Lean Management and Industry 4.0: How to Combine the Two

For several decades, manufacturers have relied on lean principles and tools to improve productivity and reduce operational complexity. 

Lean management, with its emphasis on continuous improvement and waste reduction, has been instrumental in achieving operational excellence. However, as operations become increasingly complex, companies have realized that lean management alone is not enough to address their operational challenges. 

In recent years, the emergence of Industry 4.0 technologies has provided new approaches to tackle complexity and boost productivity. By integrating lean principles with Industry 4.0 technologies, manufacturers can enhance speed, efficiency, and coordination, and even facilitate self-managing factory operations. 

To fully optimize their operations, manufacturers must comprehend the interplay between traditional lean management and Industry 4.0. By adopting a holistic approach that combines both methodologies, known as Lean Industry 4.0, companies can generate valuable synergies that propel them to the next level of operational excellence. Manufacturers that have successfully implemented Lean Industry 4.0 have achieved remarkable cost reductions, up to 40%, over a five to ten-year period. 

These reductions surpass the improvements achieved through the independent implementation of either lean or Industry 4.0. Leveraging technologies that enhance plant processes and structures, such as optimizing layouts, has played a significant role in achieving these higher cost savings. However, it is worth noting that less than 5% of observed manufacturing companies have reached a high level of maturity in Lean Industry 4.0.

In this article, we explore the synergies between lean and Industry 4.0, highlighting the benefits of their integrated application and presenting exemplary use cases for achieving operational excellence.

Lean Management and Industry 4.0 

Lean management, rooted in process standardization, continuous improvement, and empowering workers, has long been a cornerstone of operational excellence. Meanwhile, Industry 4.0 represents the digitalization and connectivity of manufacturing processes, incorporating technologies like the Internet of Things (IoT), automation, and data analytics. 

Although each approach offers significant benefits independently, their combined implementation, known as Lean Industry 4.0, has been shown to yield superior results.

Companies that have effectively deployed Lean Industry 4.0 have witnessed substantial cost reductions, outperforming those achieved through the individual application of Lean or Industry 4.0. However, less than 5% of manufacturing companies have reached a high level of maturity in Lean Industry 4.0. To capture the maximum benefits, organizations must tailor the implementation of Lean Industry 4.0 to their specific supply chain and plant-level challenges.

Achieving Significant Benefits through Integrated Solutions

The integration of lean tools and Industry 4.0 technologies offers a multitude of benefits. Let’s explore five key benefits and exemplary use cases for each:


Manufacturers aim for flexible operations that allow a single production line to accommodate multiple products. However, the advantages of flexibility are often undermined by time-consuming changeovers required to reconfigure machinery for different products. By implementing lean tools like single-minute exchange of dies, manufacturers can eliminate non-value-adding activities during changeovers, significantly reducing the processing time. 

Industry 4.0 technologies play a supporting role in this regard. New sensors and software enable machines to automatically identify products and load the appropriate program and tools without manual intervention. With automated changeovers, operators can focus on value-adding activities. 

For instance, a manufacturer successfully implemented a tracking system using radio frequency identification tags on workpieces to classify each product. Assembly stations utilize this system to identify the next product to be produced and set the tools accordingly. As a result, the production line can instantly switch over without requiring operator intervention.

Productivity: Predictive Algorithms for Autonomous Maintenance 

Predictive Algorithms for Autonomous Maintenance Equipment breakdowns and failures often lead to high inventory levels and reduced productivity in manufacturing industries. To enhance overall equipment effectiveness (OEE), companies can employ lean methods like autonomous or preventive maintenance. By assigning specific do-it-yourself maintenance activities to operators, such as autonomous maintenance, companies significantly reduce the downtime required to address minor issues. 

Leading manufacturers are leveraging advanced analytics algorithms and machine learning techniques to analyze the extensive data collected by sensors, allowing them to predict potential breakdowns before they occur. These predictive insights empower operators to perform maintenance at the optimal time, minimizing disruptions, unnecessary downtime, and replacement costs. 

