Warehouse Managers Research Articles

Comparative analysis of outsourcing and in house warehouse management system to improve productivity and stock accuracy

This study compares the impact of outsourced and in-house Warehouse Management Systems (WMS) on productivity and stock accuracy in the fast-moving consumer goods (FMCG) sector. Data was collected from a logistics services company in Palembang using quantitative methods, including measurements of productivity per person per hour and stock accuracy per SKU. Productivity was assessed based on items processed per unit time, while stock accuracy compared physical stock with system records. Additional data was gathered through a Google Form survey targeting operational staff and warehouse managers to understand the implementation of both WMS models. The survey covered critical processes such as putaway, picking, and inventory, providing insights into operational efficiency and challenges associated with each model. Dummy variable multiple regression was applied to evaluate the performance impact of each WMS model, supplemented by qualitative insights from structured interviews. Findings reveal that WMS in-house is better than outsourcing WMS. While 12.5% of respondents rated the outsourced WMS as inefficient, none reported inefficiencies in the in-house system. Additionally, 62.5% of respondents found the in-house WMS highly effective, citing smoother implementation and higher reliability. The in-house WMS also demonstrated superior operational efficiency, storage accuracy, and responsiveness. It provided better storage location guidance (33.3%) and faster, more accurate operator navigation (26.5%) compared to the outsourced system. Moreover, only 33.3% of respondents noted delays in resolving technical issues with the in-house system, versus 68.8% for the outsourced system. Statistical analysis further supported these findings, showing significant advantages for the in-house WMS in productivity (p=0.068) and stock accuracy (p=0.000). These results highlight the strategic advantages of adopting an in-house WMS, underscoring its role in enhancing operational efficiency and maintaining competitiveness in the dynamic FMCG market.

Operating policies for robotic cellular warehousing systems

Robotic Cellular Warehousing Systems provide an innovative robot-to-goods picking approach designed to improve robot transportation efficiency, where robots move to pick items and transport the picked items to workstations. In this study, we investigate the optimal operating policies for such a system by comparing two picking strategies (pick-while-sort and pick-then-sort) and three robot-to-workstation assignment rules (random, closest, and dedicated). Specifically, we develop dedicated closed queuing networks to model robot-to-goods picking and estimate warehouse throughput under different policies through single-class and multi-class models. The effectiveness of these analytical models is validated through numerical simulations, with an average gap of 5.53% between simulation and analytical results. Additionally, we conduct a series of numerical experiments to examine the impact of various factors on warehouse performance, including the numbers of robots and workstations, robot capacity, order size, and sorting efficiency. Based on the experimental findings, we provide managerial implications that offer insights into optimizing resource allocation and system configuration. These insights enable warehouse managers to improve operational efficiency and overall performance.

Integrating arrival time estimation in truck scheduling: an explorative study in grocery retailing

ABSTRACT This paper studies a new managerial approach that integrates predictive trucks’ estimated time of arrival (ETA) into truck scheduling to deal with the truck arrival time uncertainty. The approach exploits ETA to reschedule trucks by the up-to-date information and aims to minimize the trucks’ waiting time. The approach was applied in a real case. Results quantified the impact of adopting ETA for truck scheduling, also showing how the ETA accuracy and peak truck arrival rate affect the total trucks’ waiting time. The paper enriches both truck scheduling literature, investigating a new managerial approach to deal with truck arrival time uncertainty, which greatly threatens the synchronization of logistics flows, and Industry 4.0 literature, showing how real-time data availability can change traditional decision-making processes. Insights for the approach application are discussed, together with the economic, environmental, and social benefits by supply chain actors (i.e. carriers, warehouse managers, and drivers).

Evaluation of Stuffing Out in the Warehouse PT. Lyon Oceanic Trans Surabaya

This study aims to evaluate the obstacles causing delays in the stuffing out process at the warehouse of PT. Lyon Oceanic Trans Surabaya. The research method used is a qualitative approach by collecting data through observations and in-depth interviews with warehouse workers and managers. The results show that the delay in stuffing out is caused by several main factors, namely the late delivery of goods from customers to the warehouse and the lack of support tools such as forklifts, thus relying only on human labor. The conclusion of this study indicates the need for increased efficiency in the delivery of goods as well as the addition of facilities and equipment in the warehouse to expedite the stuffing out process.

