Advanced inventory planning and forecasting solutions: A case study of the UKTLCS Chinook maintenance programme

Production Planning and Control

Volumn 25, Issue 1, 2014, Pages 73-90

  Downing, Matthew ^a   Chipulu, Max ^b   Ojiako, Udechukwu ^c   Kaparis, Dinos ^d  

^a Boeing Defence UK Limited   (United Kingdom)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c UNIVERSITY OF THE WITWATERSRAND   (South Africa)

^d LANCASTER UNIVERSITY MANAGEMENT SCHOOL   (United Kingdom)

Author keywords

Forecasting; Inventory planning; Support systems

Indexed keywords

CHINOOK HELICOPTERS; FORECASTING PERFORMANCE; FORECASTING SUPPORT SYSTEM; FORECASTING SYSTEM; INVENTORY PLANNING; MAINTENANCE PROGRAMMES; SUPPORT SYSTEMS; VISUAL BASIC FOR APPLICATIONS;

MAINTENANCE; TOOLS;

FORECASTING;

EID: 84889785666     PISSN: 09537287     EISSN: 13665871     Source Type: Journal    
DOI: 10.1080/09537287.2012.658451     Document Type: Article

References (27)

1. Argyris, C. and Schon, D., 1991. Participatory action research and action science compared: a commentary. In: W. Whyte, ed. Participatory action research. Newbury Park, California: Sage.
2. Billah, B., et al., 2006. Exponential smoothing model selection for forecasting. International Journal of Forecasting, 22 (2), 239-247.
3. Boylan, J., Syntetos, A., and Karakostas, G., 2008. Classification for forecasting and stock control: a case study. Journal of the Operational Research Society, 59, 473-481.
4. Carmo, J., António, A., and Rodrigues, J., 2004. Adaptive forecasting of irregular demand processes. Engineering Applications of Artificial Intelligence, 17 (2), 137-143.
5. Clark, A., 2005. Rolling horizon heuristics for production planning and set-up scheduling with backlogs and errorprone demand forecasts. Production Planning & Control, 16 (1), 81-97.
6. Croston, J., 1972. Forecasting and stock control for intermittent demands. Operations Research Society, 23, 289-304.
7. Denicoff, M., Fennell, J., and Solomon, H., 1960. Summary of a method for determining the military worth of spare parts. Naval Research Logistics Quarterly, 7 (3), 221-234.
8. Downing, M., et al., 2011. Supply chain forecasting for the UK Chinook fleet. OR Insight, 24, 110-130.
9. Gardner, E., 2006. Exponential smoothing: the state of the art - part II. International Journal of Forecasting, 22 (4), 637-666.
10. Graman, G. and Sanders, N., 2009. Modelling the tradeoff between postponement capacity and forecast accuracy. Production Planning & Control, 20 (3), 206-215.
11. Ho, C. and Ireland, T., 1993. A diagnostic analysis of the impact of forecast errors on production planning via MRP system nervousness. Production Planning & Control, 4 (4), 311-322.
12. Huberty, C. and Morris, J., 1989. Multivariate analysis versus multiple univariate analyses. Psychological Bulletin, 105 (2), 302-308.
13. Johnsen, T., Howard, M., and Miemczyk, J., 2009. UK defence change and the impact on supply relationships. Supply Chain Management: An International Journal, 14 (4), 270-279.
14. Karr, H., 1958. A method of estimating spare-part essentiality. Naval Research Logistics Quarterly, 5 (1), 29-42.
15. Kennedy, W.J., Pattersonb, J.W., and Fredendall, L.D., 2002. An overview of recent literature on spare parts inventories. International Journal of Production Economics, 76 (20), 201-215.
16. Makridakis, S., Wheelwright, S.C., and Hyndman, R.J., 1998. Forecasting: methods and applications. New York: John Wiley & Sons, Inc.
17. Markland, R., 1970. A comparative study of demand forecasting techniques for military helicopter spare parts. Naval Research Logistics Quarterly, 17 (1), 103-119.
18. Michaels, L., 1999. The making of a lean aerospace supply chain. Supply Chain Management: An International Journal, 4 (3), 135-144.
19. Syntetos, A.A. and Boylan, J.E., 2001. On the bias of intermittent demand estimates. International Journal of Production Economics, 71, 457-466.
20. Syntetos, A.A. and Boylan, J.E., 2005. The accuracy of intermittent demand estimates. International Journal of Forecasting, 21, 303-314.
21. Syntetos, A. and Boylan, J., 2006. Comments on the attribution of and intermittent demand estimator. International Journal of Forecasting, 22, 202.
22. Syntetos, A., Boylan, J., and Croston J., 2005. On the categorization of demand patterns. Journal of the Operational Research Society, 56, 495-503.
23. Theil, H., 1966. Applied economic forecasting. Amsterdam: North-Holland Publishing Company.
24. Tysseland, B., 2009. Spare parts optimization process and results: OPUS10 cases in the Norwegian defence. International Journal of Physical Distribution & Logistics Management, 39 (1), 8-27.
25. Venkataraman, R. and Nathan, J., 1999. Effect of forecast errors on rolling horizon master production schedule cost performance for various replanning intervals. Production Planning & Control, 10 (7), 682-689.
26. Viertl, R., 2006. Univariate statistical analysis with fuzzy data. Computational Statistics & Data Analysis, 51 (1), 33-147.
27. Wallstrom, P., 2009. Evaluation of forecasting techniques and forecast errors - with focus on intermittent demand. Licentiate Thesis. Lulea University of Technology.