A transformative dose
Here we learn from SEKO how the Internet of Things (IoT) is transforming on-premise laundry dosing in healthcare.
In the healthcare sector, site management has a choice between the installation, operation and maintenance of an on-premise laundry or outsourcing the washing of items such as bed sheets, blankets, towels, clothes and uniforms to a contractor.
A common argument against an in-house setup is that, beyond the initial outlay, it brings with it ongoing costs such as utilities, chemicals, maintenance and repair. However, should the service be outsourced, it’s likely that the selected contractor faces the same costs which would ultimately be passed on to the hospital, care home or other healthcare facility.
While outsourcing laundry removes responsibility for managing the process and the need for a dedicated laundry room, it does leave the operator bound to the contractor’s inflexible turnround times and the potential for service interruption. Meanwhile, mass cleaning methods may cause chemical and mechanical damage to laundry which leads to more frequent replacement and subsequently increases costs.
Despite the many pros and cons, it is generally accepted that an on-premise laundry ultimately delivers a better wash performance, longer fabric life, and greater flexibility than can be achieved via outsourcing.
In order to manage an on-premise laundry, there’s a clear need for chemical dosing systems that have the capacity to handle high load demand across multiple machines while maintaining precision and consistency over an extended period.
This is one of the reasons web-enabled pump systems are increasingly specified for commercial laundry machines within healthcare sites, where infection control is paramount and IoT-ready dosing and control systems can help operators to consistently achieve this.
As well as the benefits for patients and residents, a major draw of IoT is that features such as up-to-date downloadable manuals, intelligent auto-tuning sensors and online step-by-step technical support can accelerate installation, setup and commissioning and reduce associated time and costs.
During operation, data is harvested on multiple pump values, including wash cycle status, chemical consumption and equipment performance, which can then be accessed historically or in real time via a cloud-based platform, thanks to the system’s built-in web server.
With this vital information at their fingertips, users can program and adjust wash formulas in order to optimise performance and minimise chemical consumption. Common features include the option to view chemical consumption in financial terms, which allows projected
32 | CLEANING CHEMICALS AND DISPENSERS
detergent and fabric softener savings to be precisely calculated and presented to key decision makers when considering dosing changes.
Reducing chemical and energy consumption this way means operators benefit from immediate efficiency improvements while being able to budget more accurately and streamline stored chemical volume – especially useful on smaller sites where space is at a premium.
Plus, wasted journeys by maintenance technicians to perform routine servicing – who may travel a considerable distance to assess a system’s condition only to find it in perfect working order – can be eliminated, as they need only be deployed when required.
As the global healthcare sector looks towards a post-COVID future, the benefits of IoT provide operators today with the ability to take control of in-house laundry costs over both the short and long term, helping to deliver reliability and confidence at a time of great uncertainty.
SEKO is a worldwide manufacturer of chemical dosing systems for multiple sectors, and has supplied its leading on- premise laundry equipment – including the highly-regarded Wash Series IoT-enabled units – to hospitals, care homes and other healthcare sites over many years. The complete range can be viewed at the website below, where you’ll also find contact details for your local SEKO representative.
www.seko.com
twitter.com/TomoCleaning
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