Optimization of warehouse picking to maximize the picked orders considering practical aspects

Majority of previous studies on optimization of warehouse order picking lack real-world application and overlook complexities such as varying items’ weight, workload balance, and heterogeneous pickers. To address these issues, in this study, mathematical programming models are developed based on two approaches to assign orders to pickers and determine pickers’ routes in a North American consumer goods warehouse. Both approaches maximize the number of picked orders. However, in the simultaneous modelling approach, decisions are made in one model, while in the sequential modelling approach, first routing decisions then order assignment decisions are made. The sequential modelling approach compared with the simultaneous one yields better results in a shorter time. For the considered warehouse, the results suggest that the warehouse may not be able to handle more than 700 orders per shift without expanding its workforce. Furthermore, adding one picker increases the number of picked orders by 2%. Additionally, balancing pickers' workload is more effective when there are fewer than 600 orders available for picking per shift, because with a higher number of orders, pickers remain busy throughout the entire shift. The proposed mathematical modelling approaches enable warehouse managers and staff to process more orders with available resources (equipment, time, staff) and make better decisions using available data.

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.

Influence of Supply Chain Technological Integration on the Performance of Formal Manufacturing Firms in Mombasa County, Kenya

Technological integration within the supply chain has emerged as a pivotal determinant for the growth and competitiveness of manufacturing companies amidst the rapidly evolving business landscape. However, in Kenya, numerous firms encounter challenges in embracing and assimilating the latest technological advancements into their supply chain operations. This study aimed to assess the impact of supply chain technological integration on the performance of formal manufacturing firms in Mombasa County. Grounded on the Innovation Diffusion Theory, the research targeted 50 general procurement managers, 100 warehouse managers, and 100 general operation managers across 50 manufacturing enterprises. Utilizing the Yamane formula, a sample size of 152 respondents was determined, and data was collected through questionnaires. Statistical analysis was conducted using SPSS. The findings show that by enhancing operational efficacy and efficiency, the integration of supply chain technology significantly enhances overall business performance. Consequently, the study concludes that supply chain technological integration plays a positive role in influencing firm performance among formal manufacturing enterprises in Mombasa County. To optimize performance, it is recommended that firms invest in robust and reliable technologies. Furthermore, there is a need for additional research to explore the impact of supply chain technological integration on firm performance across diverse industries and regions within Kenya.

Implementation of the First In First Out (FIFO) Algorithm in the Sandal and Shoe Product Inventory (Stock) Application

This study addresses the optimization of inventory management for sandal and shoe products, at CV Diva Karya Mandiri Warehouse, which covers of five key features: a dashboard, master data management, transaction data, reporting, and user management. The First In First Out (FIFO) algorithm is specifically applied to the transaction feature, ensuring timely disbursement in line with the order of receipt. It is implemented using Rapid Application Development (RAD) methodology, which consists of Planning Requirements, User Design, Construction, and Cutover phases. The developed inventory application offers two access levels: administrators with comprehensive access and warehouse managers with limited access for viewing, searching, and filtering item data. This study successfully implementing the FIFO algorithm, with 95% Blackbox testing result achieved through boundary value analysis approach.Top of Form

Waveless Picking in Supply Chain Performance of Food and Beverages Processing Firms in Kenya

