International Journal of Supply Chain Management
Vol 7, No 5 (2018): International Journal of Supply Chain Management (IJSCM)

Smart Trolley Apps: A Solution To Reduce Picking Error

Rohana Sham (Unknown)
Siti Norida Wahab (Faculty of Business and Information Science, UCSI University, Kuala Lumpur, Malaysia)
Amir Aatieff Amir Hussin (Faculty of Business and Information Science, UCSI University, Kuala Lumpur, Malaysia)



Article Info

Publish Date
29 Oct 2018

Abstract

An order picking activities refers to an act of retrieving any items from the storage locations in the warehouses. In common situation, these activities is often performed by human. Due to that condition, high human error and high cost impact were spotted on a manual order picking activities. Thus, previous studies have developed various methods to support the practitioners especially in creating a more efficient order picking process. In spite of the vast discussion and evidence that shows an order pickers tend to deviate from its optimal routes and putting the efficiency of these routing approaches at stake, very little discussion were focus on the implementation of smart application through IT usage and device to reduce the problem faced in the warehouse. Thus, it is the main intention of this this paper to presents a detailed analysis on the relative factors affecting the efficiency of order picking activities in the warehouse and suggest the smart trolley as a solution to overcome the problem. The smart trolley apps is then proposed to increase the picking process in warehouse. The results of this paper indicate that extensive use of smart trolley apps as a solution to a more effective ways of order picking.

Copyrights © 2018






Journal Info

Abbrev

IJSCM

Publisher

Subject

Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

Description

International Journal of Supply Chain Management (IJSCM) is a peer-reviewed indexed journal, ISSN: 2050-7399 (Online), 2051-3771 (Print), that publishes original, high quality, supply chain management empirical research that will have a significant impact on SCM theory and practice. Manuscripts ...