With the fourth generation - Industry 4.0 - the industrial revolution has reached a point where human labour can be supplemented or replaced by fully autonomous systems. At the centre of this development is the concept of the dark factory, a vision of fully automated factories that operate without light, breaks or human presence. However, such complete automation poses a major challenge and requires considerable investment and reorganisation.
What is a Dark Factory?
A dark factory is a production or logistics facility that is operated exclusively by machines, autonomous robots and digital technologies. The ‘dark’ in the name symbolises that these facilities can theoretically operate without light, as no human presence is required - theoretically, because certain optical sensors and cameras still require light to function correctly. These factories are designed to maximise efficiency, precision and productivity and use state-of-the-art technology to operate around the clock.
Features of a Dark Factory
Complete automation
All work processes - from the delivery of materials to the completion of a product - are controlled by machines, robots and AI. Human intervention is minimised or not necessary.
24/7 operation
As machines do not require breaks, a Dark Factory can work without interruptions, which significantly increases productivity.
Cost reduction
Operating costs are reduced due to the elimination of lighting, heating and other energy-intensive requirements for human workstations.
IoT and AI integration
Networked machines continuously collect and analyse data in order to optimise processes, minimise errors and increase productivity.
Adaptability
Dark factories utilise flexible automation technologies to adapt quickly to new requirements or product changes.
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The Rise of the Dark Factory: Fully Automated Production Floors
A Silent Revolution on the Shop Floor
Factories have long symbolized industrial progress, buzzing with human activity and machinery. However, the era of Industry 4.0 is rewriting this image. Today, “dark factories” are emerging production fcilities that operate entirely autonomously, often without human presence or even lights. These factories leverage advanced robotics, artificial intelligence (AI), Internet of Things (IoT) devices, and predictive analytics to function as self-sustaining ecosystems.
The rise of dark factories reflects a broader industrial shift, where companies pursue continuous production, high precision, and resilience against supply chain disruptions. While the promise of fully automated production is compelling, it also raises questions about workforce transformation, policy frameworks, and global competitiveness.
From Lean Manufacturing to Lights-Out Production
The idea of fully automated factories is not new. Experiments in the 1980s, such as General Motors’ lights-out initiatives, revealed the potential for autonomous operations but faced technological barriers. Robotics lacked dexterity, sensors were primitive, and computing systems could not coordinate complex workflows.
With Industry 4.0, these barriers are collapsing. Today, dark factories integrate AI-driven robotics, IoT sensors, autonomous material handling, and digital twins. Robots can assemble products, conduct inspections, and self-correct errors. IoT devices monitor machinery in real time, feeding data into cloud and edge computing systems to optimize production and predict maintenance needs. AGVs, drones, and robotic arms manage logistics without human intervention. This convergence allows factories to operate 24/7 with minimal errors and reduced costs, achieving precision and efficiency previously unimaginable.
Industrial Advantages and Adoption Drivers
The adoption of dark factories is fueled by several compelling advantages that make fully automated production an attractive strategy for manufacturers worldwide. Cost efficiency is a primary driver: robots operate without wages, breaks, or overtime, and their precision reduces errors and waste, translating into significant long-term savings for businesses. In an era where operational margins are tight, these savings can be a decisive competitive advantage.
Another key factor is continuous production. Unlike human-operated factories, dark factories can run 24/7 without fatigue, meeting the growing demand for rapid delivery and mass-customized products. This capability is particularly valuable in industries where speed-to-market is critical, enabling companies to respond quickly to changing consumer needs and market fluctuations.
Quality and precision are also central to the appeal of dark factories. AI-powered robotics and computer vision systems ensure consistent output across every unit, while real-time defect detection reduces material waste and enhances customer satisfaction. This level of reliability is especially important for high-precision sectors such as electronics, aerospace, and pharmaceuticals, where even minor errors can have significant consequences.
Dark factories also help mitigate labor shortages, a pressing concern in regions with aging populations or declining skilled labor pools, such as Europe and Japan. By automating repetitive or physically demanding tasks, manufacturers can maintain productivity even as the availability of traditional workers declines.
Safety is another advantage: hazardous or monotonous work can be fully automated, reducing workplace injuries and improving occupational health. Meanwhile, scalability allows production lines to be reprogrammed quickly for new products or variants, giving companies the flexibility to adapt to evolving market demands without extensive downtime or retraining. Collectively, these factors make dark factories a strategic investment for industries requiring high levels of precision, speed, and reliability, including electronics, automotive, aerospace, and pharmaceuticals.
