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Improvement of manual assembly line based on Value Stream Mapping (VSM) and efectiveness coefficient

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper the possibilities of process re-organizing in relation to simple principles for limiting waste in the production cycle have been presented. Based on value stream mapping and monitoring of performance indicators, the possibilities of changes identification of in the assembly line process have been presented. Furthermore, based on the availability, performance and quality values, it has been proved that relatively small changes can have a very positive effect on the assembly process. Based on the OEE coefficient, it has been found that the proposed changes improved the process's efficiency by more than 20%.
Wydawca
Rocznik
Strony
537--544
Opis fizyczny
Bibliogr. 20 poz., rys.
Twórcy
  • Czestochowa University of Technology, Poland
  • University of Pune, India
Bibliografia
  • 1.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.
  • 2.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.
  • 3.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.
  • 4.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.
  • 5.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.
  • 6.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.2018.21.07
  • 7.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.
  • 8.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.2014.05.02
  • 9.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.Maszke, A. 2019, TPM Safety Impact – Case Study, CzOTO 2019, 1(1), 639–646. DOI: 10.2478/czoto-2019-0081
  • 11.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.
  • 12.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.
  • 13.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.
  • 14.Nuchsara, K. and Nalin, P. 2007, The Assembly Line Balancing Problem: Review articles, KKU Engineering Journal 34/2, pp. 133 – 140.
  • 15.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.
  • 16.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.
  • 17.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.
  • 18.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.
  • 19.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.
  • 20.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.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2b287816-8048-4f34-8021-6f03c8756257
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