A linked data approach for the connection of manufacturing processes with production simulation models

Senington, Richard; Baumeister, Fabian; Ng, Amos H. C.; Oscarsson, Jan

doi:10.1016/j.procir.2018.03.243

Cited by 13 publications

(6 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Using OSLC for data integration requires all connected systems to support the required profiles in a compatible way, which will be a challenge for such solutions in the short term. Similar approaches like OPC-UA exist in the context of manufacturing and production [19].…”

Section: Current State Of Linked Engineering Data Management Solutionsmentioning

confidence: 95%

Supporting Linked Engineering Data Management of Smart Product Systems Through Semantic Platform Services

Gries

Eickhoff

Eiden

et al. 2020

Product Lifecycle Management Enabling Smart X

View full text Add to dashboard Cite

The increasing industrial relevance of connected smart product systems, enhanced individualized customer requirements, regulatory boundary conditions as well as advanced value networks and volatile international markets determine a new level of engineering complexity. Current engineering processes are enabled by a large number of IT applications, which are partially orchestrated by product lifecycle management solutions. Considering the dramatically increasing complexity, the IT applications are often not adequately connected as a whole, leading to interruptions in the process chains and finally resulting in quality problems, time expenditure, and additional costs.To support seamless engineering processes, a sufficiently linked information system structure is necessary. Due to the often-existing best-of-breed solutions and historically grown IT infrastructures, the direct point-to-point coupling of IT systems among each other requires disproportionately high efforts. As an approach to improve the existing situation, integration platforms utilizing loose coupling of individual heterogeneous engineering IT applications by semantic web technologies could be used to create a comprehensive, linked engineering data structure.This paper presents a conceptual IT-Service approach that utilizes this linked data structure to address problems in the area of information retrieval, data exchange, and data quality. A fundamental service function enables easy access to the information scattered throughout the whole organization. This approach could contribute to a high level of transparency within the company's internal processes and relationships between data across individual engineering IT applications. The proposed concepts for IT platform services facilitate the exchange of data between different software applications and the standardized checking and documentation of data quality.

show abstract

Section: Current State Of Linked Engineering Data Management Solutionsmentioning

confidence: 95%

Supporting Linked Engineering Data Management of Smart Product Systems Through Semantic Platform Services

Gries

Eickhoff

Eiden

et al. 2020

Product Lifecycle Management Enabling Smart X

View full text Add to dashboard Cite

show abstract

“…DT can help with optimal placement of workers, equipment, on-site resources, and work-inprocess [148]. In terms of control and execution, DT keeps track of all the activities occurring in the physical world to forecast, and enhance the control approach [149,150], and align the process with planning [151]. A DT model of a construction site can help detect and predict potential issues before they occur in the real world.…”

Section: Figure 8 Configuration and Application Of Digital Twinmentioning

confidence: 99%

Digital Twin Perspective of Fourth Industrial and Healthcare Revolution

2022

View full text Add to dashboard Cite

Digital Twin (DT) is bringing revolution to our lives by a digital representation of the physical system. DT is the creation of the joint usage of various technologies like Cyber-Physical System (CPS), Internet of Things (IoT), Big Data, Edge Computing (EC), Artificial Intelligence (AI), and Machine Learning (ML), etc. DTs are established to optimize a wide range of applications of industry, healthcare, smart cities, smart homes, etc. It is still in its early development stages. This paper fills the gaps by combining the extensive information on technologies utilized in the creation of DT in industry and healthcare. The paper focuses on studying the characteristics of DT, communication technologies and tools utilized in the creation of DT models, reference models, standards, and the researcher's recent work in smart manufacturing and healthcare. Challenges and open issues that need attention are also discussed.

show abstract

“…To create production process models, a digital twin of a physical process is needed, one that will enable process monitoring, real-time decision making, and control [47]. A digital twin represents a virtual model of a physical object which can simulate the object's behavior [48].…”

Section: Digital Twinsmentioning

confidence: 99%

Modeling and Simulation of Manufacturing Processes and Systems: Overview of Tools, Challenges, and Future Opportunities

Alquraish

2022

Eng. Technol. Appl. Sci. Res.

View full text Add to dashboard Cite

Manufacturing is an important part of the modern economy. It is characterized by complexity in terms of systems, approaches, and interactions with intrinsic and extrinsic factors. Numerous efforts have been developed to use modeling and simulation tools to improve manufacturing efficiency and productivity and to achieve maximum quality, especially with the different mutations in the factories of today. This paper reviews the conventional and modern tools used in manufacturing system design and production improvement. Challenges that need to be addressed by the simulation community are discussed in depth. Finally, the evolution, advances, current practices, and future opportunities are discussed in the context of the contemporary manufacturing industry.

show abstract

A linked data approach for the connection of manufacturing processes with production simulation models

Cited by 13 publications

References 3 publications

Supporting Linked Engineering Data Management of Smart Product Systems Through Semantic Platform Services

Supporting Linked Engineering Data Management of Smart Product Systems Through Semantic Platform Services

Digital Twin Perspective of Fourth Industrial and Healthcare Revolution

Modeling and Simulation of Manufacturing Processes and Systems: Overview of Tools, Challenges, and Future Opportunities

Contact Info

Product

Resources

About