Warehouse Costs Research Articles

ПРИМЕНЕНИЕ МОДЕЛИ PDCA И МОДИФИКАЦИИ АВС-XYZ-АНАЛИЗА В УПРАВЛЕНИИ ПРОИЗВОДСТВЕННЫМИ ЗАПАСАМИ

The article discusses the possibility of using a process approach in managing the company's inventory based on the Shewhart-Deming cycle (PDCA model), as well as identifies modern problems of using ABC-analysis and XYZ-analysis models in practice, and proposes the introduction of a modified ABC-XYZ analysis model. The results of the study showed that the development of an inventory management policy in a company based on the PDCA model with the use of the proposed modification of the ABC-XYZ analysis will make it possible to systematize the processes of warehousing and supply of stocks using the «Just-in-Time» method, minimize warehouse costs by reducing the volume of stock, reduce the volume of illiquid inventory, improve customer satisfaction, accelerate inventory turnover.

The study of joint order batching and picker routing problem with food and nonfood category constraint in online‐to‐offline grocery store

AbstractOrder picking is the process of retrieving products from the storage locations to meet customer orders, which accounts for more than 55% of the total warehouse cost. The joint order batching and picker routing problem (JOBPRP) is an effective way to improve picking efficiency. Although many warehouses face the physical constraints of products that have impact on the picking sequence, such as weight, size, shape, and fragility, JOBPRP with such physical constraints has not been widely studied in the literature. This paper is inspired by a practical case observed in an online‐to‐offline grocery store in China, where food products should not be carried under nonfood products in the picking container to maintain food safety, called category constraint. Therefore, JOBPRP with category constraint is studied. The JOBPRP optimization models with and without category constraint are formulated to minimize the total processing time, and the modified seed algorithms, with new seed addition rules and modified near‐optimal routing methods are proposed to solve the models. The performance of the proposed algorithms is evaluated in different seed addition rules, routing methods, sort time scenarios, and storage assignment strategies (SASs) in a case study. We found that considering category constraint in JOBPRP can reduce the total processing time, and the modified seed algorithms perform better than the traditional first‐come‐first‐serve benchmark algorithms and the seed algorithms with traditional seed addition rules and S‐shape routing method. The SASs where nonfood and food products are separately in fewer number of zones are recommended.

ANALISIS DAN PERANCANGAN SISTEM AKUNTANSI PERSEDIAAN PADA UD LI JAYA KUPANG

Inventory is a large asset owned by the company. Large investments invested in the form of inventory willcause problems related to the cost of organizing where the cost will increase the warehouse costs. Inventoryis very vulnerable to damage, theft, and misappropriation. The inventory accounting system plays animportant role in the arrangement of avoiding the repatriation of the company's wealth, especiallyinventory. Proper and correct accounting treatment of inventory is absolutely necessary. This is becausethe inventory post has a considerable influence in the financial statements, which is in the balance sheetand in determining the price of inventory in the income statement. The problem in the research is how todesign good documents, records, and procedures related to the inventory accounting system ofmerchandise at Usaha Dagang Li Jaya Kupang and how the internal control system prevent the multipositions, mis-recording, and possible misappropriation of inventory of at Usaha Dagang Li JayaKupang. The results showed that the inventory accounting information system at UD. Li Jaya hasweaknesses in terms of inventory recording undone because of the limited educational background of theexisting workforce and in terms of its internal controls that have not been effective. The obstacles faced byUD. Li Jaya Kupang is the absence of computerized administration in the recording system, so that isno recording at all in the warehouse section. The inventory accounting information system at UD LiJaya Kupang must have its own recording administration, so that employees do not record bythemshelves.
 Keywords : Inventory, Intenal Control, Inventory Accounting Information System

PickupSimulo–Prototype of Intelligent Software to Support Warehouse Managers Decisions for Product Allocation Problem

In this paper, a new model supporting decisions about product allocation in an order-picking shelf warehouse is presented. Industry 4.0 pays attention to inciting the processes, self-analysis and self-optimization of the short response time to market changes, and the maximum use of related data. Methods for solving the product allocation problem (PAP) are not enough to meet the requirements of Industry 4.0. The authors present a new approach for solving PAP. The novelty introduced in the model is based on correlated data—products parameters, clients’ orders and warehouse layout. The proposed model contains elements of intelligence. The model, after product classification and allocation, analyzes its effectiveness by a simulation of the order-picking process. The application of artificial neural networks (ANN) as a part of the computing model enables the analysis of large data sets in a short time. The presented study has proved the proposed model, both for practical and scientific purposes. Relying on the research results, the total warehouse cost could be reduced by 10 to 16 per cent. With the use of the proposed model, it is possible to predict the effect of future actions before their execution. The model can be implemented in most conventional warehouses to raise the throughput performance of the order-picking process.

