A Quality 4.0 Model for Architecting Industry 4.0 Systems
Fecha
2022
Título de la revista
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Editor
Elsevier
Resumen
The increasing importance of automation and smart capabilities for factories and other industrial systems has
led to the concept of Industry 4.0 (I4.0). This concept aims at creating systems that improve the vertical
and horizontal integration of production through (i) comprehensive and intelligent automation of industrial
processes, (ii) informed and decentralized real-time decision making, and (iii) stringent quality requirements
that can be monitored at any time. The I4.0 infrastructure, supported in many cases by robots, sensors, and
algorithms, demands highly skilled workers able to continuously monitor the quality of both the items to be
produced and the underlying production processes.
While the first attempts to develop smart factories and enhance the digital transformation of companies
are under way, we need adequate methods to support the identification and specification of quality attributes
that are relevant to I4.0 systems. Our main contribution is to provide a refined version of the ISO 25010
quality model specifically tailored to those qualities demanded by I4.0 needs. This model aims to provide
actionable support for I4.0 software engineers that are concerned with quality issues. We developed our model
based on an exhaustive analysis of similar proposals using the design science method as well as expertise from
seasoned engineers in the domain. We further evaluate our model by applying it to two important I4.0 reference
architectures further clarifying its application.
Descripción
This work was partially supported by the BaSys 4 project (BMBF) grant 01IS19022A. We also thank to Sonnhild Namingha for proof reading, and the colleagues involved in the evaluation tasks.
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Citación
Pablo Oliveira Antonino, Rafael Capilla, Patrizio Pelliccione, Frank Schnicke, Daniel Espen, Thomas Kuhn, Klaus Schmid, A Quality 4.0 Model for architecting industry 4.0 systems, Advanced Engineering Informatics, Volume 54, 2022, 101801, ISSN 1474-0346, https://doi.org/10.1016/j.aei.2022.101801
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