Successful software development requires good specifications, that is, correct, consistent, and unambiguous requirements. Natural language artifacts are the most used tools for writing ...specifications; nevertheless, the use of natural language can introduce many defects such as ambiguity, vagueness, and generality. In light of this, the purpose of this paper is to propose an approach for writing good specifications and extracting knowledge from them. The proposed approach uses a particular lexicon, the Language Extended Lexicon (LEL) glossary, and suggests rules for extracting knowledge (concepts, attributes, and relationships) from it. This paper also presents a prototype that implements and supports the proposed approach, as well as a preliminary evaluation of the approach. In conclusion, the proposed approach represents a theoretical contribution, which was evaluated using the System Usability Scale, and its evaluation results are promising, as it obtained the maximum score.
Un desarrollo de software exitoso necesita buenas especificaciones, es decir, requerimientos correctos, consistentes y no ambiguos. Los artefactos en lenguaje natural son la herramienta más utilizada para escribir especificaciones; sin embargo, el uso del lenguaje natural puede introducir muchos defectos: ambigüedad, vaguedad y generalidad. Por lo tanto, el objetivo de este artículo es brindar un enfoque para escribir buenas especificaciones y extraer conocimiento de ellas. El enfoque propuesto utiliza un léxico particular, el glosario Léxico Extendido del Lenguaje (LEL). Y sugiere reglas para extraer conocimientos (conceptos, atributos y relaciones) de él. Este artículo también presenta un prototipo que implementa y apoya el enfoque propuesto, así como también una evaluación preliminar del enfoque. En conclusión, el enfoque propuesto representa una contribución teoría, que fue evaluada utilizando el System Usability Scale y sus resultados son prometedores, ya que obtuvo la calificación máxima.
•A systematic literature review is conducted to explore the main features, research and technical challenges in conceiving and building Digital Twins.•Topic Modelling Analysis has been implemented to ...provide an up-to-date picture of the digital twin.•Formal Concept Analysis (FCA) has been applied to understand the digital twin trends and strategies.
Manufacturing enterprises are facing the need to align themselves to the new information technologies (IT) and respond to the new challenges of variable market demand. One of the key enablers of this IT revolution toward Smart Manufacturing is the digital twin (DT). It embeds a “virtual” image of the reality constantly synchronized with the real operating scenario to provide sound information (knowledge model) to reality interpretation model to draw sound decisions. The paper aims at providing an up-to date picture of the main DT components, their features and interaction problems. The paper aims at clearly tracing the ongoing research and technical challenges in conceiving and building DTs as well, according to different application domains and related technologies. To this purpose, the main questions answered here are: ‘What is a Digital Twin?’; ‘Where is appropriate to use a Digital Twin?’; ‘When has a Digital Twin to be developed?’; ‘Why should a Digital Twin be used?’; ‘How to design and implement a Digital Twin?’; ‘What are the main challenges of implementing a Digital Twin?’. This study tries to answer to the previous questions funding on a wide systematic literature review of scientific research, tools, and technicalities in different application domains.
Manufacturing organisations are facing the urge to adopt new strategies like sustainability to be able to respond to the market and customer's demand for sustainable products due to the scarcity of ...the natural resources or government policies. To serve this purpose, the main questions risen are 'How sustainability is defined through its dimensions?' and 'what sub-dimensions can denominate sustainable manufacturing?' Focusing on the questions, this study is cantered by a systematic literature review based on sustainability, its dimensions and sub-dimensions to investigate sustainability in manufacturing and the domains on which manufacturers can act on to be more 'sustainable'. Although the literature is more focused on the three traditional dimensions of sustainability namely: environmental, economic and social, a more detailed look through the dimensions is needed to help manufacturing organisations sketch their own sustainable strategies on more specific issues. The study of the dimensions led to a hierarchy of importance for the traditional three, in which environmental dimension of sustainability showed to be conspicuous. Therefore, the dimension was chosen for the further analysis conducted by Formal Concept Analysis (FCA) on its sub-dimensions to explore the trends in their combination by manufacturers while trying to reach sustainability.