Impact of ERP Implementation on Productivity and Profitability: An Empirical Study on the Largest Bangladeshi Steels Manufacturer

The research aims to evaluate the impact of Enterprise Resources Planning (ERP) implementation on the productivity and profitability of BSRM Steels Limited. The study focuses on addressing the gap in technology adoption literature by undertaking an empirical comparison of the impact of ERP implementation. Five productivity variables called service time, lead time, inventory turnover, output-input ratio, and warehouse cost are evaluated. Gross Profit Margin represents profitability as ERP is mainly implemented in the inventory management system of BSRM. Paired sample t-tests between the pre and post ERP performances have been used to evaluate the impact of ERP. Ten years' data ranging from 2010 to 2019 have been considered for the study. Five years' data (2010-2014) consist of before ERP period, and the other five years' data (2015-2019) represent after ERP implementation period. The study reveals that both the productivity and profitability of BSRM have significantly improved after ERP implementation. This paper will have an impactful contribution to the academic literature of technology adoption in the manufacturing sector, particularly for ERP implementation in the steel industry of Bangladesh, which could be supportive for further study on the topic.

Total Costs of Centralized and Decentralized Inventory Strategies—Including External Costs

The paper deals with the economic efficiency of decentralized and centralized strategies of distribution goods in terms of both internal efficiency of firms and external costs of logistics processes (first of all external costs of transport). The author developed a model (using an electronic spreadsheet) in order to calculate the economical efficiency in the micro and macro dimensions in order to find the distances on which distribution using one central warehouse is more profitable than decentralized distribution. The results of the simulations show that the strategy of centralized inventories can be in many cases an economically effective strategy although not for deliveries on very long distance. The results confirm that the benefits of centralization are lower inventories, although the simulations do not confirm the applicability of the square root law to calculate the level of inventories. However, they confirm a positive impact on the level of logistic customer service, measured by the availability of stocks. Better service is probably the main benefit of this strategy. In order to investigate the impact of individual parameters on the total costs of logistics processes 1300 simulations were carried out for various cases: The volume of annual sales, fluctuations in demand, the value of distributed goods, the number of warehouses in a decentralized system and the width of the product range, costs of warehousing, and maintaining stocks, and the distance of transport and in deliveries to customers.

Yağmur Suyu Toplama Sistemlerinde Optimum Depolama Yönteminin Belirlenmesi: Karabük Üniversitesi Sosyal Yaşam Merkezi Örneği

Yağmur suyu toplama (YST) sistemi, yağmur suyunu toplama ve bu serbest yağmur suyunu belirli bir amaç için tekrar kullanmadan önce depolama yöntemidir. Bu sistem, dünyadaki yerel iklim şartlarına uygun olan çoğu bölgede yaygın olarak kullanılmaktadır. Yağmur suyu toplama sistemlerinin optimum maliyetle uygulanması ve düşük geri ödeme süresiyle tasarlanması, sistemin sürdürülebilirliği ve tercih edilebilirliği açısından önemlidir. Bu çalışmada, yüksek alanda sert zemine ve çatı yüzeyine sahip olan Karabük Üniversitesi Sosyal Yaşam Merkezi’nin meydan ve çatısından elde edilebilecek yağmur suyu hasadı için yağmur suyu toplama sistemi (YST) tasarımı sürecinde uygun depo büyüklüğü hesaplanmıştır. Üniversitenin mevcut depo hacmi de göz önünde bulundurularak kurgulanan senaryolar üzerinden, kurulabilecek YST sistemi için inşaat ve depo maliyetleri göz önünde bulundurularak optimum depolama yöntemine karar verilmiştir. Çalışmanın YST sistem tasarımında ön süreç olan depo miktarı ve depolama yönteminin belirlenmesi aşamasında, sistem kurucularına ve karar vericilerine yol göstermesi beklenmektedir.

