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Analysis of application of Six Sigma in refuelling process in Brazilian airline

Published online by Cambridge University Press:  14 March 2019

H. N. P. Tucci Open the ORCID record for H. N. P. Tucci [Opens in a new window]  and
G. C. Oliveira Neto
H. N. P. Tucci*
Affiliation:
Department of Industrial Engineering, Nine of July University – UNINOVE, São Paulo, Brazil
G. C. Oliveira Neto
Affiliation:
Department of Industrial Engineering, Nine of July University – UNINOVE, São Paulo, Brazil
*
*henrricco@gmail.com
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Abstract

Aircraft refuelling is a major cause of flight delays because it is a slow process. Further, if it does not begin as soon as the aircraft is available for ground handlers, there is an increasing risk of it being terminated after the final passenger has boarded. Usually, the process only begins after information regarding the required quantity of fuel is passed through the flight dispatcher, and this information typically requires a certain time to reach the ground handlers. Therefore, it is intended to test a new scenario: to begin refuelling with a minimum level and, if necessary, fill up the remainder with the final fuel figures when received. The aim of this paper is to analyse the application of Six Sigma in this process through Student’s t-test and statistical process control. The collected data in this case study include the amount of fuel supplied and flight delays (which are mainly caused by refuelling). The results demonstrate that the new process is favourable, and that the average length of flight delays is reduced from 14 to 6 min, which is an improvement of 57%. It is concluded that the application of Six Sigma in the aircraft refuelling process saves time and improves on-time performance levels, which is relevant to the scientific literature, thereby aiding in mitigating the risk of fines and penalties.

Keywords

Six SigmaAircraft refuellingFlight delaysStudent’s t-test
Type
Research Article
Information
The Aeronautical Journal , Volume 123 , Issue 1260 , February 2019 , pp. 265 - 282
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Copyright
© Royal Aeronautical Society 2019 

