Industry 4.0 and Continuous Improvement – 'Next Gen' Lean in Manufacturing

Lean methodology focuses on Continuous Improvement and Respect for People. The manufacturing sector led the field, and has for many years employed human creativity to analyse and improve work, develop physical automation solutions and thus drive significant improvements in productivity and quality. Dangerous, repetitive or laborious tasks where human involvement can introduce risk or error are now routinely performed by machines, allowing people to focus on more value-adding aspects of their jobs. Physical systems (e.g. Kanban cards) have evolved into software that runs semi-autonomously. 

So what does Continuous Improvement look like in the years ahead? We are moving from and age in which people are supported by processes that are run by technology, to an era in which processes are run by technology with augmented support from people.

In the past, improvement ideas have come from people’s analysis and creativity. Often, the improvements have looked for physical automation to increase productivity, improve flow, reduce waste and eliminate human error (poka-yoke). This has allowed significant improvements in the gathering of data for analysis. For example, an out-of-tolerance torque reading from a drill used to assembly components can in real-time trigger an alarm, allowing engineers to compare the data from previous issues seen, assess the risk and determine if, for example, the line should be stopped, or the product should be removed from the line, or re-worked at the end of the line. As your data pool (from across your network of plants) increases, your ability to deploy AI to support those human decisions also increases. 

In the era we have now entered, improvement ideas come from both humans and technology. Non-physical improvements, such as data cleansing and algorithm fixes, are sources of competitive advantage. Guided by an unwavering focus on adding value to customers Industry 4.0 (connected assets) allows supply chains and business models evolve: rather than sequential, tiered supply base structures, manufacturers are increasing part of ecosystems that share demand information in real time and collaborate to respond effectively. Harnsessing the power of data, businesses are migrating from selling products to services – using performance data to drive predictive maintenance etc. and allow client to buy uptime, not assets, and thus focus on the real value-add part of their business model. 

Moreover, productivity gains (often in excess of 50%) and error-proofing in non-physical, ‘Extract – Transform – Load’ administrative functions are being realised through a combination of automation, artificial intelligence and end-to-end process simplification. If a decision can be made in less than one second, it can easily be automated. AI solutions (such as IBM Watson) can analyse documents, images, verbal/written conversations etc. and either make decisions that automation will then execute, or summarise to support human decisions, allowing everyone to perform with ‘full’ knowledge and reducing the impact of attrition in the labour force. Aiming for the minimum required human intervention, businesses should focus their people on adding value for customers and protecting their enterprise by collaboratively seeing and solving problems (continuous improvement), rather than working in sequenced silos. The robotic process sector is growing rapidly, and whilst research shows that many businesses are investigating the technology and rolling-out some early proof-of-concepts, few are employing Next Generation Lean methodology to overhaul and future-proof their processes. As a result, many risk embalming 20th century business procedures and missing the opportunity to create a 21st century, digitally enabled front- / back-office.

A world in which the human workforce innovates freely, and exercises judgment, empathy and creativity and the digital workforce executes flawlessly and improves in an iterative manner.   This is the world of Next Generation Lean.

This article was written for Irwin Mitchell and can be found in their latest manufacturing newsletter: