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larshep from enmore consulting AG and myself worked out a use case covering the processing of data sent by smart bins and carrying it further to the planning of waste disposal services. This blogpost will give you an overview on how data from sensors in containers can be seamlessly integrated into business processes.

Today bins are usually emptied based on a static rhythm, like every second Tuesday. This means that the bin gets emptied even though it might only be filled by 60% or even less, because the actual fill level is unknown. Using sensors to identify the actual fill level opens completely new opportunities to optimize the waste collection process.
However next to collecting and transferring the data it is also necessary to save and integrate it seamlessly into the business processes to make it actually a smart bin.



RPA

The RPA bot performs noninvasive integration by using existing technology to receive, save and interpret smart bin data. The data is collected by a sensor in the container and transferred as mails sent via a modem out of which an emptying order will be created as soon as a defined fill level is reached. The bot can be triggered daily to go through all incoming mails from the bins. The next bot task is storing the fill level in an Excel file and identifying based on a set of rules when the container needs to be emptied. When the container is filled by, for example 75%, a waste disposal order will becreated in the SAP backend system.
Storing the data even enables the possibility to use historical data for forecasts.

For further details of this RPA solution from enmore also see
https://blogs.sap.com/2021/03/10/rpa-as-a-data-interface-for-iot-smart-containers/

Indeed RPA is maybe not the most obvious option to cover this process. However SAP Intelligent Robotic Process Automation enables a fast, easy and extremly cost efficient implementation to gain experience on how to best integrate sensor data from bins into existing business processes. It´s the ideal approach in case the number of bins is still small (e. g. proof of concept phase) or if you want to test different sensors in different bins without going for a costly integration project to connect sensors directly with the ERP system.

The waste disposal order created by the RPA now needs to be dispatched to the right waste collection route/vehicle.
As the usual process mostly contains static orders like described above (every second Tuesday) there is only limited replanning involved. However, with more dynamic orders coming from Smart Bins the planning effort increases significantly.

Automated Route Planning

The SAP Waste and Recycling, automated route planning option by PROLOGA (previously known as SAP Waste and Recycling, cloud edition by PROLOGA) minimizes this manual effort for dispatching the waste disposal orders to the routes/vehicles and at the same time optimizes the routes to be driven. The solution can cover thousands of orders with different waste materials and further restrictions (e.g. pick up time, etc.) across plenty plants (with different prices) and depots where the different vehicles are based. It takes legal restrictions like working and driving hours into account as well costs for mileage, working hours and disposing the waste material.

For further details of the SAP Waste and Recycling, automated route planning option by PROLOGA (previously known as SAP Waste and Recycling, cloud edition by PROLOGA) also see
https://blogs.sap.com/2021/01/04/how-to-automate-the-planning-of-logistics-in-the-waste-and-recyclin...

Conclusion

Sensors alone do not make a bin smart. The shown combination of solutions in the SAP environment with RPA and the Automated Route Planning automatically integrates the sensor data into the business processes to make the bin actually smart. Besides the reduction of picking up containers which are still empty, this solution also enables a further reduction of operational costs by optimizing the waste collection routes. On top, the automation minimizes the manual effort of administrating and integrating data from container sensors into the business processes.
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