This paper proposes a human-in-the-loop framework that integrates machine learning models with semantic technologies to aid decision making in the domain of steelmaking. To achieve this, we convert a ...random forest (RF) into rules in a Semantic Web Rule Language (SWRL) format and represent real-world data as a knowledge graph in a Resource Description Framework (RDF) format, capturing the meta-data as part of the model. A rule engine is deployed that applies logical inference on the knowledge graph, resulting in a semantically enriched classification. This new classification is combined with external domain-expert knowledge to provide improved, knowledge-guided assistance for the human-in-the-loop system. A case study in the steel manufacturing domain is introduced, where this application is used for real-world predictive analytic purposes.
This paper introduces the Steel Cold Rolling Ontology (SCRO) to model and capture domain knowledge of cold rolling processes and activities within a steel plant. A case study is set up that uses ...real-world cold rolling data sets to validate the performance and functionality of SCRO. This includes using the Ontop framework to deploy virtual knowledge graphs for data access, data integration, data querying, and condition-based maintenance purposes. SCRO is evaluated using OOPS!, the ontology pitfall detection system, and feedback from domain experts from Tata Steel.
Cyber Physical Trust Systems (CPTS) are Cyber Physical Systems and Internet of Things enriched with trust as an explicit, measurable, testable and verifiable system component. In this paper, we ...propose to use blockchain, a distributed ledger technology, as the trust enabling system component for CPTS. We propose two schemes for CPTSs driven by blockchain in relation to two typical network model cases. We show that our proposed approach achieves the security properties, such as device identification, authentication, integrity, and non-repudiation, and provides protection against popular attacks, such as replay and spoofing. We provide formal proofs of those properties using the Tamarin Prover tool. We describe results of a proof-of-concept which implements a CPTS driven by blockchain for physical asset management and present a performance analysis of our implementation. We identify use cases in which CPTSs driven by blockchain find applications.
Following the trend of Industry 4.0, the business model of steel manufacturing is transforming from a historical inwardly focused supplier/customer relationship to one that embraces the wider ...end-to-end supply chain and improves productivity more holistically. However, the data and information required for supply chain planning and steelmaking process modelling are normally distributed over scattered sources across organisation boundaries and research communities. This leads to a major problem concerning semantic interoperability. To address this issue, this paper introduces a Common Reference Ontology for Steelmaking (CROS). CROS serves as a shared steelmaking resource and capability model that aims to facilitate knowledge modelling, knowledge sharing and information management. In contrast to most of the existing steelmaking ontologies which merely focus on conceptual modelling, our work pays special attention to the real-world implementation and utilisation aspects of CROS. The functionality and usefulness of CROS is evaluated and tested on a real-world condition-based monitoring and maintenance task for cold rolling mills at Tata Steel in the United Kingdom.
•A novel Core Reference Ontology for Steelmaking (CROS) has been introduced.•CROS formally describes essential steelmaking processes, tools, and resources.•We demonstrate the systematic ontology development process for CROS.•We evaluate the functionality and usefulness of the proposed ontology by demonstrating a real-world case study.
This paper studies the complexity of constant depth propositional proofs in the cedent and sequent calculus. We discuss the relationships between the size of tree-like proofs, the size of dag-like ...proofs, and the heights of proofs. The main result is to correct a proof construction in an earlier paper about transformations from proofs with polylogarithmic height and constantly many formulas per cedent.
We study consistency search problems for Frege and extended Frege proofs—namely the NP search problems of finding syntactic errors in Frege and extended Frege proofs of contradictions. The input is a ...polynomial time function, or an oracle, describing a proof of a contradiction; the output is the location of a syntactic error in the proof. The consistency search problems for Frege and extended Frege systems are shown to be many-one complete for the provably total NP search problems of the second-order bounded arithmetic theories U
1
2
and V
1
2
, respectively.
We show that logics based on linear Kripke frames—with or without constant domains—that have a scattered end piece are not recursively enumerable. This is done by reduction to validity in all finite ...classical models.
In the context of Industry 4.0, smart factories use advanced sensing and data analytic technologies to understand and monitor the manufacturing processes. To enhance production efficiency and ...reliability, statistical Artificial Intelligence (AI) technologies such as machine learning and data mining are used to detect and predict potential anomalies within manufacturing processes. However, due to the heterogeneous nature of industrial data, sometimes the knowledge extracted from industrial data is presented in a complex structure. This brings the semantic gap issue which stands for the lack of interoperability among different manufacturing systems. Furthermore, as the Cyber-Physical Systems (CPS) are becoming more knowledge-intensive, uniform knowledge representation of physical resources and real-time reasoning capabilities for analytic tasks are needed to automate the decision-making processes for these systems. These requirements highlight the potential of using symbolic AI for predictive maintenance.
To automate and facilitate predictive analytics in Industry 4.0, in this paper, we present a novel Knowledge-based System for Predictive Maintenance in Industry 4.0 (KSPMI). KSPMI is developed based on a novel hybrid approach that leverages both statistical and symbolic AI technologies. The hybrid approach involves using statistical AI technologies such as machine learning and chronicle mining (a special type of sequential pattern mining approach) to extract machine degradation models from industrial data. On the other hand, symbolic AI technologies, especially domain ontologies and logic rules, will use the extracted chronicle patterns to query and reason on system input data with rich domain and contextual knowledge. This hybrid approach uses Semantic Web Rule Language (SWRL) rules generated from chronicle patterns together with domain ontologies to perform ontology reasoning, which enables the automatic detection of machinery anomalies and the prediction of future events’ occurrence. KSPMI is evaluated and tested on both real-world and synthetic data sets.
•A novel hybrid approach combining statistical and symbolic AI for predictive maintenance is proposed.•KSPMI is a novel software for Industry 4.0 predictive maintenance.•KSPMI is evaluated and tested on both real-world and synthetic data sets.
Logic and Theory of Algorithms Beckmann, Arnold; Dimitracopoulos, Costas; Löwe, Benedikt
2008, 2008-06-11, Letnik:
5028
eBook
CiE 2008: Logic and Theory of Algorithms Athens, Greece, June 15-20, 2008 Computability in Europe (CiE) is an informal network of European scientists working on computability theory, including its ...foundations, technical devel- ment, and applications. Among the aims of the network is to advance our t- oretical understanding of what can and cannot be computed, by any means of computation. Its scienti?c vision is broad: computations may be performed with discrete or continuous data by all kinds of algorithms, programs, and - chines. Computations may be made by experimenting with any sort of physical system obeying the laws of a physical theory such as Newtonian mechanics, quantum theory, or relativity. Computations may be very general, depending on the foundations of set theory; or very speci?c, using the combinatorics of ?nite structures. CiE also works on subjects intimately related to computation, especially theories of data and information, and methods for formal reasoning about computations. The sources of new ideas and methods include practical developments in areas such as neural networks, quantum computation, natural computation, molecular computation, computational learning. Applications are everywhere,especially, in algebra,analysisand geometry, or data types and p- gramming. Within CiE there is general recognition of the underlying relevance of computability to physics and a broad range of other sciences, providing as it does a basic analysis of the causal structure of dynamical systems. Thisvolume,Logic andTheory of Algorithms,istheproceedingsofthefourth in a series of conferences of CiE that was held at the University of Athens, June 15-20, 2008.
PDF
