Investigation of operational parameters that affect the use of drones in goods’ stock count process: Evidence from experimental results

Abstract

Purpose: Recently, the complexity of managing warehouses has been amplified significantly due to factors that include increased requests for more frequent and smaller order fulfilment, reduction of operational cost, and improvement of customer experience. Product stock count is a critical process in order to address the aforementioned challenges. This articles presents experimental results from the adoption of drones coupled with RFID tags used for real time goods’ stock count.

Design/methodology/approach: The research methodology adopted combines three different methods, namely Systematic Literature Review (SLR) for identifying parameters that affect the performance of drones in stock count process, survey via questionnaire and interviews to logistics managers to map needs and requirements in warehouse operations, as well as laboratory testing via Design of Experiment (2⁴ full factorial design & ANOVA) methodology to investigate how certain parameters corelate and affect the reading accuracy of RFID tags as well as the time needed by a drone for stock count completion.  

Findings: The results of the experiments are encouraging, showing that the use of drones coupled with RFID tags may support faster, cost-effective, and safer stock count in warehouses. In both ambient and chilled storage environment an 100% RFID tag reading accuracy was achieved. Less stock-count completion time when compared to manual stock-count was achieved in both cases.

Research implications: Understanding the effect of technical and operational parameters of RFID technology in conjunction with unmanned aerial vehicles (UAVs)-drones may have the potential to radically transform the stock count process by considerably increase the efficiency and accuracy of the process.

Practical implications: Real-time stock count via drones has significant cost-saving implications for organizations. The elimination of manual stock counting saves operational expenses and increases staff safety. Furthermore, real-time data collection of existing product stock allows managers to efficiently allocate resources, enhancing overall efficiency and performance.

Originality/value: This research is among the first studies that aim to present evidence from experimental results that assess the use of drones coupled with RFID technology for real-time stock count. The results from laboratory experiments demonstrate the effect of certain operational parameters, such as drone speed, number of rack levels, and RFID tag location on products, during the execution of the stock count process in terms of RFID reading accuracy and stock-count completion time.