The Impact of Digital Transformation on Quality Management Systems in Manufacturing Organizations
Fragment książki (Rozdział monografii pokonferencyjnej)
MNiSW
20
Poziom I
| Status: | |
| Autorzy: | Piotrowska Katarzyna, Pizoń Jakub, Waszkowski Robert |
| Dyscypliny: | |
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| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Strony: | 313 - 325 |
| Web of Science® Times Cited: | 0 |
| Bazy: | Web of Science |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | International Scientific-Technical Conference MANUFACTURING V |
| Skrócona nazwa konferencji: | MANUFACTURING 2026 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 19 maja 2026 do 21 maja 2026 |
| Miasto konferencji: | Poznań |
| Państwo konferencji: | POLSKA |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| The paper explores how digital transformation reshapes quality management systems (QMS) in manufacturing, highlighting the role of Industry 4.0 technologies in advancing modern practices of operational excellence. It contains the contribution of tools such as the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analytics, and integrated ERP/MES platforms to the ongoing shift in quality management. The discussion also includes organizational determinants of effective digital adoption, particularly employee capabilities, institutional readiness, and collaboration across departments. Drawing on contemporary research and practical examples, the paper demonstrates that well-executed digital transformation enhances alignment with ISO 9001:2015, increases process reliability, minimizes deviations, and strengthens continuous improvement efforts. Nevertheless, companies must address obstacles including system-integration difficulties, cybersecurity concerns, investment demands, and workforce skill gaps. The analysis emphasizes that achieving the full potential of Quality 4.0 requires a deliberate, staged implementation strategy that connects technological change with organizational growth. Key recommendations include developing digital skills, establishing robust data-management practices, employing predictive-analytics tools, and building cooperative relationships with technology partners to create intelligent, adaptable, and sustainable quality-management environments. |