CHICAGO — Artificial intelligence.
Five or six years ago, AI that could think and create was something you could only encounter in the world of science fiction.
The speed of technological advancement. The past few years have seen an increase in the options for generative AI in almost every area of daily life and business operations. This also includes industrial and institutional laundry.
What started with generating content for business-related tasks (communications, reports, documents, etc.) has also moved into the washroom aisle. Insiders even claim that some laundries could be run by AI without any human intervention, or at least on a very limited basis.
The question arises, “Where is AI going in the laundry industry?”
american laundry news We asked three AI industry veterans for their thoughts on what AI is bringing to the industry today and what it will bring in the future.
David Bernstein is the founder of Propeller Solutions Group in Livingston, Texas. Rodrigo Patron is the Director of Operations at Lace House Linen Co. in Petaluma, California. David Griggs, one of our columnists, is director of operations development for Superior Linen Service in Tulsa, Oklahoma.
Where is AI already being used on the production floor in industrial and institutional laundries?
Bernstein: What we’re seeing today is a meaningful beginning of where things will go in the future. Computer vision and machine learning are used from soil (automated soil sorting systems) to cleaning (linen inspection scanners on flat ironing machines) to sort and route fibers faster and more accurately than humans. Meanwhile, AI-guided robotic feeding, folding, and sorting equipment is also emerging to address variability that previously made full automation impractical.
On the identification and tracking front, companies have applied neural networks and machine learning to radio frequency identification (RFID) readings, introducing training systems that recognize and discard bad readings with new levels of accuracy. This is important because the value of an RFID system is completely dependent on the quality of the data and therefore the quality of the reading.
On the inventory management side, the platform uses AI to analyze historical consumption data and dynamically recommend denomination levels tailored to each property, preventing both understocking and overstocking. Additionally, quality control systems are rapidly improving thanks to machine learning.
AI is already being implemented in this industry. It’s not everywhere, it’s not mature everywhere, but the foundations are being built.
Patron: AI is already being used in many industrial and institutional laundries, especially in large and highly automated plants. Some facilities are using AI for washroom optimization, predictive maintenance, route planning, production tracking, linen tracking, and quality control.
While Race House Linen doesn’t use AI directly within its production facilities like some large dry cleaners, it’s already using it in practical ways across its business. For example, we use AI to assist with email, customer communications, reports, signage, translations, operational documentation, and more. This has allowed us to save time on administrative tasks and improve consistency across the company.
Griggs: AI has been consistently expanding in the laundry space over the past few years. It might be a little different than what we imagined. Many dry cleaners have automatic rail systems installed that remove the linens from the soil chamber, program the correct formula in a continuous batch washer (CBW), and send it to the finishing area without human intervention. Shuttles, rails, and conveyors are all “robots” that eliminate employees.
How effective is AI in today’s washrooms and how can it help frontline workers?
Patron: In today’s wash aisles, AI is primarily used as a support tool to help operators make better decisions. It helps optimize formulations, chemical usage, temperature, cycle times, and water consumption based on real-time data. This improves consistency, reduces waste, and increases production efficiency.
Although Race House is not currently using AI directly in its wash aisles, it is already seeing the value it can bring by helping operators make faster, more informed decisions and taking some of the guesswork out of production.
Griggs: For several years, industrial uniform companies have had the ability to use conveyors to sort clothing by route. With the introduction of RFID chipped clothing, this process can now be categorized by employee, account, and route without human intervention.
There are companies currently working on developing automatic soil chambers to further automate the system. I’m not sure how these systems remove bags of linens from carts or how they unload carts from trucks. You will see this work well when combined with an RFID system.
Bernstein: Where AI makes the most important contribution in the wash aisle and throughout the plant is not in the fine-grained control of a single infusion pump or morsel folder. It lies in the coordination of the entire operation.
The real benefit is AI that sequences wash loads to optimize utility consumption, balances chemicals across the wash bed (especially tunnel wash systems), responds to customer priorities in real time, and continuously adjusts to eliminate bottlenecks and pull product downstream.
Think of this as the ultimate Lean Six Sigma Master Black Belt in your factory. You never get tired, you never have a bad day, you never stop looking for the next improvement.
Check back Thursday for Part 2 on the benefits of using AI in laundry and the challenges to overcome.
