Industrial Revolution 4.0 turns a factory operating with conventional technology into a smart one by integrating advanced information systems and future technologies. Thanks to the application of the most innovative digital technologies, we can see a significant “evolution” of the many continuous improvement tools such as Lean Six Sigma (LSS).
The DMAIC methodology, which Lean Six Sigma focuses on, is based on data to know the deep problems. Data is needed to generate any improvement in the process. The correct and timely identification of the key issue is based on data integrity and real-time data collection.
The shift from descriptive statistics to predictive analysis
As part of the Industrial Revolution 4.0, the use of sensors allows data to be collected across the entire value chain. This approach leads to the sophistication of planning analysis and makes the transition from descriptive statistics to predictive data analysis.
In contrast to conventional production planning, data provided by sensors allows real-time production planning along with dynamic optimization of logistics, transport and stock management.
More advanced analysis power improves the performance of Lean Six Sigma projects: in particular, data collection and process analysis are faster. So it allows for the acceleration of the stages of definition, measurement, analysis, improvement, and control in order to know the process in detail and to highlight the root causes that influence the standard deviation (Lean Six Sigma’s key concept) and must be eliminated to optimize the process.
For example, in the defining phase, with data sensors and devices connected to the Internet, data can be transmitted to a smartphone or tablet to monitor deviations in processes or products. At the measurement stage, accelerating data collection and eliminating human collection errors contribute greatly to the accuracy and integrity of data.
Alerts and Power of Predictive Data in Lean Six Sigma
Companies using conventional technology may have descriptive data and receive a warning signal of malfunction. In their case, the alert is signaled when the malfunction has already occurred, while the power of predictive data allows to measure the index of worn out of the machine and alerting the user before the machine fails. It, therefore, allows the prompt adoption of counter-measures to anticipate the future and to know the possible cause-to-effect relationships beforehand.
The relevance of the use of technology in Lean Six Sigma methodology implementation is also demonstrated in the analysis phase. The conventional implementation provides for the identification and prioritization of root causes followed by their removal.
A set of qualitative and qualitative tools are accessed to describe the process as accurate as possible. With the help of sensors and devices connected to the internet, the process of identifying root causes is significantly accelerated.
Similarly to the improvement stage when root causes are eliminated, the impact of corrective actions is monitored and behavior and practices are enhanced to meet Critical to Quality (CTQ) criteria.
The control phase highlights the positive impact of the Internet of Things (IoT) that must integrate into any operating platform or database. Monitoring must be done under any circumstances, the data be confidential and secure.
The Internet of things leads to the next level of connectivity
Applications based on the Internet of things are part of our lives and many human and industrial activities are based on this technology. The transition from energy sources to automation, information technology, and automated production to connectivity has changed the production process.
The intelligent factory is based on sensors and devices, on an ecosystem that depends on many stakeholders. This ecosystem uses the Internet of Things (IoT), Big Data and integrates the physical world with the digital world. What succeeds in changing the Industrial Revolution 4.0 is the transition from the client-centered product cycle to the product cycle centered on customer experience.
Prior to the Industrial Revolution 4.0, the client was not involved in the product cycle from initiation to the feedback phase. Now the customer experience becomes vital to the success of any company. Industry 4.0 can create value over the entire product, process, or service life cycle. The result of this revolution can be an object, but also a service designed for a final user, whose development is driven by innovation in several areas: IT, integrated systems, production, automation technology. All these are used to deliver fast and quality results.