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

Lifecycle of Erythrocytes01:22

Lifecycle of Erythrocytes

5.3K
Erythrocytes, also known as red blood cells, constantly move through blood capillaries. As a result, they damage their plasma membrane due to the continuous friction. Typically, after 100 to 120 days, erythrocytes become rigid and fragile as they wear out. As they pass through small vessels in the spleen and liver, they can get trapped and break apart into fragments.
The resident phagocytic macrophages deal with these damaged cells by engulfing them and separating their globin and heme groups....
5.3K
Decision Making01:20

Decision Making

995
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
995
Steel Manufacturing01:26

Steel Manufacturing

1.5K
Steel manufacturing is a multi-stage process that begins by smelting iron ore into cast iron in a blast furnace. This initial stage involves layering iron ore with coke, a type of fuel, and crushed limestone within the furnace. The coke is ignited with a high volume of air, leading to the creation of carbon monoxide, which acts to reduce the iron ore to pure iron.
During this smelting process, limestone plays a crucial role by forming slag. Slag captures impurities within the molten iron, such...
1.5K
Decision Making: P-value Method01:09

Decision Making: P-value Method

7.0K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
7.0K
Manufacture of Concrete Masonry Units01:27

Manufacture of Concrete Masonry Units

410
The process of manufacturing concrete masonry units begins by mixing stiff concrete composed of Portland cement, aggregates, and water. This mixture is then poured into metal molds. To ensure the concrete settles uniformly and to avoid separation of its components, the mixture in the molds is subjected to vibration. Shortly after, the still-wet blocks are removed from the molds and placed on racks.
These wet blocks are then transported for curing, which can occur in one of two environments: a...
410
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

5.5K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
5.5K

You might also read

Related Articles

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

Sort by
Same author

Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs.

Advanced engineering informatics·2026
Same author

Scalable Data Pipeline Architecture to Support the Industrial Internet of Things.

CIRP annals ... manufacturing technology·2026
Same author

Understanding sustainability data through unit manufacturing process representations: a case study on stone production.

Procedia CIRP·2024
Same author

Industry Review of Distributed Production in Discrete Manufacturing.

Journal of manufacturing science and engineering·2024
Same author

Big data analytics for smart factories of the future.

CIRP annals ... manufacturing technology·2024
Same author

The State of Integrated CAM/CNC Control Systems: Prior Developments and the Path Towards a Smarter CNC.

Smart and sustainable manufacturing systems·2024
See all related articles

Related Experiment Video

Updated: Feb 8, 2026

Microscopy of Fission Yeast Sexual Lifecycle
07:47

Microscopy of Fission Yeast Sexual Lifecycle

Published on: March 9, 2016

15.2K

Contextualising manufacturing data for lifecycle decision-making.

William Z Bernstein1, Thomas D Hedberg1, Moneer Helu1

  • 1Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.

International Journal of Product Lifecycle Management
|June 19, 2018
PubMed
Summary
This summary is machine-generated.

Integrating manufacturing data across the product lifecycle is crucial for system understanding and traceability. This study maps standard data representations to bridge information silos, enabling better decision-making.

Keywords:
digital threadknowledge managementlifecycle decision-makingmanufacturing dataproduct lifecycle managementsmart manufacturing

More Related Videos

Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot
07:40

Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot

Published on: June 10, 2020

16.0K
A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.3K

Related Experiment Videos

Last Updated: Feb 8, 2026

Microscopy of Fission Yeast Sexual Lifecycle
07:47

Microscopy of Fission Yeast Sexual Lifecycle

Published on: March 9, 2016

15.2K
Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot
07:40

Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot

Published on: June 10, 2020

16.0K
A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.3K

Area of Science:

  • Manufacturing Systems Engineering
  • Data Integration
  • Product Lifecycle Management

Background:

  • Capturing and contextualizing manufacturing data across the product lifecycle is essential for system analysis and traceability.
  • Challenges persist in integrating disparate information and facilitating efficient decision-making.
  • Standardized data representations offer a pathway to overcome these integration hurdles.

Purpose of the Study:

  • To explore mapping standard data representations (STEP, MTConnect, QIF) for integrating manufacturing information silos.
  • To demonstrate a reference implementation within the NIST Smart Manufacturing Systems Test Bed.
  • To investigate how manufacturing knowledge can support product lifecycle decision-making.

Main Methods:

  • Mapping standard data representations: Standard for the Exchange of Product Data (STEP), MTConnect, and Quality Information Framework (QIF).
  • Developing a reference implementation in the National Institute of Standards and Technology (NIST) Smart Manufacturing Systems Test Bed.
  • Creating an interactive prototype for correlating test bed data based on decision-making context.

Main Results:

  • Demonstrated the feasibility of mapping standard data representations to integrate information across the product lifecycle.
  • Successfully implemented a reference system within the NIST Smart Manufacturing Systems Test Bed.
  • Developed a prototype showcasing how contextualized manufacturing data supports lifecycle decision-making.

Conclusions:

  • Mapping standard data representations is a viable strategy for integrating information silos in smart manufacturing.
  • A contextualized approach to manufacturing data enhances its utility for lifecycle decision-making.
  • The NIST Smart Manufacturing Systems Test Bed provides a platform for validating these integration strategies.