Andon in manufacturing: a proven method backed by research.
The Andon method originated in the Toyota Production System as an expression of the Jidoka philosophy—the right and duty of every employee to stop the line the moment a problem is detected. One signal. Immediately. No hierarchy, no forms. [5]
In a classic case study of the Toyota plant in Georgetown, Harvard Business School describes how operators pull the Andon cord an average of a dozen or so times per shift. Only one in a dozen or so cases results in an actual stoppage—the rest are signals resolved on the spot before the problem escalates. [3]
Independent scientific research confirms that Andon is one of the most widely used and best-documented tools of modern Lean Manufacturing. [8] Purnomo, Maulana, et al. from the Bandung Institute of Technology demonstrated in a peer-reviewed article from 2024 that the implementation of a smart Andon system based on IIoT leads to measurable improvements in production efficiency, reduced downtime, and increased OEE. [1]
Concurrent research on the application of deep learning in Andon systems reveals concrete figures: compared to traditional manual models, a modern system can reduce downtime response times by over 60%, cut spare parts inventory by 30%, and increase productivity by approximately 8 percentage points. [2] Independent surveys from various manufacturing environments confirm these trends: plants using Andon report a 30–50% reduction in downtime and a 20–25% increase in productivity. [7] Polish studies of manufacturing plants confirm similar results. Wojakowski documents a 10–25% increase in production efficiency following the implementation of the Andon system. [9]
- 60% reduction in downtime response time vs. manual model
Fan et al., ACM 2024 [2] |
- 30% reduction in spare parts inventory
Fan et al., ACM 2024 [2] |
+ 8 pp. increase in finished goods yield
Fan et al., ACM 2024 [2] |
5.5 sec average notification time to the responsible person
Purnomo et al., 2024 [1]
Digitalization of manufacturing: tools are meant to serve people, not the other way around
The manufacturing world is moving toward full digitalization. This is an inevitable trend and the right path to take. MES systems, OEE dashboards, automated reporting, and push notifications—this isn’t the future; it’s the present, available to every plant.
But there is one condition: when implementing the Andon system and digital solutions, you must respect the people who work with them. And here comes a question that is asked far too rarely during implementations:
Will an operator who has been pressing a button for 10 years and understands three light colors want to, be able to, and have the time to use a tablet? Will an employee from Ukraine or Nepal, who doesn’t read Polish, be able to efficiently select a failure status from a drop-down list?
Purnomo and colleagues themselves point out this limitation in their research: some operators have difficulty using mobile technology, especially when the system is new or when users are unfamiliar with the touchscreen interface. [1] This is an argument for choosing the tool to fit the person, rather than the person to fit the tool.
It’s important to keep one thing in mind: if an operator fears that stopping the line will result in criticism or punishment, no system will work properly. An effective Andon system requires a culture in which reporting a problem is seen as a proactive action rather than a mistake that needs to be explained. Once this culture exists or is being built, the right step is to choose a tool that does not create obstacles for the operator.
The answer is a hybrid model: an Andon light at the workstation + AndonCloud as a production management system that handles everything that happens after the light comes on.
When does it make sense to integrate an Andon light with the system?
The hybrid model doesn’t require giving up any of the existing tools. The operator reports a problem with a single push of a button, and management receives comprehensive real-time data. This is particularly useful in the following situations:
| Foreign-language employees and temporary agency workers. One to three buttons, understandable to everyone. The system notifies the right person in the background. Reporting a malfunction without a language barrier. Zero delays resulting from communication. |
| Employees who don’t use screens. Older generations, operators wearing gloves, workstations at CNC machines in noisy, greasy environments. A tablet isn’t their tool. A button—yes. A complete report without touching the screen. The system does the rest automatically.
| High-speed assembly lines. Cycle times of 30–60 seconds. There’s no time to describe the problem. A single signal is enough; AndonCloud handles the rest. The operator doesn’t waste time—one press of a button is all it takes. A complete history is stored in the system.
| Facilities with existing infrastructure. You already have Andon lights, wiring, and buttons at workstations. In many cases, the existing infrastructure can work with AndonCloud—without the need to replace equipment. New capabilities at a lower implementation cost
| Multi-shift production. Night, weekend, a shift with fewer staff, the foreman isn’t on hand. The light comes on, and the system sends a push notification to the appropriate person on duty. Automatic escalation if no one answers.
How does the Andon system work with the software?
In the hybrid model, the operator’s role remains the same: they press a single physical button. Everything that happens next—production management, notifications, escalations, and reports—is handled by AndonCloud.
