Warehouse Performance Research Articles

Amplifying swift-trust, collaboration, and teamwork in warehouse management through blockchain-enabled technology

This study explores the application of blockchain technology in optimizing warehouse management, focusing on improving transparency, security, and operational efficiency. By utilizing a Blockchain-based Warehouse Platform (BCWP), the study enhances inventory tracking and supply chain transparency. A fuzzy-Delphi method was employed to identify and evaluate critical blockchain practices, with their relative importance assessed using the Best-Worst Method (BWM). The Combined Compromise Solution (CoCoSo) technique further ranked key performance outcomes. The findings reveal that practices such as quality inspection and information sharing play a pivotal role in boosting warehouse performance. Additionally, the integration of blockchain technology led to significant improvements in transaction speed and operational efficiency. This research contributes to the existing literature by providing a structured decision-making framework for blockchain implementation, offering practical insights for supply chain managers aiming to streamline warehouse operations and enhance decision-making processes.

Impact of responsibility shifts on warehouse performance of Indonesian police logistics staff

The primary issue addressed in this research is the need for motivation from managers to implement responsibility shifts within the Republic of Indonesia State Police. The purpose of the study was to examine the relationship between shifts in responsibility and the performance of the Indonesian Police Logistics Staff in the Inbounding and Storage processes. The study used a qualitative approach, employing the Six Sigma method along with regression analysis and hypothesis testing. A sample of 132 Police Logistics Staff was surveyed. The findings showed a positive relationship between shifts in responsibility and improvements in warehouse performance, particularly in terms of inbound and storage efficiency. The results offer recommendations for enhancing efficiency through responsibility shifts. These findings could encourage officers to consider adopting responsibility shifts within the National Police Logistics Staff warehouse. Further research with a larger population and a more in-depth exploration of the impact of this transition is recommended.

Intelligent warehousing performance management based on Internet of Things and automation technology in the context of green manufacturing

At present, there is a significant imbalance in the development level of warehousing in China, and most enterprises still use traditional material identification technology, resulting in many unnecessary manual operations in the management process, thereby reducing efficiency and causing waste. Therefore, in the context of green manufacturing, we propose an intelligent warehousing performance management solution based on Internet of Things technology and automation technology. By conducting research on the development and research status of the Internet of Things and intelligent warehousing at home and abroad, this paper delves into the various requirements of intelligent warehousing systems and formulates a targeted architecture for this system. Through experiments, it has been proven that the intelligent warehouse performance evaluation model improved by dual technology can effectively improve warehouse management level, reduce enterprise costs, and enhance enterprise efficiency. After in-depth analysis, it is concluded that this method has considerable adequacy and practicality in evaluating the performance management of intelligent warehousing. Therefore, in the context of green manufacturing, the intelligent warehouse performance management system built by adding IoT technology and automation technology has achieved automation and intelligence in performance management evaluation and warehouse entry and exit management, and has extremely high practical value.

An integrated cost based approach for warehouse performance evaluation: A new multiphase model

Warehouses represent key links in domestic and international commodity flows. The increasing shortage of workers and increasing costs on the one hand, and the increasing number and stricter demands of users on the other hand lead warehouse managers to realize their operations as efficiently as possible. A proposed model has an objective of enabling companies to monitor warehouse performance in an authoritative, reliable, and simple way and define appropriate corrective measures accordingly. The proposed empirical research consists of three stages, where in the first stage a combination of Principal Component Analysis-Data Envelopment Analysis methods was applied in order to determine efficient warehouses based on 90 decision making units. In the second phase, a completely new method called Interval Fuzzy Rough Pivot Pair-wise Relative Criteria Importance Assessment method used for determining criteria weights was developed and applied, which is one of the most important novelties of this study. In the last phase, the Interval Fuzzy Rough Measurement of Alternatives and Ranking according to the Compromise Solution method was applied to rank the alternatives. Twelve criteria were observed to evaluate 21 alternatives. Based on the results, it was concluded that salary stood out as the most important criterion, while amortization stood out as the least significant criterion. On the other hand, alternatives A9 and A10 stood out as the best-ranked alternatives while A1, A2, and A3 stood out as the least efficient ones. The paper provides clear scientific contributions that are reflected in the reduction of the gap that was observed after reviewing the literature where there is a lack of papers dealing with this task. Also, the combination of methods applied in the paper has not been used so far, so it can be said that this paper represents an excellent basis for further research. The model has practical contributions as it allows decision-makers to make quality decisions regarding the operation of their warehouses in different time periods or observation periods, as well as it represents a decision support tool that can be used for better warehouse management.