Manufacturing organisations are now facing unexpected challenges due to scarcity of the natural resources and consequent governmental rules that urge to adopt new organisational or even manufacturing ...strategies. Adopting the sustainability paradigm at the present seems to be the only viable strategy to respond appropriately to this changed market conditions and customer's demand. As the pressure for changing the traditional manufacturing approach to reach a sustainable operating condition increases, the urge for assessing their sustainability performance has been reinforced accordingly. Various methods have been accomplished so far, trying to find a way to assess the sustainability state of companies, to select among sustainable solutions, to define and to solve practical problems and to identify potential sustainable solutions. Due to this abundance, the present study is cantered by a systematic literature review based on sustainable manufacturing and sustainability assessment to explore questions on sustainable manufacturing: 'How can sustainable manufacturing be achieved?' and 'How can sustainable manufacturing be assessed?' The study led to stipulation of the true essence of sustainable manufacturing and sustainability assessment. It also brought new hints on the sustainability assessment of manufacturing recognising true gaps needed to be filled. Furthermore, to investigate the regularity of the methods and tools of sustainability assessment, a Formal Concept Analysis (FCA) was adopted. At the end, a new holistic framework for sustainability assessment in a manufacturing organisation is proposed.
Cyber-Physical Systems (CPS) are systems composed by a physical component that is controlled by a cyber-component. They are leading the 4-th Industrial Revolution characterized by high ...intercommunicating properties of its production elements in the manufacturing processes. For this reason, it is a core concept how the systems should be structurally optimized to have the adequate level of redundancy to be satisfactorily resilient. The actual proposal presents a CPS meta-model and its instantiation. Using the CPS meta-model formalization and the Formal Concept Analysis approach, this paper presents a way to optimize the modelling of CPS systems emphasizing their redundancy and resiliency.
•Reviews over than two hundred papers, that provide a contribution to knowledge by establishing the linkages between new 4.0 trends in technologies and Agri-Food Supply Chain Challenges.•A ...compressive state of the art of Agri-Food 4.0 related technologies is covered.•Reviews and contributes on the digital technologies to the new supply chain methods in Agri-Food.•Links to the agri-food supply chain challenges.•Presents new trends and models in agri-food supply chains.
The term “Agri-Food 4.0” is an analogy to the term "Industry 4.0", coming from the concept “agriculture 4.0”. Since the origins of the industrial revolution, where the steam engines started the concept of Industry 1.0 and later the use of electricity upgraded the concept to Industry 2.0, the use of technologies generated a milestone in the industry revolution by addressing the Industry 3.0 concept. Hence, Industry 4.0, it is about including and integrating the latest developments based on digital technologies as well as the interoperability process across them. This allows enterprises to transmit real-time information in terms behaviour and performance. Therefore, the challenge is to maintain these complex networked structures efficiently linked and organised within the use of such technologies, especially to identify and satisfy supply chain stakeholders dynamic requirements. In this context, the agriculture domain is not an exception although it possesses some specialities depending from the domain. In fact, all agricultural machinery incorporates electronic controls and has entered to the digital age, enhancing their current performance. In addition, electronics, using sensors and drones, support the data collection of several agriculture key aspects, such as weather, geographical spatialization, animals and crops behaviours, as well as the entire farm life cycle. However, the use of the right methods and methodologies for enhancing agriculture supply chains performance is still a challenge, thus the concept of Industry 4.0 has evolved and adapted to agriculture 4.0 in order analyse the behaviours and performance in this specific domain. Thus, the question mark on how agriculture 4.0 support a better supply chain decision-making process, or how can help to save time to farmer to make effective decision based on objective data, remains open. Therefore, in this survey, a review of more than hundred papers on new technologies and the new available supply chains methods are analysed and contrasted to understand the future paths of the Agri-Food domain.
