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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.
Summary
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.
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.
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