Revitalizing warehouse management to enhance global manufacturing competitiveness: insights from South Africa

Company operations and global trade necessitate storage. Warehouse management is essential for meeting customer expectations, ensuring product availability, and delivering globally swiftly and affordably. A company's international competitiveness can suffer from warehouse instability. This study assesses warehouse performance for competitive advantage. The report also explores top management's disregard for warehouse management's impact on manufacturing competitiveness. This paper reviews warehouse management system research from several industries. Reviewing literature for gaps and flaws. Quantitative methods include industrial specialized surveys. Three varied South African manufacturing enterprises will be case-studied. Deduction is used to analyze industry expert consultation data. Due to its accessibility and data collection suitability, convenience sampling was employed to choose participants. This study discovered many warehouse management issues in South African industrial firms. Integration and automation are lacking in current systems, hampering global competitiveness. Warehouse movements and infrastructure damage increased without zone selection. Technology-illiterate warehouse workers slowed operations. The study offers zone picking, warehouse training, and warehouse system integration and automation to address these difficulties. South African industrial firms should strengthen warehouse management systems, according to this study. These organizations can enhance operational efficiency, save money, and compete globally with the suggested changes. Zone picking, warehouse system integration, and worker technical training can alleviate challenges and provide companies an edge. This study highlights warehouse management's often overlooked significance in manufacturing competitiveness. International organizations can do better by studying warehouse management system problems and solutions. Practical warehouse management advice from this study increases South African industry competitiveness.

Last‐minute coordination: Adapting to demand to support last‐mile operations

AbstractIn the highly competitive e‐commerce industry, customer‐facing warehouses are crucial as the “order penetration points” for e‐commerce last‐mile operations. This research examines how warehouses use last‐minute coordination, an unstructured mechanism, to ensure sufficient inventory at the order penetration points. Previous research has focused on structured mechanisms like contracts and inventory management systems to enhance warehouse performance. However, these mechanisms can be ineffective when faced with unforeseen local contingencies. To adjust inventory and adapt to changes in supply and/or demand, warehouses need to engage in unstructured, last‐minute coordination with other warehouses. Using coordination and loose coupling theories, we find that coordinating with many warehouses (i.e., large coordination scope) reduces the operational efficiency of individual warehouses. At the network level, we find that a centralized coordination structure improves the operational efficiency of the entire network. We also show that demand uncertainty reinforces the existing last‐minute coordination patterns, using the Separable Temporal Exponential Random Graph Model (ST‐ERGM). This research highlights the importance of last‐minute coordination and reveals its effects on both individual warehouses and the overall network.

Use Case Diagram for Enhancing Warehouse Performance at PT. MDA Through the Implementation of 5S, Economic Order Quantity, Safety Stock, and Warehouse Management System

An industrial water pump importing company relies on a network of distribution warehouses to efficiently manage the storage and delivery of its products to clients. This paper delves into the operational intricacies of the company, with a primary focus on sustaining a superior level of service to meet customer demands, all while attempting to minimize costs and achieve optimal inventory control. The central aspects explored in this research encompass the meticulous determination of the number of pipes needed and the optimal ordering times. To address this, the Probabilistic Economic Order Quantity (EOQ) method is used and supported by 5S concept, recognized for its ability to provide reasonably accurate estimates crucial for pivotal decision-making in inventory management. The utilization of the Probabilistic EOQ method in this context reflects the company’s commitment to adopting sophisticated and proven methodologies to enhance decision-making accuracy and the warehouse area is more suitable by the 5S implementation principles. The research outcomes not only assist in refining the determination of Safety Stock levels but also contribute valuable insights into the precise quantities of goods that should be ordered. This strategic approach aligns with the company’s overarching goal of achieving cost-efficiency without compromising on the ability to efficiently meet customer demands. These upcoming insights could encompass innovative strategies, technological implementations, or advances in supply chain optimization.