The purpose of this study was to analyze the role of waveless picking in supply chain performance of food and beverages manufacturing firms in Kenya. The research concentrated on the 134 food and beverage manufacturers that are operating in Nairobi City County besides being registered with Kenya Association of Manufacturers. The study adopted a mixed research design with both qualitative and quantitative approaches. The target population of the study was the 134 food and beverages manufacturing firms in Nairobi County. A sampling frame of this study included a list of the 134 manufacturing companies in Nairobi County that are members of the Kenya Association of Manufacturers. The study utilized simple random sampling. A sample size of 100 was selected with the aid of Yamane 1967 formula. Both primary and secondary data was collected using a questionnaire. The questionnaire was tested pilot at 10 food and beverages manufacturing companies in Kiambu county. These pilot study questionnaires were filled out by warehouse managers. The statistical package for social sciences (SPSS) version 25 was used to analyze the data. Using content analysis, the qualitative data was analyzed. Quantitative data was analyzed using statistical methods involving descriptive and inferential data. A multiple linear regression model was applied to analyze the relationship between the variables. Analysis was also performed on the correlation. In this study, the findings were presented using tables and graphs. Data presentation made use of percentages, frequencies, means and other means of central tendencies. The study on revealed several ways to improve operational efficiency and productivity. Most enterprises have not reduced warehouse travel time, indicating potential for improvement. The study recommended reducing warehouse travel time, implementing batch picking, designating picking zones, increasing product forecasting accuracy, improving cash flow management and supply chain scheduling, accepting technology and automation, and promoting continuous learning and development.

Availability of essential, generic medicines before and during COVID-19 at selected public pharmaceutical supply agencies in Ethiopia: a comparative cross-sectional study

ObjectivesLockdowns and border closures impacted medicine availability during the COVID-19 pandemic. This study aimed to assess the availability of essential, generic medicines for chronic diseases at public pharmaceutical supply agencies...

Analisis Rantai Pasok Ketersediaan Bahan Baku Produk Pertanian Jenis Beras dengan Metode Supply Chain Operations Reference

Supply chain management affects the availability, sufficiency, and quality of raw material inventory. With effective supply chain management, the inventory will always be well-maintained, meeting the needs and demands when required, especially at UD. Fajar Samudra. The purpose of this research is to understand the supply chain management regarding raw material inventory at UD. Fajar Samudra using a descriptive qualitative research method that addresses in more detail the specific and in-depth issues studied at UD. Fajar Samudra. In qualitative research, the population and sample are referred to as informants (company executives, warehouse managers, and the three largest suppliers at UD. Fajar Samudra). The research results indicate that the supply chain management at UD. Fajar Samudra shows that the supply chain management has not been able to meet the raw material inventory due to several issues in the field. These issues include inadequate procurement of raw materials due to the selection of rice types that do not match the requirements, damaged rice quality due to distribution processes, and unfulfilled quantity needs or demands, leading to dissatisfaction among consumers, as measured by the Supply Chain Operations Reference (SCOR) performance metrics. The advice that can be given to UD. Fajar Samudra is to make improvements by conducting forecasting based on historical sales data, engaging suppliers that implement management information systems, and implementing line balancing to enhance production strategies.

Analiza osobina subjekata krivičnih dela protiv Vojske Srbije određenih Krivičnim zakonikom

The Criminal Code of the Republic of Serbia recognizes individuals as perpetrators of offenses against the Serbian Armed Forces in a manner that, although linguistically similar to the way relationships are determined within the Serbian Armed Forces and the Ministry of Defense, fundamentally differs from the definitions provided by the Law of the Serbian Armed Forces. This may pose a challenge for authorized individuals leading criminal proceedings, as they often lack sufficient knowledge of the organization of the Serbian Armed Forces and struggle with its numerous regulations. The issue of legally defining individuals designated as perpetrators of criminal offenses by the Criminal Code is therefore explored through the method of content analysis and a comparison of regulations and broader scientific literature. According to the Criminal Code of the Republic of Serbia, individuals designated as perpetrators of criminal offenses against the Serbian Armed Forces include: military personnel; military superiors; subordinates; officials performing border duties; warehouse manager; citizen of Serbia; commander of a warship; member of a warship's crew; and member of a military aircraft crew. Through further analysis of the content of the regulations of the Serbian Armed Forces, clear definitions are provided for individuals such as subordinates, warehouse managers, citizens of Serbia, and members of a military aircraft crew in all comparative laws and regulations. Minor terminological deviations arise in the definition of the concept of military personnel, while some other subjects are significantly differently defined in the mentioned regulations (such as military superiors, who are actually individuals with the functional duty of a superior; officials performing border duties, who, since 2007, fall under the jurisdiction of the Ministry of Internal Affairs and cannot commit criminal offenses against the Serbian Armed Forces; or the commander of a warship and a member of a warship's crew, who can only be found on a military vessel).