Prognostics and Health Management (PHM) approaches aim to intervene in the equipment of production systems before faults occur. To properly implement a PHM system, data-centric steps must be taken, ...including data acquisition and manipulation, detection of machine states, health assessment, prognosis of future failures, and advisory generation. The data generated by different data sources, such as maintenance management systems, equipment manufacturer manuals, design documentation, and process monitoring and control systems, are fundamental for PHM steps. Discovering and using the knowledge embedded in this data is relevant because, for example, data-driven techniques require knowledge, maintenance data often contain tacit knowledge that can facilitate knowledge transfer and collaboration between maintenance personnel with different levels of experience and expertise, and the knowledge related to the same types of systems could be context-dependent. However, the heterogeneity of data sources, the variety of data types, and the possibility of context-dependent data pose challenges in revealing the real value of data and discovering the useful, yet hidden, patterns embedded in maintenance data that can lead to explicit knowledge. Ontologies can effectively contribute to this issue through the organization of data, semantic annotation, integration, and checking of consistency. Several ontologies contributing to the PHM process have been proposed in the scientific literature. However, to the best of our knowledge, no overview of the available ontologies contributing to the PHM steps of production systems is present in the literature. Therefore, this paper aimed to investigate the ontologies and knowledge graphs proposed in the literature for the PHM of production systems. A systematic analysis and mapping of the literature was performed, and the main information was extracted and discussed according to (i) the type and year of the publication, (ii) the ontological and non-ontological resources adopted for designing the ontology/knowledge graph, (iii) the method adopted for implementing the approach, (iv) the type of application, (v) the step(s) of the PHM process on which the article is focused, and (vi) the type of decisions (strategical, tactical, or operational) to which the ontology/knowledge graph is adopted. Subsequently, the conducted analysis led to the definition of a research agenda in the domain, including the following challenges to address: (1) alignment of the ontologies in the maintenance field with respect to top-level ontologies, (2) connection among the different PHM steps at the operational level, (3) major exploitation of the combination of data-driven AI, ontologies, and reasoning for predictive maintenance, and (4) supporting sustainability-related challenges through the connection between the production system, maintenance system, and product.
Smart Enterprises, Smart Manufacturing, and Cyber-Physical Systems are gaining traction in many industry areas. On top of that, the amounts of available data grow rapidly, and organizations are eager ...to exploit their advantages. To accomplish that, it is mandatory to have a wide variety of methods and algorithms for knowledge extraction in order to fit the different needs and problems of the industry. In this study, we review and dissect the current state of the art in knowledge extraction applied to smart enterprises, smart manufacturing, and cyber-physical systems. More specifically, we provide a classification of the characteristics of the available methods in the literature according to their applications, and point out areas of improvement.
The interoperability among a variety of systems, in or across manufacturing enterprises, has been widely accepted as one of the important factors that affect the efficiency of production. Many ...research works, related to the interoperability at different levels, have been carried out to tackle the information exchange, transformation, discovery and reuse. One of the main challenges in these research works is to overcome the semantic heterogeneity in the exchanged information between enterprise applications along the life cycle of a product. As a possible solution to support the semantic interoperability issue, semantic annotations have gained more and more attention. This paper identifies several existing drawbacks and proposes a formal semantic annotation approach to support the semantic enrichment of models in a product lifecycle management context.
•Explore the invariance concept may improve the modelling effort to implement DT.•Propose and develop a new approach to designing a digital twin by recurring the concept of "modelling patterns" and ...the idea of their invariance property.•Design and build a digital twin for a die-casting aluminium process based on the modelling patterns instantiation.
The Digital Twin (DT) is one of the most promising technologies in the digital transformation market. A digital twin is a virtual copy of a physical system that emulates its behaviour to predict failures and opportunities for change, prescribe actions in real-time, and optimise and/or mitigate unexpected events. Modelling the virtual copy of a physical system is a rather complex task and requires the availability of a large amount of information and a set of accurate models that adequately represent the reality to model. At present, the modelling depends on the specific use case. Hence, the need to design a modelling solution suitable for virtual reality modelling in the context of a digital twin. The paper proposes a new approach to design a DT by endeavouring the concept of "modelling patterns" and their invariance property. Modelling patterns are here thought of as data-driven, as they can be derived autonomously from data using a specific approach devised to reach an invariance feature, to allow these to be used (and re-used) in modelling situations and/or problems with any given degree of similarity. The potentialities of invariance modelling patterns are proved here by the grace of a real industrial application, where a dedicated DT has been built using the approach proposed here.
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