Global Case Studies
The potential of dark factories is illustrated by several leading examples around the world. Siemens’ Amberg Electronics Plant in Germany operates almost entirely lights-out, achieving a remarkable 99.99885% quality rate. Human involvement is largely limited to supervising AI systems and optimizing operations, demonstrating how automation can handle complex, high-precision tasks with minimal human oversight.
In Japan, Fanuc’s robotics plant showcases another extreme of automation: the facility can run for up to 30 days without human supervision, highlighting the feasibility of fully autonomous industrial operations on a large scale. This approach not only improves efficiency but also reduces dependence on human labor for routine tasks.
In the United States, Tesla’s Gigafactories integrate extensive AI and robotics into battery and electric vehicle assembly. While not fully dark, these facilities demonstrate a hybrid model of automation, combining human expertise with machine precision to achieve scalability and rapid production.
China’s Shenzhen electronics factories provide another perspective, producing smartphones and other components with minimal human intervention. These factories exemplify how automation can support high-volume, precision manufacturing while maintaining cost efficiency and operational speed.
Together, these case studies demonstrate that dark factories are commercially viable, scalable, and strategically significant. They represent a new paradigm in manufacturing, offering unprecedented efficiency, precision, and adaptability, and positioning companies to compete more effectively in a global industrial landscape.
Adoption Statistics by Industry
The adoption of AI in manufacturing has accelerated significantly in recent years, with Germany serving as a prime example of this trend. Between 2020 and 2023, the percentage of German manufacturers utilizing AI rose from just 6% to 13.3%. This rapid growth underscores how quickly Industry 4.0 technologies are reshaping traditional production environments. Projections suggest that by 2030, AI-driven manufacturing could have a substantial economic impact, boosting productivity, enabling highly customized production, and supporting Germany’s position as a leader in advanced industrial engineering.
In the services sector, the uptake of AI has been even more pronounced. By 2024, nearly 40% of service-sector firms worldwide reported using AI to enhance operations, customer service, and back-office efficiency. Importantly, about 34% of these firms have invested in retraining their workforce, ensuring employees can adapt to new roles created by automation. This dual approach adoption of AI alongside workforce upskilling illustrates how services are balancing innovation with inclusivity, ensuring that the benefits of automation extend beyond cost savings to workforce transformation.
The electronics and automotive industries have emerged as clear frontrunners in the application of AI-driven robotics and automation. These sectors are leveraging predictive maintenance systems, machine vision for quality control, and autonomous logistics solutions, enabling them to achieve higher operational efficiency and tighter quality benchmarks. In the automotive sector, AI is integral not just in assembly lines, but also in supply chain optimization and electric vehicle production. Meanwhile, the electronics industry benefits from precision manufacturing and accelerated innovation cycles, driven by the integration of smart automation technologies.
Research consistently highlights the tangible benefits of AI adoption across industries. Companies implementing AI in production environments report productivity gains ranging from 20% to 40%, alongside significant reductions in defect rates and operational downtime. Additionally, AI-enabled automation shortens time-to-market for new products, giving companies a critical edge in highly competitive global markets. These statistics reinforce the idea that AI is not simply a cost-cutting tool it is a strategic enabler of innovation, agility, and long-term competitiveness.
Country-Wise Trends and Policy Insights
United States: AI investment reached $67.2 billion in 2023, nearly nine times higher than China. The U.S. emphasizes AI regulation and governance, with 21 agencies overseeing AI technologies.
Germany: Strong adoption in manufacturing is backed by policies supporting smart factories and industrial automation. Incentives for AI deployment in Industry 4.0 initiatives have accelerated adoption.
United Kingdom: The AI market exceeds £21 billion in 2025, with plans to integrate AI into public services and industry, aiming to become a global AI superpower by 2035.
European Union: Denmark leads with 27.58% of enterprises using AI, followed by Sweden (25.09%) and Belgium (24.71%). Romania lags at 3.07%. EU regulations focus on balancing innovation with ethical AI use and data privacy.
United Arab Emirates: The UAE Strategy for AI aims to position the country as a global leader by 2031, promoting AI across healthcare, energy, transportation, and governance.
These trends indicate that policy frameworks, investment incentives, and workforce strategies are key drivers of adoption, in addition to technological readiness.