Cold Storage Order Picking Performance: Effects of Load Unit Utilization and Product Volume

Increasing labor costs in retail have intensified the focus on order-fulfillment performance, particularly in warehouse operations. In this context, manual picker-to-parts systems, especially in cold storage environments processing deep-frozen products below -20°C, are of significant interest. Our study explores order picking in such cold storage environments, where products are packed into insulated, roll containers serving as load units. While existing research has explored the effects of product characteristics such as weight, volume, and different load units like pallets from a theoretical perspective, the specific interplay between load unit utilization levels and product volume remains underexplored in practical settings. To address this gap, we conducted a field study focusing on a cold storage of a prominent German brick-and-mortar grocery retailer and analyzed a comprehensive longitudinal dataset comprising 227,274 storage location visits by 29 order pickers in January 2023. Employing a mixed-effects model, we examined the impact of these factors on order picking time (OPT). Our findings revealed a subtle relationship: a 1% increase in load unit utilization level correlates with a 1% increase in OPT, signifying that higher utilization levels negatively impact pickers’ performance. Notably, our analysis also indicated that product volume moderates this effect. Specifically, lower product volumes can mitigate the adverse effects of high load unit utilization, whereas higher product volumes amplify these effects. This research offers valuable insights for warehouse managers, particularly in cold storage settings on finding the balance between OPT and load unit utilization.

A single-valued neutrosophic-based methodology for selecting warehouse management software in sustainable logistics systems

Warehouse operations cover activities that must be carried out systematically. Warehouse management systems (WMS) are needed for successful warehouse management. With digitalization, alternative software programs for WMS have increased. In this study, the selection of the WMS software program for the general warehouse type is discussed. The main motivation of the research is to develop a suitable alternative selection methodology based on criteria for warehouse managers. The research is carried out in several stages. In the first stage, the software selection criteria are determined based on the literature review. In the second stage, the criteria are weighted with the criteria importance through the intercriteria correlation (CRITIC) method based on single-valued neutrosophic sets (SVNSs). In the third stage, alternatives for WMS software are ranked with the technique for order preference by similarity to an ideal solution (TOPSIS) based on SVNSs. Three decision-makers, four alternatives, and eight criteria are used in the study. The empirical research is conducted on a warehouse providing general storage services in Turkey. In addition, the sensitivity analyses are performed and the results are compared. According to the research findings, the most valuable criterion in WMS software selection is determined as “ease of use”. As a result of the research, suggestions are developed for WMS software manufacturers, warehouse managers, and researchers. The novelty of this research is that WMS selection is applied for the first time using multi-criteria decision-making methods.

Swot Analysis of Corn Plant in Nganjuk District

Corn is a food commodity as a staple food besides rice in Indonesia. Corn is a plant that can be planted in rice fields or gardens. The aim of the research is to study the SWOT analysis of corn plants spread across Nganjuk Regency. The research method uses quantitative descriptive. The results of the SWOT analysis of corn plants in Nganjuk Regency are as follows: average corn production, total annual production capacity is 203,402 tons. The obstacles that occur in the field are the Human Resources management system for warehouse managers, the operations of warehouse institutions are relatively low. The market network is considered to be less extensive and the sense of trust in corn farmers is still low while purchasing prices from farmers are low, therefore farmers sell their products in local markets. Supply chain management is also still very low. So it is very necessary to improve the management of farmer empowerment, and the quality of all parties involved must be improved in order to produce good results.

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.

