Excitedly we read in cleaning magazines and on the internet about new generation machines being introduced to the industry. Production companies report a great interest for their latest products suggesting that manual floor cleaning would be history. And yes, our industry needs these developments, as available workforce is already short supply, and that availability will not be improving in future neither.
But looking at those articles and videos, we should also ask ourselves are the cleaning companies getting the correct support they need? Too often the machines are presented as miracle products that can do all the work and yet it might lead to disinvestments and frustration on the customer side.
5 to 10% of today’s buildings are accessible for today’s robots, new age (manually operated) scrubber dryers can possibly access 20-30% of floor areas. In the case of machine cleaning, however, how are corners and edges cleaned? What is happening to the cost/profit per m2?
Manual cleaning has improved and compared to new methods; machine cleaning, either AI r manual, will always be slower in production than manual cleaning. The machines on the other hand will be more efficient on the cleaning effort as they produce more mechanical force, one of the elements of Sinner circle.Machines do not get tired and supply a continuous quality level, but dust settles down at corners and edges, under chairs and tables, areas machines cannot reach, and which may get airborne by machines generating turbulence. Machines are heavy and face barriers, which an operator with a manual tool do not hinder. If the machines are operating stand alone, the traffic percentage of the cleaning operator between storage and cleaning objects will dramatically increase.
If only considering the cleaning process as the sum of products, the cleaning company will be facing increasing budget costs. We must start thinking process wise, integrating machines and robots into the process,changing our cleaning processes and frequencies, avoiding machines standing unemployed in storage and deep cleanings still frequently needed. By segmenting areas, taking turns on manual and machine methods, cleaning on demand processes can being optimized and by that cost being controlled.
If a robot cleans an area, most of the touched areas are cleaned automatically and 24/7, however they still need supervising and maintenance. The corners and edges, where dust settles down, need a manual finishing, but does it have to be as frequent cleaned and in the same way as before? There will be areas the robot cannot access, are the accessible areas cost/profit enough when considering the manual assistance, even the frequency can be lower? To find the break-even point the entire process needs to be considered.
In case a battery driven scrubber dryer is available, they will have deeper access than a robot, but is manually operated. What is the break-even footage of a slower but deeper cleaning machine and a more frequent but faster manual cleaning? How to process? Integrated or separately operated has an impact on the traffic and operational costs. These types of machines need areas to be pre-dusted. Areas not covered by machines need to be done manually. Also, here the question: what is the break-even point footage between machine and manual cleaning? Only when considering the complete process of cleaning within a project the right answers can be found.
And then there is still a large segment that needs to be done manually, because either the building is not accessible for machines, the area is too small for an investment, or hygiene protocol does not allow machines.
Less water,using non-health-risking chemicals with higher mechanical force without making it harder for the cleaning operator; a smarter way of floor cleaning.
We as a supplier of cleaning products feel responsible, advising cleaning companies in a correct way with our Process Cleaning approach and we call our colleagues in the robot and machine cleaning business to do the same.
Only a realistic approach of suppliers is helping our clients to make the right decisions on manual products, trolleys, and machines/robots.