Challenges and Risks
While dark factories promise efficiency, cost savings, and scalability, their adoption is not without hurdles. One of the most significant barriers is the capital investment required. Building a fully automated facility involves substantial upfront costs for robotics, AI platforms, IoT sensors, and supporting digital infrastructure. For large multinational corporations, this investment can be justified through long-term gains, but for small and medium-sized enterprises (SMEs), such costs often remain prohibitive, limiting widespread adoption.
Cybersecurity presents another critical challenge. Dark factories, by design, are fully connected ecosystems, with every machine, sensor, and control system linked through networks. This connectivity makes them highly vulnerable to cyberattacks, industrial espionage, and data breaches. A single breach could halt operations across an entire factory, potentially leading to massive financial and reputational damage. As a result, building robust cybersecurity frameworks has become as important as installing robots or AI systems themselves.
Reliability is also a key concern. Even the most advanced machines and AI-driven systems are not immune to errors, breakdowns, or unforeseen failures. Downtime in a dark factory can be particularly costly, as there are few or no human workers on-site to intervene quickly. This makes predictive maintenance systems, redundancy planning, and remote troubleshooting capabilities essential for minimizing risks and ensuring operational continuity.
Beyond technical issues, ethical considerations loom large. The displacement of workers in repetitive or manual roles is an inevitable consequence of large-scale automation. Policymakers and business leaders face the challenge of ensuring equitable access to reskilling programs, creating pathways for displaced workers to transition into higher-value roles. Moreover, governance frameworks must be developed to ensure AI systems are transparent, explainable, and aligned with ethical business practices. Without addressing these concerns, the promise of dark factories could be overshadowed by societal pushback and inequality.
Future Outlook: Beyond Dark Factories
Dark factories represent only the beginning of a broader shift toward fully autonomous, intelligent manufacturing ecosystems. The next frontier lies in cognitive manufacturing, where AI systems do more than execute instructions they make autonomous production decisions, optimize energy usage, and manage maintenance schedules with little to no human oversight. This will mark a fundamental transformation in how factories think and operate, evolving from programmable automation to adaptive intelligence.
Another promising development is the move toward sustainable manufacturing. By leveraging smart automation, factories will play a pivotal role in advancing the circular economy. AI systems can minimize waste, optimize resource consumption, and reduce energy intensity, turning sustainability from a regulatory requirement into a competitive advantage. This transition will not only lower environmental footprints but also open new business models centered on recycling, reuse, and sustainable innovation.
Equally transformative is the rise of augmented human collaboration. Instead of working directly on assembly lines, human operators will supervise and manage multiple factories remotely. Using digital twins, augmented reality (AR), and virtual reality (VR) platforms, workers will be able to monitor production, simulate scenarios, and troubleshoot issues in real time, regardless of physical location. This knowledge-driven oversight ensures that while machines handle repetitive, dangerous, and data-intensive tasks, humans can focus on creativity, strategic thinking, and ethical decision-making.
Ultimately, the future of dark factories is not about replacing humans but redefining their role. As machines take over execution, humans will be freed to concentrate on innovation, design, and leadership. The synergy between autonomous systems and human intelligence will shape the factories of tomorrow not as dark and empty spaces, but as intelligent ecosystems where efficiency, sustainability, and human creativity coexist.
Dark factories symbolize the next frontier of Industry 4.0, combining autonomy, intelligence, and efficiency to transform manufacturing. They promise continuous, precise, and resilient production, while also reshaping the workforce and global industrial landscape. For industrial leaders, CIOs, and policymakers, the challenge is clear: embrace automation while managing workforce transitions, cybersecurity, and ethical governance. As the lights dim on traditional production floors, the opportunities for innovation, operational efficiency, and global competitiveness have never been brighter.
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The Tech Enabling China's 'Dark Factories'
They are not just prototypes or experiments. They are the beginning of a transformation. China is entering a new age of manufacturing with the rise of 'dark factories,' fully automated facilities that operate without any human workers or even lights. Inside these eerily quiet plants, robotic arms weld, cut, and assemble products nonstop. Fleets of autonomous vehicles deliver materials across factory floors without human oversight.
As they are built entirely around machines, these factories eliminate the need for lighting, heating, break rooms, and other human-centric infrastructure.
The result is a system optimized for continuous productivity. It reduces costs, improves precision, and functions at all hours. Powering this new production paradigm is a convergence of technologies such as artificial intelligence (AI), advanced robotics, the Internet of Things (IoT), and dense sensor networks. Together, they create self-regulating ecosystems where machines work together with extraordinary coordination, even with the lights off.
