Framework for Data Analytics in Data-Driven Product Planning

Massmann, Melina; Meyer, Maurice; Frank, Maximilian; Enzberg, Sebastian von; Kühn, Arno; Dumitrescu, Roman

doi:10.1016/j.promfg.2020.11.058

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…• Bewertungsanforderungen: Quantitative Wirtschaftlichkeitsanalyse [28,31], qualitative strategische Bewertung [26,28,31,32], systematische Selektion [28], Unsicherheitstoleranz [32], situative Anpassung [26,25]. • Kontextspezifische Anforderungen: Montagerelevante Zielgrößen [6,28,33,34], Hilfestellung zur Identifikation potenzieller Anwendungsfälle [11,35], Berücksichtigung der Datenverfügbarkeit und -qualität [36], Unterstützung zur Identifikation des Nutzenpotenzials [31,37], Berücksichtigung des Synergiepotenzials [38]. In der Literatur verfügbare Evaluationsmethoden [11,25,28,37] wurden hinsichtlich der Erfüllung der aufgelisteten Anforderun-gen untersucht.…”

Section: Anforderungen Und Bestehende Methodenunclassified

Evaluation von Data Analytics Anwendungsfällen/Identification and evaluation of data-based use cases for assembly – Evaluation of Data Analytics Use Cases

Stahl¹,

Wurst²,

Huber³

2023

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Die Identifizierung und Bewertung von Anwendungsfällen im Bereich der Datenanalyse erfordert sowohl datenwissenschaftliche als auch fachliche Expertise, was Unternehmen oft vor Schwierigkeiten stellt. Aufgrund der Komplexität und des ungewissen wirtschaftlichen Nutzens möglicher datenanalytischer Anwendungsfälle gibt es Herausforderungen, die die Realisierung von Data Analytics Projekten erschweren. In diesem Beitrag wird eine Methode zur Identifizierung und Bewertung von Anwendungsfällen der Datenanalyse vorgestellt. Identifying and realistically evaluating use cases in the field of data analytics requires expertise in both data science and domain knowledge, which often confronts companies with difficulties. Due to the complexity and the uncertain economic benefit of possible data analytic use cases, there are often challenges that make it difficult to realize data analytics projects. This publication presents a method for identifying and evaluating use cases of data analytics.

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Section: Anforderungen Und Bestehende Methodenunclassified

Evaluation von Data Analytics Anwendungsfällen/Identification and evaluation of data-based use cases for assembly – Evaluation of Data Analytics Use Cases

Stahl¹,

Wurst²,

Huber³

2023

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“…For this reason, insights gained from utilization can relate to both individual assets and asset groups. A corresponding methodical procedure for the use of data analyses in the context of strategic product planning is given by Massmann et al (Massmann et al, 2020).…”

Section: Acquisition Use and Analysis Of Data And Derivation Of Findingsmentioning

confidence: 99%

“…Five fields of action (AF), shown in Figure 1., are addressed by the project. Previous publications have concentrated in particular on methods for product investigation (Meyer et al, 2020a), data analytic (Massmann et al, 2020), and strategic product planning (Meyer et al, 2020b), and focusing in particular on the aspects of organization and people. This contribution deals with the concepts of technical support for data networking and provision, which be assigned to the fifth field of action, "tool support."…”

Section: Introductionmentioning

confidence: 99%

Closed-Loop Engineering Approach for Data-Driven Product Planning

Dickopf

Apostolov

2022

Proc. Des. Soc.

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This contribution introduces an approach for data-driven optimization of products and their product generations through a Closed-Loop Engineering approach resulting from the German research project DizRuPt. The approach focuses on data-driven product planning by ensuring data consistency and traceability between product planning, product development, and product operation by combining aspects and functions from Product Lifecycle Management (PLM) and the Internet of Things (IoT). The presented approach is illustrated and validated by pilot applications from the research project.

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Production Planning Digitalization Using Open-Source Big Data Technologies

Suleykin

Panfilov²

2023

Lecture Notes in Mechanical Engineering

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Framework for Data Analytics in Data-Driven Product Planning

Cited by 6 publications

References 6 publications

Evaluation von Data Analytics Anwendungsfällen/Identification and evaluation of data-based use cases for assembly – Evaluation of Data Analytics Use Cases

Evaluation von Data Analytics Anwendungsfällen/Identification and evaluation of data-based use cases for assembly – Evaluation of Data Analytics Use Cases

Closed-Loop Engineering Approach for Data-Driven Product Planning

Production Planning Digitalization Using Open-Source Big Data Technologies

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