A Platform to Integrate Manufacturing Engineering and Product Lifecycle Management

Lentes, Joachim; Eckstein, Holger; Zimmermann, Nikolas

doi:10.3182/20120523-3-ro-2023.00425

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Bringing the data together for various engineering processes requires data exchange, synchronization or a decentralized approach. Currently, a variety of solution approaches for cross-system data management exist, such as (Lentes et al, 2012;Abramovici and Herzog, 2016). Thus, data stored in different systems is partially synchronized with other systems, which allows straightforward access for users from the affected systems, but by definition introduces some redundancy.…”

Section: Lifecycle Information Management In the Context Of Digital T...mentioning

confidence: 99%

Approach for Developing Digital Twins of Smart Products Based on Linked Lifecycle Information

2022

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The ongoing digitization of engineering processes and the increasing prevalence of smart products create possibilities for new business models and services. Digital twins enable the collection of all required data about a smart product in order to make these possibilities a reality. This paper describes a flexible approach towards a digital product twin that is tightly integrated with existing product models while being lightweight and easy to integrate with existing IT solutions.

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Section: Lifecycle Information Management In the Context Of Digital T...mentioning

confidence: 99%

Approach for Developing Digital Twins of Smart Products Based on Linked Lifecycle Information

2022

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“…Basierend auf den beschriebenen grundlegenden Techniken und Konzepten gibt es eine Reihe von Integrationsplattformen wie in [27], [28], [29] und [30]. Diese werden im Allgemeinen speziell für unterschiedliche Use-Cases entworfen und integrieren die in diesem fachlichen Kontext notwendigen Daten.…”

Section: Stand Der Technikunclassified

Anforderungen an ein Daten-Backend-System zur Unterstützung industrieller Datenanalyse-Anwendungen in digitalen Engineering-Prozessen dynamischer Wertschöpfungsnetzwerke

Eiden¹,

Gries²,

Eickhoff³

et al. 2020

Proceedings of the 31st Symposium Design for X (DFX2020)

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Industrial data analytics needs well-structured and linked data from different data sources. The increasing mass of data, scattered IT-structures and a lack of knowledge, especially in small and medium-sized companies (SMEs) are factors that hinder the usage of data analytics. The goal of the research project AKKORD is to build a toolkit for companies to facilitate distributed and integrated industrial data analytics inside valueadding networks. A core part of this toolkit is a data backend system, which collects and links data from different source systems together in a single meta-model. This paper describes the requirements analysis of the data backend system by conducting structured interviews and workshops.

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“…Product Lifecycle Management and Enterprise Resource Planning (ERP), existing over decades, have been applied to a multitude of use cases across the product lifecycle. However, these solutions often coexist as separate information technical and organizational ecosystems within the corresponding departments of a company [11]. As a result, these solutions typically manage data such as requirement data, product models, and source code, supplemented by numerous authoring software applications, which are specific to a particular life cycle phase or engineering discipline.…”

Section: Current State Of Linked Engineering Data Management Solutionsmentioning

confidence: 99%

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

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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.

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A Platform to Integrate Manufacturing Engineering and Product Lifecycle Management

Cited by 5 publications

References 14 publications

Approach for Developing Digital Twins of Smart Products Based on Linked Lifecycle Information

Approach for Developing Digital Twins of Smart Products Based on Linked Lifecycle Information

Anforderungen an ein Daten-Backend-System zur Unterstützung industrieller Datenanalyse-Anwendungen in digitalen Engineering-Prozessen dynamischer Wertschöpfungsnetzwerke

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

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