Navigating Human-Robot Disagreements in ASEAN Factories

The Rise of Industrial Robots in ASEAN: A New Challenge for Human-Operator Interaction \\[10pt] As the adoption of industrial robots accelerates across Southeast Asia, manufacturers are facing a new challenge: what happens when an experienced operator believes the machine is wrong? This question is becoming increasingly relevant as the global stock of industrial robots surpassed five million units in 2025, with over 600,000 new installations that year. In countries like Thailand, Vietnam, Indonesia, and Malaysia, where manufacturing is a key economic driver, the integration of advanced robotics is transforming production lines. However, the speed and precision of these machines can sometimes lead to unexpected outcomes, and it is crucial to have a clear process for addressing such situations. \\[10pt] ## The Importance of a Clear Escalation Process \\[10pt] The latest advancements in industrial robots, such as ABB’s IRB 1700 models, promise up to 20 percent shorter cycle times, along with improved precision and energy efficiency. While these improvements help businesses meet their production targets, they also reduce the time available for operators to identify and address any issues. For example, imagine a machine-vision system marks a batch of parts as defective, but a veteran operator suspects that the issue is due to residue on the camera lens rather than a production defect. In such a scenario, it is essential to have a well-defined escalation process that allows the operator to safely challenge the machine's decision without compromising safety. \\[10pt] ## Testing Human-Response Protocols Before Deployment \\[10pt] Before deploying a new robotic system, it is important to test not only the technical aspects but also the human response to potential disagreements. BlueBotics CEO Nicola Tomatis has emphasized the importance of testing traffic, charging, routes, and fleet capacity during the simulation phase. Similarly, testing the human response to a disagreement is equally critical. This can be done through three types of rehearsals: introducing a plausible false positive, presenting a conflicting instruction, and testing the changeover between shifts. These rehearsals ensure that operators are prepared to handle unexpected situations and that the necessary information is retained and communicated effectively. \\[10pt] ## Practical Priorities for Plant Managers \\[10pt] For plant managers in ASEAN, the National Institute of Standards and Technology (NIST) roadmap for AI and machine learning in smart manufacturing highlights the need for reliable, explainable operation and the integration of complex industrial systems. This includes metrics for human-AI teaming and methods to evaluate operator understanding of AI solutions. An effective commissioning scorecard should include not just line speed, accuracy, and uptime, but also the time to register an operator challenge, the time to reach a qualified decision-maker, the share of challenges resolved with documented evidence, and the number of recurring faults discovered across shifts. \\[10pt] ## Conclusion: Ensuring Readiness for Production \\[10pt] Before signing off on the commissioning of a new robotic system, it is essential to conduct a final rehearsal where one operator disagrees with the robot while the whole team observes the process. If the response is uncertain, the workflow is not ready for a production shift. By ensuring that operators are well-prepared to handle disagreements, factories in Thailand, Vietnam, Indonesia, and Malaysia can maximize the benefits of automation while maintaining safety and efficiency. \\[10pt] **Takeaway for Factory Buyers:** Ensure that your commissioning process includes thorough testing of human-robot interaction, including rehearsals for handling disagreements. This will help you avoid costly mistakes and ensure a smooth transition to automated operations.