Performance Evaluation of Retail Warehouses: A Combined MCDM Approach Using G-BWM and RATMI

Background: The retail sector has experienced significant growth in recent years, necessitating efficient supply chain management and sustainable logistics practices. Evaluating the performance of retail warehouses is crucial for meeting customer expectations and enhancing operational efficiency. Methods: This study employed a combined multi-criteria decision-making (MCDM) approach, using the group best–worst method (G-BWM) for weighting criteria and ranking the alternatives based on the trace-to-median index (RATMI) for warehouse ranking. The performance criteria were cost, quality, time, productivity, and safety. Data were collected from four mega retail warehouses in the western region of Saudi Arabia for evaluation and analysis. Results: The evaluation of retail warehouse performance using the MCDM approach provided valuable insights for decision-makers and warehouse experts. The criteria weights were determined using the G-BWM, and the RATMI enabled the ranking of the warehouses based on their weighted performance scores. The results highlight the strengths and weaknesses of each warehouse, facilitating strategic planning, resource allocation, and operational improvements. Conclusions: This study presents a novel combined MCDM performance evaluation approach for retail warehouses. The study has implications for effective decision-making processes, resource allocation, and operational efficiency. Furthermore, it serves as a foundation for future research, exploring additional dimensions of warehouse performance and enabling sustainable logistics within the broader supply chain context.

Optimizing warehouse operations for environmental sustainability: A simulation study for reducing carbon emissions and maximizing space utilization

Loading and unloading operations for Stock Keeping Units (SKUs) in warehouses are critical to logistics management systems. However, these operations also have a significant impact on the environment, particularly in terms of carbon dioxide (CO2) emissions. As such, warehouse management must consider not only operational efficiency but also environmental impact. The reduction of CO2 emissions in warehouses is becoming increasingly important, both for legal compliance and to meet sustainability targets. In this article, we will emphasize the environmental impact of warehouse operations, particularly on CO2 emissions, and explore ways to minimize them while still maximizing warehouse performance. We will review various optimization models proposed to address this issue and highlight the importance of considering environmental objectives when designing warehouse operations. We will also describe a simulation study conducted to determine the Pareto optimal frontier for a warehouse design, considering transportation, space utilization, and CO2 emissions. The outcomes of implementing this simulation's results include reduced CO2 emissions and increased space utilization, which demonstrate the potential benefits of considering environmental objectives in warehouse design and management.

A model for inventory management and warehouse performance in the South African retail industry

A model for inventory management and warehouse performance in the South African retail industry

Pengaruh Service Level Supplier Terhadap Performance Logistic pada Warehouse di Pt.Xyz Branch Batam

This research analyzes the influence of supplier service quality variables and Transportation Distribution regulations on warehouse performance, influenced by regional regulations. The survey method used in this research is the observation method and data sampling using a questionnaire. Questionnaires were distributed to 25 respondents, these respondents were suppliers who had been selected according to predetermined provisions. Based on the results of the questionnaire regarding supplier locations, it was found that 76% of suppliers were in the Batam area while 24% were outside Batam. Research findings show that supplier service quality has a positive and significant impact on warehouse performance, and improvements in such services can significantly improve warehouse performance. Apart from that, transportation and distribution variables also contribute positively to warehouse performance, and have a positive and significant influence on local government regulations. The positive correlation between local government regulations and warehouse performance shows that managing letter requirements to fulfill these regulations can smooth the flow of goods distribution and increase service levels which will have an impact on warehouse performance..

