Context-Aware Workflow Management for Smart Manufacturing: A Literature Review of Semantic Based Approaches

Ochoa, William; Larrinaga, Félix; Pérez, A.

doi:10.2139/ssrn.4218412

Cited by 4 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, a context-aware system uses context to deliver information and/or services relevant to a user's task (Abowd et al, 1999). Context refers to any data that can be used to understand the current state, whether situational or locational, of an entity (Ochoa et al, 2023). Context can be categorized from both operational and conceptual perspectives.…”

Section: Recommendation System and Context-awarenessmentioning

confidence: 99%

A context-aware framework for recommendation-based adaptive user interfaces in Smart Product-Service System

Carrera-Rivera,

Larrinaga,

Lasa

et al. 2024

Preprint

View full text Add to dashboard Cite

Smart Product-Service Systems (S-PSS) represent an innovative business model that integrates intelligent products with advanced digital capabilities and corresponding e-services. The User Experience (UX) within an S-PSS is heavily influenced by the individualization of services and customer empowerment. However, conventional UX analysis primarily focuses on the design stage and may not adequately respond to the evolving user needs during the usage stage and how to exploit the data surrounding the use of S-PSS. To overcome these limitations, this article introduces a practical framework for developing adaptive user interfaces within S-PSS. This framework integrates ontologies and context-aware recommendation systems, with user interactions serving as the primary data source, facilitating the development of adaptive user interfaces. One of the main contributions of this work lies on the integration of various components to achieve the creation of adaptive user interfaces for digital services. A case study of a smart device app is presented, to demonstrate the practical implementation of the framework, with a hands-on development approach, considering technological aspects and utilizing appropriate tools. The results of the evaluation of the recommendation engine show that using a context-aware approach improves the precision of recommendations. Furthermore, pragmatic aspects of UX, such as usefulness and system efficiency, are evaluated with participants with an overall positive impact on the use of the smart device.

show abstract

Section: Recommendation System and Context-awarenessmentioning

confidence: 99%

A context-aware framework for recommendation-based adaptive user interfaces in Smart Product-Service System

Carrera-Rivera,

Larrinaga,

Lasa

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Such process description mappings are used by all the workflow management and execution approaches presented in this paper. A current review of workflow management in smart manufacturing is presented in [12].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Execution of Engineering Processes in Cyber-Physical Systems of Systems Toolchains

Montori,

Tatara,

Varga

2024

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

Engineering tools support the process of creating, operating, maintaining, and evolving systems throughout their lifecycle. Toolchains are sequences of tools that build on each others' output during this procedure. The complete chain of tools itself may not even be recognized by the humans who utilize them, people may just recognize the right tool being used at the right place in time. Modern engineering processes, however, do not value such ad-hoc choice of tooling, because of their uncontrolled nature. Building upon the Extended Automation Engineering Model defined by the IEC 81346 standard, this paper proposes to automate the toolchain building and execution process for Cyber-Physical System of Systems (CPSoS), utilizing key principles of the Eclipse Arrowhead framework. The proposed toolchain automation solution addresses issues such as tool interoperability, interaction, automation, and dynamic choreography. The feasibility of this set of integrated concepts is validated through an Arrowhead-based toolchain choreography demonstration.Note to Practitioners-The paper discusses approaches to the automated execution of various industry-related processes. As the processes are becoming more complex and involve numerous systems which have to be orchestrated, a simple and preprogrammed workflow is not enough anymore. Therefore, building on top of the principles of the Eclipse Arrowhead framework, an adequate model of toolchains, allowing for their automated execution, is proposed. Different approaches to supervision of toolchain execution are discussed showing the benefits of reaching higher automation levels. Further, four adoption levels are introduced, which are a measure of the toolchain automation progress. Finally, a simplified demonstrator is shown and steps to elevate it to higher adoption levels are highlighted. To ensure that the approach is industry-oriented, several examples of how the proposed methodology can be used in the industrial context are discussed.

show abstract

“…In IoT, service discovery and composition involve connecting different IoT devices, which requires using various technologies such as the semantic web, service-oriented architecture, and cloud computing [5]. These technologies enable the development of a flexible and adaptable service infrastructure, that can meet the changing requirements of the smart city [6].…”

Section: Introductionmentioning

confidence: 99%

Meet User’s Service Requirements in Smart Cities Using Recurrent Neural Networks and Optimization Algorithm

Sefati

Arasteh

Halunga

et al. 2023

IEEE Internet Things J.

View full text Add to dashboard Cite

Despite significant advancements in Internet of Things (IoT)-based smart cities, service discovery and composition continue to pose challenges. Current methodologies face limitations in optimizing Quality of Service (QoS) in diverse network conditions, thus creating a critical research gap. This study presents an original and innovative solution to this issue by introducing a novel three-layered Recurrent Neural Network (RNN) algorithm. Aimed at optimizing QoS in the context of IoT service discovery, our method incorporates user requirements into its evaluation matrix. It also integrates Long Short-Term Memory (LSTM) networks and a unique Black Widow Optimization (BWO) algorithm, collectively facilitating the selection and composition of optimal services for specific tasks. This approach allows the RNN algorithm to identify the top-K services based on QoS under varying network conditions. Our methodology's novelty lies in implementing LSTM in the hidden layer and employing backpropagation through time (BPTT) for parameter updates, which enables the RNN to capture temporal patterns and intricate relationships between devices and services. Further, we use the BWO algorithm, which simulates the behavior of black widow spiders, to find the optimal combination of services to meet system requirements. This algorithm factors in both the attractive and repulsive forces between services to isolate the best candidate solutions. In comparison with existing methods, our approach shows superior performance in terms of latency, availability, and reliability. Thus, it provides an efficient and effective solution for service discovery and composition in IoT-based smart cities, bridging a significant gap in current research.

show abstract

Context-Aware Workflow Management for Smart Manufacturing: A Literature Review of Semantic Based Approaches

Cited by 4 publications

References 0 publications

A context-aware framework for recommendation-based adaptive user interfaces in Smart Product-Service System

A context-aware framework for recommendation-based adaptive user interfaces in Smart Product-Service System

Dynamic Execution of Engineering Processes in Cyber-Physical Systems of Systems Toolchains

Meet User’s Service Requirements in Smart Cities Using Recurrent Neural Networks and Optimization Algorithm

Contact Info

Product

Resources

About