Core Technologies: The Pillars of Automation
At the center of every dark factory is an army of robotic workers. These include not only robot arms that weld and paint but also specialized machines that handle tasks like microassembly, product inspection, and polishing. China has become the global leader in industrial robot deployment. In 2022, it installed over 290,000 units, which accounted for more than half of the world’s total.
By 2023, China’s robot density had reached 392 per 10,000 workers, significantly above the global average of 141. Companies like Foxconn are leading this shift. The electronics giant has replaced over 60,000 workers at its Kunshan factory with robots and aims to automate 30 percent of its operations by 2025. Similarly, BYD, a key player in electric vehicles, has installed robotic systems across its battery and vehicle body manufacturing lines.
Mobile robotics are just as vital. Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) move materials across the floor, reposition tools, and deliver parts. In Jetour Auto’s Fuzhou factory, these mobile robots have cut logistics time by more than 40 percdnt and helped reach an output of one completed car every 100 seconds.
Artificial Intelligence: The Brain Behind the Operation
A dark factory needs more than robots. It needs intelligence that can manage those machines. Artificial intelligence fills that role. AI functions as the factory’s brain by directing robot movements, analyzing data in real time, and making continuous adjustments to keep systems efficient.
At Xiaomi’s smart factory in Changping, the AI platform HyperIMP oversees every aspect of production. It coordinates 11 robotic production lines, monitors equipment health, and reroutes tasks when issues arise. This coordination allows the plant to produce one smartphone every 3 seconds, without manual oversight.
AI is also used in machine vision systems that detect flaws and maintain product quality. These systems can find microdefects that humans would likely miss. Siemens has reported a 99.99 percent product quality rate in its automated facilities, and Xiaomi is reaching a similar level of consistency with its vision-based inspections.
Another crucial role of AI is predictive maintenance. Instead of waiting for machines to fail, AI analyzes sensor data such as temperature, vibration, and motor current. It identifies wear patterns and schedules maintenance before breakdowns occur. The manufacturing sector is expected to gain $3.8 trillion by 2035 from AI adoption. Jetour’s 'Smart Brain' platform has reduced downtime at its Fuzhou facility by more than 60 percent and has improved assembly accuracy across the board.
IoT and Sensor Networks: The Central Nervous System
The IoT and sensor networks act as the nervous system of a dark factory. Every machine is connected through high-speed networks and constantly shares status updates, location data, and quality metrics. This web of data enables real-time adjustments.
Sensors play a critical role in guiding robots. Cameras, infrared sensors, laser scanners, and LIDAR devices help machines perceive their environment. These technologies make it possible for AGVs to navigate in total darkness and for robot arms to place components with micrometer-level accuracy.
All of this data is collected and processed by AI systems, which analyze it to optimize the workflow. At Gree Electric’s 5.5G-enabled smart factory in Zhuhai, this full-stack integration has improved overall production efficiency by 86 percent.
Operational Advantages Driven by Technology
These combined technologies create significant operational benefits. One of the most obvious is 24/7 production. Without human workers, dark factories do not require breaks, shift changes, or holidays. Machines can keep running continuously.
Costs are also significantly reduced. Companies save on salaries, training, and safety measures. They also reduce utility expenses by eliminating the need for lighting, air conditioning, and other systems designed for people. According to the International Energy Agency, dark factory automation can lower industrial energy use by 15 to 20 percent.
Dark factories also deliver extremely high precision. Robotic systems can operate with consistency that surpasses human capabilities. When paired with real-time vision inspection, this leads to fewer defects and higher product reliability.
Another key advantage is cleanliness. Contamination risks drop dramatically with very few humans involved. This is especially important for industries like semiconductors, medical devices, and electronics, where clean environments are critical.
Finally, automated facilities offer resilience. They are less vulnerable to labor disruptions caused by pandemics, strikes, or demographic shifts. This makes them more stable in a volatile global supply chain environment.
The Human Element: Skills for the Factory of the Future
While dark factories require little human intervention on the shop floor, people remain critical to their success. These automated environments still depend on experts to design robotic systems, oversee AI, maintain equipment, and resolve issues. As automation advances, the worker’s role is shifting from manual labor to skilled technical and supervisory positions that support continuous operations.
