TY - JOUR
T1 - Contributions of Industry 4.0 to quality management - A SCOR perspective
AU - Müller, J.M.
N1 - Conference code: 156996
Cited By :25
Export Date: 14 December 2023
Correspondence Address: Müller, J.M.; Salzburg University of Applied SciencesAustria; email: [email protected]
References: Birkel, H.S., Veile, J.W., Müller, J.M., Hartmann, E., Voigt, K.I., Development of a risk framework for industry 4.0 in the context of sustainability for established manufacturers (2019) Sustainability, 11 (2), p. 384; Buer, S.V., Strandhagen, J.O., Chan, F.T., The link between Industry 4.0 and lean manufacturing: Mapping current research and establishing a research agenda (2018) International Journal of Production Research, 56 (8), pp. 2924-2940; Foidl, H., Felderer, M., Research challenges of industry 4.0 for quality management (2015) International Conference on Enterprise Resource Planning Systems, pp. 121-137. , Springer, Cham; Gunasekaran, A., Subramanian, N., Ngai, E., Quality management in the 21st century enterprises: Research pathway towards Industry 4.0 (2019) International Journal of Production Economics, 207, pp. 125-129; Ivanov, D., Sokolov, B., Ivanova, M., Schedule coordination in cyber-physical supply networks Industry 4.0 (2016) IFAC-PapersOnLine, 49 (12), pp. 839-844; Jayaram, A., Lean six sigma approach for global supply chain management using industry 4.0 and IIoT (2016) 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), , Institute of Electrical and Electronics Engineers IEEE; Kagermann, H., Wahlster, W., Helbig, J., Recommendations for implementing the strategic initiative Industrie 4.0 - Final report of the Industrie 4.0 Working Group (2013) Communication Promoters Group of the Industry-Science Research; Kiel, D., Müller, J.M., Arnold, C., Voigt, K.-I., Sustainable industrial value creation: Benefits and challenges of industry 4.0 (2017) International Journal of Innovation Management, 21, p. 8; Kolberg, D., Zühlke, D., Lean automation enabled by industry 4.0 technologies (2015) IFAC-PapersOnLine, 48 (3), pp. 1870-1875; Lasi, H., Kemper, H., Fettke, P., Feld, T., Hoffmann, M., Industry 4.0 (2014) Business and Information Systems Engineering, 6 (4), pp. 239-242; Lennartson, B., Bengtsson, K., Yuan, C., Andersson, K., Fabian, M., Falkman, P., Akesson, K., Sequence planning for integrated product, process and automation design (2010) Transactions on Automation Science and Engineering, 7 (4), pp. 791-802; Leyh, C., Martin, S., Schäffer, T., Analyzing industry 4.0 models with focus on lean production aspects (2017) Information Technology for Management. Ongoing Research and Development, pp. 114-130. , Springer, Cham; Leyh, C., Martin, S., Schäffer, T., Industry 4.0 and Lean Production-A matching relationship? An analysis of selected Industry 4.0 models (2017) Proceedings of the Institute of Electrical and Electronics Engineers (IEEE), 2017 Federated Conference on Computer Science and Information Systems (FedCSIS); Müller, J.M., Business model innovation in small- And medium-sized enterprises: Strategies for industry 4.0 providers and users (2019) Journal of Manufacturing Technology Management, , press, available online; Müller, J.M., Antecedents to digital platform usage in industry 4.0 by established manufacturers (2019) Sustainability, 11 (4), p. 1121; Müller, J.M., Buliga, O., Voigt, K.-I., Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0 (2018) Technological Forecasting and Social Change, 132, pp. 2-17; Müller, J.M., Kiel, D., Voigt, K.I., What drives the implementation of industry 4.0? The role of opportunities and challenges in the context of sustainability (2018) Sustainability, 10, p. 1; Müller, J.M., Voigt, K.I., Sustainable industrial value creation in SMEs: A comparison between industry 4.0 and made in China 2025 (2018) International Journal of Precision Engineering and Manufacturing-Green Technology, 5 (5), pp. 659-670; Müller, J.M., Maier, L., Veile, J., Voigt, K.I., Cooperation strategies among SMEs for implementing industry 4.0 (2017) Proceedings of the