Prediction of Milking Robot Utilization

For the planning of the barn layout, cow traffic and facility locations (such as: cubicles, forage lane, etc.), the farmer has to know the milking robot utilization of his production herd. Therefore, prediction of the milking robot utilization has to be done. The milking robot utilization depends on the cow´s visiting pattern and capacity of the milking robot. The models used for prediction were generalized multiple regression models. Behavioural data were obtained by video observations and electronic measurements. For eleven behavioural variables used in the model from all three experiments, only two (number of cows and sum of milk yields per hour in kilograms) were statistically significant (p ≤ 0.05) and measurable on a commercial farm. A part from the milking capacity, forage feeding routine influenced utilization of the robot. Combined cow traffic used in experiments appeared to be feasible.Izgled staje, kretanje krava, te raspored pojedinih dijelova staje (npr. ležišta, "krmna zabrana"...) ovisi o stupnju iskorištenja robota za strojnu mužnju u postojećem stadu krava. Zbog toga je važno predvidjeti stupanj iskorištenja robota za strojnu mu.nju. On ovisi o redoslijedu posjeta krava robotu i kapacitetu robota za strojnu mužnju. Statistički modeli korišteni za predviđanje su općeniti modeli multiple regresije. Opisni podaci o kravama su prikupljeni pomoću video opreme i elektronskih mjerenja. Od jedanaest varijabli korištenih u statistikom modelu od tri eksperimenta, samo dvije (broj krava i ukupna količina izmuzenog mlijeka (kg/h)) su bile statistički signifikantne (p ≤0.05) i mjerljive na komercijalnoj farmi. Osim kapaciteta strojne mu.nje na stupanj iskorištenja robota za strojnu mužnju utjecao je i vremenski raspored hranjenja na "krmnoj zabrani". Kombinirani način kretanja krava u staji se pokazao izvediv

Prediction of Milking Robot Utilization

For the planning of the barn layout, cow traffic and facility locations (such as: cubicles, forage lane, etc.), the farmer has to know the milking robot utilization of his production herd. Therefore, prediction of the milking robot utilization has to be done. The milking robot utilization depends on the cow´s visiting pattern and capacity of the milking robot. The models used for prediction were generalized multiple regression models. Behavioural data were obtained by video observations and electronic measurements. For eleven behavioural variables used in the model from all three experiments, only two (number of cows and sum of milk yields per hour in kilograms) were statistically significant (p ≤ 0.05) and measurable on a commercial farm. A part from the milking capacity, forage feeding routine influenced utilization of the robot. Combined cow traffic used in experiments appeared to be feasible.Izgled staje, kretanje krava, te raspored pojedinih dijelova staje (npr. ležišta, "krmna zabrana"...) ovisi o stupnju iskorištenja robota za strojnu mužnju u postojećem stadu krava. Zbog toga je važno predvidjeti stupanj iskorištenja robota za strojnu mu.nju. On ovisi o redoslijedu posjeta krava robotu i kapacitetu robota za strojnu mužnju. Statistički modeli korišteni za predviđanje su općeniti modeli multiple regresije. Opisni podaci o kravama su prikupljeni pomoću video opreme i elektronskih mjerenja. Od jedanaest varijabli korištenih u statistikom modelu od tri eksperimenta, samo dvije (broj krava i ukupna količina izmuzenog mlijeka (kg/h)) su bile statistički signifikantne (p ≤0.05) i mjerljive na komercijalnoj farmi. Osim kapaciteta strojne mu.nje na stupanj iskorištenja robota za strojnu mužnju utjecao je i vremenski raspored hranjenja na "krmnoj zabrani". Kombinirani način kretanja krava u staji se pokazao izvediv

Robotic Milking and heat stress

The objectives of the workshop are to share our knowledge, to develop a research framework for future co-operative research between Israel and the Netherlands, and to explore the possibilities for funding of this research. As a starting point, a seminar is held in which available knowledge on robotic milking and on heat stress is shared and discussed. This proceedings gives a view of the knowledge presented during this one-day seminar

Ground and Aerial Robots for Agricultural Production: Opportunities and Challenges

Crop and animal production techniques have changed significantly over the last century. In the early 1900s, animal power was replaced by tractor power that resulted in tremendous improvements in field productivity, which subsequently laid foundation for mechanized agriculture. While precision agriculture has enabled site-specific management of crop inputs for improved yields and quality, precision livestock farming has boosted efficiencies in animal and dairy industries. By 2020, highly automated systems are employed in crop and animal agriculture to increase input efficiency and agricultural output with reduced adverse impact on the environment. Ground and aerial robots combined with artificial intelligence (AI) techniques have potential to tackle the rising food, fiber, and fuel demands of the rapidly growing population that is slated to be around 10 billion by the year 2050. This Issue Paper presents opportunities provided by ground and aerial robots for improved crop and animal production, and the challenges that could potentially limit their progress and adoption. A summary of enabling factors that could drive the deployment and adoption of robots in agriculture is also presented along with some insights into the training needs of the workforce who will be involved in the next-generation agriculture

3D numerical modelling of temperature and humidity index distribution in livestock structures: a cattle-barn case study

In dairy cattle farming, heat stress largely impairs production, health, and animal welfare. This study aims to develop a workflow and a numerical analysis procedure to provide a real-time 3D distribution of the temperature and humidity index (THI) in a generic cattle barn based on temperature and humidity monitored in sample points, besides characterising the relationship between indoor THI and outside weather conditions. This research was carried out with reference to the study case of a cattle barn. A model has been developed to define the indoor three-dimensional spatial distribution of the Temperature-Humidity Index of a cattle barn based on environmental measurements at different heights of the building. As a core of the model, the Discrete Sibson Interpolation method was used to render a point cloud representing the THI values in the non-sampled areas. The area between 1-2 meters was emphasised as the region of most significant interest to quantify the heat waves perceived by dairy cows. The model represents an effective tool to distinguish different areas of the animal-occupied zone characterised by different values of THI

Ethical Issues in Engineering Models: Personal Reflections

I start this contribution with an overview of my personal involvement—as an Operations Research consultant—in several engineering case-studies that may raise ethical questions; these case studies employ simulation models. Next, I present an overview of the recent literature on ethical issues in modeling, focusing on the validation of the model’s assumptions; the decisive role of these assumptions leads to the quest for robust models. Actually, models are meant to solve practical problems; these problems may have ethical implications for the various stakeholders; namely, modelers, clients, and the public at large. Finally, I briefly discuss whistle blowing.ethics;code of conduct;stakeholders;validity;risk analysis;simulation;operations research