Welcome to the era of Industry 4.0. The world is currently undergoing a technological disruption that is changing the way we live and work. Cars can now drive themselves, robots are working in factories and restaurants, data is stored in the cloud, and gadgets are interconnected and communicate with each other. Machines are even learning on their own and exhibiting intelligence that was once thought to be unique to humans. This revolution, coined as Industry 4.0, is the fourth industrial revolution and is characterized by the integration of digital technologies into industries and everyday life.
The term Industry 4.0 was first used by Klaus Schwab, the founder and executive chairman of the World Economic Forum, to describe a world in which individuals rely on connected technology to manage their lives and move between digital domains and offline realities. The concept of Industry 4.0 was introduced at the Hanover Trade Fair in 2011, where representatives from business, policy, and science came together to promote Germany as a global leader in technological innovation.
Industry 4.0 aims to provide higher levels of operational effectiveness and productivity through automation, adaptation, optimization, and customization of production and value-added services. It also focuses on automated data exchange, communication, and human-machine interaction. This revolution builds upon major technological innovations such as machine learning, artificial intelligence, big data and analytics, the Internet of Things (IoT), robotics, quantum computing, blockchain, nanotechnology, augmented reality, virtual reality, additive manufacturing (3D printing), cloud computing, and cybersecurity.
The goal of Industry 4.0 is to transform working and living environments to unprecedented levels by synthesizing digital, physical, and biological entities. However, the implementation of Industry 4.0 in various industrial settings poses significant challenges to academia and businesses alike. There is still much to learn about the various aspects and functions of Industry 4.0 and how to effectively implement its tools in different industries.
One crucial aspect of Industry 4.0 is the role of quality management. Just like in the previous industrial revolutions, the quality function is expected to play a pivotal role in the success of Industry 4.0. Quality is not solely focused on technology but encompasses other elements such as people, processes, tools, techniques, methodologies, and analytical thinking. Quality 4.0 does not replace traditional quality methods but builds upon them and improves them.
Quality 4.0 refers to the digitalization of quality work in the context of Industry 4.0. It aims to pursue quality performance in the era of digital transformation. The understanding and implementation of Quality 4.0 are still in their early stages, with limited empirical and conceptual research available. Most of the existing literature on Quality 4.0 is practitioner-oriented and lacks robust theory and research.
To address this gap in knowledge, there is a need for more conceptual and empirical research on Quality 4.0. Researchers should strive to develop and standardize survey instruments and measurement models that can accurately assess the level of Quality 4.0 implementation in organizations. This will help in understanding the requirements of Quality 4.0 and guide practical implementation efforts.
The objectives of this research work are to review the relevant literature on quality management and identify the dimensions of Quality 4.0, design a measurement instrument to measure the degree of Quality 4.0 implementation, and develop and standardize a measurement model using confirmatory factor analysis (CFA) to ensure model fit, validity, and reliability.
The evolution of the quality discipline has been a combination of various Japanese and US philosophies, concepts, and approaches. While there have been countless works on quality management practices, most of them focused on understanding critical dimensions and advocating models and frameworks for implementing quality management across industries. However, the literature on Quality 4.0 is still in its infancy, with only a few studies providing insights into its dimensions and implementation.
Based on a review of the literature, 12 axes of Quality 4.0 have been identified. These axes include strategic leadership, quality culture, customer centricity, quality management system, compliance, analytical thinking, competence, customer-centric metrics, data-driven decision making, improvement-based approaches, workforce skills and capabilities, and organizational roadmap. These axes highlight the importance of traditional quality practices, along with technology-driven aspects, in achieving Quality 4.0.
A survey instrument consisting of 68 items has been developed to measure the different axes of Quality 4.0. The responses are collected on a 9-point scale, and a pilot study with experts in the field has validated the instrument. The instrument has undergone refinement based on expert feedback and is designed to capture all aspects of Quality 4.0.
To validate the measurement model, a survey was conducted with 217 professionals from manufacturing and process organizations that have some degree of awareness and implementation of Quality 4.0. The data collected were analyzed using CFA, and the model fit indices, reliability, and validity measures were assessed. The results indicate strong evidence of model fit, reliability, and validity, supporting the hypothesis that Quality 4.0 is a multidimensional construct consisting of the identified 12 axes.
The development of a standardized measurement instrument for Quality 4.0 provides researchers and practitioners with a tool to assess the level of implementation in organizations. This can help in identifying areas for improvement and developing strategies for effective deployment of Quality 4.0. The instrument can also be used to study the impact of Quality 4.0 on organizational performance, agility, and sustainability.
In conclusion, this research work contributes to the understanding of Quality 4.0 by identifying its dimensions and developing a measurement instrument. The findings highlight the importance of both traditional quality practices and technology-driven aspects in achieving Quality 4.0. Further research is needed to explore the causal relationships among the different axes of Quality 4.0 and their impact on organizational outcomes. The standardized instrument can be used by researchers and practitioners to assess the level of Quality 4.0 implementation and guide improvement efforts.
Reference
Sureshchandar G.S. (2023). Quality 4.0 – a measurement model using the confirmatory factor analysis (CFA) approach. International Journal of Quality and Reliability Management, 40(1), 280-303, DOI: 10.1108/IJQRM-06-2021-0172.