The effects of seasonality, management, infrastructure, and automation on the milking efficiency of herringbone and rotary milking parlors in Ireland.

The objective of this study was to document the milking efficiency of a sample of Irish dairy farms and to understand the effects of (1) seasonality, (2) management practices, (3) parlor infrastructure, and (4) parlor automations on milking efficiency metrics. A novel methodology based on empirical data from video cameras, infrastructure surveys, and milk yield data allowed for the accurate computation of milking efficiency metrics and quantification of the effects of seasonality, number of operators, and parlor automations on milking efficiency across 2 parlor types. The data for this study were collected over 2 periods: period 1 (July 28, 2020, to October 23, 2020, peak-late production) and period 2 (April 12, 2021, to May 19, 2021, early-peak production) from a sample of 16 herringbone and 10 rotary commercial Irish dairy farms. Milking efficiency was evaluated on each farm using 3 key performance indicators: (1) cows milked per hour (cows/h), (2) cows milked per operator per hour (cows/h per operator), and (3) liters of milk harvested per hour (L/h). Milking efficiency key performance indicators were calculated using "total process time," defined as the time between the first cow entering the holding yard and the end of the cleaning process. Average herd sizes for herringbone and rotary farms were 180 and 425 cows, respectively. Average system sizes for herringbone and rotary farms were 20 and 50 clusters, respectively. For herringbone farms, the average milking efficiency was 94 cows/h, 73 cows/h per operator, and 1,012 L/h, whereas rotary farms achieved an average milking efficiency of 170 cows/h, 132 cows/h per operator, and 1,534 L/h. Parlor size was strongly correlated with milking efficiency (cows/h) for herringbone parlors (0.91) but was only moderately correlated for rotary parlors (0.50). Hence, we documented the effect of parlor size on milking efficiency is relative to parlor type. Cluster utilization values on herringbone farms were 5 cows/cluster per h, 4 cows/cluster per operator per h, and 51 L/cluster per h, which were 67%, 33%, and 65% greater than rotary farms, respectively. We found for both herringbone and rotary farms hourly cow throughput (cows/h, cows/h per operator) were greatest during period 1 and that the volume of milk harvested per hour (L/h) was greatest for period 2. Thus, we documented an inverse seasonal relationship between hourly rates of cows milked and milk harvested. We observed that for herringbone farms, milking efficiency (cows/h, L/h) had a strong positive correlation (0.75, 0.74) with the levels of automation use. However, the minimal variation in automations used among rotary farms made it difficult to evaluate their effect on milking efficiency. Similarly, we found that the effect of automations on milking efficiency was dependent on parlor type. On average, a second operator at milking for both herringbone (H) and rotary (R) farms increased values for cows/h (+19%, H; +34%, R) and L/h (+21%, H; +12%, R) but lowered values for cows/h per operator (-35%, H; -12%, R). The holistic methodology applied in this study allowed us to add novel data to the literature by quantifying the effects of seasonality, the number of operators present at milking, and parlor automation use on milking efficiency across 2 parlor types.

Identifying strategies to enhance the milking and operator efficiency of herringbone and rotary parlor systems in Ireland.

International trends of increasing dairy herd sizes coupled with scarcity of labor has necessitated the enhancement of labor efficiency for dairy production systems. This study quantified the effects of infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors used on pasture-based farms in Ireland. Data from 592 milkings across 26 farms (16 herringbones and 10 rotaries) was used. The metrics of cows milked per hour (cows/h), cows milked per operator per hour (cows/h per operator) and liters of milk harvested per hour (L/h) described milking efficiency. The metrics of total process time per cow (TPT, s/cow), milk process time per cow (MPT, s/cow), work routine time (WRT, s/cow), cluster time (CT, s/cluster), and attachment time per cow (ATC, s/cow) described operator efficiency. Automations investigated were backing gates, cluster flush, plant wash, cluster removers (ACRs), feeders, entry gates, rapid-exit, and teat spray. Additional operator presence at milking was also investigated. Herringbone and rotary parlors were assigned to quartiles from their cows/h per operator values to examine infrastructure, automations, and management practices variations. Fourth quartile herringbones based on cows/h per operator values (Q4) averaged 93 cows/h per operator using average system sizes of 24 clusters with 5 parlor automations. Q4 rotaries averaged 164 cows/h per operator using average system sizes of 47 clusters and an average CT of 13 s/cluster. Cows/h per operator values for Q4 herringbone and rotary parlors were 82% and 54% higher, respectively, than values observed on Q1 parlors, indicating the considerable potential to improve efficiency. To determine if infrastructure, automations, or additional operators at milking significantly affected operator efficiencies, general linear mixed models were developed. For parlor infrastructure, additional clusters had greater significance on operator efficiencies (MPT) for herringbones (-1.3 s/cow) as opposed to rotaries (-0.2 s/cow). Hence, increases in system size was likely to result in improved efficiencies for herringbones but less so for rotaries. For automations, ACRs significantly reduced herringbone TPT, CT, and WRT values by 13.3 s/cow, 18.9 s/cluster, and 32.6 s/cow, respectively, whereas rapid-exit significantly lowered CT by 18.6 s/cluster. We found no significant effect on rotary TPT, MPT, CT, or WRT values from the use of automatic teat sprayers. An additional operator at milking was found to significantly reduce herringbone TPT but not MPT or CT. For rotaries, a second operator had no significant effect on TPT, MPT, CT, or WRT values. We documented strong negative correlations between operator efficiencies (TPT, MPT) and milking efficiency (cows/h) for both herringbone (-0.91, -0.84) and rotaries (-0.98, -0.89). Strong negative correlations between the herringbone automation count and TPT (-0.80), MPT (-0.72), and CT (-0.75) suggested highly automated parlors were likely to achieve greater operator efficiencies than less automated parlors. The strong negative correlation (-0.81) between rotary milking efficiency (cows/h) and CT suggested lower CT values (i.e., rotation speed) resulted in increased milking efficiency. In conclusion, our study quantified the effects of parlor infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors.