Intelligent agent based framework to augment warehouse management systems for dynamic demand environments

Binos, Tania; Bruno, Vince; Adamopoulos, Arthur

doi:10.3127/ajis.v25i0.2845

Cited by 13 publications

(5 citation statements)

References 36 publications

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“…In the publication by Binos et al [93], an intelligent agent-based framework is introduced to enhance warehouse management systems (WMS) in dynamic demand environments. The authors provide a novel framework that offers a triple contribution, encompassing innovative design principles and approaches for efficient WMS implementation.…”

Section: Miscellaneousmentioning

confidence: 99%

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

Belter,

Hering,

Weichbroth

2023

Applied Sciences

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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.

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Section: Miscellaneousmentioning

confidence: 99%

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

Belter,

Hering,

Weichbroth

2023

Applied Sciences

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“…Pulungan et al (2013) proposed an intelligent WMS (i-WMS), which comprises five subsystems, and the design integrates advanced intelligent system applications such as neural network, fuzzy control, bee colony optimization. And a decision support system and technologies such as RFID and Androidbased handheld devices (Binos et al, 2021, Pulungan et al, 2013. Minbo et al (2011) suggested RFID-based Intelligent WMS (RFID-IWMS), addressing critical limitations of the traditional bar-code base system, such as lack of integration with the WMS and difficulty to get Key Performance Indicator (KPI) data of the operation.…”

Section: Advanced Features Of Extended Warehouse Management Systems (...mentioning

confidence: 99%

Impact of Extended Warehouse Management System Implementation on Warehouse Operational Performance: A Case Study of Fast Moving Consumer Goods Industry

Edirisinghe,

Liyanage

2022

ICBM

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Warehouses operating in the Fast-moving consumer goods (FMCG) industry are affected by the supply chain disruptions. Therefore, it is critical to develop faster and effective mechanisms of managing warehouse operational performance. In this regard, this paper aims to evaluate the impact of Extended Warehouse Management System (EWMS) implementation on warehouse operational performance. It intended to achieve two objectives: to examine the advanced features of EWMS and the impact of EWMS implementation on warehouse operational performance. The case study method gathered operational quantitative and qualitative data from multiple sources, ensuring data richness. Descriptive statistics and mean comparison tests through hypothesis testing were used as quantitative data analysis techniques, using the IBM SPSS Statistics 21 statistical analysis software package. The Framework Approach was used to analyse qualitative data. By mapping Process Flowcharts before and after the implementation, the improvements and drawbacks were identified with their root causes. Advanced features of EWMSs are presented by reviewing the literature. The study's findings reveal that implementation of EWMS increases the throughput, average receiving rate, average allocation and picking rate, average loading rate, average last truck dispatch time, and average on-time delivery. The scope of the research is limited to evaluating the EWMS implementation impact on warehouse operational performance in a selected FMCG warehouse. Future researchers can focus on the effects of EWMS on supply chain capability enhancements and the strategic performance of supply chain partners. The in-depth analysis of performance improvements in the extent of the throughput, average receiving rate, average allocation and picking rate, average loading rate, average last truck dispatch time, and average on-time delivery signals warehouse managers in decision making on effective utilisation EWMS implementation. This paper is among the very few evaluating Extended WMS, specifically, empirical investigation of the impact of EWMS system implementation on FMCG warehouse operational performance. Keywords: Extended Warehouse Management Systems, Advance Features, FMCG Warehouses, Warehouse Operational Performance

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“…Analyzing the technologies that led to the development of Warehousing, it is worth paying attention to the evolution of Warehouse Management Systems (WMS), as one of the most important components on the basis of which the requirements for warehouse automation in Smart Manufacturing are implemented and achieved [28][29][30][31][32]. Based on the analysis, the following technologies were selected as the basis for each stage of WMS development, which are presented in table 2 for ease of comparison.…”

Section: Fig 2 Evolution Of Warehousingmentioning

confidence: 99%

Evolutions of Group Management Development of Mobile Robotic Platforms in Warehousing 4.0.

Nevliudov

Yevsieiev

Klymenko³

et al. 2021

ITSSI

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The subject of this research is the technology of management of mobile robot groups in the concept of Industry 4.0 and its composition. The purpose of this article is to find ways to implement an effective strategy for building and managing mobile robotic platforms in Warehousing, as a key tool of Lean Production. To achieve this goal, it is necessary to solve the following tasks: to analyze the management of supply chains in Smart Manufacturing, within Industry 4.0 and its impact on achieving the goals of Lean Production; to study the evolution of technologies used in Warehousing in the dynamics of the Industrial Revolution; to analyze the evolution of Warehouse Management Systems (WMS) as one of the most important components on the basis of which the requirements for automation of Warehousing automation in Smart Manufacturing with group management of mobile robotic platforms are implemented and achieved; to compare the impact of the technologies used by Warehousing 4.0 and Warehouse Management Systems on the key indicators of Lean Production. Results: One of the promising ways to achieve the effectiveness of the implementation of Lean Production tools in WMS systems is the use of Collaborative Robot System technology, which makes it possible to ensure a high density of product storage in Warehousing. However, modern mobile robotic platforms have their limitations both in the methods of loading and unloading products, and in the design. Therefore, the authors see the task in improving the design of mobile robotic platforms, which will develop a new intelligent group method of loading and unloading products, increasing the storage density for a variety of goods. Conclusions: The paper compares the impact of Warehousing 4.0 and Warehouse Management Systems on key Lean Production tools, which shows how the introduction of new group management technologies for robotic platforms in Warehousing 4.0 and Warehouse Management Systems (WMS) affects the effectiveness of Lean Production tools such as Heijunka, Just-in-time, 5S. This suggests that the introduction of new models and methods of managing complex warehouses with high density and chaotic storage of products, through the use of mobile robotic autonomous systems, will significantly optimize the process of supply chain management in Smart Manufacturing.

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Intelligent agent based framework to augment warehouse management systems for dynamic demand environments

Cited by 13 publications

References 36 publications

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

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

Impact of Extended Warehouse Management System Implementation on Warehouse Operational Performance: A Case Study of Fast Moving Consumer Goods Industry

Evolutions of Group Management Development of Mobile Robotic Platforms in Warehousing 4.0.

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