Estimating efficiency in automatic milking systems.

Discipline: management; Key words: automatic milking, dairy, data envelopment analysis, efficiency, milking frequency, visit time. 

Changing from a conventional milking system (CMS) to an automatic milking system (AMS) necessitates a different management approach and a corresponding change in labour tasks. Together with labour savings, AMS farms have been found to have higher capital costs, primarily because of higher maintenance costs and depreciation. Therefore, it is expected that AMS farms differ from CMS farms in the capital to labour ratio and possibly their technical efficiency, at least during the learning period. Two studies evaluated overall operating efficiency, the one in the Netherlands comparing an AMS with a CMS during transition and the one in Spain how efficiency in the AMS can be improved. The respective references are: W. Steeneveld, L.W. Tauer, H. Hogeveen & A.G.J.M. Oude Lansink 2012. Comparing technical efficiency of farms with an automatic milking system and a conventional milking system. Journal of Dairy Scienc, Vol 95, pages 7391to 7398 and A.Castro, J.M. Pereira, C. Amiama & J. Bueno 2012. Estimating efficiency in automatic milking systems. Journal of Dairy Science, Vol 95, pages 929 to 936.

In the Netherlands study actual farm accounting data from AMS and CMS on dairy farms were used to investigate the substitution of capital for labour in the AMS farms and to determine if the technical efficiency of the AMS farms differed from the CMS farms. The 63 AMS farms and the 337 CMS farms in the data set did not differ in general farm characteristics such as the number of cows, number of hectares and the amount of milk quota. The results showed that farms with AMS had significantly higher capital costs (€12.71 per 100 kg of milk) than CMS farms (€10.10 per 100 kg of milk). However, the total labour costs and net outputs were not significantly different between AMS and CMS farms, which indicates that a clear substitution of capital for labour with the adoption of an AMS could not be observed. Although the AMS farms had a slightly lower technical efficiency (0.76) than the CMS farms (0.78), a significant difference in these estimates was not observed. This suggests that the farms were not different in their ability to use inputs (capital, labour, cows and land) to produce outputs (total farm revenues). The technical efficiency of farms invested in an AMS in 2008 or earlier was not different from the farms invested in 2009 or 2010, indicating that a learning effect during the transition period was not observed. Furthermore, the results indicate that the economic performance of AMS and CMS farms were similar. What these results show is that other than higher capital costs, the use of AMS rather than CMS does not affect farm efficiency and that the learning costs to use an AMS are not present as measured by any fall in technical efficiency.

In the Spanish study milking data of 34 single AMS units were analyzed to determine the system capacity on each farm under actual working conditions. The number of cows, milk yield, milkings per cow per day, actual milking time, rejected milking time, cleaning time and machine downtime were used to determine the number of cows milked per AMS unit to obtain the optimal values of milkings per cow and milk production. An AMS unit on average milked 53 cows daily at 2.7 milkings per cow, with a total milking downtime of 1950 hours per year and a milk yield of 549,735 kg per year. Individual cows and milk flow rate had a far greater influence on the milk yield per AMS than milkings per cow and rejections. It was shown that it is possible that the AMS on these dairy farms could facilitate an increase of about 17 cows per AMS at 2.4 to 2.6 milkings per cow without impairing milking performance; in this way, the quantity of milk obtained per unit could be increased by 185,460 kg per year. This would make it possible to recoup the cost of the system earlier.