Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The article is a case study of the use of snapshot observation to analyse the factors causing time losses at selected laser burner stations, and to propose changes that will increase the effective utilization of working time. The purpose of this paper is to determine the best and worst utilization of working time at the examined workplaces, analyse the amount of time lost and identify the causes of losses, and propose solutions that will improve the utilization of working time. According to the snapshot observation, procedure 2 main - work and non-work - time fractions and 10 detailed time fractions in the working day were distinguished, and their percentage share for the analysed workstations was calculated. Analyses of the working day time utilization depending on the type of machines, days of observation, single shifts were done and selected results were averaged. The paper indicates that organizational and technical aspects, as well as the employees' faults, were the main reasons for time losses. Research has shown that the generally examined group of workstations was characterized by a high utilization level of working time. An unfavourable phenomenon was the ratio of the main time to the auxiliary time, the high share of the maintenance time fraction of the workstations, and incorrect organization of the interoperation transport, low workers motivation, rush, and routine. It was found that further improvement of work efficiency and reduce time losses requires paying attention to the optimization of employees' working conditions, training, motivation systems, and implementation of lean concept tools and MES/CMMS solutions into production.
Czasopismo
Rocznik
Tom
Strony
137--147
Opis fizyczny
Bibliogr. 51 poz., rys., tab.
Twórcy
autor
- Czestochowa University of Technology, Faculty of Management, Department of Production Engineering and Safety, 42-200 Czestochowa, Poland
Bibliografia
- 1. Aalto, A., Goncalves, J., 2019. Linear system identification from ensemble snapshot observations, 58th Conference on Decision and Control (CDC). 7554-7559, DOI: 10.1109/CDC40024.2019.9029334.
- 2. Al-Saleh, K.S., 2011. Productivity Improvement of a Motor Vehicle Inspection Station Using Motion and Time Study Techniques, Journal of King Saud University - Engineering Sciences, 23, 33-41.
- 3. Almeida, D., Ferreira, J., 2009. Analysis of the Methods Time Measurement (MTM) Methodology through its Application in Manufacturing Companies. 19th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2009), Middlesbrough, UK, DOI: 10.13140/RG.2.1.2826.1927
- 4. Akansel, M., Yagmahan, B., Emel, E., 2017. Determination of Standard Times for Process Improvement: A Case Study. Global Journal of Business, Economics and Management: Current Issues, 7, 62, DOI: 10.18844/gjbem.v7i1.1400
- 5. Anvari, F., Edwards, R., Starr, A., 2010. Evaluation of overall equipment effectiveness based on market, Journal of Quality in Maintenance Engineering, 16, 256-270, DOI: 10.1108/13552511011072907
- 6. Baraniak, B., 2009. Work research methods, Academic and Professional Publishing House, Warsaw. (in Polish)
- 7. Bartnicka, J., Kabiesz, P., Kaźmierczak, J., 2020. Standardization of human activities as the component of a workflow efficiency model – a research experiment from a meat producing plant, Production Engineering Archives, 26(2), 73-77, DOI: 10.30657/pea.2020.26.15
- 8. Bieda, J., Bieniok, H., 2011. Methods and techniques of testing and standardizing working time, In: Efficient management methods, H. Bieniok (Ed.), Warsaw, Placet (in Polish)
- 9. Borkowski, S., Knop, K., Mielczarek, M., 2012. The Use of Six Sigma indicators for Measurement the Process Quality of Products' Conformity Assessment in the Alternative Control, In: Quality Control as Process Improvement Factor, S. Borkowski, M. Konstanciak (Eds.), Oficyna Wydawnicza Stowarzyszenia Menedżerów Jakości i Produkcji, Częstochowa, 116-131.
- 10. Brzeziśnki, 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 (METAL 2016), Ostrava, Tanger, 1750-1755.
- 11. Chase, R.B., Aquilano, N.J., Jacobs, F.R., 2001. Operations Management for Competitive Advantage, McGraw-Hill.
- 12. Cimino, A., Longo, F., Mirabelli, G., Papoff, E., 2008. MOST and MTM for work methods optimization: A real case study based on modeling & simulation, International Conference on Harbour, Maritime and Multimodal Logistics Modelling and Simulation, 1, 35-41.