Dynamic Scheduling Optimization Method for Multi-AGV-Based Intelligent Warehouse Considering Bidirectional Channel

With the implementation of AGV technology and automated scheduling, storage and retrieval systems have become widely utilized in warehouse management. However, due to the use of unidirectional channels, AGV movement is restricted, and detours may occur frequently. Additionally, as the number of AGVs increases, deadlocks can arise, which lead to delays in order packaging and a decrease in overall warehouse performance. Hence, this paper proposes a dynamic scheduling method for task assignment and route optimization of AGVs to prevent collisions. The routing optimization method is based on an improved A* algorithm, which takes into account the dynamic map as input. Moreover, this paper investigates highly complex collision scenarios in bidirectional channels. Through simulation experiments, it is evident that scheduling methods based on bidirectional channels offer a clear advantage in terms of efficiency compared to those based on unidirectional channels.

Review-based method for evaluating key performance indicators: an application on warehouse system

This paper presents a procedure for selecting, evaluating, and ranking the key performance indicators (KPIs) in the context of warehouse systems. The method aims to help warehouse managers identify and prioritize KPIs most relevant to their business objectives and performance goals, ultimately driving continuous improvement in warehouse performance. The paper provides three main scientific contributions: (i) a selection composed of 70 KPIs extracted from the analysis of 203 scientific articles and clustered according to their business and sustainability objectives, (ii) a KPI ranking based on four different metrics measured analyzing 585 scientific papers from Scopus and, finally, (iii) a fifth metric, measured trough a survey submitted to 15 industrial experts from as many different Italian companies, that is added to improve the ranking system. As a part of the method applied to a case study, the paper provides a comprehensive review of the current scientific literature and industrial sector state of the art on warehouse KPIs. This article proposes an overview of the most used KPIs in research and industry, a support for understanding formalizing definitions, and a guide on how they can be measured and used to manage warehouses.

The time-window strategy in the online order batching problem

When an order arrives at a warehouse it is usually assigned to a batch and a decision is made on how long to wait before assigning the batch to a picker and starting the picking tour. If the idle time of the pickers is minimised, the batch is immediately assigned, and the picking starts. Alternatively, if a time window is introduced, other orders may arrive, and more efficient batches may be formed. The method to decide how long to wait (the time-window strategy) is therefore important but, surprisingly, almost completely overlooked in the literature. In this paper, we demonstrate that this lack of attention is unwarranted, and that the time-window method significantly influences the overall warehouse performance. In the context of the online order batching problem (OOBP), we first demonstrate that the effects of different time-window strategies are independent of the methods used to solve the other subproblems of the OOBP (batching and routing). Second, we propose two new time-window strategies, compare them to existing methods, and prove that our methods outperform those in the literature under various scenarios. Finally, we show how time-window methods influence different objective functions of the OOBP when varying numbers of orders and pickers.

System Dynamic Analysis of the Fleet Availability and Reliability Influence on the Lead Time of the Delivery Order Process

The inventory replenishment process in the warehouse becomes difficult if there is uncertainty. It can cause warehouse performance not to be as expected. The warehouse is an important part of the supply chain subsystem, which smooths the flow of goods from upstream to downstream throughout the system. This paper uses system dynamics modeling to analyze the replenishment of raw materials where there is randomness in availability and reliability and their effects on the delivery lead time of the fleet. The model obtained is much simpler but more robust when compared to the analytical-mathematical model or the discrete-events simulation. Tests on the model show that the model can behave as it should logically. Several experiments were conducted to see how fleet availability's reliability can affect the delay in receiving or delivery lead time. One interesting thing revealed is that reliability does not have to be 100%, but there is a certain minimum threshold for the system to perform well. This is different from availability, which must be 100%.

