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Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review
Parkash Tambare1, Chandrashekhar Meshram2, Cheng-Chi Lee3,4
1Water Resources & Applied Mathematics Research Lab, Nagpur 440027, Maharashtra, India.
Sensors (Basel, Switzerland)
|January 11, 2022
Summary
Industry 4.0 utilizes advanced technologies for efficient manufacturing. This study examines how industrial standards are used for performance measurement and quality management in smart manufacturing environments, addressing current knowledge gaps.
Area of Science:
- Manufacturing Engineering
- Industrial Management
- Information Technology
Background:
- The evolution of manufacturing from mass production to digitalization, driven by Information and Communication Technology (ICT).
- The emergence of Industry 4.0, characterized by technologies like IoT, AI, cloud computing, and big data, transforming production processes.
- The challenges in understanding and implementing Industry 4.0 technologies, particularly concerning performance measurement and quality management.
Purpose of the Study:
- To investigate the application of industrial standards in Industry 4.0 for performance measurement and quality management.
- To address the existing uncertainty and knowledge gaps regarding performance measurement and quality control in smart manufacturing.
- To explore the concept of Quality 4.0 as the digitalization of quality management.
Main Methods:
- Review of current methods and industrial standards for performance measurement in data-driven Industry 4.0.
- Analysis of Key Performance Indicators (KPIs) utilized in smart manufacturing environments.
- Inclusion of case studies to illustrate practical applications of Industry 4.0 technologies in manufacturing.
Main Results:
- Identification of various industrial standards and KPIs employed by manufacturing industries for performance and quality assessment.
- Demonstration of how smart manufacturing companies leverage Industry 4.0 technologies through case study analysis.
- Discussion on the digitalization of quality management, termed Quality 4.0.
Conclusions:
- Industrial standards are crucial for measuring performance and managing quality in the context of Industry 4.0.
- Further research is needed to address challenges and explore opportunities in data-driven Industry 4.0 performance and quality management.
- The adoption of Quality 4.0 principles is essential for optimizing smart manufacturing operations.
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