Time Optimization Implementation in Conventional Lathe Machining Operations

  • Jumázulhisham Abdul ShukorEmail author
  • Syed Ahmad Faiz Syed Mohd
  • Mozaimi Mohamad
Part of the Advanced Structured Materials book series (STRUCTMAT, volume 102)


A study of time optimization in conventional lathe machining operations of the higher technical learning institutions in Malaysia was performed. This is to ensure that the students may complete a project within 30 contact hours. Based on previous experiences, almost 50% projects may not be able to completed on time. Time optimization is a process to increase productivity of machinists while reducing wastes. Three objectives were identified in this study, focused to identify time waste, simulate and suggest methods of the improvement. A few quantitative methods to identify the problem, i.e. the experimenting samples method, simulate and verification were used. As a result, time taken for machinist’s movement, inspections and storage were improved and this contributes to the highest improvement. Hence, the idle time has been minimized. The enhancement of standard operating procedure, audio-visual learning and layout design in the study played significant roles in completing the study. The movement and storage times were suggested for enhancement to reduces the issue of productivity.


Conventional lathe machining Time improvement Process flow Kaizen Productivity 



Thanks to the UniKL MSI Conventional Machining technicians who allow researchers to conduct the study for the sake of improvement in teaching and learning process.


  1. 1.
    Dimitrov, D., Saxer, M.: Productivity improvement in tooling manufacture through high speed 5 axis machining. In: 5th CIRP Conference on High Performance Cutting 2012, pp. 277–282 (2012)CrossRefGoogle Scholar
  2. 2.
    Singh, J., Singh, H.: Continuous improvement approach: state-of-art review and future implications. Int. J. Lean Six Sigma 3(2), 88–111 (2012)CrossRefGoogle Scholar
  3. 3.
    Thessaloniki: Kaizen definition and principles in brief: a concept tools for employees improvement. Retrieve from on 11 Jan 2016 (2006)
  4. 4.
    Iberahim, H., Mazlinda, H., Marhainie, H.D., Hidayah, A.N.: Determines the sustainable continuous improvement practices in mail processing service operation. Procedia Soc. Behav. Sci. 219, 330–337 (2015)Google Scholar
  5. 5.
    Jamaludin, K.R., Haron, H.N.: Nurturing Lean Manufacturing Concepts in the Industrial Engineering Subject at the Undergraduate Level. Proceedings of the Regional Conference on Engineering Education. Dec 12–13, 2005, Johor, Malaysia (2005)Google Scholar
  6. 6.
    Magar, V.M., Shinde, V.B.: Application of 7 quality control (7QC) tools for continuous improvement of manufacturing process. Int. J. Eng. Res. Gen. Sci. 2(4), 364–371 (2014)Google Scholar
  7. 7.
    Allen, T.T.: Introduction to Engineering Statistics and Lean Sigma: Statistical Quality Control and Design of Experiments and Systems, p. 128. Springer, Berlin (2010). ISBN 978-1-84882-999-2. Retrieved 17 Feb 2011Google Scholar
  8. 8.
    Magu, P., et al.: Path process chart—a technique for conducting time and motion study. Procedia Manuf. 3, 6475–6482 (2015)CrossRefGoogle Scholar
  9. 9.
    Environmental Modeling Center: NCEP Medium-Range Ensemble Forecast (MREF) System Spaghetti Diagrams. National Oceanic and Atmospheric Administration. Retrieved 2011-02-17 (2003-08-21)Google Scholar
  10. 10.
    Graham, B.B.: Detail process charting: speaking the language of process, Online-Ausg. edn., p. 2. Wiley, Hoboken, N.J. (2004)Google Scholar
  11. 11.
    Johansson, P.E.C.: Current state of standardized work in automotive industry in Sweden. Procedia CIRP 7, 151–156 (2013)CrossRefGoogle Scholar
  12. 12.
    Kabir, M.E., Boby, M.M.I., Lutfi, M.: Productivity improvement by using six-sigma. Int. J. Eng. Technol. 3(12), 1056–1084 (2013)Google Scholar
  13. 13.
    Jirasukptasert, P., Garza-Reyes, J.A., Kumar, V., Lim, M.K.: A six sigma and DMAIC application for the reduction of defects in a rubber gloves manufacturing process. Int. J. Lean Six Sigma 5(1), 2–21 (2014)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jumázulhisham Abdul Shukor
    • 1
    Email author
  • Syed Ahmad Faiz Syed Mohd
    • 1
  • Mozaimi Mohamad
    • 1
  1. 1.Malaysian Spanish Institute, Universiti Kuala LumpurKulimMalaysia

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