The design of robotic dairy barns using closed queueing networks

Halachmi, I.; Adan, Ijbf Ivo; Wal, van der J Jan; Heesterbeek, J.A.P.; Beek, van P

doi:10.1016/s0377-2217(99)00312-4

Cited by 24 publications

(13 citation statements)

References 7 publications

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“…The farm design and its effect on cow performance were described previously (farm E; Halachmi 2004). The study was conducted in the first open cowshed (not a free-stall or cubicle system) reported in the scientific literature to be originally designed for AMS (Halachmi, 1999(Halachmi, , 2000(Halachmi, , 2004Halachmi et al, 2000aHalachmi et al, , 2001Halachmi et al, , 2002, and operated in a hot climate with high-yielding cows. The farm was designed to enable cows to move freely between the BM feeding lane and resting areas.…”

Section: Managementmentioning

confidence: 99%

“…However, they are motivated to visit the robot as the only way of accessing the pellets, either in the robot or in the CSF, because CSF was accessible only after cows passed through the robot, which provided an additional incentive to pass the milking stall. Halachmi et al (1998Halachmi et al ( , 2000a coined this situation as "semi-free cow-traffic". The cowshed was designed to hold 65 to 75 cows in milking with about 20 m 2 /cow, and was equipped with a cow cooling system near the robot and the CSF.…”

Section: Managementmentioning

confidence: 99%

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Feeding of Pellets Rich in Digestible Neutral Detergent Fiber to Lactating Cows in an Automatic Milking System

Halachmi

Shoshani

Solomon

et al. 2006

Journal of Dairy Science

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If the milking frequency in an automatic milking system (AMS) is increased, the intake of concentrated pellets in the robot may be raised accordingly. Consumption of a large quantity of starchy grains within a short time can impair the appetite, decrease voluntary visits to the milking stall, and lower intakes of dry matter (DM) and neutral detergent fiber (NDF). Therefore, the hypothesis to be tested in this study was whether conventional starchy pellets fed in the AMS could be replaced with pellets rich in digestible NDF without impairing the cows' motivation to visit a milking stall voluntarily. Fifty-four cows were paired according to age, milk yield, and days in milk, and were fed a basic mixture along the feeding lane (19.9 kg of DM/cow per d), plus a pelleted additive (approximately 5.4 kg of DM/cow per d) that they obtained in the milking stall and in the concentrate self-feeder that they could enter only after passing through the milking stall. The 2 feeding regimens differed only in the composition of the pelleted additive, which, for the control group, contained 49% starchy grain, and for the experimental group contained 25% starchy grain plus soy hulls and gluten feed as replacement for part of the grain and other low-digestible, NDF-rich feeds. Both diets resulted in similar rates of voluntary milkings (3.31 vs. 3.39 visits/cow per d). Average yields of milk and percentages of milk protein were also similar in the 2 groups. The results suggest that an alternative pellet composition can be allocated in the AMS in conjunction with basic mixture in the feeding lane, without any negative effect on appetite, milk yield, milk composition, or milking frequency of the cows. It also opens the opportunity to increase yields of milk and milk solids by increasing the amount of pelleted concentrates that can be allocated to selected high-yielding cows via the AMS, because this can be done while maintaining a high frequency of voluntary milkings.

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Section: Managementmentioning

confidence: 99%

Section: Managementmentioning

confidence: 99%

Feeding of Pellets Rich in Digestible Neutral Detergent Fiber to Lactating Cows in an Automatic Milking System

Halachmi

Shoshani

Solomon

et al. 2006

Journal of Dairy Science

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“…In contrast to conventional milking parlours, a milking robot allows the cows more freedom to control their daily activities and rhythms (Halachmi et al, 2000a and2000b;Halachmi, 2004;Jacobs and Siegford, 2012). The cows on a farm with milking robots are typically calmer and more 'independent' -that is, herd synchronization with respect to lying, feeding and milking is reduced (Winter and Hillerton, 1995;Ketelaar de Lauwere et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, BW and voluntary visits to the milking robot

Steensels

Antler

Bahr

et al. 2016

animal

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Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows' routine. The objectives of this study were to develop and apply a behaviour-and performance-based health-detection model to post-calving cows in a roboticmilking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination-and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian's diagnosis served as a binary reference for the model (healthy-sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.

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“…In a case study conducted by Halachimi, Adan, Wal, Heesterbeek, and Beek (2000), a robotic milking barn was designed by using closed queuing networks. Their technique uses an approximate mean value algorithm (AMVA) to evaluate important performance criteria such as the number of cows waiting to be milked, their waiting time and the utilization of the facilities.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance analysis in a probabilistic re-entrant for an environmental stress testing operation

Omar

Kumar

2008

Computers & Industrial Engineering

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The design of robotic dairy barns using closed queueing networks

Cited by 24 publications

References 7 publications

Feeding of Pellets Rich in Digestible Neutral Detergent Fiber to Lactating Cows in an Automatic Milking System

Feeding of Pellets Rich in Digestible Neutral Detergent Fiber to Lactating Cows in an Automatic Milking System

A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, BW and voluntary visits to the milking robot

Performance analysis in a probabilistic re-entrant for an environmental stress testing operation

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