When the operator uses the Andon lamp: The system identifies the workstation and automatically triggers the assigned scenario. Pressing the button at a given workstation always reaches the right person and creates the appropriate task, without any additional action required from the operator.
A classic lamp typically has three buttons to which specific scenarios can be assigned—for example: red triggers a failure report and a notification to Maintenance, yellow signals a material shortage and notifies the warehouse, and green indicates normal operation. The possibilities are limited, but basic reports—the most common and important ones—can be efficiently handled this way.
When the operator uses a panel or tablet: The operator selects a status from a list. Each status triggers a different scenario. Below are a few examples—the status tree can be expanded in detail so that the recipient of the notification knows exactly what is happening at the workstation even before they arrive there:
- Machine failure — the system records downtime and automatically creates a service order in the CMMS. This data serves as the basis for calculating MTBF and MTTR.
- Material shortage — logistics and the warehouse receive a push notification within seconds. No intermediaries, no phone calls.
- Quality control — the inspector receives an alert with the workstation number and product reference. Immediate response without involving the foreman.
- Changeover — the operator receives a task with a procedure description and product information. Ready to act before arriving at the workstation.
- Scheduled downtime — the system automatically distinguishes between scheduled downtime and breakdowns. OEE calculated based on actual data, not estimates.
- Statuses, recipients, and escalation rules are configured by the production manager in the admin panel. No programmers, no integrators — configuration is simple and intuitive.
How does AndonCloud support key departments within the facility?
Connecting the Andon lamp to the AndonCloud production management system benefits more than just floor operators. The data collected by the system is valuable to Maintenance, HR, and management. Each of these areas gains a different perspective, but all rely on the same real-time data from the workstations.
Production
AndonCloud gives the foreman and production manager a complete, real-time overview of the status of every workstation. The system records the history of every incident. Time of report, workstation, response time, and resolution method. Push notifications are sent to the foreman automatically, regardless of where they are at the moment. Shift reports are generated automatically based on recorded events, without manual entry after the shift ends. The OEE dashboard is based on actual data, not estimates.
Maintenance
When a failure is reported, the system automatically creates a service order based on predefined procedure and order templates. The mechanic receives the order without having to manually enter data; their only task is to complete the checklist assigned to the procedure, if one has been configured.
AndonCloud maintains a complete history of events at each workstation. The performance widget allows you to compare the number and duration of failures at a selected workstation over any period, even up to 12 months in the past. This serves as the basis for planning preventive actions before a failure occurs, rather than reacting to it in an emergency.
HR / Work Scheduling
AndonCloud provides data that supports work scheduling at the operational level. Analyzing workstation workload over time helps identify stations generating the most reports, which may indicate a need for training, staffing changes, or process adjustments. The frequency of incidents broken down by shift provides an objective basis for evaluating team effectiveness based on facts, not on the subjective assessments of supervisors.
The system also supports employee rotation planning by indicating which positions require more experience. The built-in tool for planning staffing levels and position assignments facilitates scheduling and resource allocation in accordance with actual production needs.
Management / Production Manager
A clear dashboard displays OEE, workstation statuses, productivity, and production in real time. It allows you to compare shifts, workstations, and departments based on the same data and the same measurement methodology. Reports can be exported to PDF or Excel. The system sends alerts when defined thresholds are exceeded, e.g., when OEE falls below a specified level or the number of incidents exceeds the accepted standard. The performance widget shows the duration of each status during a selected period, with the option to compare it to previous months.
Market Data: The Digitization of Andon Systems Is Gaining Momentum
The global market for digital Andon systems reached $1.65 billion in 2024 and is projected to grow to $5.04 billion by 2033, at a compound annual growth rate of 13.4%. [6]
This growth is no accident. Manufacturers around the world—from small plants to global corporations—are seeking solutions that give them real control over what is happening on the shop floor. Not after the fact, not from a report compiled the next morning, but in real time.
This growth is driven by several parallel trends: the growing demand for real-time production monitoring, the digitization of production as part of Industry 4.0 strategies, and the pressure to reduce downtime and improve OEE amid rising labor and raw material costs.
AndonCloud fits into this trend, but with one key difference. It doesn’t require a revolution at the plant. You can start with a single line, keep the existing light-based infrastructure where it makes sense, and expand the system gradually. Digitizing production doesn’t have to mean replacing everything at once.
A proven method, modern capabilities
Digitizing production does not mean discarding what works. Research on the integration of Lean Manufacturing with Industry 4.0 technologies clearly shows that tools such as Andon do not lose their relevance in the digital age; on the contrary, they gain new capabilities through integration with IIoT, MES, and ERP systems.
