Dark Factories, Warehouses

Companies like Amazon and Ocado have achieved significant success with automated warehouses. Amazon's robotic warehouses have made order processing faster and more efficient, yet even these are not fully automated systems. Human labor remains essential, particularly for supervision, maintenance, and more complex tasks. Similarly, Xiaomi has made significant strides in automated manufacturing, especially in producing rapidly changing technological devices. However, human labor remains crucial in their factories too, particularly for quality control and complex manufacturing processes.

In contrast, experiments by companies like Adidas and Tesla have questioned the widespread applicability of this model. For instance, Adidas eventually shut down its Speed Factory projects as fully automated production did not yield the expected benefits. Elon Musk also admitted that "excessive automation" in Tesla's factories proved to be a mistake, and he continues to emphasize the importance of people in the manufacturing process.

Fully automated warehouses and factories have still not been widely realized because the technology, although advanced, is still not flexible or reliable enough to automate every manufacturing process. Many manufacturing processes are complex, variable, and require human decision-making, which current automation technologies cannot yet fully replace. Furthermore, the high initial costs of automation and the maintenance demands of the technological infrastructure can also hinder a complete transition. The flexibility and problem-solving abilities of human workers remain crucial, especially in situations that machines are not pre-programmed to handle.

However, automation remains the most significant area and opportunity for increasing productivity. Developments and experiments in this field are ongoing. The obstacles that have hindered the realization of lights-out factories so far are expected to diminish soon.

Transformation into a Lights-Out Factory

Globally, there are already innovative examples (beyond the aforementioned retail giants) that demonstrate the long-term viability of lights-out factories.

Overcoming Challenges: Transitioning to automation involves overcoming numerous technical and financial hurdles. For instance, processes within factories are often predefined and easily automatable, but the deployment and maintenance of robots still require expertise.

Adaptation and Redesign: For tasks that cannot be easily automated, creative solutions are needed. For example, the 'kitting' task (see Moravec's Paradox), which is challenging for robots, was addressed in one instance by implementing a QR code-based warehousing system, allowing robots automatic identification and task execution.

Kitting is a concept used in robotic manufacturing and assembly processes that involves the robot pre-collecting and organizing necessary parts, tools, and other items for a specific task or product. This approach increases productivity, reduces the chance of errors, and supports lean manufacturing principles. Performing kitting tasks can be challenging for robots. Identifying, grasping, and arranging parts of various shapes and sizes requires complex coordination from the robot. Preparing and handling tools and other supplies demands additional sensing and manipulation capabilities. Furthermore, kitting often involves variable, unique tasks, which poses difficulties for robots compared to repetitive, pre-programmed operations. Therefore, enhancing robot flexibility and adaptability is crucial for successful kitting execution.

AI: The Key to a New Era of Automation

The rapid development of AI technology is opening up new possibilities for lights-out factories. AI-powered robots can perceive and adapt to the manufacturing environment, thereby increasing factory efficiency and reliability.

Simpler Instructions: With AI, programming robots becomes much simpler, reducing the costs of automation. Applications now exist that allow robots to be controlled using voice or text commands.

Flexible Task Execution: Instead of traditional robots specialized for a single task, general-purpose AI robots are coming to the forefront, capable of performing multiple types of tasks, thereby increasing factory efficiency.

Situational Adaptation: With AI technology, robots will be able to adapt to changing industrial environments. This flexibility is particularly important for lights-out factories, where technology is constantly evolving.

On the Threshold of the Future: Prepare for the Automated World

The future of automation no longer hinges solely on technological barriers. Decisions will increasingly depend on economic factors and corporate agility. Manufacturers ready to adapt quickly stand to gain significant advantages in this new era.

Automation is not just about reducing production costs. The introduction of robots and AI-based systems fundamentally transforms how companies operate. Beyond increasing the efficiency of manufacturing processes, it opens up new opportunities for better data utilization and informed business decision-making. For example, the continuous data stream generated by robots allows managers to make decisions based on real-time information, thereby reducing the risk of errors and downtime.

Furthermore, automated systems can adapt more flexibly to changes in market demand. AI-powered robots and systems can quickly reconfigure themselves to produce new products or optimize processes without significant human intervention. This flexibility is especially important in rapidly changing industries, where rapid response is essential for maintaining a competitive edge.

However, automation brings not only opportunities but also significant challenges, particularly for the workforce.

The emergence of 'dark' factories and warehouses fundamentally changes the structure of workplaces and the skills required. The introduction of new technologies means that many current jobs may disappear, while other, technology-oriented roles will come to the fore. Operating, maintaining, and optimizing automated systems will require new skills, the acquisition of which can pose a significant challenge for employees.

It remains uncertain whether fully automated facilities will create as many new jobs as they eliminate. This is a question of paramount importance not only from an economic perspective but also from a social one. The scale and speed of this transformation will be crucial in determining how workers and society can adapt to the new circumstances. Companies capable of managing this transition humanely may gain an advantage not only in the technological race but also in terms of social responsibility.