A Cyber-Physical Warehouse Management System Architecture in an Industry 4.0 Context

Moufaddal, Mariam; Benghabrit, Asmaa; Bouhaddou, Imane

doi:10.1007/978-3-030-51186-9_9

Cited by 4 publications

(2 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Intelligent cloud-based technology is making a significant impact on the logistics sector, as cloud computing is used for autonomous logistics to synchronize the real time flow of material and information [35]. IoT utilizing cyber-physical systems (CPS), equipped with electronics and software, connects the physical system with the digital world to optimize the system's performance [36]. Vehicular cyber-physical systems (VCPS) are designed for smart roads by realizing mobile cloud computing services where vehicles and mobile devices are connected to both cloud servers and clients [37], as illustrated in Figure 2b.…”

Section: Big Data Iot and Intelligent Transportationmentioning

confidence: 99%

Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh

et al. 2021

View full text Add to dashboard Cite

Background: Retail chains aim to maintain a competitive advantage by ensuring product availability and fulfilling customer demand on-time. However, inefficient scheduling and vehicle routing from the distribution center may cause delivery delays and, thus, stock-outs on the store shelves. Therefore, optimization of vehicle routing can play a vital role in fulfilling customer demand. Methods: In this research, a case study is formulated for a chain of retail stores in Dhaka City, Bangladesh. Orders from various stores are combined, grouped, and scheduled for Region-1 and Region-2 of Dhaka City. The ‘vehicle routing add-on’ feature of Google Sheets is used for scheduling and navigation. An android application, Intelligent Route Optimizer, is developed using the shortest path first algorithm based on the Dijkstra algorithm. The vehicle navigation scheme is programmed to change the direction according to the shortest possible path in the google map generated by the intelligent routing optimizer. Results: With the application, the improvement of optimization results is evident from the reductions of traveled distance (8.1% and 12.2%) and time (20.2% and 15.0%) in Region-1 and Region-2, respectively. Conclusions: A smartphone-based application is developed to improve the distribution plan. It can be utilized for an intelligent vehicle routing system to respond to real-time traffic; hence, the overall replenishment process will be improved.

show abstract

Section: Big Data Iot and Intelligent Transportationmentioning

confidence: 99%

Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh

et al. 2021

View full text Add to dashboard Cite

show abstract

“…A modern warehouse is managed by software systems, intended to organize the work and control and administer a set of policies and processes. Nowadays, the most advanced WMSs automate processes by delegating labour-intensive and manual or dangerous tasks to robots, including goods inventory [3] and heavy cargo transfer and loads [4]. Economies around the world have driven various sectors such as agriculture, construction, healthcare, manufacturing, and retail to achieve highly efficient operations in order to increase output and meet consumer demand [5].…”

Section: Introductionmentioning

confidence: 99%

Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

Belter,

Hering,

Weichbroth

2023

Applied Sciences

View full text Add to dashboard Cite

Background: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016 to 2023. The review was driven by a protocol that comprehends inclusion and exclusion criteria to identify relevant papers. Results: Considering the Warehouse Management Systems, five categories of motion trajectory prediction methods have been identified: Deep Learning methods, probabilistic methods, methods for solving the Travelling-Salesman problem (TSP), algorithmic methods, and others. Specifically, the performed analysis also provides the research community with an overview of the state-of-the-art methods, which can further stimulate researchers and practitioners to enhance existing and develop new ones in this field.

show abstract

A Novel Interoperability Evaluation Framework for the Warehouse Management System

Thayil,

Zhang,

Vadakkepat

et al. 2023

IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

View full text Add to dashboard Cite

A Cyber-Physical Warehouse Management System Architecture in an Industry 4.0 Context

Cited by 4 publications

References 54 publications

Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh

Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh

Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

A Novel Interoperability Evaluation Framework for the Warehouse Management System

Contact Info

Product

Resources

About