Essential roles now include AI system trainers, robotics technicians, data analysts, IoT specialists, and cybersecurity professionals. These workers ensure that smart factory systems communicate efficiently, adapt to real-time data, and stay secure. With rising complexity, manufacturing increasingly values interdisciplinary expertise that combines engineering, software development, and data science.
To secure roles in these environments, candidates should highlight skills like Python, PLC programming, SCADA systems, and machine vision. Familiarity with platforms such as TensorFlow, ROS, and MES software is highly regarded. Industry certifications from Siemens, FANUC, or Cisco are also beneficial. Soft skills, including real-time problem-solving and cross-functional communication, are important for leadership and systems oversight.
To meet growing demand, companies and Chinese agencies are investing in reskilling programs. Xiaomi began retraining assembly workers as robotics technicians in 2024, and Gree Electric collaborates with institutes to prepare workers for 5.5G factory roles. The future of manufacturing will depend on how effectively humans are trained to manage, improve, and collaborate with machines.
Case Studies: Xiaomi’s Changping Smart Factory
Xiaomi’s $330 million dollar factory in Beijing spans 81,000 square meters and is one of China’s most advanced dark factories. It is capable of producing 10 million smartphones annually. Inside, 11 robotic lines operate continuously, managed by the company’s proprietary HyperIMP AI system. Vision systems monitor quality, while AGVs handle logistics. The plant can manufacture one smartphone every 3 seconds with zero human involvement on the production floor.
Jetour’s Fuzhou Dark Factory
Jetour’s Fuzhou facility produces SUVs with near-total automation. Over 300 robots carry out welding, painting, tire installation, and even CNC bonding of windshields. It builds a car every 100 seconds and uses its 'Smart Brain' AI to oversee equipment, quality, and scheduling. AMRs and AGVs support flexible logistics, which has helped the factory reach daily efficiency goals faster than previous plants.
Other Industry Leaders
Changying Precision Technology reduced its workforce by 90 percent in one facility by switching to robotics. Output increased, and error rates fell. Meanwhile, Gree Electric’s Gaolan facility uses 5.5G connectivity to support real-time machine learning and ultra-fast response times. These upgrades led to an 86 percent boost in output efficiency.
Strategic Drivers and Global Context
The growth of dark factories aligns with China’s 'Made in China 2025' policy. This strategy aims to upgrade the nation’s manufacturing base by promoting automation and advanced technologies. In 2023 alone, the government invested $1.4 billion in robotics research and development, along with further subsidies to promote AI and smart factory adoption.
China’s labor costs have risen in recent years, making automation economically attractive. At the same time, international competition is increasing. Countries such as Germany, the United States, Japan, and South Korea are also investing heavily in automation. However, China’s scale and state-level support allow it to move faster and deploy technology more widely than many peers.
China’s dark factories are not just prototypes or experiments. They are the beginning of a transformation in how products are made. By uniting robotics, AI, IoT, and sensing technologies into fully autonomous systems, these facilities achieve new levels of speed, quality, and reliability.
The benefits are clear, but the shift raises important questions about the future of human labor and economic structure. As machines become more capable, companies and governments will need to invest in new skill development and social planning. China is leading the way, and the rest of the world is watching as dark factories illuminate the path to the next industrial era.
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What are 'Dark Factories,' and Do They Really Exist?
The first Industrial Revolution profoundly changed the way goods are manufactured, resulting in then-unthinkable gains in productivity, quality control, and consistency. Since then, three more revolutions have occurred, with manufacturers currently reaping the industrial automation benefits of Industry 4.0.
Theoretically, the next step in this evolution would be full automation, in which workers are no longer needed to create output. Known as a dark factory, this environment is fully automated, with no required human labor. Without this, such a facility can literally operate in the dark, without heat, light or other environmental needs – hence, the “dark factory” moniker – to serve a workforce.
Do Dark Factories Actually Exist?
“There’s always the story out there that there’s that one facility somewhere, usually in some faraway or unknown place,” said Guy Courtin, vice president of Industry and Advanced Technology for Montreal-based Tecsys, a supply chain software provider. “But if it exists, it would seem to be less of an actual production facility and more of a display that it can be done. Even if a fully automated facility exists, you probably still need at least some full-time employees to maintain that automation. So, is that truly a dark factory? Under the definition, no.”
There are certainly shades of gray in this concept. Unlike a dark factory, a fully automated factory relies on robotics to perform tasks, but that equipment still needs to be maintained by humans. Another take on the concept is the use of cobotics, the collaborative robots that help employees do their jobs.
