In the landscape of modern manufacturing, the concept of jidoka emerges as a fundamental pillar within the Lean Manufacturing philosophy (Sordan and Chiabert, 2024) and, notably, as one of the two pillars supporting the renowned Toyota Production System (Li and Skai, 2024), in response to the relentless pursuit of efficiency and quality.
But what is jidoka? Essentially, jidoka means automation with a human touch, or “autonomation” in English. This approach allows machines to detect anomalies and stop automatically, preventing the production of defects and promoting quality at the source.
In this article, we will explore the jidoka system in depth, its relationship with other concepts such as Six Sigma, poka-yoke, and Just-in-Time, and how its implementation can transform manufacturing processes.
What is Jidoka?
The term Jidoka (自動化) originates from Japanese and translates as “intelligent automation” or “automation with human intelligence.” It is based on the ability of machines to detect problems and stop automatically when a defect occurs in the production process. Kitazuka and Moretti (2012) emphasize that more than just a technique or tool, Jidoka is a principle that seeks quality production and disengages the process from direct supervision.
Phatale (2020) reports that the primary objective of Jidoka is to quickly identify the causes of problems and halt the assembly process immediately when the first defect occurs, ensuring that only quality products leave the assembly station.
However, “intelligent automation” is not limited to machine operations but can also be used in combination with manual operations. In this regard, Åhlström (2015) highlights that “human Jidoka” allows operators to stop the process in case of a problem, often involving visual control, which enables a quick assessment of the production process status and the visibility of process standards.
According to Sordan and Chiabert (2024), Jidoka combines automation with a human touch (autonomation). In this regard, it is crucial to differentiate between simple “automation” and “autonomation,” a term often used synonymously with jidoka. Automation refers to the automatic execution of tasks by a machine, whereas autonomation implies that the machine has the capability to detect when an abnormal condition occurs and immediately stop the work. This autonomous detection and stoppage capability is what fundamentally distinguishes jidoka from conventional automation.
Origin of Jidoka
The origin of jidoka dates back to the early 1920s, thanks to the vision of Sakichi Toyoda, the founder of the Toyota Group (Reke et al., 2024). His revolutionary invention was an automatic textile loom that would stop automatically when a thread broke (de Carvalho et al., 2025).
Previously, if a thread broke, the loom would continue producing large amounts of defective fabric, requiring constant supervision by an operator for each machine.
Toyoda’s innovation allowed a single operator to control multiple machines, leading to significant productivity gains. This invention not only solved a practical problem in textile manufacturing but also laid the foundation for the development of the jidoka principle as we know it today.
Principles of Jidoka
The “jidoka process” is based on four fundamental principles that ensure the delivery of defect-free products. These principles, which answer the question “what does jidoka mean?”, are the cornerstone of its effectiveness in improving quality and efficiency.
Detect an abnormality
This means that both machines and operators must have the ability to identify when a defect or problem occurs. In the case of machines, this is achieved through sensors and other automatic detection mechanisms. Operators, on the other hand, are trained to be alert to any deviations from normal standards.
Stop the process
Once an abnormality is detected, whether by the machine or the operator, the production process must stop immediately. This preventive action prevents defective products from continuing to be produced and allows the problem to be addressed at its source. A commonly used system to signal issues and stop production is the Andon system, which can be activated by an operator or automatically by equipment.
Take corrective action
Once the process is stopped, the next step is to address the problem that caused the stoppage. This may involve a quick repair or an adjustment to restore the process to its normal state.
Investigate and resolve the root cause or prevent recurrence
After solving the immediate problem, it is essential to analyze why it occurred and implement countermeasures to prevent it from happening again in the future. To identify the root cause, techniques such as the “5 Whys” are often used.
Benefits of Implementing Jidoka in Companies
As previously explained, Jidoka allows for the automatic detection of abnormal situations in machines and stops production upon detecting a failure. In this way, “intelligent automation” grants machines basic decision-making capabilities, enabling them to identify deviations and pause operations until human intervention occurs (de Carvalho et al., 2025).
According to Tekin et al. (2019), the benefits of implementing Jidoka in companies include achieving high-quality products and increased productivity through defect-free production, improved quality, prevention of machine, tool, and equipment failures, and process safety.
Romero et al. (2019) indicate that by gradually developing and/or adopting Jidoka Systems instead of directly implementing full automation solutions, SMEs can find a sustainable approach to supporting workforce learning, optimizing their manufacturing processes, and increasing productivity in an affordable manner.
Implementation of Jidoka in Lean Manufacturing
The “implementation of Jidoka” in Lean Manufacturing requires a systematic approach and commitment from the entire organization. One of the best ways to drive the implementation of “intelligent automation” is to implement a Kaizen program (Kitazuka and Moretti, 2012). Escott (2024) describes that the Jidoka methodology is organized into three sequential stages:
Discovery
This phase focuses on gathering information, assessing the current state of the legacy system, understanding the scope and requirements of modernization, and establishing a plan. Key activities include stage planning, repository setup, conducting “tech spikes” to address risks, planning the use of existing platform assets, initiating modeling (UI, requirements, team, migration), and automating discovery activities.
