CHICAGO — Artificial intelligence.

Five or six years ago, AI that could almost think and create was something only encountered in science fiction.

How quickly technology advances. In the past few years, generative AI options have multiplied in almost every area of daily life and in business operations. That includes industrial and institutional laundries.

What started with generating content for business-related tasks (think communication, reports, documents) has moved onto the wash aisle. Insiders have even posited that some laundries could be operated by AI without any, or at least very limited, human involvement.

It begs the question, “Where is AI heading in the laundry industry?”

American Laundry News sought input from three industry veterans who are familiar with AI, what it’s doing for the industry today, and what it might provide in the future.

David Bernstein is the founder of Propeller Solutions Group in Livingston, Texas. Rodrigo Patron is director of operations for Lace House Linen in Petaluma, California. David Griggs — one of this magazine’s columnists at large — is director of operations development with Superior Linen Service in Tulsa, Oklahoma.

BERNSTEIN: What we are seeing today is a meaningful start to where things are headed in the future. Computer vision and machine learning are being used from soil (automated soil-sorting systems) to clean (linen inspection scanners on flatwork ironers) to classify and route textiles faster and more accurately than humans can. In between, we are also seeing robotic feeding, folding, and sorting equipment guided by AI to handle the variability that used to make full automation impractical. 

On the identification and tracking side, companies have applied neural networks and machine learning to radio-frequency identification (RFID) reading, training systems to recognize and discard bad reads with a new level of accuracy. That matters because the value of any RFID system is entirely dependent on the quality of its data and, by extension, its reads.

On the inventory management side, platforms are using AI to analyze historical consumption data and dynamically recommend par levels tailored to each property, preventing both shortfalls and overstocks. And quality control systems are improving rapidly thanks to machine learning.

AI is already in production in this industry. It is not everywhere, and it is not mature everywhere it exists, but the foundation is being built.

PATRON: AI is already being used in many industrial and institutional laundries, especially in larger and highly automated plants. Some facilities are using AI for wash-aisle optimization, predictive maintenance, route planning, production tracking, linen tracking and quality control.

At Lace House Linen, we are not yet using AI directly inside production equipment like some larger laundries are, but we are already using it in practical ways throughout the business. For example, we use AI to help with emails, customer communication, reports, signage, translations, and operational documents. It has helped us save time on administrative tasks and improve consistency across the company.

GRIGGS: AI has been consistently expanding in laundries for several years now. It may look a little different than we imagined it would. Many laundries have automatic rail systems that take the linen from the soil room, program the correct formula in the continuous-batch washer (CBW), and send it to the finishing area without human intervention. The shuttles, rails and conveyors are all forms of “robots” that have eliminated employees. 

PATRON: In today’s wash aisle, AI is mainly being used as a support tool to help operators make better decisions. It can help optimize formulas, chemical usage, temperatures, cycle times and water consumption based on real-time data. That leads to better consistency, less waste and more efficient production.

At Lace House, even though we are not currently using AI directly in our wash aisle, we can already see the value it could bring by helping operators make faster, more informed decisions and reducing some of the guesswork in production.

GRIGGS: Industrial uniform companies have had the ability to sort garments by route for several years using conveyors. With the introduction of RFID-chipped garments, this process can be made to sort by employee, account, and route with no human intervention.

Currently, there are companies working on the automatic soil room that will further automate the system. I am not familiar with how these systems remove bags of linen from carts or how they get the carts from the trucks. I can see this working well when paired with RFID systems.

BERNSTEIN: If you ask me where AI will make its most significant contribution in the wash aisle and across the entire plant, it is not in the granular control of a single dosing pump or small-piece folder. It is in the orchestration of the whole operation. 

The real prize is AI that sequences wash loads to optimize utility consumption, balances chemistry across the wash floor (particularly in tunnel washing systems), responds to customer priorities in real time, and continuously adjusts to eliminate bottlenecks and pull product downstream.

Think of it as the ultimate in-plant Lean Six Sigma Master Black Belt — one that never gets tired, never has a bad day, and never stops looking for the next improvement.

Check back Thursday for part 2 about more benefits of AI use in laundries and challenges to overcome.