OEE measurement at the automotive semi-automatic assembly lines


  • Peter Dobra Adient Hungary Kft, Hammerstein u. 2, 8060 Mór, Hungary
  • János Jósvai Széchenyi István University, Department of Vehicle Manufacturing Egyetem tér 1, 9026 Győr, Hungary




KPI, OEE, MES, assembly line


Manufacturing companies continuously evaluate their achieved performance based on different Key Performance Indicators (KPI). This article gives an overview about the OEE values. The study aims to provide practical OEE data of semi-automatic assembly lines used in the automotive industry. Its novelty is the revealed relationship between seat assembly lines and seat subassembly lines. Firstly, a literature review shows the scientific relevance and several cases are collected to increase OEE percentage. Secondly, the connection between chassis, tracks, recliner and mechanism assembly lines is described. Each part of OEE (availability, performance, quality) are analysed in terms of their impact.


Download data is not yet available.


R. Glawar, F. Ansari, Cs. Kardos, K. Matyas, W. Sihn, Conceptual design of an integrated autonomous production control model in association with a prescriptive maintenance model (PriMa), Procedia CIRP 80 (2019) pp. 482–487. doi: https://doi.org/10.1016/j.procir.2019.01.047

F. Antreter, The Possibilities of the Performance Measurement to the Estimating of the to Logistic Processes Joining Supplementary Work Hour Demand at the Automobile Manufacturer Factory, Acta Technica Jaurinensis 3 (3) (2010) pp. 267-283.

M. Sokovic, D. Pavletic, K. K. Pipan, Quality improvement methodologies – PDCA Cycle, RADAR Matrix, DMAIC and DFSS, Journal of Achievements in Materials and Manufacturing Engineering 43 (2010) pp. 476-483.

J. Oliveira, J.C. Sa, A. Fernandes, Continuous Improvement through ‘Lean Tools’: An Application in a Mechanical Company, Procedia Manufacturing 13 (2017) pp. 1082–1089. doi: https://doi.org/10.1016/j.promfg.2017.09.139

T. L. Nguyen, M. T. Le, T. T T.Vu, N. H. Do, Lean line balancing for an electronics assembly line, Procedia CIRP 40 (2016) pp. 437–442. doi: https://doi.org/10.1016/j.procir.2016.01.089

H. ElMaraghy, W. ElMaraghy, Smart Adaptable Assembly Systems, Procedia CIRP 44 (2016) pp. 4–13. doi: https://doi.org/10.1016/j.procir.2016.04.107

M. Subramaniyan, A. Skoogh, H. Salomonsson, P. Bangalore, J. Bokrantz, A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines, Computers & Industrial Engineering 125 (2018) pp. 533–544. doi: https://doi.org/10.1016/j.cie.2018.04.024

B. Denkena, M.A. Dittrich, S. Wilmsmeier, Automated production data feedback for adaptive work planning and production control, Procedia Manufacturing 28 (2019) pp. 18–23. doi: https://doi.org/10.1016/j.promfg.2018.12.004

A. Kusiak, Smart manufacturing, International Journal of Production Research 56 1–2 (2018) pp. 508–517.doi: https://doi.org/10.1080/00207543.2017.1351644

C. L. Constantinescu, E. Francalanza, D. Matarazzo, O. Balkan, Information Support and Interactive Planning in the Digital Factory: Approach and Industry-Driven Evaluation, Procedia CIRP 25 (2014) pp. 269–275. doi: https://doi.org/10.1016/j.procir.2014.10.038

S. Nakajima, Introduction to TPM: Total Productive Maintenance, Productivity Press Cambridge, 1988.

R. Hedman, M. Subramaniyan, P. Almström, Analysis of critical factors for automatic measurement of OEE, Procedia CIRP 57 (2016) pp. 128–133. doi: https://doi.org/10.1016/j.procir.2016.11.023

LP Steenkamp, D. Hagedorn-Hansen, G.A. Oosthuizen, Visual Management System to Manage Manufacturing Resources, Procedia Manufacturing 8 (2017) pp. 455–462.

doi: https://doi.org/10.1016/j.promfg.2017.02.058

M. Mainea, L. Duta, Patic C., I. Caciula , A method to optimize the Overall Equipment Effectiveness, IFAC Proceedings (2010) pp. 237–241. doi: https://doi.org/10.3182/20100908-3-PT-3007.00046

P. De Grotte, Maintenance performance analysis: A practical approach, Journal of Quality in Maintenance Engineering 1 (2) (1995) pp. 4-24.

S. Saito, Reducing labour costs using industrial engineering techniques, Maynard’s Industrial Engineering Handbook, McGraw-Hill, New York, 2001.

K. Mahmood, M. Lanz, V. Toivonen, T. Otto, A Performance Evaluation Concept for Production Systems in an SME Network, Procedia CIRP 72 (2018) pp.603–608. doi: https://doi.org/10.1016/j.procir.2018.03.182

M. Subramaniyan, Production Data Analytics – To identify productivity potentials, Chalmers University of Technology, Gothenburg, Sweden, 2015.

R.C. Hansen, Overall Equipment Effectivness: A powerful production / maintenance tool for increased profits, New York Industrial Press, 2001.

P. Almström, A. Kinnander, Productivity Potential Assessment of the Swedish Manufacturing Industry, Swedish Production Seminar, (2007)

I. Antoniolli, P. Guariente, T. Pereira, L. P. Ferreira, F.J.G. Silva, Standardization and optimization of an automotive components production line, Procedia Manufacturing 13 (2017) pp. 1120–1127. doi: https://doi.org/10.1016/j.promfg.2017.09.173

D. Mourtzis, D. Tsakalos, F. Xanthi, V. Zogopoulos, Optimization of highly automated production line: An advanced engineering educational approach, Procedia Manufacturing 31 (2019) pp. 45–51. doi: https://doi.org/10.1016/j.promfg.2019.03.008

E. Permin, F. Bertelsmeier, M. Blum, J. Bützler, S. Haag, S. Kuz, D. Özdemir, Self-Optimizing Production Systems, Procedia CIRP 41 (2016) pp. 417–422. doi: https://doi.org/10.1016/j.procir.2015.12.114

F. Tao, Q. Qi, A. Liu, A. Kusiak, Data-Driven Smart Manufacturing, Journal of Manufacturing Systems 48 (2018) pp. 157–169. doi: https://doi.org/10.1016/j.jmsy.2018.01.006

G. Schuh, T. Potente, C. Thomas, F. Brambring, Improving data integrity in production control, Procedia CIRP 9 (2013) pp. 44–48. doi: https://doi.org/10.1016/j.procir.2013.06.166

C. Reuter, F. Brambring, Improving data consistency in production control, Procedia CIRP 41 (2016) pp. 51–56. doi: https://doi.org/10.1016/j.procir.2015.12.116




How to Cite

Dobra, P., & Jósvai, J. (2021). OEE measurement at the automotive semi-automatic assembly lines. Acta Technica Jaurinensis, 14(1), 24–35. https://doi.org/10.14513/actatechjaur.00576



Research articles