Warehouse Management Systems for Social and Environmental Sustainability: A Systematic Literature Review and Bibliometric Analysis

Background: With the continuing growth of warehouses globally, there is an increasing need for sustainable logistics solutions in warehousing, but research linking warehouse management systems (WMS) and sustainability is lacking. Methods: A systematic literature review and bibliometric analysis were conducted in Scopus and Web of Science databases from 2006 to 2022 to investigate academic knowledge of WMS contributing to warehouses’ social and environmental sustainability. Results: Findings revealed only 12 topic-relevant articles from 2013 to 2022, primarily published recently. More recent articles have received more citations than earlier published works. The articles were from multiple research fields, such as business economics, engineering, computer science, and social sciences, with only one article on environmentally sustainable technologies. The top keywords were “warehouse management system”, “internet of things”, “industry 4.0” and “supply chain”. Only six articles had environmental sustainability terms in the keywords. Findings show more discussions about social rather than environmental sustainability. Most studies suggest integrating WMS with other systems to support sustainability efforts in warehousing. Conclusions: The study addressed a gap in academic literature regarding WMS and sustainability. Research findings added knowledge of practical activities to achieve warehouse operations and performance sustainability and proactively reduce warehouse operations’ environmental and social impacts.

Warehouse Performance Improvement During Big Event using Discrete Event Simulation approach : A Case Study of Food and Beverages Company in Shah Alam

The purpose of this study is to see how customer demand changes when Malaysian e-commerce hosts a major event affect the warehouse operations. This is due to the fact that, when compared to non-major events, the pricing are very reasonable. As a result, when the major events happen, e-commerce especially the warehouse operations will face significant challenges in managing customer orders. Long lines can be found in the picking and packing sections. Orders will then be shipped later than anticipated. In this study, Company X is one of the e-commerce companies affected by this issue. Discrete Event Simulation (DES) was used as the method in measuring the warehouse performance under study. By introducing several scenarios that are appropriate for company X, the company's warehouse performance is found to be more efficient in terms of reducing process queuing time and resource utilization.

Determination of Warehouse Performance Measurement Indicators at PT Pos Logistik Indonesia with The Balanced Scorecard Method

Determination of Warehouse Performance Measurement Indicators at PT Pos Logistik Indonesia with The Balanced Scorecard Method

Managing the Logistics Distribution Performance Using Digitalization in the FMCG Sector

The logistics performance of fast-moving consumer goods (FMCG) depends profoundly on transportation and warehouse performance, which can be worked on through digitalization. This paper studies the distribution of FMCG and tries to identify inefficiencies in transportation and warehousing operations. The factors leading to inefficiencies in transportation and warehouse performance are identified through a literature review. The goal is to assess the impact of digitalization on composed activities scattering execution. The information was gathered through organized polls from 256 managers and executives in the FMCG area. The information is examined through structural equation modelling with AMOS. The calculated model is formed, and speculations are tried in light of the model. The measuring model’s parameters were assessed for reliability, convergent and discriminant validity. The results of the study indicate the optimization of transport performance and warehousing performance has a positive impact on the logistics distribution performance of FMCG. The partly mediating effect of digitalization is also supported and found to be substantial in enhancing logistics distribution performance.

Optimizing storage assignment, order picking, and their interaction in mezzanine warehouses

In warehouses, order picking is known to be the most labor-intensive and costly task in which the employees account for a large part of the warehouse performance. Hence, many approaches exist, that optimize the order picking process based on diverse economic criteria. However, most of these approaches focus on a single economic objective at once and disregard ergonomic criteria in their optimization. Further, the influence of the placement of the items to be picked is underestimated and accordingly, too little attention is paid to the interdependence of these two problems. In this work, we aim at optimizing the storage assignment and the order picking problem within mezzanine warehouse with regards to their reciprocal influence. We propose a customized version of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for optimizing the storage assignment problem as well as an Ant Colony Optimization (ACO) algorithm for optimizing the order picking problem. Both algorithms incorporate multiple economic and ergonomic constraints simultaneously. Furthermore, the algorithms incorporate knowledge about the interdependence between both problems, aiming to improve the overall warehouse performance. Our evaluation results show that our proposed algorithms return better storage assignments and order pick routes compared to commonly used techniques for the following quality indicators for comparing Pareto fronts: Coverage, Generational Distance, Euclidian Distance, Pareto Front Size, and Inverted Generational Distance. Additionally, the evaluation regarding the interaction of both algorithms shows a better performance when combining both proposed algorithms.