Related Experiment Video
Updated: Jul 21, 2026
11:02
The Use of an Automated System (GreenFeed) to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
Distribution fitting and parameterization of individual operator work routine times for small dairy parlors
T F Burks1, L W Turner, W L Crist
1Biosystems and Agricultural Engineering Department, University of Kentucky, Lexington 40546, USA. tfburks@ifas.ufl.edu
Journal of Dairy Science
|May 17, 2006
Summary
This study analyzed milking parlor efficiency on small dairy farms, finding the Pearson #5 and lognormal distributions best model operator work times for improved parlor throughput.
Area of Science:
- Agricultural Engineering
- Operations Research
- Dairy Science
Background:
- Optimizing milking parlor operations is crucial for dairy farm efficiency.
- Small dairy farms (<100 cows) require specific time-motion analyses for workflow improvements.
Purpose of the Study:
- To analyze operator work routine times in small dairy farm milking parlors.
- To identify the best statistical distribution models for predicting operator performance and parlor throughput.
Main Methods:
- Conducted time and motion studies using video analysis on 13 small dairy farms.
- Collected data on 34 operator work routine times within 3-6 stall parlors.
- Utilized UNIFIT software to fit data to gamma, lognormal, Weibull, and Pearson #5 distributions.
Main Results:
- Pearson #5 and lognormal distributions best fitted 12 and 10 work routine times, respectively.
- Common tasks like attaching the milker showed lower variance than complex routines.
- Validated models accurately predicted parlor throughput in small- to medium-sized parlors.
Conclusions:
- Statistical modeling of operator work times can accurately predict milking parlor efficiency.
- Understanding routine variances is key to optimizing workflow in small dairy operations.
- The lognormal distribution effectively models critical tasks like milker attachment.
Related Concept Videos
01:09One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution
The one-compartment open model is a simplified approach used in pharmacokinetics to understand the distribution and elimination of a drug administered through an intravenous bolus. This model assumes rapid drug dispersal throughout the body and elimination using a first-order process. Key pharmacokinetic parameters, such as the elimination rate constant (k), half-life (t1/2), and the apparent volume of distribution (Vd), can be estimated from this model. The elimination rate is calculated from...
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
01:05Noncompartmental Analysis: Mean Residence Time
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
01:15Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations
Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
01:25Determination of Multiple Dosing Parameters: Loading and Maintenance Doses
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
01:25Introduction to Partial Derivatives
In many real-world situations, an output depends on more than one input. In a high-tech assembly plant, total production may depend on technician labor and machine capacity at the same time. This relationship can be represented by a continuous function P(T, M), where T denotes technician labor input, and M denotes machine capacity. When demand increases, but the budget remains fixed, the manager must determine which input will improve production more efficiently.Partial derivatives provide a...