- 13. Czerwinska, K., Pacana, A., 2020. Analysis of the internal door technological process, Production Engineering Archives, 26(1), 25-29, DOI: 10.30657/pea.2020.26.06
- 14. Duran, C., Çetindere, A., Aksu, Y.E., 2015. Productivity Improvement by Work and Time Study Technique for Earth Energy-glass Manufacturing Company, Procedia Economics and Finance, 26, 109-113, DOI: 10.1016/S2212-5671(15)00887-4
- 15. Fin, J., Vidor, G., Cecconello, I., de Campos Machado, V., 2017. Improvement based on standardized work: an implementation case study, Brazilian Journal of Operations & Production Management, 14, 388, DOI: 10.14488/BJOPM.2017.v14.n3.a12
- 16. Forsyth, P., 2004. Effective time management, Helion, Warsaw (in Polish)
- 17. Ghongadi, T.D., Babu, S.S., Kulkarni, M.H., 2015. A Case Study on Operator Workload Balancing for Assembly Stations, International Journal of Engineering Sciences & Research Technology, 4(11), 369-375.
- 18. Golden, L., 2012. The Effects of Working Time on Productivity and Firm Performance: a research synthesis paper, International Labour Office, Geneva.
- 19. Grudzewski, W., 1966. Study of labour productivity reserves using the snapshot method, Państwowe Wydawnictwo Ekonomiczne, Warsaw. (in Polish)
- 20. Ingaldi, M., Dziuba Sz. T., 2015. Modernity Evaluation of the Machines Used During Production Process of Metal Products, 24th International Conference on Metallurgy and Materials (METAL 2015), Ostrava, Tanger, 1908-1914.
- 21. Jagusiak-Kocik, M., Krynke, M., 2016. Analysis of Machines Effectiveness in the Company which Produces Electronic Equipment, Systems Supporting Production Engineering, 3(15), 79-86.
- 22. Kardas, E., 2012. Evaluation of Efficiency of Working Time of Equipment in Blast Furnace Department, Journal of Achievements in Materials and Manufacturing Engineering, 55(2), 876-880.
- 23. Kardas, E., Brzozova S., Pustejovska P., Jursova S., 2017. The Evaluation of Efficiency of the Use of Machine Working Time in the Industrial Company - Case Study, Management Systems in Production Engineering, 25(4), 241-245, DOI: 10.1515/mspe-2017-0034
- 24. Krynke, M., Mielczarek, K., 2018. Applications of linear programming to optimize the cost-benefit criterion in production processes, MATEC Web of Conferences 183, DOI: 10.1051/matecconf/201818304004
- 25. Lan, S., Wang, X., Ma, L., 2009. Optimization of Assembly Line Based on Work Study, Industrial Engineering and Engineering Management, IE&EM '09,16th International Conference, 4, 813-816.
- 26. Lawlor A., 1970. Technical aspects of supervision, Oxford, Pergamon Press.
- 27. Kanawaty, G., 1992. Introduction to Work Study, 4th (Revised) Edition, International Labour Office, Geneva.
- 28. Kulkarni, P.P., Kshire, S.S., Chandratre, K.V., 2014. Productivity Improvement through Lean Deployment & Work Study Methods, International Journal of Research in Engineering and Technology, 3(2), 429-434.
- 29. Knop, K., 2020. Indicating and analysis the interrelation between terms – visual: management, control, inspection and testing, Production Engineering Archives, 26(3), 110-121, DOI: 10.30657/pea.2020.26.22
- 30. Knop, K., Ulewicz R., 2019. Assessment of Technology, Technological Resources and Quality in the Manufacturing of Timber Products, 12th International Scientific Conference WoodEMA 2019, Digitalisation and Circular Economy: Forestry and Forestry Based Industry Implications, Union of Scientists of Bulgaria, Sofia, 251-256.
- 31. 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), 6-9.
- 32. Korkmaz, I., Alsu, E., Özceylan, E., Weber, G-W. 2020. Job analysis and time study in logistic activities: a case study in packing and loading processes, Central European Journal of Operations Research, 28, DOI: 10.1007/s10100-019-00624-1
- 33. Lockyer, K.G., Muhlemann, A., Oakland, J., 1992. Production and Operations Management, Financial Times Prentice Hall, Hoboken, NJ, USA.