“In theory and in practice, could you have a dark shift in a factory?” asked Courtin. “That’s entirely possible and more likely. For example, there could be a fully autonomous, robotic overnight shift that works in the dark that preps workstations with inventory. Or orders could get pre-picked in a warehouse and be ready for processing and shipping by the next FTE shift.”
While the concept of a true dark factory has certainly captured attention within the industry, it is much like an elusive unicorn. Rumors, yes. Actual proof and implementation? Not really.
“Right now, we’re more in a state where companies are less interested in implementing the full dark factory concept and more focused on how automation can complement labor, and this nuance gets lost in the excitement of robots,” he said.
Some operations are already implementing automated forklift technology, which relies on a variety of components – from wrap-around cameras to microphones – to allow for remote operation by employees. Taking this technology a step further are autonomous guided vehicles (AGV), which remove the human operator completely by using pre-programmed routes and tasks.
Other operations are pushing forward with additional autonomous applications. Europe’s largest pork processing plant, located in Denmark, uses human labor to start the processing, but robotics quickly take over. Using infrared technology to assess each hook, a series of six robots processes up to 18,000 units per shift. Human-powered processing lines typically process an average of 977 units an hour or around 7,800 per eight-hour shift.
A diesel automotive facility in China has also implemented more of a dark-factory approach to automate its assembly line more fully. Sensors embedded in the robotics alert workers when bottlenecks occur, or when the machine’s state and run time require human intervention. Integrating advanced analytics and Internet of Things (IoT) technology has also helped the facility use predictive maintenance to avoid equipment breakdowns.
“Automotive manufacturers have been applying this type of technology for years,” said Courtin. “That industry already knows that there are certain functions that are better suited to robotics – tasks that are repetitive or dangerous, for example.”
But at the same time, robotic technology has not advanced past human capacities in certain areas. “There are just some things human beings still do better,” said Courtin. “We remain better than robots at picking parts out of a box, for example.”
Humans also have a much greater capacity to troubleshoot. A simple issue that can be resolved by human understanding and reasoning can cause a robotic shutdown if it is outside of the program or beyond the capacity of the machine’s learning and artificial intelligence (AI). Humans also have much greater abilities to communicate, assess a situation, and infer conclusions within a system or organization. Robotics and machinery are fairly limited to error codes, streams of data, and other purely objective information. To use this information, automation must still be trained using AI and machine learning.
Pros and Cons of Automated Factories
With businesses perpetually focused on ways to improve efficiencies, cut costs and advance productivity, automation and robotics certainly are on the manufacturing and supply chain radar. Courtin noted automation helps eliminate natural human reasons to be away from work, such as illness or family vacations.
“They don’t have to commute, so they’re not burning fossil fuels in cars to get to and from work,” he added.
Human error is removed from the automation equation, along with attitude problems, homelife distractions, politics and workplace conflict. The human-nature, soft-issue problems that can plague workplaces around the world are removed when humans are replaced by robotics.
While in theory full automation might make sense in some cases, implementing it isn’t always so easy.
“What isn’t often talked about is the relationship with labor,” said Courtin. “Using automation poses the threat to reduce head count. There’s a certain uneasiness in introducing automation in that respect. It’s a delicate line to walk.”
On the other side of the equation, a dark factory could remove existing labor needs and concerns, an advantage in countries where labor costs are high. In parts of the world where labor costs are low, the ROI on a dark factory may take years.
“Creating a true a dark factory means that you don’t have to locate your facility near an established workforce – so you could build one where property values are less expensive,” said Courtin. “But then you also have to keep in mind logistics: if you’re really remote, there are also going to be extra supply chain and fulfillment costs.”
Labor and workforce issues aside, many existing factories also lack the ability to retrofit robots due to their age and infrastructure, making the concept an expensive proposition to consider.
Some manufacturing facilities are decades old and are often in brownfield locations. A conversion to a dark factory would require a significant capital investment, along with a suspension of operations, so that the new equipment can be installed, calibrated and tested before operations resume. Building from scratch assumes that the operation would never need labor, which can limit the facility’s future should operations ever change.
Yet, the concept intrigues the manufacturing industry. Whether fully dark factories every become the norm or not remains to be seen.
“Being able to run a factory 24/7 with [limited] labor and high efficiencies – that’s really the holy grail of manufacturing,” says Courtin. “You can definitely understand the interest.”