Recommendations:
- Management commitment and allocation of necessary resources for training, technology implementation, and process improvements. Visible leadership is crucial to fostering a culture of quality and continuous improvement.
- Empowering and training the workforce to identify issues and halt production if necessary. Operators must understand the importance of quality and have the authority to act when detecting an abnormality.
- Establishing clear communication channels for problem reporting and resolution. Using Andon systems as a visual management tool is essential for quickly alerting teams to issues and facilitating timely responses.
- Starting with small pilot projects before implementing Jidoka organization-wide. This allows for testing and refining the approach before full-scale implementation.
Modernization
This phase focuses on executing the discovery plan and the actual modernization of the legacy system. The goal is to achieve a replacement as close as possible to the original system from the end-user perspective (Like-for-Like – L4L) to minimize organizational change and retraining needs. Kanban boards, quality checklists (DoR/DoD), and DevOps pipeline reports (testing, code quality, security, performance) are utilized.
Recommendations:
- Equipping machines with intelligent automation systems that enable real-time anomaly detection and automatic production stoppage when an issue is detected. This includes installing sensors and other monitoring devices.
- Integrating poka-yoke (error-proofing) mechanisms to complement Jidoka by preventing errors from occurring in the first place.
- Measuring and reporting the effectiveness of “intelligent automation” implementation to identify areas for improvement and demonstrate the initiative’s value.
Optimization
This stage occurs after the new system is launched and focuses on ensuring its security, monitoring, and readiness for continuous improvements. At this phase, improvements postponed during modernization can be implemented more efficiently due to new technology.
Recommendations:
- Regular maintenance and calibration of equipment are necessary to ensure the optimal performance of detection and automation systems. This reduces the risk of false detections or system failures.
- Implementing continuous improvement practices, including root cause analysis and feedback cycles, is essential to prevent problem recurrence.
Jidoka and Its Connection to Other Lean Concepts
Jidoka is a fundamental Lean principle that contributes to waste reduction, quality improvement, and customer satisfaction. It helps create a defect-free production system, a key goal of Lean Manufacturing. Additionally, Jidoka empowers employees, a central aspect of Lean management.
However, Jidoka does not operate in isolation; it is intrinsically connected to other Lean Manufacturing principles and tools.
Jidoka and Just-in-Time
Jidoka and Just-in-Time (JIT) are the two fundamental pillars of the Toyota Production System. While JIT focuses on the efficiency of material and information flow, Jidoka ensures that quality is built into the manufacturing process. “Intelligent automation” guarantees quality, which is crucial for the smooth functioning of JIT by preventing defects that could disrupt the flow. JIT emphasizes producing only what is needed, when needed, and in the necessary quantity, and Jidoka supports this by ensuring that what is produced is of high quality.
Difference Between Poka-Yoke and Jidoka
Poka-yoke is defined as an error-proofing system or mechanism designed to prevent errors from occurring in the first place. Jidoka, on the other hand, focuses on detecting abnormalities and stopping the process, allowing for correction and preventing recurrence.
While Poka-yoke proactively prevents errors, “intelligent automation” reacts to errors by stopping the process. An example of Jidoka is a printer stopping due to a paper jam, whereas an example of Poka-yoke is a uniquely shaped part that can only be installed in one direction.
Table: Jidoka vs. Poka-Yoke
| Characteristic | Jidoka | Poka-Yoke |
|---|---|---|
| Primary Objective | Detect abnormalities and stop the process; address the root cause | Prevent errors from occurring in the first place |
| Approach | Reactive (responds to detected abnormalities) | Proactive (prevents errors) |
| Mechanism | Automated sensors, operator intervention (e.g., Andon cord) | Physical restrictions, sensors, checklists, etc. |
| Example | The machine stops when a part is misaligned | A connector that only fits in one way |
Jidoka and Six Sigma
While Jidoka is primarily associated with Lean, its focus on quality and defect reduction aligns with Six Sigma’s objectives. While Lean focuses on eliminating waste and improving flow, Six Sigma aims to reduce variation and defects. Jidoka contributes to both by stopping defective products from advancing down the line.
The Jidoka-Six Sigma combination is a powerful approach that integrates early defect detection with statistical methodologies to enhance quality.
For example, in an automobile manufacturing process, “intelligent automation” can detect a welding issue, while Six Sigma analyzes root causes to prevent future occurrences. Together, these approaches create a robust system that maximizes efficiency and quality.
Examples of Jidoka in Use
Toyota Assembly System
A classic example of Jidoka is Toyota’s assembly system. On a production line, if an operator detects a problem, they can stop the line using a cord called Andon. This allows the team to resolve the issue before continuing, preventing the production of defective vehicles.
