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... Thus, the objectives of this research involve: (1) development of a BIM-based ontology model to help rescue route planning, considering the factors such as path length, building components and materials, and forcible entry tools; (2) collection and analysis of the data set on the time use of each tool against different building components and materials; and (3) examination of real fire investigation reports to gauge the differences between the original routes and the ones generated from the proposed approach, with the help from domain experts. In this research, an ontology model plays an important role in integrating BIM data and dismantling knowledge, because it has been successfully used to express sophisticated knowledge for highly dynamic environments, similar to the fire rescue operations described in this research [23][24][25][26][27]. The manuscript is structured as follows: Section 2 reviews related literature, while Section 3 describes the proposed ontology model and the data collection process regarding forcible entry tools usage. ...
As our society ages, more and more elderly or disabled people live in long-term care (LTC) facilities, which are vulnerable to fires and may result in heavy casualties. Because of the low mobility of LTC residents, firefighters often need to enter the facility to save people. In addition, due to LTC facility management needs, many doors or windows on the passages for a fire rescue operation may be blocked. Thus, firefighters have to employ forcible entry tools such as disk cutters for passing through, which may lengthen the rescue time if an incorrect route or tool is utilized. As new information technologies such as ontology and building information modeling (BIM) have matured, this research aims at proposing a BIM-based ontology model to help firefighters determine better rescue routes instead of using rules of thumb. Factors such as the path length, building components and materials encountered, and forcible entry tools carried are considered in the model. Real LTC fire investigation reports are used for the comparisons between the original routes and the ones generated by the proposed model, and seven experts joined the evaluation workshop to provide further insights. The experts agreed that using the proposed approach can lead to better fire rescue route planning. The proposed BIM-based ontology model could be extended to accommodate additional needs for hospital fire scenes, in the hopes of enhancing the efficiency and effectiveness of firefighters’ rescue operations in such important facilities.
... Standards have significant importance for realizing the Industry 4.0 vision and industrial digital chain monitoring to reduce costs. ere are several studies [45,46] concerning the management of Industry 4.0-related standards and terminologies as well as the creation of knowledge-based frameworks. A good overview is provided by an ontology called Industry 4.0 Knowledge Graph [47], which has been developed in order to represent and categorize standards, standardization organizations, and standardization frameworks involved in the domain of Industry 4.0 [46]. ...
... ere are several studies [45,46] concerning the management of Industry 4.0-related standards and terminologies as well as the creation of knowledge-based frameworks. A good overview is provided by an ontology called Industry 4.0 Knowledge Graph [47], which has been developed in order to represent and categorize standards, standardization organizations, and standardization frameworks involved in the domain of Industry 4.0 [46]. In Figure 9, the complexity of this field is highlighted. ...
... Industry 4.0 standards by means of semantic technologies[46]. ...
Effective information management is critical for the development of manufacturing processes. This paper aims to provide an overview of ontologies that can be utilized in building Industry 4.0 applications. The main contributions of the work are that it highlights ontologies that are suitable for manufacturing management and recommends the multilayer-network-based interpretation and analysis of ontology-based databases. This article not only serves as a reference for engineers and researchers on ontologies but also presents a reproducible industrial case study that describes the ontology-based model of a wire harness assembly manufacturing process.
... Existing data integration approaches rely on the description of the characteristics of entities to solve interoperability by discovering alignments among them. Specifically, in the context of I4.0, semantic-based approaches have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks [4,6,18,19]. Despite informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. ...
... Then, the homophily prediction principle is applied in a way that similar standards in a community are considered to be related. 4 The I4.0RD Architecture Figure 3 presents I4.0RD, a pipeline that implements the proposed approach. I4.0RD receives an I4.0KG G, and returns an I4.0KG G that corresponds to a solution of the problem of discovering relations between standards. ...
Industry 4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of empowering interoperability in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.
... Existing data integration approaches rely on the description of the characteristics of entities to solve interoperability by discovering alignments among them. Specifically, in the context of I4.0, semantic-based approaches have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks [4,6,18,19]. Despite informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. ...