An aluminium producer, for example, provides its maintenance teams with real-time information on equipment performance via mobile devices. This enables them to detect breakdowns or impending issues and understand their underlying causes. Maintenance teams can access relevant documents and receive remote guidance on necessary repair tools through mobile devices.

Speed: Real-Time Data for Accelerated Production Management 

Manufacturers grapple with the complexity of production planning as they strive to increase the number of product variants while reducing batch sizes. While lean management tools like shop floor management aid in responding to daily deviations in production, identifying issues, and communicating changes in production plans, they are not sufficient for real-time planning and control. 

Algorithms offer a solution to manage production in real time effectively. Two key elements in using algorithms include a centralized “control tower” that collects and directs all material movement inside and outside the factory and a horizontally integrated value chain. 

For instance, a home appliance manufacturer improved the reliability and stability of its production process before developing an algorithm that generates daily production plans based on orders, capacity utilization, and inventories. 

A control tower consolidates data from various sources in an integrated value chain and feeds it into the algorithm. This enables the company to select real-time plans based on criteria like efficiency, lead time, and customer priority.

Quality: Data-Driven Quality Control for Self-Inspection 

Production capacity is squandered if products fail to meet specifications. Shipping poor-quality products incurs higher costs and damages customer trust. Lean management tools like self-inspection, poka yoke, and jidoka have been developed to minimize errors and enhance the rate and speed of error detection. 

Self-inspections, for instance, accelerate error detection and reduce defects by 50% to 70% by improving the process of providing feedback to engineers and operators. However, to achieve zero defects, manufacturers must employ a data-driven analytics approach to identify the root causes of errors. 

Industry 4.0 technologies provide reliable context data and facilitate detailed tracking, bolstering error analysis through methods like camera-based visual inspection, correlation models, and real-time monitoring of process parameters. 

An automotive supplier successfully improved quality control by adopting an integrated Lean Industry 4.0 approach. They introduced a self-inspection process that empowered workers to conduct visual quality checks on their output. 

Additionally, they implemented a camera system linked to the quality system, which automatically generated failure reports and detailed analytics, reducing visual inspection and manual reporting time by 70%. Real-time analysis of inspection system data ensures adherence to high-quality standards.

Safety: Sensors and Virtual Reality Training for Improved Working Conditions 

Safety is a crucial key performance indicator in manufacturing. Lean approaches address safety through signs that guide operators and detailed incident tracking to identify areas for improvement. Low-cost wireless sensors can enhance safety efforts further by alerting operators to dangerous gases or potential clashes with forklifts or trucks. 

Virtual reality training is another tool that can improve safety by allowing workers to train in a virtual environment. Offsite training in a simulated setting is more efficient and effective compared to on-site training, and it particularly appeals to the younger generation of workers. 

To reduce accidents among new hires, a service rig provider developed immersive training sessions where workers practice potentially hazardous tasks within a virtual simulation of the work site.

Wrapping it up

To embark on the Lean Industry 4.0 journey and achieve higher levels of operational excellence, a structured approach is essential. This journey encompasses three main phases: innovate, pilot, and scale. The innovation phase involves gaining transparency into business needs, challenges, improvement opportunities, and the availability of Lean Industry 4.0 enablers. 

iLSSi offers a comprehensive assessment to evaluate the current state of implementation and identify improvement priorities. The pilot phase focuses on testing solutions in specific parts of the supply chain or plant, developing minimum viable solutions, and iteratively improving them using agile development methods.

ILSSI’s global reach cannot be overlooked. ILSSI’s connectivity to international markets, through its skilled workforce, world-class research collaborations, and strong ties to industry leaders, positions it as a hub for attracting talent, investment, and business opportunities from around the world.

To achieve the highest level of operational excellence, manufacturers must recognize that reliance on lean management or Industry 4.0 alone is inadequate. Instead, they should combine both methodologies in innovative ways. By embracing Lean Industry 4.0 and leveraging the synergies between lean tools and Industry 4.0 technologies, manufacturers can become champions of operational excellence in the years to come.