[Brzeziński, S., Klimecka-Tatar, D. 2016, Effect of the changes in the forming metal parameters on the value streams flow and the overall equipment effectiveness coefficient, 25th Anniversary International Conference on Metallurgy and Materials, Tanger Ltd., Ostrava, pp. 1750-1755.]Search in Google Scholar
[Favi, C., Germani, M., Marconi, M. 2017, A 4M Approach for a Comprehensive Analysis and Improvement of Manual Assembly Lines. Procedia Manufacturing 11, pp. 1510–1518. DOI: 10.1016/j.promfg.2017.07.283.10.1016/j.promfg.2017.07.283]Open DOISearch in Google Scholar
[Godina, R., Pimentel, C., Silva, F.J.G., Matias, J.C.O. 2018, Improvement of the Statistical Process Control Certainty in an Automotive Manufacturing Unit, Procedia Manufacturing 17, pp. 729–736. DOI: 10.1016/j.promfg.2018.10.123.10.1016/j.promfg.2018.10.123]Open DOISearch in Google Scholar
[Harari, N.S., Fundin, A., Carlsson, A.L. 2018, Components of the Design Process of Flexible and Reconfigurable Assembly Systems, Procedia Manufacturing 25, pp. 549–556. DOI: 10.1016/j.promfg.2018.06.118.10.1016/j.promfg.2018.06.118]Open DOISearch in Google Scholar
[Jagusiak-Kocik, M., 2014. Ensuring continuous improvement processes through standardization in the automotive company. Production Engineering Archives 2/1, pp.12–15. DOI: 10.30657/pea.2014.02.04.10.30657/pea.2014.02.04]Open DOISearch in Google Scholar
[Klimecka-Tatar, D. 2018, Context of production engineering in management model of value stream flow according to manufacturing industry, Production Engineering Archives 21, pp. 32-35. DOI: 10.30657/pea.2018.21.0710.30657/pea.2018.21.07]Open DOISearch in Google Scholar
[Klimecka-Tatar, D., 2017. Value stream mapping as lean production tool to improve the production process organization – case study in packaging manufacturing. Production Engineering Archives 17, pp. 40–44. DOI: http://dx.doi.org/10.30657/pea.2017.17.09.10.30657/pea.2017.17.09]Open DOISearch in Google Scholar
[Krynke, M., Knop, K., Mielczarek, K. 2014, Using Overall Equipment Effectiveness indicator to measure the level of planned production time usage of sewing machine, Production Engineering Archives 5/4, pp. 6-9. DOI: 10.30657/pea.2014.05.0210.30657/pea.2014.05.02]Open DOISearch in Google Scholar
[Lee, Dong-Hyeong; Na, Min-Woo; Song, Jae-Bok; Park, Chan-Hun; Park, Dong-Il. 2019, Assembly process monitoring algorithm using force data and deformation data, Robotics and Computer-Integrated Manufacturing 56, pp. 149–156. DOI: 10.1016/j.rcim.2018.09.008.10.1016/j.rcim.2018.09.008]Open DOISearch in Google Scholar
[Maszke, A. 2019, TPM Safety Impact – Case Study, CzOTO 2019, 1(1), 639–646. DOI: 10.2478/czoto-2019-008110.2478/czoto-2019-0081]Open DOISearch in Google Scholar
[Menn, J.P., Sieckmann, F., Kohl, H., Seliger, G. 2018, Learning process planning for special machinery assembly, Procedia Manufacturing 23, pp. 75–80. DOI:10.1016/j.promfg.2018.03.164.10.1016/j.promfg.2018.03.164]Open DOISearch in Google Scholar
[Moreira, B.M.D.N., Gouveia, R.M.,Silva, F.J.G.; Campilho, R.D.S.G. 2017, A Novel Concept of Production and Assembly Processes Integration, Procedia Manufacturing 11, pp. 1385–1395. DOI: 10.1016/j.promfg.2017.07.268.10.1016/j.promfg.2017.07.268]Open DOISearch in Google Scholar
[Naebulharam, R., Zhang, L. 2013, Performance Analysis of Serial Production Lines with Deteriorating Product Quality, IFAC Proceedings Volumes 46/9, pp. 501–506. DOI: 10.3182/20130619-3-RU-3018.00105.10.3182/20130619-3-RU-3018.00105]Open DOISearch in Google Scholar
[Nuchsara, K. and Nalin, P. 2007, The Assembly Line Balancing Problem: Review articles, KKU Engineering Journal 34/2, pp. 133 – 140.]Search in Google Scholar
[Renu, R.Sh.; Mocko, G. 2016, Computing similarity of text-based assembly processes for knowledge retrieval and reuse. Journal of Manufacturing Systems 39, pp. 101–110. DOI: 10.1016/j.jmsy.2016.03.004.10.1016/j.jmsy.2016.03.004]Open DOISearch in Google Scholar
[Roldán, J.J., Crespo, E., Martín-Barrio, A., Peña-Tapia, E., Barrientos, A. 2019, A training system for Industry 4.0 operators in complex assemblies based on virtual reality and process mining, Robotics and Computer-Integrated Manufacturing 59, pp. 305–316. DOI: 10.1016/j.rcim.2019.05.004.10.1016/j.rcim.2019.05.004]Search in Google Scholar
[Schmitt, R., Dietrich, F., Dröder, K. 2019, Methodology and experimental analysis of failure connections in precision assembly process data. Procedia CIRP 79, pp. 170–175. DOI: 10.1016/j.procir.2019.02.039.10.1016/j.procir.2019.02.039]Open DOISearch in Google Scholar
[Shen, C.-C. 2015, Discussion on key successful factors of TPM in enterprises. Journal of pp. Applied Research and Technology 13/3 pp. 425–427. DOI: 10.1016/j.jart.2015.05.002.10.1016/j.jart.2015.05.002]Open DOISearch in Google Scholar
[Shim, M., Kim, J-H. 2018, Design and optimization of a robotic gripper for the FEM assembly process of vehicles, Mechanism and Machine Theory 129, pp. 1–16. DOI: 10.1016/j.mechmachtheory.2018.07.006.10.1016/j.mechmachtheory.2018.07.006]Open DOISearch in Google Scholar
[Tracht, K., Funke, L., Schottmayer, M., 2015, Online-control of assembly processes in paced production lines, CIRP Annals 64/1, pp. 395–398. DOI: 10.1016/j.cirp.2015.04.112.10.1016/j.cirp.2015.04.112]Open DOISearch in Google Scholar