According to Li and Skai (2024), Toyota’s experience with Jidoka is integral to its production approach, promoting a culture of early problem detection, failure prevention, and a line design that prioritizes overall equipment reliability.
CNC Machine
Romero et al. (2019) describe that modernizing a CNC machine using Jidoka involves a gradual approach, starting with existing resources, incorporating low-cost technology for data collection, applying machine learning to predict issues (such as tool wear), and implementing mechanisms for automated decision-making, with human intervention reserved for critical situations, supported by effective human-machine interfaces for communication.
Jidoka 4.0
The classic Jidoka method uses sensors or mechanical principles to allow autonomous process correction. However, with the rise of Industry 4.0, there is significant potential for a predictive approach to quality improvement in manufacturing processes, leading researchers to develop the concept of Jidoka 4.0.
Jidoka 4.0 focuses on predicting potential errors before they occur and evaluating their impact on product and process quality, enabling the anticipation and prevention of quality deviations (Deuse et al., 2020).
In this regard, Koteswarapavan and Pattanaik (2024) propose a framework for upgrading to Jidoka 4.0, advocating for the use of Industry 4.0 technologies such as the Internet of Things (IoT), cyber-physical systems (CPS), big data analytics, and cloud computing.
Conclusion
Jidoka remains highly relevant in modern manufacturing, especially with the rise of smart manufacturing and Industry 4.0 technologies. The integration of IoT, artificial intelligence (AI), and data analytics further enhances the capabilities of “intelligent automation”, enabling more precise anomaly detection and more efficient problem resolution.
In conclusion, adopting Jidoka as a key strategy for achieving operational excellence is essential for companies seeking to maintain a competitive advantage in today’s market. By building quality into processes, empowering employees, and fostering a culture of continuous improvement, “intelligent automation” stands as a fundamental principle for achieving the desired efficiency and quality.
Frequently Asked Questions
✅ What does Jidoka mean?
Jidoka means automation with a human touch or “intelligent automation”, allowing machines to detect and correct anomalies.
✅ What is the difference between Poka-Yoke and Jidoka?
Poka-Yoke prevents errors from occurring, while Jidoka is a comprehensive system that detects and corrects anomalies in real time.
✅ How is Jidoka related to Six Sigma?
Jidoka detects defects in real time, while Six Sigma analyzes root causes to prevent future problems.
✅ What is an example of Jidoka?
A classic example is Toyota’s assembly system, where operators can stop the production line if they detect a problem.
✅ How can I implement Jidoka in my company?
Implementing Jidoka requires training, anomaly detection, automatic stoppage, fast resolution, and continuous improvement.
References
Åhlström, P. (2015). Jidoka. Wiley Encyclopedia of Management, 1-1.
de Carvalho, P. T., Lopes, J. D., & Raimundo, R. J. (2025). Innovation Impact in the Textile Industry: From the Toyota Production System to Artificial Intelligence. Sustainability, 17(3), 1170. https://doi.org/10.3390/su17031170
Deuse, J., Dombrowski, U., Nöhring, F., Mazarov, J., & Dix, Y. (2020). Systematic combination of Lean Management with digitalization to improve production systems on the example of Jidoka 4.0. International Journal of Engineering Business Management, 12, 1847979020951351.
Escott, E. (2024). Jidoka: automation with a human touch. Software and Systems Modeling, 1-20.
Kitazuka, R. E., & Moretti, C. (2012). Jidoka. In Toyota by Toyota (pp. 43-54). Productivity Press.
Koteswarapavan, C., & Pattanaik, L. N. (2024). A novel tool-input-process-output (TIPO) framework for upgrading to lean 4.0. International Journal of Production Management and Engineering, 12(1), 65-77.
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Phatale, A. 2020. An Essential Guide to Lean Production Tools and Techniques: Enhancing Efficiency and Quality in Manufacturing. International Journal of Science and Research (IJSR)
Reke, E., Powell, D., Yokozawa, K., & Finnestrand, H. (2024). Smart Collaboration–Review of Human-Machine Collaboration in Lean Production, Zero Defect Manufacturing and Human Centered Manufacturing. In International Conference on Flexible Automation and Intelligent Manufacturing (pp. 432-438). Springer, Cham.
Romero, D., Gaiardelli, P., Powell, D., Wuest, T., & Thürer, M. (2019). Rethinking jidoka systems under automation & learning perspectives in the digital lean manufacturing world. IFAC-PapersOnLine, 52(13), 899-903.
Sordan, J. E., & Chiabert, P. (2024). From Jidoka to Jidoka 4.0. In Lean Manufacturing in Latin America: Concepts, Methodologies and Applications (pp. 151-174). Cham: Springer Nature Switzerland.
Tekin, M., Arslandere, M., Etlioğlu, M., Koyuncuoğlu, Ö., & Tekin, E. (2019). An application of SMED and Jidoka in lean production. In Proceedings of the International Symposium for Production Research 2018 18 (pp. 530-545). Springer International Publishing.
