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

Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems

Rapid changes in the open manufacturing environment are imminent due to the increase of customer demand, global competition, and digital fusion. This has exponentially increased both complexity and uncertainty in the manufacturing landscape, creating serious challenges for competitive enterprises. For enterprises to remain competitive, analysing manufacturing activities and designing systems to address emergent needs, in a timely and efficient manner, is understood to be crucial. However, existing analysis and design approaches adopt a narrow diagnostic focus on either managerial or engineering aspects and neglect to consider the holistic complex behaviour of enterprises in a collaborative manufacturing network (CMN). It has been suggested that reflecting upon ecosystem theory may bring a better understanding of how to analyse the CMN. The research presented in this paper draws on a theoretical discussion with aim to demonstrate a facilitating approach to those analysis and design tasks. This approach was later operationalised using enterprise modelling (EM) techniques in a novel, developed framework that enhanced systematic analysis, design, and business-IT alignment. It is expected that this research view is opening a new field of investigation

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Utilization of Product Lifecycle Data from PLM Systems in Platforms for Industrial Symbiosis

Industrial Symbiosis represents a promising approach to foster the transformation towards a circular economy. To involve businesses in Industrial Symbiosis, online platforms and input-output matching tools for facilitating the exchange of by-products have been provided by industry organizations and facilitators. Regarding the discrete parts and product manufacturing industry (DPPM), little success is being reported for such platforms and tools. Within the scope of this research, a list of Input-Output matching tools was analysed regarding data sources which are currently used for input-output Matching. Specifications of by-products in the DPPM industry were reviewed in order to identify a list of requirements for data sources. Shortcomings of the currently existing input-output matching tools were identified and suggestions for additional data sources used for input-output matching in IS in DPPM were given. Results show that datasets currently used do not include organisational data sources such as Product Data Management (PDM) systems, Enterprise Resource Planning (ERP) systems, Supply Chain Management (SCM) systems, and or Manufacturing Execution Systems (MES)

Eco‐Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain Towards Digital Transition

The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects

Industry 4.0 and human factor: How is technology changing the role of the maintenance operator?

Abstract Industry 4.0 is revolutionizing not only the manufacturing industry but also maintenance strategies. As consequence of the introduction of Industry 4.0 technologies, new skills are demanded to maintenance operators that has to be able to interact, as instance, with Cyber Physical Systems and robots. In this paper, we first investigate the state-of-the-art of Industry 4.0 technologies that are transforming operations and production management and finally we discuss how the role of maintenance operators is changed in a such digitalized environment. We found that, the maintenance Operator 4.0 should be able to find relevant information and predict events by a proper use of Big Data analytics, in addition to the ability of interacting with computers, digital databases and robots. Finally, the ability to rapidly adapt his skills to innovations is also strongly demanded

Smart eco-industrial parks: A circular economy implementation based on industrial metabolism

In order to conserve natural environments, the Circular Economy (CE) is considered as a suitable way to carry out the transition from current economic models to models of a more sustainable nature. From the biological perspective however, industrial systems are generally inefficient. Manufacturing systems from the biological perspective therefore require the incorporation of tools to support decision making, thereby enabling organizations to improve their functions and competitiveness in a global and integrated perspective. Accordingly, at meso level, eco-industrial parks are gaining importance as an approach towards ensuring CE. In this work, an ontological framework for CE, based on industrial metabolism, is developed as the technology for information and knowledge models to share the circularity of resources through industrial ecosystems, based on ecological, economic, and social criteria. The ontology developed is modelled using Ontology Web Language and integrated in an architecture based on bio-inspired Multi-Agent Systems (MAS). Moreover, a quantitative method, Ecological Network Analysis, is incorporated into MAS knowledge to analyze and establish relationships and metabolic pathways between companies, which can increase the circularity of technical nutrients and reduce biological nutrient extraction. The integrated model is applied to a case study on the product life cycle for the establishment of its metabolic pathway through an eco-industrial park. The subsequent incorporation of MAS thereby establishes the Smart Eco-Industrial Park

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

Enterprise-specific ontology-driven process modelling

Different process models are created within an enterprise by different modelers who use different enterprise terms. This hinders model interoperability and integration. A possible solution is formalizing the vocabulary used within the enterprise in an ontology and put this ontology as bases for constructing process models. Given that an enterprise is an evolving entity, the ontology needs to evolve to properly reflect the domain of the enterprise. This paper proposes an enterprise-specific ontology-driven process modelling method which tackles the two aforementioned issues by assisting the modeller in creating process models using terminology from the ontology and simultaneously supporting ontology enrichment with feedback from those models. When the modeller creates a model, matching mechanisms incorporated in the method are working together to suggest a list of ontological concepts that have a high potential to be useful for a particular modelling element. When the model is created, its quality is first evaluated from different perspectives to make sure that it can be used within the enterprise, and second to discover whether its feedback can be useful for the ontology. When the feedback is extracted, the proposed method incorporates guidelines on how to use this feedback