Early Learnings from a Logistics Testbed
capabilities of all three companies complemented each other in a way that covers all aspects of the envisioned solution . Ranging from the sensing capabilities , connectivity and cloud all the way to operational excellence and deep logistics experience .
The starting point of the testbed was the identification of a cooperative value scenario based on the capabilities of the partners . The companies defined transparency in terms of intralogistics as the basis for the value scenario . Based on transparency , the partners jointly optimize intralogistics with a focus on forklifts and the warehouse .
Therefore the companies defined the following Key Performance Indicators ( KPIs ) to measure the success of the cooperative value scenario : throughput , cycle time , transport performance , effectiveness , and availability . The defined KPIs were visualized in dashboards to enable continuous monitoring of the intralogistics and additionally the dashboards were used to generate insights and potentially new knowledge to optimize internal logistics systems - optimizations in a way that would be difficult to achieve with traditional methods . Based on optimization , the companies developed further value scenarios - increasing the productivity of the forklift fleet , material tracking and order management .
The digital twins were instantiated in a cooperative data space hosted by one of the companies . The forklifts ' digital twins included the following states like the current position and whether the vehicle bears a load . These were complemented by the digital twins of transported goods . These digital twins included an item ID , the date of storage and the current position . Finally , a digital twin of the factory site was created , this digital twin included storage zones and the filling levels of these storage zones . Through the chosen architecture , we created interconnectivity and interaction across the intralogistics objects and systems .
The described data ecosystem was initiated in an outdoor area in an industrial plant in the south of Germany . As part of the testbed 16 forklifts were equipped with the necessary sensing equipment and connected to a cloud instance . Transparency was achieved by analyzing the vehicles ’ digital twins ’ states over a period of one and a half years . The companies evaluated the success of the testbed based on market potential , technical feasibility , costs , and risks .
After the evaluation , the project partners decided to jointly scale the offering on the market . To achieve the defined value scenarios , the partners specified and implemented digital twins . The following figure summarizes the testbed , based on the viewpoints of the Industrial Internet Reference Architecture ( IIRA ).
Journal of Innovation 17