Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Methods of Medium Optimization

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

Bioreactor Controls-III

Bioreactor Controls-III

Strain improvement is a foundational strategy in industrial microbiology aimed at maximizing microbial productivity, particularly because natural isolates typically yield commercially valuable products in very low concentrations. Although optimizing the culture medium and environmental conditions can improve yields, these adjustments are inherently limited by the organism’s genetic potential. As a result, the focus shifts toward genetic modifications to enhance biosynthetic capacity. The...

Designing Growth Media for Bioreactors

Designing Growth Media for Bioreactors

Growth media provide essential nutrients that support cell growth and metabolism, thereby enhancing the yield of valuable products such as enzymes, antibiotics, and biomass. Designing an effective growth medium involves balancing all components to prevent nutrient limitations or toxic excesses, both of which can impair growth and reduce product yields.Composition of a Typical Growth MediumA typical growth medium contains carbon and nitrogen sources, salts, vitamins, trace elements, and...

You might also read

Related Articles

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

Sort by

Same author

Pressure Injury Risk Assessment in Nursing Practice: A Head-to-Head Comparison of the Braden Scale and Machine Learning Models.

Journal of clinical medicine·2026

Same author

Hybrid Nature-Inspired Optimization for the Cell Formation Problem with Machine Reliability and Alternative Routings.

Biomimetics (Basel, Switzerland)·2026

Same author

Evaluating Bio-Inspired Metaheuristics for Dynamic Surgical Scheduling: A Resilient Three-Stage Flow Shop Model Under Stochastic Emergency Arrivals.

Biomimetics (Basel, Switzerland)·2026

Same author

Bioinspired Optimization for Feature Selection in Post-Compliance Risk Prediction.

Biomimetics (Basel, Switzerland)·2026

Same author

A Novel Binary Dream Optimization Algorithm with Data-Driven Repair for the Set Covering Problem.

Biomimetics (Basel, Switzerland)·2026

Same author

Bioinspired Deep Neural Networks for Predicting Income-Reporting Discontinuities in the Chilean Student Loan Program.

Biomimetics (Basel, Switzerland)·2026

Same journal

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026

Same journal

Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks.

Biomimetics (Basel, Switzerland)·2026

Same journal

A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.

Biomimetics (Basel, Switzerland)·2026

Same journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026

Same journal

Empirical Logic for Bio-Inspired Soft Computing: Illustrative Applications in Control Engineering and Cluster Analysis.

Biomimetics (Basel, Switzerland)·2026

Same journal

A Modified Multi-Strategy Dhole Optimization Algorithm and Its Engineering Applications.

Biomimetics (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 28, 2026

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

Enhancing Manufacturing Cell Formation Through Availability-Based Optimization Using the Black Widow Optimizer

Paulo Figueroa-Torrez¹, Orlando Duran², Broderick Crawford³

¹Departamento de Ciencias Industriales, Medio Ambiente y Energía, Universidad Católica Boliviana "San Pablo", Colón 734, Tarija, Bolivia.

Biomimetics (Basel, Switzerland)

|May 26, 2026

Summary

This summary is machine-generated.

This study introduces a manufacturing cell design model that incorporates machine availability, reliability, and repair times. The Black Widow Optimizer efficiently solves this complex problem, ensuring cost-effective and robust production layouts.

Keywords:

Black Widow Optimizer alternative routes machine availability manufacturing cell formation metaheuristics multi-period optimization

More Related Videos

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Published on: December 15, 2017

Related Experiment Videos

Last Updated: May 28, 2026

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Published on: December 15, 2017

Area of Science:

Operations Research
Manufacturing Systems Engineering
Industrial Engineering

Background:

Traditional cell formation problems often overlook machine reliability and repair dynamics.
Equipment availability significantly impacts production efficiency and cost.
Dynamic changes in manufacturing systems over time require advanced modeling approaches.

Purpose of the Study:

To develop a multi-period Generalized Cell Formation Problem with Machine Availability (GCFP-MA) model.
To integrate equipment reliability (Mean Time Between Failures - MTBF, Mean Time to Repair - MTTR) and temporal degradation into cell design.
To optimize manufacturing cell configurations considering dynamic system behavior and downtime costs.

Main Methods:

Formulation of the GCFP-MA incorporating availability-based constraints and downtime penalties.
Utilization of Markov-Chain models to represent machine availability states.
Implementation and validation of the Black Widow Optimizer (BWO) metaheuristic for solving the NP-hard optimization problem.

Main Results:

The Black Widow Optimizer (BWO) effectively finds the global optimum for the GCFP-MA.
BWO demonstrates significantly reduced computational effort compared to exhaustive search benchmarks.
The model prevents infeasible or over-optimistic cell designs by considering availability and repair dynamics.

Conclusions:

Integrating machine availability and repair dynamics leads to more cost-effective and robust manufacturing cell layouts.
The proposed unified framework enhances production system design by incorporating availability engineering principles.
The BWO metaheuristic offers an efficient solution for complex cell formation problems with dynamic machine availability.