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A Systematic Literature Review:Key Performance Indicatorson Feeding-as-a-Service
KTH, School of Industrial Engineering and Management (ITM), Production engineering, Industrial Production Systems.ORCID iD: 0000-0003-2993-511X
Blekinge Institute of Technology, Karlskrona, Sweden.ORCID iD: 0000-0002-5076-3300
KTH, School of Industrial Engineering and Management (ITM), Production engineering, Industrial Production Systems.ORCID iD: 0000-0002-0723-1712
2024 (English)In: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024), IOS Press , 2024, Vol. 52, p. 256-267Conference paper, Published paper (Refereed)
Abstract [en]

In the evolving landscape of modern manufacturing, a novel concept known as Feeding-as-a-Service (FaaS) is emerging, part of the larger Automationas-a-Service (AaaS) framework. FaaS aims to optimize feeding systems in cloud manufacturing environments to meet the demands of mass customization and allow for quick responses to production changes. Therefore, it fits into the Manufacturing as-a-Service (MaaS) system as well. As the manufacturing industry undergoes significant transformations through automation and service-oriented models, understanding how FaaS fits into the other frameworks is essential.This study presents a systematic literature review with two primary objectives: first, to contextualize FaaS within AaaS and MaaS, highlighting similarities, differences,and distinctive characteristics; second, to identify and clarify the essential Key Performance Indicators (KPIs) crucial for its strategic implementation.KPIs are pivotal metrics guiding organizations toward manufacturing excellence.In this context, common KPIs focus on efficiency and quality, such as resource utilization, and error rates. Other KPIs are also crucial, such as the ones related tocost reduction and customer satisfaction. For FaaS, the most relevant include also data security, data management, and network speed.This research provides a valuable KPI framework for FaaS developers, aidingin strategic decision making and deployment in industrial settings. It also contributes to a broader understanding of KPIs in manufacturing, which benefits both researchers and industrial practitioners.The results of the review, though, fail to address other crucial indicators for ‘asa-Service’ business, such as Churn Rate and Total Contract Value. Future research will address these limitations through methods ranging from questionnaires to practitioner interviews, with the aim of gathering the knowledge needed for real-world implementations.

Place, publisher, year, edition, pages
IOS Press , 2024. Vol. 52, p. 256-267
Series
Advances in Transdisciplinary Engineering ; 52
Keywords [en]
Key performance indicators, feeding-as-a-service, automation-as-aservice, manufacturing-as-a-service, cloud manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Engineering
Identifiers
URN: urn:nbn:se:kth:diva-345682DOI: 10.3233/ATDE240170Scopus ID: 2-s2.0-85191338996OAI: oai:DiVA.org:kth-345682DiVA, id: diva2:1852447
Conference
Swedish Production Symposium 2024, Trollhättan, Sweden, April 23-26, 2024
Note

QC 20240429

Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2024-05-14Bibliographically approved

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Monetti, Fabio MarcoMaffei, Antonio

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