Par(lour) for the course

Teagasc research on Irish dairy farms is highlighting how milking process efficiency can be improved through parlour infrastructure, automation, and management practices.

A more quantifiable understanding of milking parlour infrastructure, automation and management practices can improve milking efficiency. Photo credit: PeopleImages/istockphoto.com

With growing herd sizes and intensifying pressure on farm infrastructure and labour resources, how can dairy farmers improve their milking efficiency? Recent research on Irish dairy farms highlights novel information on the effects that parlour infrastructure, automation specification, and management practices can have on improving milking process efficiency.

The abolition of the European Union milk quotas in 2015 enabled significant economic growth in the Irish dairy industry. Herd sizes increased by 37% – from a national average figure of 68 cows per herd in 2015, to 98 cows in 2024. This expansion has been central to advancing Ireland as a global dairy exporter, with annual exports exceeding 1.6 million tonnes at an estimated value of €6.3 billion.

However, this period of expansion has introduced new pressures, explains Ryan Prendergast, a Research Technician at Teagasc Moorepark.

“Labour availability across the Irish agricultural sector has declined, with this shortage being acutely felt in dairy farming. As a result, some farms require excessive labour inputs – i.e. hours per cow per year – reducing time available for other activities, while outdated infrastructure further restricts progress.”

Unless addressed, these challenges pose considerable risk to both individual farm viability and the long-term competitiveness of the Irish dairy industry.

Influencing factors

Across both pasture and confinement-based dairy production systems, the milking process requires the largest annual labour input of any individual farm task (33–75%). Therefore, enhancing milking efficiency creates an opportunity for reducing labour requirements.

Significant knowledge gaps exist around how these factors interact to influence milking efficiency, Ryan notes.

“Providing farmers with clear, evidence-based insights can inform decisions towards optimal parlour configuration, automation investments, and milking management practices.”

Distinct metrics

To gain a clearer picture of current milking efficiency, data were collected from 26 commercial Irish dairy farms, using a multi-faceted approach combining video recordings, infrastructure surveys, and milk yield data. Of the 26 farms, 16 had herringbone parlours and 10 had rotary parlours. (See Figure 1 for details of these respective parlour layouts.)

Statistical analysis was used to assess how infrastructure, automation, and management factors influence performance.

Figure 1. Layout of herringbone and rotary parlours

Differing systems

“Our study found notable differences in the milking efficiency levels between herringbone and rotary parlour systems, and which factors significantly affected milking efficiency,” notes Ryan.

In terms of parlour infrastructure, parlour size strongly influenced outcomes, although the effects differed by system type. Rotary parlours achieved higher milking efficiency, but herringbone parlours achieved greater efficiencies per cluster. Increasing cluster numbers had a greater effect in reducing milking process time for herringbones than in rotaries.

For management practices, the effect of operator numbers on milking efficiency metrics was explored. For both parlour types, two-operator milkings increased cows/h and litres/h, but reduced cow/h per operator. While using a second operator significantly reduced total process time in herringbone systems, it had no comparable effect in rotaries.

In herringbone parlours, greater use of automation strongly correlated with higher milking efficiency. Specifically, automatic cluster removers (ACRs) and rapid exits were found to significantly reduce total process time and row times at milking. For rotary parlours, backing gates – automated barriers for controlling cows’ movement into the milking parlour – did not enhance efficiency, but were seen to remove the operators’ need to fetch cows from the holding yard.

“Judging from this, we hypothesised that backing gates in rotary parlours offer more ergonomic benefits for the operator, rather than process efficiency gains,” Ryan adds.

Developing simulations

Beyond observed data, researchers built simulation models to explore alternative parlour configurations and management strategies. To identify scenarios for optimal efficiency, they developed two simulations: the Rotary Parlour Model (RPM) and the Herringbone Parlour Model (HPM).

RPM simulation results showed that low rotation times (i.e. fast rotation speeds) substantially improved efficiency in larger parlours (>50 clusters) but had little benefit in smaller parlours.

Increasing the ACR flow rate detachment threshold (from 0.2 to 0.8kg/min) reduced the occurrence at milking of ‘go-around’ cows – i.e. cows with a milking time that exceeds the time required for the platform to complete one full rotation, hence additional rotations are required.

This reduced the number of rotations needed at milking, which in turn reduced milking process time and thereby enhanced milking efficiency, Ryan explains. “Further analysis determined that the optimal go-around cow occurrence at milking ranged between 2-20% and was dependent on parlour size, rotation time, ACR threshold used, and herd size at milking.”

Results of the HPM simulations show that the benefits of automation vary with parlour size, Ryan adds. “In smaller herringbones (e.g. 16 clusters), automations such as rapid exit systems or ACRs provided substantial efficiency gains, but these gains decreased as parlour size increased (e.g. 24 clusters).”

Giving farmers control

This research helps give a clearer image of the milking efficiency of Irish dairy farmers operating in a post-quota climate, providing a formal method and comparable metrics for evaluating efficiency.

Specifically, it offers a more quantifiable understanding of how milking efficiency is affected by parlour size, automation specifications, and various milking management practices, concludes Ryan.

“Knowledge generated from our research will allow farmers to take more control of their milking efficiency. It provides them with a formalised method of process evaluation, intuitive benchmarks for comparison, and a verified mechanism for identifying efficiency improvement strategies.”

Milking efficiency is influenced by four main factors:

1) Parlour infrastructure (i.e. parlour type, the number of clusters in the parlour)

2) Automation (i.e. the level of automation in the parlour, automation specification)

3) Management (i.e. work routines employed, the number of operators at milking)

4) Cow-level variables (i.e. milking duration of individual cows, seasonality).

Acknowledgements

The authors would like to express their sincere thanks to all the farmers that participated in this research project.

Contributors

Ryan Prendergast, Research Technician, Teagasc Moorepark.

ryan.prendergast[at]teagasc.ie

John Upton, Principal Research Officer, Teagasc Moorepark.

Michael D. Murphy, Lecturer, Munster Technological University.