... Then, the homophily prediction principle is applied in a way that similar standards in a community are considered to be related. 4 The I4.0RD Architecture Figure 3 presents I4.0RD, a pipeline that implements the proposed approach. I4.0RD receives an I4.0KG G, and returns an I4.0KG G that corresponds to a solution of the problem of discovering relations between standards. ...
Industry~4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of \emph{empowering interoperability} in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans$^*$ family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.
... These publications introduced the initial definitions of the standard and standardization framework concepts. Further progress has been presented by Bader et al. [2], enhancing the graph with Industry 4.0 reference frameworks and new application patterns of Web-based visualization services and interactive views. ...
... Starting with six top-level concerns (Data Sovereignty, Internet of Things, Trustworthiness, Data Analytics, Interoperability, Business Context), cycle-free dependencies of sub-concerns are formed. Further details about the concerns themselves have been presented also by Bader et al. [2]. Figure 3 shows a set of I40KG instances. ...
... While we constantly extend and update the graph, a perfect coverage is neither possible nor intended. Nevertheless, a sufficient completeness of the domain is necessary and has been examined by Bader et al. [2]. The presented selection criteria show how academic and industry impact have been examined to optimally discover and filter the I40KG entities. ...
One of the most crucial tasks for today’s knowledge workers is to get and retain a thorough overview on the latest state of the art. Especially in dynamic and evolving domains, the amount of relevant sources is constantly increasing, updating and overruling previous methods and approaches. For instance, the digital transformation of manufacturing systems, called Industry 4.0, currently faces an overwhelming amount of standardization efforts and reference initiatives, resulting in a sophisticated information environment. We propose a structured dataset in the form of a semantically annotated knowledge graph for Industry 4.0 related standards, norms and reference frameworks. The graph provides a Linked Data-conform collection of annotated, classified reference guidelines supporting newcomers and experts alike in understanding how to implement Industry 4.0 systems. We illustrate the suitability of the graph for various use cases, its already existing applications, present the maintenance process and evaluate its quality.
... These publications introduced the initial definitions of the standard and standardization framework concepts. Further progress has been presented by Bader et al. [2], enhancing the graph with Industry 4.0 reference frameworks and new application patterns of Web-based visualization services and interactive views. ...
... Starting with six top-level concerns (Data Sovereignty, Internet of Things, Trustworthiness, Data Analytics, Interoperability, Business Context), cycle-free dependencies of sub-concerns are formed. Further details about the concerns themselves have been presented also by Bader et al. [2]. this is usually the IEC webstore site of the respective standard. ...
... While we constantly extend and update the graph, a perfect coverage is neither possible nor intended. Nevertheless, a sufficient completeness of the domain is necessary and has been examined by Bader et al. [2]. The presented selection criteria show how academic and industry impact have been examined to optimally discover and filter the I40KG entities. ...
One of the most crucial tasks for today's knowledge workers is to get and retain a thorough overview on the latest state of the art. Especially in dynamic and evolving domains, the amount of relevant sources is constantly increasing, updating and overruling previous methods and approaches. For instance, the digital transformation of manufacturing systems, called Industry 4.0, currently faces an overwhelming amount of standardization efforts and reference initiatives, resulting in a sophisticated information environment. We propose a structured dataset in the form of a semantically annotated knowledge graph for Industry 4.0 related standards, norms and reference frameworks. The graph provides a Linked Data-conform collection of annotated, classified reference guidelines supporting newcomers and experts alike in understanding how to implement Industry 4.0 systems. We illustrate the suitability of the graph for various use cases, its already existing applications, present the maintenance process and evaluate its quality.
Adequate information management is critical for the development of manufacturing processes. Therefore, this chapter aims to provide a systematic overview of ontologies that can be utilized in building Industry 4.0 applications and highlights that ontologies are suitable for manufacturing management. Additionally, industry-related standards and other models are also discussed.
Comprehensive, independently operating digital representations of physical assets, provisioned and manipulated through standardized interaction patterns, dissolve between the tangible and virtual world. Real-world developments are reflected in digital models and vice versa. The concept of digital twins combines these facets to integrated entities, specifying the description, appearance, and behavior of real-world entities in virtual models. This chapter explains how smart services enact as digital twins but also how they interact in flexible, loosely coupled networks.
