Why Robot Adoption Is Lagging in Food, Cosmetics, and Pharmaceutical Manufacturing
As the push for digital transformation and automation grows across manufacturing, robot adoption rates vary widely by industry. Automotive and electronics have used industrial robots for decades. But in food, cosmetics, and pharmaceuticals—the industries closest to our daily lives—production floors still rely heavily on manual labor for repetitive, physically demanding tasks.
Why is automation so far behind in these sectors? This article explores the worsening labor shortage, breaks down the fundamental barriers holding back existing robot technology, and outlines practical solutions for the modern production floor.
The Worsening Labor Shortage in Manufacturing—and the "2027 Cliff"
A Labor Crisis That's Already Locked In
Before exploring why robot adoption has lagged, it's important to understand the critical situation facing Japan's manufacturing sector. The labor market is approaching a major turning point known as the "2027 Cliff." Labor supply is projected to drop sharply starting in 2027, with a nationwide shortage of approximately 11 million workers by 2040.
This isn't a cyclical downturn—it's a demographic certainty. In manufacturing, 66.7% of businesses already cite labor shortages as a challenge affecting their operations as of 2024.* Production systems that depend on manual labor are heading toward a hard limit.
(*Source: Ministry of Economy, Trade and Industry, White Paper on Manufacturing Industries 2025)
Robot Adoption in Small and Mid-Sized Factories: Only Around 30%
Automation is urgently needed, yet a stark gap exists between large and small manufacturers. While 66.7% of companies with 300+ employees have adopted robots, the rate drops to just 32.1% for those with 50 or fewer employees.*
Food, cosmetics, and pharmaceutical industries are dominated by small and mid-sized factories handling high-mix, low-volume production—and this directly contributes to the slow adoption across these sectors.
(*Source: Ministry of Economy, Trade and Industry, White Paper on Manufacturing Industries 2025)
Why Adoption Stalls: The 4 Barriers Facing Conventional Robots
High-performance robots are already common in automotive manufacturing—so why haven't they spread to food, cosmetics, and pharmaceutical factories?
The answer lies in how traditional industrial robots are designed: for large-scale, single-product production lines. This creates four major barriers for industries that don't fit that mold.
1. The Space Barrier: Factories Are Too Tight for Large Robots
Most food and cosmetics factories operate in existing buildings where conveyors and equipment are already packed in tight. There's little room to add anything new.
Traditional industrial robots aren't just large—they also require safety fencing to protect workers. This means installations often need a footprint of 5 meters square or more. For factories with cramped production lines, retrofitting simply isn't physically possible.
2. The Knowledge Barrier: Complex Operation, No In-House Expertise
Operating a robot requires "teaching"—programming its movements. With conventional robots, this means using a dedicated device (a teach pendant) to manually input coordinates one by one. Even for a skilled technician, this takes around 8 hours.
Automotive plants often have specialists on staff, but food and pharmaceutical facilities typically don't. Every time a product changes, you'd need to call in an outside integrator (SI). For high-mix, low-volume production, this becomes a critical bottleneck.
3. The Cost Barrier: High Upfront Investment and Major Construction
The biggest obstacle to robot adoption is upfront cost. Beyond the robot itself, you're looking at safety fencing, layout changes for conveyors and peripheral equipment, and significant installation work.
Total initial investment can easily climb into the hundreds of thousands of dollars. For small and mid-sized factories with limited budgets, the ROI simply doesn't add up—and many are forced to abandon automation altogether.
4. The Technology Barrier: Irregular Shapes, Bulk Piles, High-Mix Production
Food and cosmetics production presents a unique challenge: the nature of the products themselves. Unlike metal parts, these industries handle "irregularly shaped items" that shift and deform.
Picture a bento box line with sauce packets, wasabi pouches, and noodle broth sachets piled randomly. Traditional camera systems and robots struggle to accurately detect the position of overlapping, shifting objects. What's easy for a human hand and eye is extremely difficult for a machine—which is why tasks like placing sachets or packing boxes have remained stubbornly manual.
Next-Generation AI Collaborative Robots: Breaking Through the Barriers
In recent years, breakthrough technology has emerged to overcome the four barriers unique to food, cosmetics, and pharmaceutical manufacturing. The game-changer: compact, easy-to-use collaborative robots powered by AI and advanced software.
Closer Robotics, an AI robotics company spun out of the University of Tsukuba, delivers solutions built specifically for this underserved space—automating small and mid-sized production lines.
No Expertise Required. Space-Saving. Designed for Real Factory Floors.
Closer's compact collaborative palletizing robot, Palletizy, automates the heavy labor of stacking cartons and bags weighing 20–30 kg onto pallets.
The key advantage: as a true collaborative robot, Palletizy works safely alongside people—no safety fencing required. This makes it possible to retrofit even the tightest existing spaces. A patented auto-layout feature delivers smartphone-like touchscreen operation, so staff with zero robotics experience can complete setup in as little as 3 minutes—just enter the box and pallet dimensions.
Advanced AI Vision Makes Irregular Item Picking Possible
For sachet placement—a task long considered impossible to automate—Closer's PickPacker steps in.
Proprietary 3D vision AI and advanced robot control technology enable PickPacker to instantly recognize and locate randomly piled sachets (sauce packets, wasabi pouches, and more), then pick them at high speed. This brings flexible, human-replacement automation to high-mix, low-volume lines in food and cosmetics factories.
Summary:
Don't Wait Until Manual Labor Hits Its Limit. Consider Closer's Robot Solutions.
The slow adoption of robots in food, cosmetics, and pharmaceutical manufacturing isn't due to a lack of effort on the factory floor. The real issue: existing robots were too big, too complex, too expensive—and couldn't handle irregularly shaped items. These were structural barriers, not operational failures.
But technology has evolved. The old assumptions no longer hold.
With the "2027 Cliff" fast approaching and labor shortages threatening business continuity, the path forward is clear: let machines handle the heavy lifting and repetitive tasks, and free your people for higher-value, more creative work.
Have you given up on automation because your factory is too small, you don't have robotics expertise, or the budget isn't there?
At Closer Robotics, engineers with deep experience in food, cosmetics, and pharmaceutical production deliver AI-powered robots that let you start small—no major construction required. Our systems are already running on smaller lines at major food manufacturers, changing what's considered "normal" on the factory floor.
If labor shortages are holding you back, it's time to explore how Closer's AI robots can eliminate heavy labor and boost productivity.
The factory of the future starts here—and it starts now.
