to ensure the feasibility of the process management decisions, through the CC Domain, allows the development of systematic DMM creation procedures: this domain classifies the constrains (balances, sequence, etc.), adds abstrae! elements to them (e.g.: produced and consumed amounts) and allows to generalize the relation of its compone nis with the information associated to the PS Domain. The last part of this Thesis deals with the integration of the PS and CC Domains, and their application for the generation of new decision-making systems . For this, algorithms have been designed that, starting from the previously identified and classified restrictions, and patterns of DMMs also previously identified from existing cases, exploit the information available through the instances in the PS Domain, to generate new DMMs according to the user's specifications. lts use is illustrated through cases from different environments, demonstrating the generalisation capacity of the created systematics.Esta Tesis aborda la construcción sistemática de Modelos para la toma de Decisiones (DMMs) desde la etapa de conceptualización hasta su aplicación en situaciones concretas, con especial énfasis en el tratamiento de escenarios en los que existe una jerarquía de niveles de decisión, habitual en la Industria de Proceso (PS). Aunque las metodologías desarrolladas son genéricas, el alcance de esta Tesis se limita a la perspectiva de la Ingeniería de Procesos. El componente central requerido para construir un DMMs es la descripción conceptual de la realidad a la que se orienta, que a su vez respalda la sistematización de los procedimientos de gestión. Durante esta descripción, se pueden identificar planteamientos asociados a dos dominios diferentes: el Dominio del Proceso (PS), útil para describir la estructura del proceso como tal (realidad física y forma en la que se relacionan sus elementos), y el Dominio de Gestión, asociado a las Restricciones Conceptuales (CC) que describen las restricciones asociadas a la gestión del proceso. El Dominio PS incluye conceptos y relaciones que aparecen en los estándares de control del proceso que sigue la empresa: la descripción del proceso a desarrollar, la descripción de los equipos físicos en los que se desarrolla, y la de sus interacciones, que dan lugar al control de ejecución de los procedimientos; este dominio debe permitir la construcción, el diseño, la operación y el control de cualquier sistema de fabricación. Por su parte, el Dominio CC contiene la información asociada a los conceptos y las relaciones que deben cumplirse para asegurar un conjunto coherente de decisiones, con el propósito de identificar y representar la sistemática a seguir durante el proceso de toma de decisiones, dando lugar a la representación conceptual de esta sistemática y, finalmente, a la construcción del correspondiente DMM. El primer reto abordado en esta Tesis está asociado a la sistematización del modelado conceptual a partir de información semántica, para construcción de ontologías a partir de fuentes textuales y de un procedimiento para verificar la coherencia interna de dichas fuentes. La aplicación de esta metodología se ha utilizado para la identificación de los conceptos y las relaciones esenciales en el Dominio PS, permitiendo crear un modelo genérico, común y compartido, a diferencia de los modelos existentes. En el siguiente paso, este Dominio PS se ha utilizado para la resolución de problemas de gestión en sistemas que comprenden múltiples niveles de jerarquías funcionales. El proceso de toma de decisiones resultante permite integrar las decisiones tomadas en cada nivel, asegurando su coherencia a partir de un enfoque que contempla simultáneamente la gestión de toda la información disponible (datos y conocimiento). Por su parte, la introducción de los conceptos y relaciones necesarios para asegurar la factibilidad de las decisiones de gestión del proceso, a través del Dominio CC, permite el desarrollo de procedimientos sistemáticos de creación de DMMs: este Dominio clasifica las restricciones (balances, secuencia, etc.), agrega elementos abstractos a dichas restricciones (p.e.: cantidad producida y consumida) y permite generalizar la relación de sus componentes con la información asociada al Dominio PS. En la última parte de esta Tesis se aborda la integración de los Dominios PS y CC, y su aplicación para la generación de nuevos sistemas de toma de decisiones. Para ello, se han diseñado algoritmos que, partiendo de las restricciones anteriormente identificadas y clasificadas, y patrones de DMMs también previamente identificados a partir de casos ya existentes, explotan la información disponible a través de las instancias del Dominio PS, para generar de nuevos modelos de toma de decisión de acuerdo con las especificaciones del usuario. Su utilización se ilustra a través de casos procedentes de diferentes entornos, demostrando la capacidad de generalización de la sistemática creada.Postprint (published version

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Blockchain-Based Digitalization of Logistics Processes—Innovation, Applications, Best Practices

Blockchain technology is becoming one of the most powerful future technologies in supporting logistics processes and applications. It has the potential to destroy and reorganize traditional logistics structures. Both researchers and practitioners all over the world continuously report on novel blockchain-based projects, possibilities, and innovative solutions with better logistic service levels and lower costs. The idea of this Special Issue is to provide an overview of the status quo in research and possibilities to effectively implement blockchain-based solutions in business practice. This Special Issue reprint contained well-prepared research reports regarding recent advances in blockchain technology around logistics processes to provide insights into realized maturity