review

The Fourth Industrial Revolution or Industry 4.0 has brought about a significant shift in the way we approach industrial processes. It is all about harnessing the power of big data to make better decisions, leading to higher productivity. This revolution has also given rise to concurrent fields, such as Quality 4.0, Maintenance 4.0, and Pharma 4.0, which are all related to Industry 4.0.

One critical area in need of transformation is the traditional framework of quality assurance in higher education. To address this need, a Quality 4.0 Assurance (Q4A) framework has been developed. A literature review on this topic has been conducted, and the challenges and solutions related to the implementation of Q4A have been discussed.

In today's fast-paced world, manufacturers are looking for innovative ways to improve their product quality and traceability. Integrating Industry 4.0 (I4.0) with Quality 4.0 (Q4.0) is one such approach that can help achieve these goals. A recent study reveals that the use of Cyber-Physical Systems (CPSs), big data analytics, and smart sensors can significantly enhance product quality and traceability.

The study emphasizes the importance of upskilling and reskilling the workforce to adapt to the latest technologies. It also highlights the significance of top management commitment and the establishment of strategic goals, objectives, and indicators, which play a crucial role in the successful implementation of Q4.0. The authors suggest that collecting and analyzing data using smart sensors, RFID, bar codes, and cameras can help identify areas for improvement and make informed decisions.

The Fourth Industrial Revolution, also known as Industry 4.0, is transforming the business world as we know it. With the rapid advancement of technology, organizations must adapt and embrace new technologies to remain competitive. Quality management practices have also evolved over time. Total Quality Management (TQM) has been a popular approach that emphasizes the integration of people and social aspects alongside technical and production-related factors. However, with the advent of Industry 4.0, there is a need for quality practices to adapt and align with modern methodologies. Quality 4.0 is the new era of quality management practices that combines advanced technologies with traditional quality management practices to achieve efficiency, effectiveness, and creativity in business operations.

Quality Management (QM) has come a long way since its inception. Initially, it focused on quality planning, quality assurance, quality control, and continuous improvement. However, with the advent of Industry 4.0 (I4.0)-driven digitalisation, the role of QM professionals has transformed from "supervisor" to "change agent." Digital technologies, such as big data analytics, IoT, cloud-based platforms, and digital dashboards, have significant implications for integrating QM systems with other enterprise-wide systems like ERP.

Artificial intelligence (AI) has been gaining traction in various industries, including manufacturing. The combination of zero-defect manufacturing (ZDM) and AI provides new opportunities for advanced problem-solving and quality management in manufacturing. By using machine learning algorithms, AI can process complex datasets and make optimal decisions in real-time, enabling smart manufacturing.

However, implementing AI in manufacturing is not a straightforward process and requires overcoming several challenges, such as data quality and the lack of a standardized approach to collecting data from production systems. The consequences of false positives and false negatives should also be carefully considered when building an AI solution.

Total Quality Management (TQM) has been a popular approach to management for quite some time now. It aims to achieve excellence in business through quality, increase customer satisfaction, and promote employee involvement through teamwork. With the emergence of the concept of Quality Culture (QC), which highlights the importance of continuous improvement and commitment to quality, TQM has become even more crucial in the organizational culture of industries that have implemented quality management (QM) elements.

However, with the advent of Industry 4.0 (I4.0), a new industrial phase that encourages the application of different technological tools, including cyber-physical systems (CPSs), to collect data in all sectors of the industry, TQM needs to adapt to changes by involving human resources and technologies in the industrial development process based on quality. Quality 4.0 is a branch of I4.0 that aims to boost quality through algorithms and intelligent solutions.

The industrial revolution has come a long way since the first, with the fourth industrial revolution characterized by the digitization and integration of processes, equipment, and people into cyber-physical systems. This has advanced the field of quality management (QM) with the introduction of Quality 4.0 (Q4.0), which enhances human intelligence, decision-making speed and quality, and other aspects of QM. However, QM remains a challenge for many organizations to achieve consumer expectations, and current QMSs do not fit the fourth industrial era.

The Fourth Industrial Revolution has brought about various technological advancements such as digital information, the Internet of Things, data analysis, artificial intelligence, virtual reality, and additive manufacturing. These technologies have had a significant impact on both the manufacturing and service industries, and companies must keep up with them to survive in the digital age. One of the critical challenges that companies face in this era of digital transformation is quality management.