The key conclusion drawn from the literature and the practices of manufacturing plants is simple: the value of the Andon system lies not in the signal itself, but in what happens after it is sent. Response speed, the quality of information reaching the right person, and the data collected by the system—these factors determine the real impact on production efficiency.
A hybrid model—a signal lamp where the operator needs simplicity, and a digital panel where greater status differentiation is possible—allows plants to implement digitization in a thoughtful manner. Without excluding employees, without an infrastructure revolution, but with full analytical benefits: measurable OEE, event history, and data for planning preventive actions.
The decision to digitize the Andon system is not a choice between tradition and modernity. It is a decision about whether the plant wants to manage production based on facts or on hunches.
FAQ — Frequently Asked Questions
Is an Andon lamp still necessary in the age of digitalization?
Yes, especially where foreign-language operators work, employees without touchscreen access, or on lines with very high production speeds. The lamp sends a single signal without a language barrier and without the need to operate an interface.
How does the classic Andon system differ from the hybrid model with AndonCloud?
A classic lamp signals a problem visually on the shop floor, but it does not record data, does not automatically notify the right person, and does not create an event history. The hybrid model combines the simplicity of the lamp with automation: when a button is pressed, the system automatically notifies the right person, creates a service order, and records the event for OEE reports.
How does AndonCloud integrate with an existing Andon light?
In many cases, the existing infrastructure—lights, wiring, and workstation buttons—can work with AndonCloud without the need to replace equipment. Compatibility depends on the class and age of the devices. It’s worth discussing the details individually with the implementation team.
How many statuses can be configured in AndonCloud?
The status tree can be expanded as needed. The system imposes no restrictions. Each status can be assigned a different notification recipient, a different escalation rule, and a different task type. Configuration is done in the admin panel without the need for developers.
Is AndonCloud suitable for facilities with foreign-language employees?
Yes, this is one of the key use cases. The operator presses a physical button on a light or selects a status on a panel with icons. The system automatically notifies the appropriate person. A language barrier on the operator’s side does not affect the effectiveness of the notification.
What production metrics does AndonCloud measure?
AndonCloud offers a comprehensive set of KPIs and metrics, individually configurable for each workstation in the admin panel. The core KPIs are Availability, Productivity, Quality, and OEE—all updated in real time. These are supplemented by detailed metrics: operating time, downtime, number of good and defective units, expected number of units per operating time, and number of operators. Each facility selects indicators tailored to its processes and production goals.
Sources and Bibliography
The following is a list of all academic, market, and expert sources used in this article, including detailed bibliographic information and links to the original publications.
[1] Purnomo W., Maulana G.G., Suryatini F., Sunarya A.S. (2024) Smart Andon System Based on Industrial Internet of Things (IIoT) Jurnal Rekayasa Mesin, Vol. 15, No. 2, pp. 771-781. DOI: 10.21776/jrm.v15i2.1532 https://doi.org/10.21776/jrm.v15i2.1532
[2] Fan J., Hao H., Xu Y. (2024) Application and Optimization of Deep Learning-Powered Intelligent Andon System in Lean Manufacturing CAICE 2024, ACM Digital Library. DOI: 10.1145/3672758.3672786 https://dl.acm.org/doi/10.1145/3672758.3672786
[3] Mishina K. (1995) Toyota Motor Manufacturing, U.S.A., Inc. Harvard Business School Case Study 9-693-019.
[4] Mohamad E., Rahman M.S.A., Ito T., Rahman A.A.A. (2019) Framework of Andon Support System in Lean Cyber-Physical System Production Environment Proceedings of Manufacturing Systems Division Conference, p. 404. DOI: 10.1299/jsmemsd.2019.404 https://www.researchgate.net/publication/336042593
[5] Ohno, T. (1988). *The Toyota Production System: Beyond Large-Scale Production*. Productivity Press.
[6] Growth Market Reports (2024). *Digital Andon System Market Research Report 2033: Global Market Data*. https://growthmarketreports.com/report/digital-andon-system-market
[7] Learn Lean Sigma (2025) Guide: Andon Aggregate of research results from various production environments. https://www.learnleansigma.com/guides/andon/
[8] Habe et al. (2023) Andon within the framework of contemporary Lean Manufacturing practices. Cited in: Florescu & Catana (2025). https://innovaromorir.com/en/andon-system-manufacturing-guide-visual-efficiency
[9] Wojakowski P. (2017) Implementation of Andon System Projects in Manufacturing Plants. Research on Enterprise in Modern Economy, 21(2), 179–188. DOI: 10.19253/reme.2017.02.015 https://journal.mostwiedzy.pl/reme/article/view/93
