Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Digital Transformation in Industry
Abstract
Deliverable D3.5 Production Planning & Reconfiguration v1 provides an overall status update of two core components developed within the CIRCMAN5.0 project’s Work Package 3 (WP3). They are aligned with WP3’s purpose that is to deliver novel simulation and modelling software to improve process and product manufacturing. The first component corresponds to task T3.4 titled “ML-Assisted Production Planning”, is led by ICCS and is dedicated to the development of Machine Learning (ML) algorithms that support the production planning and resource allocation. The second component corresponds to subtask T3.4.1 titled “Embedded edge computing system for the automatic detection of multi-type defects”, is led by CERTH and is dedicated to the automatic detection of multi-type defects in silicon photovoltaic (PV) modules through the design and development of an on-line embedded Internet of Things (IoT) edge computing system. In this first version of D3.5, the challenges and opportunities associated with the transition towards Industry 5.0 (I5.0) are analysed. Based on the analysis, the adoption of I5.0 principles within Production Planning and Control (PPC) systems is investigated, with particular emphasis given on the incorporation of Machine Learning (ML) algorithms and Artificial Intelligence (AI) techniques into the sub-processes constituting the PPC systems. Furthermore, D3.5, establishes the conceptual link between the two components to be developed under tasks T3.4 and T3.4.1 and the PPC sub-processes, as well as provides a detailed methodology for their development, evaluation, and validation. Lastly, D3.5 outlines planned future activities including the finalization of the ML automation scenarios followed by the development of the algorithms based on data from CIRCMAN5.0 pilot environments and presentation of the results.
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The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
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The perception of the impact of agile methods is predominantly positive, and several challenge areas were discovered, but based on this study, agile methods are here to stay.
M. Laanti, O. Salo, P. Abrahamsson· Information and Software Tec...· 260 citations· ⚡20
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