SciELO - Scientific Electronic Library Online

 
vol.21 número1Quality performance: The case of construction projects in the electricity industry in KenyaHybrid supply chains in emerging markets: The case of the Mexican auto industry índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Em processo de indexaçãoSimilares em Google

Compartilhar


South African Journal of Industrial Engineering

versão On-line ISSN 2224-7890
versão impressa ISSN 1012-277X

S. Afr. J. Ind. Eng. vol.21 no.1 Pretoria  2010

 

CASE STUDIES

 

A case study on maximising the profitability of a form fill and seal machine by optimising interruption intervals

 

 

P.J. VlokI; C.J. FourieII

IDepartment of Industrial Engineering, University of Stellenbosch, South Africa. pjvlok@sun.ac.za
IIDepartment of Industrial Engineering, University of Stellenbosch, South Africa. cjf@sun.ac.za

 

 


ABSTRACT

The practice of delivering consumer liquids in sachets, as opposed to alternative disposable packaging, has gained significant ground in the market in recent years because of environmental considerations, the cost benefit of sachets, and the relatively simple machinery required to produce sachets. In this paper, data obtained from a form, fill and seal (FFS) sachet producing machine is analysed for financial feasibility. A statistical model is fitted to the data to optimise production interruptions, and the model's relevance and value is confirmed on a second data set obtained from the same machine.


OPSOMMING

Die gebruik om verbruikersvloeistowwe in sakkies eerder as alternatiewe weggooibare verpakkingsmateriaal af te lewer het beduidende vooruitgang gemaak in die mark in die onlangse verlede as gevolg van omgewingsvriendelikheid, die koste-voordeel van sakkies, en die relatief eenvoudige toerusting wat benodig word vir die produksie van sakkies. In hierdie artikel word data wat verkry is van 'n Vorm, Vul en Seël (VVS) sakkie vervaardigingsmasjien geanaliseer vir ekonomiese lewensvatbaarheid. 'n Statistiese model word gepas oor die data om die produksie-onderbrekings te optimeer, en die model se toepaslikheid en waarde word bevestig met 'n tweede data-stel verkry van dieselfde masjien.


 

 

“Full text available only in PDF format”

 

 

REFERENCES

[1] Dada, A.C. 2009. Sachet water phenomenon in Nigeria, African Journal of Microbiology Research, 3(1), 015-021.         [ Links ]

[2] Austrialian Department of Foreign Affairs and Trade. 2004. India's economy at the midnight hour: Australia's India strategy, Commonwealth of Australia, Australian Government Publishing Service.         [ Links ]

[3] Kwakye-Nuako, G., Borketey, P., Mensah-Attipoe, I., Asmah, R. & Ayeh-Kumi, P. 2007. Sachets in medicine, Ghana Medical Journal, 41 (2), 62-67.         [ Links ]

[4] Crowder, M.J., Kimber, A.C., Smith, R.L. & Sweeting, T.J. 1991. Statistical analysis of reliability data, Chapman and Hall.         [ Links ]

[5] Andersen, P.K. 1985. Counting process models for life history data: A review, Scandinavian Journal of Statistics, 12, 97-158.         [ Links ]

[6] Jardine, A.K.S. & Anderson, M. 1988. Use of concomitant variables for reliability estimation, Maintenance Management International 5, 135-140.         [ Links ]

[7] Etezadi-Amoli, J. & Ciampi, A. 1987. Extended hazard regression for censored survival data with covariates: A spline approximation for the baseline hazard function. Biometrics, 43, 181-192.         [ Links ]

[8] Ascher, H.E. & Feingold, H. 1984. Repairable systems reliability: Modeling, inference, misconceptions and their causes, Marcel Dekker.         [ Links ]

[9] Cox, D.R. 1955. Some statistical methods connected with series of events, Journal of the Royal Statistical Society, 17, 129-164.         [ Links ]

[10] Calabria, R. & Pulcini, G. 2000. Inference and test in modeling the failure/repair process of repairable mechanical equipments. Reliability Engineering and System Safety, 67, 41-53.         [ Links ]

[11] Kalbfleisch, J.D. & Prentice, R.L. 1980. The statistical analysis of failure time data, New York: John Wiley & Sons.         [ Links ]

[12] Cox, D.R. & Lewis, P.A. 1966. The statistical analysis of series of events, Metheun,London.         [ Links ]

[13] Huang, J., Miller, C.R. & Okogbaa, O.G. 1995. Optimal preventive replacement intervals for the Weibull life distribution: Solutions and applications, Proceedings of the Annual Reliability and Maintenance Symposium, 370-377.         [ Links ]

[14] Hines, W.W. & Montgomery, D.C. 1980. Probability and statistics in engineering and management science (2nd ed.), John Wiley and Sons.         [ Links ]

[15] Vlok, P.J., Coetzee, J.L., Banjevic, D., Jardine, A.K.S & Makis, V. 2002. Optimal component replacement decisions using vibration monitoring and the Proportional Hazards Model. Journal for the Operational Research Society, 53, 2.         [ Links ]

[16] Anderson, T.W. & Darling, D.A. 1954. A test of goodness of fit. Journal of the American Statistical Association, 49, 765-769.         [ Links ]

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons