inventory. This sometimes causes additional costs between 10 and 20% of the annual machine costs.
With all these difficulties, new technologies such as IoT can provide valuable services, but here, cleaning companies face two main challenges:
Manufacturer silos versus mixed fleets: Typically, cleaning companies have mixed fleets, i.e., assets from several manufacturers. At the moment almost every manufacturer is trying to launch their own proprietary silo solution for the management of their equipment. However, cleaning companies usually have a limited interest in being so closely tied to a machine supplier, or would like to retain a certain degree of independence.
Running costs versus economic requirements: Today's digitisation solutions from manufacturers sometimes cost between £10-30 per asset a month. This is too expensive for most cleaning companies and makes an economically viable business case very difficult. The reason for these high costs is that the majority of machine builders follow the traditional approach of data streaming.
The technical implementation
In order to enable a comprehensive – and at the same time efficient – digitalisation of asset and resource management, it is first necessary to consider the different areas of application and functionalities of the resources. The goal should not be to create a ‘chicken and egg’ solution that can cover everything, but rather to put together an intelligent symphony of different connectivity options: from wireless IoT modules to Bluetooth tags, or NFC transponders to QR codes.
All these technologies can also be linked together: for example, the Bluetooth tag on a vacuum can communicate with the IoT module on an automatic scrubber dryer. This is a small smart box that’s connected to the machine and can act as a gateway to collect the fleet's data, process it and send it
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to the cloud in a GDPR-compliant manner using a SIM card. This saves costs and creates wide-ranging coverage.
It’s also important to think carefully about what data is needed to optimise economic decision-making and operational processes. Think, for example, of automatic messages when the machine leaves its assigned location or is moved outside core hours. A technology that has proven itself in this regard is so-called ‘edge computing’. Here, the data is continuously analysed on the IoT module directly attached to the machine, and only the findings relevant for an evaluation are sent to the cloud.
It is also significant to choose a scalable IT infrastructure that can cope with high data volumes and workloads, such as Microsoft Azure or Amazon Web Services (AWS). In the past, many companies have relied on their own in-house servers and on-premise solutions.
Finally, it’s important to ensure that the system is easy to use and also suitable for mobile use. Employees are usually under a lot of time pressure and must be able to find their way around quickly. If this is not sufficiently given, the employees may not use the systems and revert to the old familiars – for example, to Excel and paper.
Live in a few days
There are already systems on the market, such as ToolSense, that make it easier to get started with digital asset management, and the advantages of the IoT technologies can be used within a few days. Experience shows that a cleaning company with a turnover of around £30m can save between 10-20% of machine costs and reduce annual inspection costs by up to £70,000 with a proper asset management system. The site managers can also save up to 100 hours of working time per year.
In addition to service providers such as ISS or WISAG, suppliers such as Numatic, i-team, Cleanfix, Columbus, STIHL, and many others also use the ToolSense platform and IoT hardware.
www.toolsense.io/en CLEANING MACHINES | 47
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