Dark factory: robotics and automation today
Actualizado: 2026-05-03
The dark-factory concept, also called lights-out manufacturing, has existed since the 1980s but was anecdote rather than model for decades. In 2025 that is changing. Xiaomi runs a plant in Changping capable of producing a smartphone every three seconds with just nine quality-control operators per shift. Foxconn has announced five dark factories in China. Fanuc has built robots with robots for 20 years in Oshino, Japan. The pattern is multiplying outside Asia too, though more slowly.
Key takeaways
- The strict definition is a factory that runs full shifts with no human presence on the production line; the practical definition is softer: minimal presence only for occasional intervention.
- Mature cases share three traits: few references with low variability, very high volume, and an also-automated input supply chain.
- The model breaks on variability: each reference change requires reconfiguring robotic cells, recalibrating vision, and adjusting trajectories — still often faster with human operators.
- Cobots (collaborative robots without safety cages) are gaining ground faster than the full dark model in Europe: cheaper, reusable across tasks, and socially less disruptive.
- Spain has very automated factories but no strictly dark factories: high product variability, strong union consensus, and the economics of the last human links explain the gap.
What defines a dark factory
The strict definition is a factory that can run full shifts with no human presence on the production line. The practical definition is softer: a factory where human presence on night or weekend shifts is minimal and limited to occasional intervention. Almost no real factory runs completely dark 24/7, but many run that way during lower-demand shifts.
Turning the lights off literally is practical. Robots do not need visible lighting, and human climate control is a significant cost in a large factory. Cutting lighting, cooling, and air conditioning for unstaffed hours saves between 15 and 25 percent of electrical consumption depending on plant type.
What does work in 2025
Mature dark-factory cases share traits:
- Few references with low variability: phones, flash memory, standardized electronics, serial mechanical parts. The more uniform the product, the easier to automate.
- Very high volume, which amortizes investment in specialized robotics.
- Input supply chain also automated: materials arriving on continuous conveyors or autonomous vehicles, not boxes someone has to open and sort.
Xiaomi’s Changping line is a good example: 11 fully automated production lines, computer vision at each station for defect detection, internal logistics with autonomous mobile robots, and a management system that coordinates everything.
Fanuc in Oshino produces industrial robots using industrial robots. The process is extremely mature because they have iterated for 20 years. The plant runs 24/7 and typically has one or two people supervising from a control room at night, not on the line.
Where the promise breaks
The model breaks on variability. Any process that handles dozens or hundreds of distinct references, with different geometries, heterogeneous materials, or frequent design changes, does not fit the full dark-factory model. Each reference change requires reconfiguring robotic cells, recalibrating vision, and adjusting trajectories, and that is still often faster with human operators.
Clear examples are European automotive plants that mix models on the same line. Volkswagen and Stellantis produce several models on a single highly automated line, but not in dark mode. The reason is not lack of technology but economics: frequent reference changes and product complexity make the marginal cost of removing the last operators exceed the savings.
Another break point is internal supply-chain reliability. In a well-running factory, a tilted part or a jammed screw is a rare incident an operator resolves in seconds. Without operators, that same incident can stop a full line for hours until someone arrives.
The cobot question
An interesting trend complicating the dark-factory definition is the rise of cobots, collaborative robots designed to work near humans without safety cages. Universal Robots, Rethink Robotics, FANUC CRX, and ABB’s collaborative lines have normalized over five years in mid-size factories, especially in Germany and the Nordics.
The cobot is the philosophical opposite of the dark factory. Instead of removing the operator, it augments them with a robotic partner that handles repetitive tasks while the human handles exceptions. The resulting model is not dark but hybrid: one person supervises two or three collaborative cells that together do the work of five traditional operators.
In practice this hybrid model is gaining ground faster than the full dark model in Europe. The reason is economic and sociopolitical at once. Cobots are cheaper than complex robotic cells, reusable across tasks, and their deployment does not require the same social consensus as closing a factory entirely to personnel.
Computer vision: the quiet enabler
The technical advance most pushing dark-factory viability over the last two years is computer vision. Industrial cameras combined with deep learning models have reached prices unimaginable five years ago. An inspection cell that cost 80,000 euros in 2019 now costs 15,000, detects more defect types, and trains in hours rather than weeks.
This changes the math because quality inspection was one of the last jobs where humans were hard to replace. Recent Vision Transformer-based models have closed that gap in many categories. In sectors like food processing, where product variability is intrinsic, this was the main bottleneck. In 2025 that is changing, though not overnight.
The Spanish reality
Spain has very automated factories but no strictly dark factories. SEAT in Martorell, Mercedes in Vitoria, or Gestamp in its stamping plants run at high automation with continuous human presence. The reasons match the rest of Europe: high product variability, strong union consensus, and economics where the last human links are cheaper than automating them.
There are exceptions in specific sectors. Some electronics component plants in Catalonia and the Basque Country run partially dark shifts, and several pharmaceutical plants have critical areas without humans at night, more for hygiene than cost.
The transition toward more darkness in Spain will likely pass through cobots and robotized cells in sectors with high cost pressure and low variability. We will not see a Spanish automotive plant running 100% dark this decade, but we will see more autonomous cells inside hybrid plants.
My take
The dark factory is a real model, mature in certain sectors and geographies, but exaggerated in general applicability. Painting it as the universal future of manufacturing ignores that product variability, changeover economics, and limits of automated fault detection still strongly condition where going human-free pays off.
For an average Spanish manufacturer the reasonable horizon is not dark factory but intelligent automation with smaller teams and integrated cobots. That transition is already underway and is far less disruptive than the full-darkness promise. Investing today in collaborative cells and computer vision is concrete progress toward the future.
What matters to understand from Spain is that Chinese dark factories already compete with us on production cost for certain products. Responding by trying to replicate their exact model makes no sense, but understanding where labor cost is the dominant factor and where it is not does. In sectors where labor is 40% of cost, the Chinese dark factory is unbeatable medium-term. In sectors where labor is 10%, the difference is nearly irrelevant and there is room to compete on design, quality, and flexibility. Smart industrial strategy identifies which is which instead of trying to win a race that cannot be won.
