The first industrial revolution (IR) occurred in the 18th century with the invention of steam power, which replaced muscle power in the manufacturing industry. This invention led to a significant increase in production and had far-reaching socio-economic implications. The second IR, which took place in the 19th century, was characterized by the invention of electricity, the introduction of assembly lines, and the growth of the steel industry. These advancements also had a significant impact on manufacturing activities, resulting in increased output and lower costs. The third IR, which occurred in the 20th century, introduced electronics and information technology (IT), leading to increased automation. And now, we are in the midst of the fourth industrial revolution, which is being guided by cyber-physical systems (CPSs) that integrate the physical world with the advanced information era for further industrial advancement.
With each industrial revolution, there have been strategic variations in productivity and quality. Quality itself has undergone several revolutions as industrial evolution has taken place. During the first industrial revolution, quality went through what is known as Quality 1.0, which was characterized by quality control (QC) and measurement. This was followed by Quality 2.0 during the second industrial revolution, which involved quality assurance (QA). In the third industrial revolution, Quality 3.0 emerged, which focused on quality management as a strategic approach. And now, during the fourth industrial revolution, we have Quality 4.0, which is characterized by digitalization and the integration of CPS.
However, each of these quality approaches faced challenges along the way. For example, the inspection and QC approaches had issues with the costs associated with reworks of defects and the expenses of hiring inspectors. The introduction of QA helped overcome some of these challenges but did not provide a holistic view of the organization. This led to the adoption of a new approach called total quality management (TQM), which integrated the entire organization and emphasized principles such as leadership, continuous improvement, customer focus, and employee participation.
While TQM has been effective in improving quality management, it also has its drawbacks. TQM relies heavily on audits as a continuous improvement monitoring system, which can be time-consuming and cause delays in quality management. This has prompted researchers and practitioners to explore new approaches based on market demand and available technologies, leading to the emergence of Quality 4.0.
Quality 4.0 is an emerging quality approach that is aligned with the fourth industrial revolution. It leverages technologies such as big data, the internet of things (IoT), artificial intelligence (AI), and blockchain to enhance quality management in manufacturing industries. However, there is still a lack of clarity and comprehensive understanding of what exactly Quality 4.0 entails.
To address this gap, researchers have conducted a bibliometric and scientometric analysis of the theoretical underpinnings of Quality 4.0 in manufacturing industries. They have explored the definitions, models, technologies, readiness factors, and motivations for adopting Quality 4.0. This study aims to provide answers to key research questions such as the universal definition of Quality 4.0, the enablers and motivations for its adoption, and how technologies can be leveraged for Quality 4.0 in the manufacturing industry.
The study found that there is no universal definition of Quality 4.0, but it is generally understood as a modern approach to quality management that involves digitalization and integration of processes, technologies, and people. The readiness factors for adopting Quality 4.0 include vision and strategy, collaboration, leadership support, cultural change, and knowledge and training. The motivations for adopting Quality 4.0 include improved customer satisfaction, increased efficiency, and the ability to leverage technologies such as big data and AI.
Technologies such as big data analytics, IoT, augmented reality, autonomous robots, blockchain, and AI are identified as key enablers for Quality 4.0 in manufacturing industries. These technologies offer benefits such as real-time data collection, remote monitoring, improved decision-making, and increased efficiency. However, there are still challenges and limitations to implementing Quality 4.0, such as the management of large volumes of data, the integration of operational and information technologies, and the need for skilled and competent workers.
In conclusion, Quality 4.0 is an emerging quality management concept aligned with the fourth industrial revolution. It leverages technologies to enhance quality management in manufacturing industries. However, there is still a need for further research and development to fully understand and implement Quality 4.0.
Reference
Maganga D.P.; Taifa I.W.R. (2023). Quality 4.0 conceptualisation: an emerging quality management concept for manufacturing industries. TQM Journal, 35(2), 389-413, DOI: 10.1108/TQM-11-2021-0328.