Warehouse Automation Implementation Environment: Case of Central Warehouse Management in Mali, West Africa

The implementation of warehouse automation has proven to be an effective way to increase productivity and inventory accuracy, lower labor costs, and improve safety in the warehouse environment. This research aims to investigate the factors contributing to the success of warehouse automation implementation. This study offers a unique and modern warehouse automation environment model as a solution for complete implementation in warehouse automation operations. The study was conducted in Mali, West Africa. A total of 100 responses were collected among warehouse managers through an online Microsoft Forms survey. Smart PLS version 4.0 software was used to analyze the data.

Current state and improvement prospects of warehouse workers health and safety practices in Bulgarian manufacturing and trading organizations

Occupational health and safety (OHS) of warehouse workers is a crucial issue for warehouse managers. The importance of OHS practices has increased over recent years due both to high levels of fatal accidents in the logistics industry, and chronic shortage of labor in the sector, which requires systematic efforts to reduce absenteeism and increase warehouse employee motivation. This article aims to address the current state of some fundamental OHS practices of warehouse workers in Bulgarian manufacturing and trading organizations, and to outline some recommendations for their future improvements. The data were collected using the questionnaire survey method among 91 manufacturing and trading organizations in Bulgaria, which operate warehouses, and were processed using Chi-square analysis. The results show that the share of trading organizations, which implement OHS practices is lower, in comparison with surveyed manufacturing organizations. In addition, small organizations lag behind medium and large regarding the use of fundamental measures to protect warehouse workers. The main research findings indicate that there is a need to expand the frequency of OHS practices applied in trading organizations through a wider implementation of joint firefighting drills with fire and emergency safety authorities, adaptation of warehouse infrastructure, clear designation of emergency exits and placement of signs/work instructions for safe work at workplaces. Furthermore, it is critical to increase the use of appropriate work clothing and personal protective equipment (PPE), as well as to provide regular safety briefings in trading warehouses and small organizations.

Warehouses without aisles: Layout design of a multi-deep rack climbing robotic system

In the last decade, different multi-deep rack climbing robotic (MRR) systems have been introduced, particularly in e-commerce warehouses. These systems have great benefits, as aisles are no longer needed, allowing a high storage density on a small footprint. They only need vertical channels through which battery-powered robots can climb the racks, retrieve totes from any desired position, and bring them to a workstation. This paper studies two novel MRR system layouts: the cross and the compact layout. In addition, we compare performance with the more traditional aisle-based layout. The system performance, particularly operational cost and energy consumption, depends on these system layouts. The paper establishes queuing network models to investigate the trade-off between storage capacity and throughput of the system with these three layouts, taking robot blocking prevention into account. We compare the throughput, storage density, horizontal travel time, and energy consumption of the system. The results show that, in most cases, the compact layout outperforms other layouts on throughput. For energy consumption, the choice of layout depends on the footprint. We formulate a model to assist warehouse managers in choosing a layout of minimum annual operational cost, with a required storage and throughput capacity. We also compare the MRR system with an alternative robotic compact storage and retrieval system on operational cost and energy consumption. The MRR system appears to always have lower energy consumption and operational cost.

Leveraging autonomous mobile robots for Industry 4.0 warehouses: a multiple case study analysis

PurposeDespite its potential, warehouse managers still struggle to successfully assimilate autonomous mobile robots (AMRs) in their operations. This paper means to identify the moderating factors of AMR assimilation for production warehouses that influence the digital transformation of their intralogistics via AMRs.Design/methodology/approachDrawing on innovation of assimilation theory (IAT), this study followed an explorative approach using the principles of the case study method in business research. The cases comprised of four AMR end users and six AMR service providers. Data were collected through semi-structured interviews.FindingsFour clusters of moderators that affect each stage of AMR assimilation were identified. These clusters include organizational attributes of end users (i.e. production warehouses), service attributes of service providers, technology attributes of AMRs and relational attributes between the AMR service providers and the AMR end users.Originality/valueThe authors extend the IAT framework by identifying various moderating factors between different stages of the AMR assimilation process. To the authors' knowledge, this is the first study to introduce the perspective of AMR end users in conjunction with AMR service providers to the “Industry 4.0” technology assimilation literature. The study propositions regarding these factors guide future intralogistics and AMR research.