Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks.
The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN.
This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on business needs.
The paper also discusses integration of IT and OT through protocols such as MQTT and Apache Kafka to enable real-time connectivity and explores how sensor data acquisition can support predictive analytics, including calibration compliance and maintenance forecasting.
The proposed multi-layered framework combining sensing, communication, and predictive intelligence demonstrates how digital tool tracking enhances efficiency, reduces downtime, and supports Lean manufacturing principles such as just-in-time readiness, continuous improvement, and overall equipment effectiveness (OEE).