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Quality Assurance

Quality Assurance

Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...

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Methods and Tools for Performance Assurance of Smart Manufacturing Systems.

Deogratias Kibira¹, K C Morris², Senthilkumaran Kumaraguru³

¹Morgan State University, Baltimore, MD 21251.

Journal of Research of the National Institute of Standards and Technology

|August 26, 2021

Summary

This summary is machine-generated.

Smart manufacturing systems leverage real-time data for enhanced efficiency. Performance assurance measures are crucial for these complex systems to ensure reliable operation and decision-making.

Keywords:

agility manufacturing performance challenges manufacturing performance methods performance measurement productivity smart manufacturing sustainability

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Area of Science:

Manufacturing Engineering
Industrial Systems
Data Science

Background:

Smart manufacturing systems integrate new technologies for improved information flow and control.
These systems utilize real-time data to enhance awareness, agility, productivity, and resilience.
Optimizing data collection and analysis for decision-making in smart manufacturing is complex.

Purpose of the Study:

To review current methods and tools for performance assurance in smart manufacturing systems.
To identify key trends in data systems, integration, and performance measurement vital for assured performance.
To propose future research directions for assessing and improving manufacturing performance.

Main Methods:

Literature review of existing performance assurance methods and tools.
Identification and analysis of trends in data and information systems, integration, and performance measurement.
Analysis of how identified trends apply to current methods and proposal of future research.

Main Results:

Current performance assurance activities span design, operation, assessment, evaluation, analysis, decision-making, and control.
Key trends include advancements in data and information systems, system integration, and performance measurement/analysis.
Adaptations to traditional approaches are needed to address the dynamic nature of smart manufacturing.

Conclusions:

Performance assurance is vital for the successful implementation and operation of smart manufacturing systems.
Emerging trends in data management and analysis are critical for maintaining system performance.
Further research is needed to develop robust methods for performance assessment and improvement in uncertain, multi-objective environments.