Multi-Agent Simulation Environment for Logistics Warehouse Design Based on Self-Contained Agents

We propose a multi-agent simulation environment for logistics warehouses. Simulation is a crucial part of designing industrial systems, such as logistics warehouses. A warehouse is a multi-agent system (MAS) that consists of various autonomous subsystems with robots, material-handling equipment, and human workers. It is generally difficult to analyze the performance of a MAS thus, it is important to model a warehouse and conduct simulations to design and evaluate the possible system configurations. However, the cost of modeling warehouses and modifying the models is high because there are various components and interactions compared to conventional multi-agent simulations. We proposed a self-contained agent architecture and message architecture of a multi-agent simulation environment for logistics warehouses to reduce the simulation-model development and modification costs. We quantitatively evaluated our environment in terms of development costs by comparing such costs of our environment and a widely used multi-agent simulation environment.

Online trading as a key direction of commercial business development for steel companies

Intensive development of specialized electronic trade platforms through Internet changes significantly the mechanism of interaction at the market of industrial goods. Development of online trade allows to steel manufacturers to expand the geography of metal products sales, to deal with small orders customers, to improve the service, as well as to make the process of marketing transparency. The role of online sales in the forming of income of metallurgical companies grows stably, and increase of share of sales through online shops becomes an important part of their further development strategy. It was shown, that practically all big Russian steel companies like NLMK, “Severstal”, OMK, TMK, ChTPZ and other the trade internet platforms have trade internet platforms. Big steel manufacturers use the new possibilities and take advantage of competitive preference. In parallel significant transformations at the market of metal products are observed. In particular, the reduction of transaction expenses due to automation of sales processes excludes practically middlemen - metal traders out the process, who earlier accomplished a significant share of internal sales of steel-works' products. This change resulted in an increase of the number of direct contractors, allows to the producers of metal products to understand better the demand status at the market, needs and expectations of customers. Another important factor is the additional stimulating of production and commercial cooperation of metal products manufacturers within a frame of a model of competitive cooperation, joint usage of technological and infrastructural potential with a purpose of synergy effect obtaining. Therefore, the deeper interaction of companies within a frame of infrastructure of online commerce creates a base for rationalization of production and logistic activity in steel industry, as the following: determination of optimal assortment and volume of production, reduction of logistic arm of delivery and decrease of warehouse costs.

Cross Docking as a factor of Distribution Efficiencies Improving in conditions of Governance Digitalization

This paper is an attempt to investigate the impact of cross docking on transportation and distribution efficiencies, while focusing on role of cross docking to reduce warehousing cost. 1073 Respondents from the logistic industry were selected through restricted probability sampling, for crawling the perceptions/responses on the proposition of this research while the 1000 responses were filtered and recorded for evaluating the hypotheses and extracting the empirical findings on the impact of cross docking on improving distribution efficiencies and reducing warehousing cost. The responses to gauge the propositions / hypotheses of the study were collected from the respondents belong to logistic industry from four major Asian countries including China, Pakistan, India and Sri Lanka, while, the respondents were contacted through their LinkedIn and Facebook profiles. The findings confirmed that 1% improvement in cross docking reduces 32.4% warehousing cost and improves 35.6% distributions efficiencies significantly.

