Statistical process control in dairy management

The main topic of research presented in this thesis is to change the dairy managers' decision making process by introducing the concept of analysis of variation/consistency in performance on a dairy operation by means of Statistical Process Control Charts. In Part 1, three specific objectives were explored: (1) identifying potential associations between dairy management practices and consistency in milk quality, (2) creating a benchmarking tool to help dairy managers interpret the variation of their milk quality characteristics, and (3) evaluating the capability of the measurement system for milk quality characteristics.;Part 2 of the thesis focused on: (1) investigating whether dry matter (DM) or water intake is affected by the presence of disease or estrus in dairy cows and whether water intake can serve as an accurate substitute for monitoring changes in dry matter intake (DMI), (2) developing an SPC monitoring scheme providing methods of analysis and interpretation of milk yield and milk conductivity measurements of individual cows that will allow for early detection of change in cow status. Results presented in this part of the thesis demonstrate that water intake can serve as an alternative to measurements of DMI for groups of cows and has the potential of predicting change in individual cow health and estrus status. Developed CUCUM-Shewhart monitoring schemes based on milk yield and milk electric conductivity issue health alerts earlier relative to the day of disease diagnosis, are more sensitive, and give less false positive alerts than the monitoring scheme currently used.