Quality 4.0: Enhancing organisations’ quality management practices to the next level
Jiju Antony, Professor of Quality Management and Lean Six Sigma Master Black Belt at Heriot-Watt University, proposes the key ingredients for effective implementation of Quality 4.0.
The term Quality 4.0 was coined by Dan Jacob, research director and principal analyst with LNS research, a leading manufacturing research and advisory firm (i). Quality 4.0 is the application of Industry 4.0’s digital technologies to the traditional quality management practices which would result in increased operational efficiency, improved business performance and business models. Its many benefits include real-time process monitoring, data collection and analytics-supported predictive maintenance. The application of digital technologies can change the quality in various ways, for instance an organisation can monitor processes and extract data from real-time sensors. The big data generated from these sensors can be further analysed to predict quality issues and maintenance needs of the organisation so that defects and breakdowns can be significantly reduced. In order to succeed with the successful introduction, development and sustainability of Quality 4.0, organisations should adopt a multifaceted approach, explicitly addressing not only technological issues but also strategic, operational, tactical and cultural issues.
Quality 4.0 will have an immense role in the entire value chain of an organisation, starting from R&D all the way through to customer service/after sales service. In the R&D function, Quality 4.0 can be utilised for understanding the type of customers for today and tomorrow and their expectations through Big Data analytics and Voice of the Customer (VoC) analysis. Moreover, product development time and costs can be reduced using the tools of Quality 4.0 in the R&D phase. In the case of after-sales service, field technicians can use mobile digital solutions such as field service software to enhance preventive quality and upgrade the customer experience.
The key ingredients for the successful implementation of Quality 4.0 in any organisational setting
Leadership for Quality 4.0: It is absolutely essential that Quality 4.0 is a priority on the leadership agenda and a major component of the corporate business strategy. Leaders should define the vision and roadmap for Quality 4.0 and communicate at all levels about how it contributes to creating a sustainable competitive advantage. Quality 4.0 requires a leadership style that considers innovation and learning. What we need is knowledge-oriented leadership which is more specific to learning and innovation and this style of leadership combines both transactional and transformation styles.
Organisational culture for Quality 4.0: Organisational culture influences members of the organisation such as influencing their behaviour, performance outcomes, and organisations external environment. As quality is everyone’s responsibility, it is important to foster a culture in which all employees take ownership and accountability of quality. More research with a variety of organisations with different sizes and nature has to be carried out to understand the impact of various cultures and leadership styles for the successful implementation of Quality 4.0.
Handing the Big data: The recent development of affordable sensors, improved data acquisition systems and fast communication systems in the Cyber Physical Systems of Industry 4.0 has generated a large amount of data which can be used by quality management systems. The big data will enable the understanding of customers’ needs in a holistic and all-encompassing manner, as almost all customers’ needs will be mapped and analysed. The end-to-end integration across the product life cycle is one of the striking features of Quality 4.0. This will result in a large amount of product usage data (ii), which can be used by manufacturers to monitor the quality and reliability of the product. Consequently, the quality of performance can also be effectively monitored by collecting and analysing the product usage data in customer’s hands through in an automated manner using artificial intelligence.
Top Management Support for Quality 4.0: A transparent and visible top management support encourages positive user attitudes towards quality 4.0 system. Top management support within an organisation can encourage the practices and behaviours that lead to quality performance throughout the organisation. Moreover, they should utilise an operational strategy which is based on continuous improvement using both digital technologies and big data so that organisations can compete on quality and sustain their competitive advantage.
Training for Quality 4.0: For quality 4.0, a range of new skills are required for quality professionals and training will play a major role as different skills might be required at different levels (i.e. quality engineers, managers, directors). Senior management should also think of defining a digital talent strategy that addresses how to close skill gaps - whether by upskilling, retraining the current workforce or recruiting digital specialists. There would also be a requirement of transformational skills such as adaptability, critical thinking, creativity and social skills such as teamwork, change management and knowledge transfer.
Using Prescriptive Analytics Algorithms for Quality Metrics: Poor metrics is one of the primary barriers for accomplishing quality objectives, because the current quality metrics such as defect and failure rates primarily describes what happened, why it happened and what might happen next. It seldom describes what actions need to be taken in a prescriptive manner (iii). Predictive tools give manufacturers unprecedented power to analyse massive amounts of data and discover correlations between critical variables. These insights enable companies to address the root causes of problems pre-emptively - before quality issues occur. Prescriptive analytics algorithms in quality management can provide two levels of human intervention for decision making (iv). The first level of intervention is decision support systems. The second level of prescriptive analytics will be based on intelligent algorithms which result in decision automation through machine learning. This type of prescription algorithm will help in implementing the prescribed action in an automated and self-regulating manner.
The future of Quality 4.0
Quality 4.0 successfully aligns the best practices of quality management with the digital environment. Companies who are investing in Quality 4.0 will gain significant value chain improvements across operational and service efficiency, customer satisfaction and company culture. Quality 4.0 is not about technology, but about the people who use the technology and their processes. It does not replace traditional quality management practices, but builds and improves on it. Researchers at Heriot-Watt University under the leadership of Professor Antony will be conducting a global study into Quality 4.0 to understand the challenges, associated tools of Quality 4.0, benefits of Quality 4.0 and developing a self-assessment tool for assessing the readiness for Quality 4.0.
About the author
Professor Jiju Antony is recognised worldwide as a leader in Lean Six Sigma methodology for achieving and sustaining process excellence. He is a Professor of Quality Management in the Edinburgh Business School at Heriot-Watt University, Edinburgh, Scotland and has authored over 400 journal, conference and white papers and 12 text books of which 4 are related to Lean Six Sigma. He has published over 250 papers on Six Sigma and Lean Six Sigma topics and is considered to be one of the highest in the world for the number of Six Sigma publications. Professor Antony has worked on a number of consultancy projects with several blue chip companies such as Rolls-Royce, Bosch, Parker Pen, Siemens, Ford, Scottish Power, Thales, Nokia, Philips, General Electric, NHS, Glasgow City Council, Scottish Water, ACCESS, Police Scotland and University Sectors. He is a Certified Lean Six Sigma Master Black Belt and has trained over 1200 people as Lean Six Sigma Yellow, Green and Black Belts from over 20 countries representing over 175 organisations in the last 14 years.
References
i. Johnson, S. (2019). Quality 4.0: A TREND WITHIN A TREND. Quality, 58(2), 21–23
ii. Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry 4.0. Procedia Cirp, 40, 536–541.
iii. Pedersen, B. (2017). The Quality Leader’s Guide to Quality 4.0. Retrieved from GxP Lifeline website: https://www.mastercontrol.com/gxp-lifeline/the-quality-leaders-guide-to-quality-4.0/
iv. Hagerty, J. (2017). Planning Guide for Data and Analytics. Gartner. Published: 13 October 2016