Hamburg International Conference of Logistics (HICL), pp. 301-318. , epubli; Sanders, A., Elangeswaran, C., Wulfsberg, J., Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing (2016) Journal of Industrial Engineering and Management, 9 (3), pp. 811-833; Santana, A., Afonso, P., Zanin, A., Wernke, R., Costing models for capacity optimization in Industry 4.0: Trade-off between used capacity and operational efficiency (2017) Procedia Manufacturing, 13, pp. 1183-1190; Sony, M., Industry 4.0 and lean management: A proposed integration model and research propositions (2018) Production & Manufacturing Research, 6 (1), pp. 416-432; Tortorella, G.L., Fettermann, D., Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies (2018) International Journal of Production Research, 56 (8), pp. 2975-2987; Yin, R., (2009) Case Study Research: Design and Methods, , Sage, Thousand Oaks; Zezulka, F., Marcon, P., Vesely, I., Sajdl, O., Industry 4.0-An Introduction in the phenomenon (2016) IFAC-PapersOnLine, 49 (25), pp. 8-12
PY - 2019
Y1 - 2019
N2 - Industry 4.0 is a concept for future industrial value creation, aiming to generate economic, ecological and social benefits, relating to the Triple Bottom Line of sustainability. This shall be achieved through horizontal and vertical interconnection on the basis of cyber-physical systems and the Internet of Things. So far, the majority of scientific papers has dealt with technological foundations or showcases within the concept, whereas economic, ecological and social aspects have been considered less. In particular, the exact potentials of Industry 4.0 remain opaque in industrial application. The paper aims to contribute to this research gap by identifying potentials related to quality management achieved through Industry 4.0. Therefore, 204 manufacturing plants worldwide of a German industrial company are investigated through a quantitative survey. Potentials associated to quality management are assessed, applying the SCOR model. On this basis, the paper can highlight to which potentials Industry 4.0 so far contributes.
AB - Industry 4.0 is a concept for future industrial value creation, aiming to generate economic, ecological and social benefits, relating to the Triple Bottom Line of sustainability. This shall be achieved through horizontal and vertical interconnection on the basis of cyber-physical systems and the Internet of Things. So far, the majority of scientific papers has dealt with technological foundations or showcases within the concept, whereas economic, ecological and social aspects have been considered less. In particular, the exact potentials of Industry 4.0 remain opaque in industrial application. The paper aims to contribute to this research gap by identifying potentials related to quality management achieved through Industry 4.0. Therefore, 204 manufacturing plants worldwide of a German industrial company are investigated through a quantitative survey. Potentials associated to quality management are assessed, applying the SCOR model. On this basis, the paper can highlight to which potentials Industry 4.0 so far contributes.
KW - Industrial Internet of Things
KW - Industry 4.0
KW - Lean Management
KW - Quality Management
KW - SCOR model
KW - Ecology
KW - Embedded systems
KW - Industrial internet of things (IIoT)
KW - Industrial management
KW - Quality management
KW - Social aspects
KW - Industrial companies
KW - Lean management
KW - Manufacturing plant
KW - Scientific papers
KW - SCOR models
KW - Social benefits
KW - Triple Bottom Line
KW - Vertical interconnections
KW - Industrial economics
UR - https://www.mendeley.com/catalogue/0c7fb56f-eb9f-327c-aae8-757dad477539/
UR - https://www.mendeley.com/catalogue/0c7fb56f-eb9f-327c-aae8-757dad477539/
U2 - 10.1016/j.ifacol.2019.11.367
DO - 10.1016/j.ifacol.2019.11.367
M3 - Conference article
SN - 2405-8963
VL - 52
SP - 1236
EP - 1241
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
IS - 13
T2 - 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019
Y2 - 28 August 2019 through 30 August 2019
ER -