Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

14
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...
14
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

116
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
116
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

191
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
191
Multimachine Stability01:25

Multimachine Stability

247
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
247
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

14
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...
14
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

813
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
813

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Ultrasound-guided acupotomy release combined with <i>Tongdu Tiaoshen</i> acupuncture for post-stroke talipes varus: a randomized controlled trial].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion·2026
Same author

Real-Time Monitoring of Lipolysis Based on Polystyrene Inverse Opal Layer by Optical Interferometry.

Analytical chemistry·2026
Same author

Beyond Cash: Associations Between Social Security Benefits, Healthcare Accessibility, and Psychological Health Among Older Adults in Tanzania.

Journal of aging and health·2026
Same author

Microglia-Dependent BDNF Signaling in the Dentate Gyrus Underlies the Antidepressant Effects of Gardiquimod, a Toll-Like Receptor 7 Agonist, in Chronically Stressed Mice.

Neurochemical research·2026
Same author

Moderating Role of Job Satisfaction on Organizational Climate and Professional Identity in Nurses: A Multicenter Cross-Sectional Study.

Journal of nursing management·2026
Same author

Food-grade TiO<sub>2</sub> impairs intestinal mucus barrier via disrupting the gut microbiota-ILA-mucin sulfation axis: novel insights and dietary intervention strategies.

Journal of nanobiotechnology·2026

Related Experiment Video

Updated: Oct 8, 2025

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.2K

The Demand Supply Steady-State Process-Based Multi-Level Spare Parts Optimization.

Jiaju Wu1,2, Huijun Liu2, Hongfu Zuo1

  • 1College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Sensors (Basel, Switzerland)
|December 28, 2021
PubMed
Summary

This study introduces a new analytical model for optimizing spare parts inventory, outperforming the VARI-METRIC model in low equipment availability scenarios. The new model improves prediction accuracy and cost-effectiveness for essential equipment support.

Keywords:
demand ratemulti-leveloptimization processspare partsspare parts support processsupply ratesystem availability

More Related Videos

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K
A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars
05:32

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars

Published on: August 4, 2018

12.8K

Related Experiment Videos

Last Updated: Oct 8, 2025

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.2K
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K
A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars
05:32

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars

Published on: August 4, 2018

12.8K

Area of Science:

  • Operations Research
  • Supply Chain Management
  • Engineering Management

Background:

  • Effective spare parts management is crucial for equipment availability and cost-efficiency.
  • Increasing equipment complexity and costs strain traditional inventory models.
  • Existing models like VARI-METRIC struggle with accuracy in low equipment availability scenarios.

Purpose of the Study:

  • To develop and validate an analytical model for multi-level spare parts optimization.
  • To address the limitations of the VARI-METRIC model in low equipment system availability.
  • To improve inventory prediction accuracy and cost-effectiveness in critical support systems.

Main Methods:

  • Developed a multi-level spare parts optimization model based on steady-state demand-supply processes.
  • Deduced methods for calculating demand rate, demand-supply rate, and system availability.
  • Employed marginal analysis for inventory allocation and cost-benefit evaluation.
  • Validated the model using a simulation approach.

Main Results:

  • The proposed analytical model demonstrated significantly higher inventory prediction accuracy compared to VARI-METRIC under low equipment availability (e.g., 0.4, 0.6 availability).
  • Achieved relative errors of 3.54% and 3.86% for specific low availability scenarios.
  • Identified cost savings and optimal inventory allocation strategies.

Conclusions:

  • The new analytical model offers superior performance for spare parts management in low equipment availability settings.
  • The findings provide a more accurate and cost-effective approach to inventory prediction for critical systems.
  • Future research should explore dynamic conditions and advanced optimization techniques.