- 34. Mor, R.S., Bhardwaj, A., Singh, S., Sachdeva, A., 2019. Productivity gains through Standardization-of-Work: Case of Indian manufacturing industry, Journal of Manufacturing Technology Management, 30(6), 899-919, DOI: 10.1108/JMTM-07-2017-0151
- 35. Mor, R.S., Bhardwaj, A. Singh, S., 2018. Benchmarking the interactions among Performance Indicators in Dairy supply chain: An ISM approach, Benchmarking: An International Journal, 25(9), 3858-3881, DOI: 10.1108/BIJ-09-2017-0254
- 36. Morlock, F., Kreggenfeld, N., Louw, L., Kreimeier, D., Kuhlenkötter, B., 2017. Teaching Methods-Time Measurement (MTM) for Workplace Design in Learning Factories, Procedia Manufacturing, 9, 369-375, DOI: 10.1016/j.promfg.2017.04.033
- 37. Mundel, M.E., 1973. Motion and time study principles and practices, Prentice-Hall, New Delhi.
- 38. Niebel, B.W., Freivalds, A., 2003. Methods, standards and work design. McGraw-Hill, New York.
- 39. Nesterak, J., Siudy, J., 2020. Automation of snapshot analysis in a manufacturing enterprise, Knowledge-economy-society. Socio-economic conditions of development of contemporary organizations. Chapter 12. TNOiK Organizer's House, 163-174 (in Polish)
- 40. Panasiuk, J., Kaczmarek, W., 2019. Robotization of production processes, PWN, Warsaw.
- 41. Pisuchpen, R., Chansangar, W., 2014. Modifying Production Line for Productivity Improvement: A Case Study of Vision Lens Factory, Songklanakarin Journal of Science and Technology, 36(3), 345-357.
- 42. Siwiec, D., Pacana, A., 2021. Method of improve the level of product quality, Production Engineering Archives, 27(1), 1-7, DOI: 10.30657/pea.2021.27.1
- 43. Shikdara, A., Sawaqedb, N., 2004. Ergonomics, and occupational health and safety in the oil industry: a managers’ response, Computers & Industrial Engineering, 47, 223-232.
- 44. Stasiak-Betlejewska, R., 2018. The Machines Operation Effectiveness Analysis in Polish Industry Enterprise, Terotechnology 2017, A. Szczotok, J. Pietraszek, N. Radek (Eds.), Materials Research Forum LLC, Millersville.
- 45. Stasiak-Betlejewska, R., Ulewicz, R., 2018. The Effectiveness of Selected Machinery and Equipment in the Woodworking Joinery, 9 th International Conference on the Path Forward for Wood Products: a Global Perspective, Baton Rouge, USA, WoodEMA, 149-156.
- 46. Subramanian, A., 2008. Time Standards and Disability: A Work Measurement Perspective, International Journal of Industrial Engineering, 15, 113-121.
- 47. Tippett, L.H.C., 1982. The Making of an Industrial Statistician. The Making of Statisticians, J. Gani (Eds.), New York, NY, Springer.
- 48. Ulewicz, R., Mazur, M. 2019. Economic aspects of robotization of production processes by example of a car semi-trailers manufacturer. Manu-facturing Technology, 19(6), 1054-1059.
- 49. Ulewicz, R., Ulewicz, M., 2020. Problems in the Implementation of the Lean Concept in the Construction Industries, Proceedings of Advances in Resource-Saving Technologies and Materials in Civil and Environmental Engineering 2019, Z. Blikharskyy, P. Koszelnik, P. Mesaros (Eds.), Springer, Cham, 495-500.
- 50. Ulewicz, R., Novy, F., 2019. Quality Management Systems in Special Processes, 13th International Scientific Conference on Sustainable, Modern and Safe Transport (TRANSCOM 2019), University of Zilina, Zilina, 113-118.
- 51. Waciskowska, M., 2011. Working time 2011. Practical solving of problems related to planning and settling working time, CH Beck, Warsaw. (in Polish)
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5f5c6277-1afc-4a68-b3e5-220b881ca7bb