Skip to main content

Why slow down? Factors affecting speed loss in process manufacturing

Abstract

Loss of production speed is an unavoidable reality for process manufacturers. Reduced production speeds are shown to consume 9–15% of available production capacity in various production contexts and create substantial costs for capital-intensive process industries. Amongst the least examined of the six big efficiency losses measured within total productive maintenance, speed loss presents significant opportunities for potential efficiency improvements in manufacturing companies. Based on the literature, this paper presents a framework of the factors related to speed loss, including three overall dimensions: technology factors, human factors and product factors. Next, a case study of two production lines to investigate this framework and quantify the scale of speed loss for the factors identified in the case study. For quantification, generalised least squares regression is performed to study the relationship between each factor and speed loss. The analysis of the production data reveals that technology and human factors have the strongest correlations with speed losses in this industry and account for the most speed loss. This research can directly support operational improvement initiatives in practice by identifying the factors with the strongest relationships to speed loss, aiding practitioners to select the most relevant means to improve speed and identify appropriate overall equipment effectiveness targets.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. 1.

    Nakajima S (1988) Introduction to total productive maintenance (TPM). Productivity Press, Cambridge

    Google Scholar 

  2. 2.

    Tsarouhas P (2007) Implementation of total productive maintenance in food industry: a case study. J Qual Maint Eng 13:5–18. https://doi.org/10.1108/13552510710735087

    Article  Google Scholar 

  3. 3.

    Ljungberg Õ (1998) Measurement of overall equipment effectiveness as a basis for TPM activities. Int J Oper Prod Manag 18:495–507. https://doi.org/10.1108/01443579810206334

    Article  Google Scholar 

  4. 4.

    Ahmed S, Hassan MH, Taha Z (2004) State of implementation of TPM in SMIs: a survey study in Malaysia. J Qual Maint Eng 10:93–106. https://doi.org/10.1108/13552510410539178

    Article  Google Scholar 

  5. 5.

    Nakajima S (1989) TPM Development Program: implementing total productive maintenance. Productivity Press, Cambridge

    Google Scholar 

  6. 6.

    Zuashkiani A, Rahmandad H, Jardine AKS (2011) Mapping the dynamics of overall equipment effectiveness to enhance asset management practices. J Qual Maint Eng 17:74–92. https://doi.org/10.1108/13552511111116268

    Article  Google Scholar 

  7. 7.

    Jonsson P, Lesshammar M (1999) Evaluation and improvement of manufacturing performance measurement systems - the role of OEE. Int J Oper Prod Manag 19:55–78

    Article  Google Scholar 

  8. 8.

    Benjamin SJ, Marathamuthu MS, Murugaiah U (2015) The use of 5-WHYs technique to eliminate OEE’s speed loss in a manufacturing firm. J Qual Maint Eng 21:419–435. https://doi.org/10.1108/JQME-09-2013-0062

    Article  Google Scholar 

  9. 9.

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

    Article  Google Scholar 

  10. 10.

    Ljungberg Õ (1997) Att Förstå & Tillämpa TPM (in Swedish). Novum Grafiska AB, Gothenburg

    Google Scholar 

  11. 11.

    Dal B, Tugwell P, Greatbanks R (2000) Overall equipment effectiveness as a measure of operational improvement – a practical analysis. Int J Oper Prod Manag 20:1488–1502. https://doi.org/10.1108/01443570010355750

    Article  Google Scholar 

  12. 12.

    Muchiri P, Pintelon L (2008) Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion. Int J Prod Res 46:3517–3535. https://doi.org/10.1080/00207540601142645

    Article  MATH  Google Scholar 

  13. 13.

    De Ron AJ, Rooda JE (2006) OEE and equipment effectiveness: an evaluation. Int J Prod Res 44:4987–5003. https://doi.org/10.1080/00207540600573402

    Article  MATH  Google Scholar 

  14. 14.

    Chan FTS, Lau HCW, Ip RWL et al (2005) Implementation of total productive maintenance: a case study. Int J Prod Econ 95:71–94. https://doi.org/10.1016/j.ijpe.2003.10.021

    Article  Google Scholar 

  15. 15.

    Ahmad N, Hossen J, Ali SM (2018) Improvement of overall equipment efficiency of ring frame through total productive maintenance: a textile case. Int J Adv Manuf Technol 94:239–256. https://doi.org/10.1007/s00170-017-0783-2

    Article  Google Scholar 

  16. 16.