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References

1. Pande, P.S., Neuman, R.P. and Cavanagh, R.R. The Six Sigma Way (1 ed.), McGraw-Hill, New York, 2000.Google Scholar
2. Nair, A., Malhotra, M.K. and Ahire, S.L. Toward a theory of managing context in Six Sigma process-improvement projects: an action research investigation, J Operations Management, 2011, 29, (211), pp 529–548.Google Scholar
3. Pysdek, T. The Six Sigma Handbook, McGraw-Hill, ebook edition, New York, 2003.Google Scholar
4. Antony, J., Kumar, M. and Madu, C.N. Six Sigma in small and medium sized UK manufacturing enterprises: some empirical observations, Int J Quality & Reliability Management, 2005, 22, (8), pp 860–874.Google Scholar
5. El Moudani, W. and Mora-Camino, F. A dynamic approach for aircraft assignment and maintenance scheduling by airlines, J Air Transport Management, 2000, 6, (4), pp 233–237.Google Scholar
6. Harry, M. and Schroeder, R. Six Sigma: The Breakthrough Management Strategy Revolutionizing the World’s Top Corporations. Doubleday, New York, 2000.Google Scholar
7. GE. General Electrics – Our company – What is Six Sigma. URL http://www.ge.com/en/company/companyinfo/quality/whatis.htm. [Accessed 13 March 2015].Google Scholar
8. Henderson, K.M. and Evans, J.R. Successful implementation of Six Sigma: benchmarking General Electric Company, Benchmarking: An Int J, 2000, 7, (4), pp 260–282.Google Scholar
9. Akbulut-Bailey, A.Y., Motwani, J. and Smedley, E.M. When Lean and Six Sigma converge: a case study of a successful implementation of Lean Six Sigma at an aerospace company, Int J Technology Management, 2012, 57, (1), pp 18–32.Google Scholar
10. Maleyeff, J. and Krayenvenger, D.E. Goal setting with Six Sigma mean shift determination, Aircraft Engineering and Aerospace Technology, 2004, 76, (6), pp 577–583.Google Scholar
11. Thomas, A.J., Mason-Jones, R., Davies, A. and John, E.G. Reducing turn-round variability through the application of Six Sigma in aerospace MRO facilities, J Manufacturing Technology Management, 2015, 26, (3), pp 314–332.Google Scholar
12. Abdelghany, K., Abdelghany, A. and Raina, S. A model for the airlines’ fuel management strategies, J Air Transport Management, 2005, 11, (4), pp 199–206.Google Scholar
13. Babic, O. Optimization of refuelling truck fleets at an airport, Transportation Research Part B Methodological, 1987, 21, (6), pp 479–487.Google Scholar
14. Shackel, B. and Klein, L. ESSO London airport refueling control centre redesign – an ergonomics case study, Applied Ergonomics, 1976, 7, (1), pp 37–45.Google Scholar
15. Ryerson, M.S. and Hansen, M. Capturing the impact of fuel price on jet aircraft operating costs with Leontief technology and econometric models, Transportation Research Part C, 2013, 33, (8), pp 282–296.Google Scholar
16. Narangajavana, Y., Garrigos-Simon, F.J., Garcia, J.S. and Forgas-Coll, S. Prices, prices and prices: a study in the airline sector, Tourism Management, 2014, 41, (4), pp 28–42.Google Scholar
17. IATA – International Air Transport Association. Enabling Aviation to Drive Growth in Latin America. http://www.iata.org/pressroom/pr/Pages/2015-11-16-01.aspx. [Accessed 16 November 2015].Google Scholar
18. Muller, E.R. and Chatterji, G.B. Analysis of aircraft arrival and departure delay characteristics. AIAA’s Aircraft Technology, Integration, and Operations, 2002.Google Scholar
19. Davies, M. The Standard Handbook for Aeronautical and Astronautical Engineers (1st ed.), McGraw-Hill, New York, 2003.Google Scholar
20. Kinnison, H.A. and Siddiqui, T. Aviation Maintenance Management (2 ed.), McGraw-Hill, New York, 2012.Google Scholar
21. IATA – International Air Transport Association. Standard IATA Delay Codes AHM730. IATA Airport Handling Manual 38th Edition, 2018.Google Scholar
22. Blokland, W.W.A.B.V., Waard, A.D. and Santema, S.C. Design of a lean MRO business process for EPCOR. 8th. AIAA Aviation Technology, Integration and Operations (ATIO) Conference, 2008.Google Scholar
23. Sumranwong, D. Adaptation DMAIC to develop an eLearning model for aerospace repair station. International Conference on e-Education, Entertainment and e-Management, 2011.Google Scholar
24. Ho, Y.C., Chang, O.C. and Wang, W.B. An empirical study of key success factors for Six Sigma Green Belt projects at an Asian MRO company, J Air Transport Management, 2008, 14, (5), pp 263–269.Google Scholar
25. Wei, Z., Chen, Z., Yajun, C. and Peng, Z. The discussion of the application of the six sigma in the civil aviation. International Conference on Transportation Information and Safety (ICTIS) - American Society of Civil Engineers (ASCE), 2011.Google Scholar
26. Chang, H.M., Huang, C. and Torng, C.C. The construction of production improvement model for aerospace manufacturing suppliers. 9th Asia-Pacific Conference on Materials Processing (APCMP), 2010.Google Scholar
27. Weber, N.O. Product development teams and tools applied to the aircraft industry, World Class Design to Manufacture, 1994, 1, (6), pp 20–26.Google Scholar
28. Wong, K.M., Halim, T. and Tan, Y.W. Improvement to the Freight Management of ITAR Controlled Items using Lean Six Sigma. International Conference on Industrial Engineering (IEEE) – Industrial Engineering and Engineering Management (IEEM), 2013, pp 191–195.Google Scholar
29. Shanmuganathan, V.K., Haran, A.P., Ragavendran, S. and Gayathri, N. Aero-engine maintenance cost optimization by RCM, Life Science J, 2013, 10, (1), pp 2891–2896.Google Scholar
30. O’Kelly, M.E. Air freight hubs in the FedEx system: analysis of fuel use, J Air Transport Management, 2014, 36, (4), pp 1–12.Google Scholar
31. Swan, W.M. and Adler, N. Aircraft trip cost parameters: a function of stage length and seat capacity, Transportation Research Part E, 2006, 42, (2), pp 105–115.Google Scholar
32. Seristo, H. and Vepsalainen, A.P.J. Airline cost drivers: cost implications of fleet, routes, and personnel policies, J Air Transport Management, 1997, 3, (1), pp 11–22.Google Scholar
33. Jupp, J.A. The design of future passenger aircraft – the environmental and fuel price challenges, The Aeronautical Jnal, 2016, 120, (1), pp 37–60.Google Scholar
34. AIN – Aviation International News. Contract fueling, fuel cards and suppliers, operators look to fuel as a cost they can control, AIN Publications, 2016, 48, (5), pp 34–38.Google Scholar
35. NY Times – Delta buys refinery to get control of fuel costs. http://www.nytimes.com/2012/05/01/business/delta-air-lines-to-buy-refinery.html [Accessed 29 August 2016].Google Scholar
36. ABEAR – Outlook. 2014. The Brazilian air transport industry data and analysis. http://www.abear.com.br/uploads/arquivos/dados_e_fatos_arquivos_eng/!ABEAR_Panorama_19OUT_INGLES_SIMPLES.PDF [Accessed 29 August 2016].Google Scholar
37. Eisenhardt, K.M. and Graebner, M.E. Theory building from cases: opportunities and challenges, Academy of Management J, 2007, 50, (1), pp 25–32.Google Scholar
38. Yin, R.K. Case Study Research: Design and Methods (5th ed.), SAGE, California, 2015.Google Scholar
39. Eisenhardt, K.M. Building theories from case study research, Academy of Management Review , 1989, 14, (4), pp 532–550.Google Scholar
40. Student, The problem error of a mean, Biometrika, 1908, 6, (1), pp 1–25.Google Scholar
41. Privitera, G.J. Statistics for the Behavioral Sciences (2nd ed.), SAGE, California, 2014.Google Scholar
42. AIRBUS – Getting to grips with aircraft performance. Flight Operations Support and Line Assistance, Customer Services. Airbus, Toulouse, 2002.Google Scholar