The effectiveness of humanitarian supply chain management in Zimbabwe

Background: Supply chain management (SCM) implementation in selected drought-stricken areas in Zimbabwe has been negatively influenced by the marginalisation of indigenous leaders and an intolerant political system.Objectives: This study examines the influence of culture and leadership attitudes, as well as the political, economic and legal framework, on the effectiveness of the humanitarian supply chain (HSC) during droughts in Zimbabwe. The effect of culture, leadership attitudes, and the political, economic and legal framework on HSC effectiveness in Zimbabwe has not been explored by researchers.Method: The study adopted a quantitative exploratory research design utilising the case study approach. The study sample consisted of 130 respondents comprising government and non-governmental organisation (NGO) officials whose primary responsibilities are drought disaster operations.Results: The study results revealed that the culture, leadership attitudes and political state did not positively influence the effectiveness of the HSC in Zimbabwe. In addition, the economic state and legal framework positively influenced the effectiveness of the HSC on drought management. Accordingly, the empirical results found that the existing legal framework positively influenced the effectiveness of the HSC. Furthermore, an association between educational background and work experience had an impact on the reduction of transport and warehouse costs, which are critical components of a humanitarian relief supply chain.Conclusion: This study is expected to significantly contribute to the crafting of effective HSC and intervention strategies. The study also adds to the body of knowledge in HSC and disaster management as there is a shortage of empirical data in this field of study.

The Sustainable Economic Order Quantity Model: A Model Consider Transportation, Warehouse, Emission Carbon Costs, and Capacity Limits

Recently, the problem of minimizing emission carbon in the industry has become a focus of much research. One of the efforts that were successfully carried out was managing the sustainable economics order quantity (SEOQ). However, several SEOQ had assumption such as (1) Transportation and warehouse costs are ignored, (2) Transportation emissions are avoided, and (3) warehouse Capacity Limit are ignored. In this paper, we developed the SEOQ model with warehouse costs and capacity limits. There are two proposed SEOQ models. Model 1 was the SEOQ model with Transportation and warehouse costs also emission carbon. At Model SEOQ 2, this model considered Transportation and warehouse costs, emission carbon, and capacity. We also proposed procedures to minimize total inventory costs. Finally, a numerical experiment was conducted to test the model. Based on numerical experiments, the proposed model useful to solve SEOQ problems with Transportation and warehouse also costs capacity limits.

Strategic Decisions on the Establishment of an Offshore Warehouse for Manufacturers with an E-Commerce Channel

While Chinese manufacturers increasingly use cross-border e-commerce platforms to sell products to overseas customers, international express delivery is commonly used to meet the requirement of short order-to-delivery time for the online end customers. In order to reduce the logistics cost while meeting the service level, many manufacturers are considering renting or constructing an offshore warehouse. Goods are shipped in bulk to the offshore warehouse in advance and the daily customer orders are fulfilled by the warehouse inventory. Strategic decisions arise regarding the need for as well as the location and capacity of an offshore warehouse. This paper establishes a dedicate discrete-event simulation model to analyse these strategic decisions with considerations of key variables in different scenarios, including the order arrival rate, inventory cost and warehouse costs. The optimal inventory policy of the offshore warehouse is obtained via a metaheuristic method embedded in the simulation model. Experiments and sensitivity analysis are conducted to evaluate the impact of the key variables on the strategic decisions. The established model provides a systematic method for the decision-making regarding the optimal design of offshore warehouses for the fast-growing cross-border e-commerce industry.

Using different machine learning approaches to evaluate performance on spare parts request for aircraft engines

The Aircraft uptime is getting increasingly important as the transport solutions become more complex and the transport industry seeks new ways of being competitive. To reach this objective, traditional Fleet Management systems are gradually extended with new features to improve reliability and then provide better maintenance planning. Main goal of this work is the development of iterative algorithms based on Artificial Intelligence to define the engine removal plan and its maintenance work, optimizing engine availability at the customer and maintenance costs, as well as obtaining a procurement plan of integrated parts with planning of interventions and implementation of a maintenance strategy. In order to reach this goal, Machine Learning has been applied on a workshop dataset with the aim to optimize warehouse spare parts number, costs and lead-time. This dataset consists of the repair history of a specific engine type, from several years and several fleets, and contains information like repair claim, engine working time, forensic evidences and general information about processed spare parts. Using these data as input, several Machine Learning models have been built in order to predict the repair state of each spare part for a better warehouse handling. A multi-label classification approach has been used in order to build and train, for each spare part, a Machine Learning model that predicts the part repair state as a multiclass classifier does. Mainly, each classifier is requested to predict the repair state (classified as “Efficient”, “Repaired” or “Replaced”) of the corresponding part, starting from two variables: the repairing claim and the engine working time. Then, global results have been evaluated using the Confusion Matrix, from which Accuracy, Precision, Recall and F1-Score metrics are retrieved, in order to analyse the cost of incorrect prediction. These metrics are calculated for each spare part related model on test sets and, then, a final single performance value is obtained by averaging results. In this way, three Machine Learning models (Naïve Bayes, Logistic Regression and Random Forest classifiers) are applied and results are compared. Naïve Bayes and Logistic Regression, that are fully probabilistic methods, have best global performances with an accuracy value of almost 80%, making the models being correct most of the times.

