The objective of this thesis was to determine the effect of housing and feeding management and cow characteristics on the behavioral patterns of cows in automated milking systems (AMS). In a first study, increasing frequency of feed delivery from 1 to 2x/d for cows milked in an AMS resulted in longer lying duration. In that study, lame cows milked less frequently, had increased lying durations and more frequent lying bouts. In a second, cross-sectional study of 13 AMS farms it was found that cows had longer lying durations when given more space at the feed bunk and when their feed was pushed up more frequently. Milking frequency increased as cows/AMS decreased. Milk yield increased with space at the feed bunk. Overall, these results suggest that feeding management, robot and bunk-space availability, and health status affect the behavior and production of AMS-milked cows. / Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) and the Canadian Bovine Mastitis Research Network (CBMRN)

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Dairy farming as one part of agriculture has thousands of year’s history. The increasingdemands of dairy products and the rapid development of technology bring dairyfarming tremendous changes. Started by first hand milking, dairy farming goes throughvacuum bucket milking, pipeline milking, and now parlors milking. The automatic andtechnical milking system provided farmer with high-efficiency milking, effective herdmanagement and above all booming income.DeLaval Automatic Milking Rotary (AMRTM) is the world’s leading automatic milkingrotary system. It presents an ultimate combination of technology and machinerywhich brings dairy farming with significant benefits. AMRTM technical milking capacityis 90 cows per hour. However, constrained by farm management, cow’s condition andsystem configuration, the actual capacity is lower than technical value. In this thesis, anoptimization system is designed to analyze and improve AMRTM performance. The researchis focusing on cow behavior and AMRTM robot timeout. Through applying knowledgediscover from database (KDD), building machine learning cow behavior predictionsystem and developing modeling methods for system simulation, the optimizing solutionsare proposed and validated. / Mjölkproduktion är en del av vårt jordbruks tusenåriga historia. Med ökande krav påmejeriprodukter tillsammans med den snabba utvecklingen utav tekniken för det enormaförändringar i mjölkproduktionen. Mjölkproduktion började inledningsvis med handmjölkningsedan har mjölkproduktionsmetoder utvecklats genom olika tekniker och gettoss t.ex. vakuum mjölkning, rörledning mjölkning, fram till dagens mjölkningskarusell.Nu har det automatiska och tekniska mjölkningssystem försedd bönder med högeffektivmjölkning, effektiv djurhållningen och framför allt blomstrande inkomster.DeLaval Automatic Milking Rotary (AMRTM) är världens ledande automatiska roterandemjölkningssystemet. Den presenterar en ultimat kombination av teknik och maskinersom ger mjölkproduktionen betydande fördelar. DeLaval Automatic Milking Rotarytekniska mjölknings kapacitet är 90 kor per timme. Den begränsas utav jordbruksdrift,tillståndet hos kor och hantering av systemet. Det gör att den faktiska kapaciteten blirlägre än den tekniska. I denna avhandling undersöks hur ett optimeringssystem kan analyseraoch förbättra DeLaval Automatic Milking Rotary prestanda genom fokusering påkors beteenden och robot timeout. Genom att tillämpa kunskap från databas (KDD), skapamaskininlärande system som förutsäger kors beteenden samt utveckla modelleringsmetoderför systemsimulering, ges lösningsförslag av optimering samt validering.