Generating Industry 4.0 Asset Administration Shells with Data from Engineering Data Logistics

Lüder, Arndt; Behnert, Anna-Kristin; Rinker, Felix; Biffl, Stefan

doi:10.1109/etfa46521.2020.9212149

Cited by 21 publications

(5 citation statements)

References 14 publications

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“…Human Resource Development according to [14] is formed from four dimensions, namely education, work experience, skills, and technological capabilities. While the indicators for HR Development according to [15] consist of three indicators, namely: Motivation, Personality, and Skills.…”

Section: Literature Review 21 Hr Developmentmentioning

confidence: 99%

Human Resources (Hr) Development at the Employee Level Ethos

Marisya

K²,

Sugiarto

2023

Jurnal Ekonomi

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The purpose of this research is to identify the description of Human Resource Development at the level of Employee Work Ethics at the Hotel Hilton Bandung. Employees at the Hotel Hilton Bandung, which has a population of 52 people, provided the data. The sample methodology used is saturation sampling, which means sampling based on the existing population. The research method used in this study is associative research. Based on research conducted by evaluating the data gathered there is a relationship between Human Resource Development Factors and a positive and significant influence on Employee Work Ethics at Hilton Bandung Hotel with a value of 3.962, while t table is 2.006, so the t value is 3.962> 2.006. The coefficient of determination results

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Section: Literature Review 21 Hr Developmentmentioning

confidence: 99%

Human Resources (Hr) Development at the Employee Level Ethos

Marisya

K²,

Sugiarto

2023

Jurnal Ekonomi

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“…Figure 1 illustrates an I4AN with the relevant engineering artifacts and the links between the assets. This model can be created automatically by exploiting appropriate engineering data logistic systems [12]. This overall model can be the starting point to identify common reusable patterns [19].…”

Section: A I40 Asset Based Network With Dependenciesmentioning

confidence: 99%

“…Section IV). Furthermore, there is insufficient interdisciplinary exchange between the domains, leading to hard to extract/collect/validate dependencies from heterogeneous engineering artifacts and domain experts [12]. Hence, it is crucial in this multi-disciplinary environment to thoroughly model the (interdisciplinary) dependencies and boundaries in pattern analysis to reduce the risk of broken reusable assets.…”

Section: Introductionmentioning

confidence: 99%

Patterns for Reuse in Production Systems Engineering

Meixner¹

2021

Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering

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In Production Systems Engineering (PSE), domain experts aim at reusing production processes implemented as Industry 4.0 assets and software. However, the knowledge on reusable assets is often scattered on multi-disciplinary engineering artifacts and domain experts, making it hard to find suitable reusable assets and map them to requirements. In this paper, we (i) identify challenges and requirements for reuse in PSE based on a domain analysis; (ii) introduce the Industry 4.0 Asset Network (I4AN) that integrates multi-disciplinary dependencies between the assets and exposes recurring patterns; and (iii) present four patterns for reuse in PSE that aim at improving reuse efficiency and risk. We evaluate the I4AN with reuse scenarios in a feasibility study. The study results indicate that the I4AN model satisfies the elicited requirements and enables PSE domain experts to identify patterns for reuse in their contexts.

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“…The virtual description criterion plays a fundamental role in providing valuable information regarding the asset, that is used across the asset lifecycle, e.g., technical data, schematics, configuration parameter values and communication information [1], [12], [15]- [20], [24], [25], as well as information about the maintenance, guiding the operator on how to perform this process for each asset [13]. In this context, AutomationML may be used for describing and storing information wrapped in AAS submodels [1], [12], [15], [17], [28]. OPC UA and AutomationML.…”

Section: Securitymentioning

confidence: 99%

“…OPC UA. [28] This paper focus on AutomationML-based AAS to support the collection of engineering dataset and the serialization of AAS.…”

Section: Securitymentioning

confidence: 99%

Towards the Digitization using Asset Administration Shells

Sakurada

Leitão

Prieta

2021

IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society

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Industry 4.0 (I4.0) is promoting the digitization of traditional manufacturing systems towards flexible, reconfigurable and intelligent factories based on Cyber-Physical Systems (CPS). In this context, the Reference Architecture Model Industrie 4.0 (RAMI4.0) provides guidelines to develop I4.0 compliant solutions based on industrial standards. As the main RAMI4.0 specification, the Asset Administration Shell (AAS) is a standard digital representation of an industrial asset that plays a pivotal role in enabling interoperable communication among I4.0 components across the value chain. This paper provides an analysis of the current state-of-the-art of implementing AAS, discussing, amongst others, the key enabling technologies used to implement the AAS and the alignment of the research works found in the literature with the I4.0 components criteria.

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Generating Industry 4.0 Asset Administration Shells with Data from Engineering Data Logistics

Cited by 21 publications

References 14 publications

Human Resources (Hr) Development at the Employee Level Ethos

Human Resources (Hr) Development at the Employee Level Ethos

Patterns for Reuse in Production Systems Engineering

Towards the Digitization using Asset Administration Shells

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