    Morales Méndez JD, Rodriguez RS (2017) Total productive maintenance (TPM) as a tool for improving productivity: a case study of application in the bottleneck of an auto-parts machining line. Int J Adv Manuf Technol 92:1013–1026. https://doi.org/10.1007/s00170-017-0052-4

    Article  Google Scholar 

  17. 17.

    Ohunakin OS, Leramo RO (2012) TPM implementation in a beverage industry. J Eng Appl Sci 7:128–133

    Google Scholar 

  18. 18.

    Tsarouhas PH (2013) Equipment performance evaluation in a production plant of traditional Italian cheese. Int J Prod Res 51:5897–5907. https://doi.org/10.1080/00207543.2013.807373

    Article  Google Scholar 

  19. 19.

    Ogle RA, Carpenter AR (2014) Calculating the capacity of chemical plants. Chem Eng Prog 110:59–63

    Google Scholar 

  20. 20.

    Anderson S, Sedatole KL (2013) Evidence on the cost hierarchy: the association between resource consumption and production activities. J Manag Account Res 25:119–141. https://doi.org/10.2308/jmar-50293

    Article  Google Scholar 

  21. 21.

    Fisher ML, Ittner CD (1999) The impact of product variety on automobile assembly operations: empirical evidence and simulation analysis. Manag Sci 45:771–786. https://doi.org/10.1287/mnsc.45.6.771

    Article  Google Scholar 

  22. 22.

    Allwood JM, Childs THC, Clare AT et al (2015) Manufacturing at double the speed. J Mater Process Technol 229:729–757. https://doi.org/10.1016/j.jmatprotec.2015.10.028

    Article  Google Scholar 

  23. 23.

    Aboutaleb A, Kang PS, Hamzaoui R, Duffy A (2017) Standalone closed-form formula for the throughput rate of asynchronous normally distributed serial flow lines. J Manuf Syst 43:117–128. https://doi.org/10.1016/j.jmsy.2016.12.006

    Article  Google Scholar 

  24. 24.

    Hopp WJ, Spearman ML (2008) Factory physics, 3rd edn. Waveland Press, Inc., Long Grove

    Google Scholar 

  25. 25.

    De Ron AJ, Rooda JE (2005) Equipment effectiveness: OEE revisited. IEEE Trans Semicond Manuf 18:190–196. https://doi.org/10.1109/TSM.2004.836657

    Article  Google Scholar 

  26. 26.

    Berry WL, Cooper MC (1999) Manufacturing flexibility: methods for measuring the impact of product variety on performance in process industries. J Oper Manag 17:163–178

    Article  Google Scholar 

  27. 27.

    SEMI (2014) Specification for definition and measurement of equipment productivity, SEMI E079-0814E. Mt. View, CA

  28. 28.

    Nurani RK, Akella R (1992) Quality and speed trade-offs in manufacturing systems. In: Proceedings of the 1992 IEEE International Conference on Robotics and Automation. Nice, France, pp 1145–1149

  29. 29.

    Yin RK (2018) Case study research and applications: design and methods. 6th Ed, Los Angeles

    Google Scholar 

  30. 30.

    Hayes RH, Wheelwright SC (1979) Link manufacturing process and product life cycles. Harv Bus Rev 57:133–140

    Google Scholar 

  31. 31.

    Google (2018) Google Translate. https://translate.google.com/. Accessed 1 Jun 2018

  32. 32.

    R Core Team (2018) R: a language and environment for statistical computing

  33. 33.

    Pinheiro J, Bates D, DebRoy S et al (2018) nlme: linear and nonlinear mixed effects models

  34. 34.

    Wooldridge JM (2006) Introductory econometrics: a modern approach, 3rd edn. Thomson Higher Education, Mason

    Google Scholar 

Download references

Acknowledgements

The researchers thank the Innovation Fund of Denmark for its sponsorship of this research.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Alexandria Trattner.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Trattner, A., Hvam, L. & Haug, A. Why slow down? Factors affecting speed loss in process manufacturing. Int J Adv Manuf Technol 106, 2021–2034 (2020). https://doi.org/10.1007/s00170-019-04559-4

Download citation

Keywords

  • Speed loss
  • Total productive maintenance
  • Overall equipment effectiveness
  • Productivity
  • Process industry