(untitled) (International Journal of Management and Sustainability, 2016)
Market competition, customer expectation and increasing warehouse operations cost have motivated third-party logistics practitioners in the continuous improvement on warehouse operations. Cargo tracing in order picking process is time-consuming for warehouse operators when handling enormous flow of goods through the warehouse each day. Internet of Things (IoT) with mobile cargo tracing apps and database management systems are developed in this research to reduce cargo tracing time in the order picking process of a third-party logistics firm. An operations review was carried out with identified opportunities for improvement, including inaccurate inventory record in warehouse management system, excessive tracing time with stored products, and product misdelivery. The facility layout was improved by modifying the designated locations of various types of products. The relationships among pick and pack processing time, cargo tracing time, delivery accuracy, inventory turnover, and inventory count operation time in the warehouse are evaluated. The correlation of the factors affecting the overall cycle time is analysed. A mobile app is developed with the use of MIT App Inventor and Access management database to facilitate cargo tracking anytime, anywhere. The information flow framework from warehouse database system to cloud computing document sharing, and further to the mobile app device is developed. The improved performance of cargo tracing in the order processing cycle of warehouse operators is evaluated. The developed mobile voice picking and tracking systems have brought significant benefits to the third-party logistics firm, including eliminating unnecessary cargo tracing time in order picking process and reducing warehouse operators overtime cost. A mobile tracking device is planned to enhance the picking time and cycle count of warehouse operators with voice picking system in the developed mobile apps.