Evaluation of the effectiveness of methods and criteria for product classification in the warehouse

The paper presents an algorithm for calculating the approximate picking time. In order to perform a simulation, the PickupSimulo software was developed. For this purpose, the PHP language and MySQL relational databases were used. The PickupSimulo makes it possible to define the warehouse topology, solve the product allocation problem (PAP) based on pre-defined criteria and calculate an approximate time of the picking process for that product layout. The warehouse under analysis enables the stocking of over 22,000 pallets. Two variants were analysed. In the first one, the product weight does not matter, whilst in the other the picker must make sure the lightest products are placed at the top of the logistic unit. Such an approach reduces the risk of damaging light products by heavy ones. The research results show that the presented method enables a reduction of the total warehouse costs by 10–16%. [Received: 18 August 2017; Revised: 20 May 2018; Revised: 18 December 2018; Accepted: 20 May 2019].

Evaluation of the effectiveness of methods and criteria for product classification in the warehouse

The paper presents an algorithm for calculating the approximate picking time. In order to perform a simulation, the PickupSimulo software was developed. For this purpose, the PHP language and MySQL relational databases were used. The PickupSimulo makes it possible to define the warehouse topology, solve the product allocation problem (PAP) based on pre-defined criteria and calculate an approximate time of the picking process for that product layout. The warehouse under analysis enables the stocking of over 22,000 pallets. Two variants were analysed. In the first one, the product weight does not matter, whilst in the other the picker must make sure the lightest products are placed at the top of the logistic unit. Such an approach reduces the risk of damaging light products by heavy ones. The research results show that the presented method enables a reduction of the total warehouse costs by 10–16%. [Received: 18 August 2017; Revised: 20 May 2018; Revised: 18 December 2018; Accepted: 20 May 2019].

Model Economic Production Quantity dengan Rework Process dan Batasan Gudang

Rework products and warehouse capacity are common problems experienced by companies in the production process. Several Economic Production Quantity (EPQ) models were developed to minimize the costs of purchasing raw materials. This study aims to develop an Economic Production Quantity (EPQ) model with rework processes and warehouse constraints, assuming that the product is not perfect and can rework. The proposed model considers several cost components, including setup, holding, production, rework, and warehouse. The two proposed models are EPQ models with reworks and warehouse costs, and EPQ models with reworks and warehouse constraints. Based on several tests conducted, it obtains that the increase in the value of the maximum inventory amount did not have an impact on the production costs and the cost of the rework process. Based on several numerical experiments, the total cost of the rework process and production costs do not change to the maximum inventory value.

Modelling inventory management: Separate issues for construction and application

<div><p class="TtuloAbstract">The model of inventory management on the basis of which the calculations of the efficiency of the use of inventories, minimizing the total costs associated with their delivery, storage and fines for lack of stocks in the presence of demand for them have been made and presented in the article. Using it in practice will allow managing the logistics and warehouse costs, the risk of not receiving or reducing the company's profits due to the excess costs and the efficiency of turnover of inventories. The proposed model takes into account the depending on the price of shipment from the supplier to the warehouse, the cost of holding stocks, the cost of holding the stocks, the amount of storage costs and penalties for non-shipped products. It is proved that rationally organized order in stock management allows companies to calculate the order quantity, its optimal size and time interval between orders taking into account the prospect of delay in supply, to plan the amount of profit, to organize the accounting of the profitable level of stocks, to determine the sizes of the highest and guarantee level of the stock. Approbation of the developed model was carried out on the basis of the data of the woodworking enterprise. We used elements of the Data Mining Results technology – the MARSPline module in the application package Statistica to achieve the goals. This made it possible to construct a regression model in multidimensional space and spline surfaces through the main functions.</p></div>

ADVANCED WAREHOUSE TECHNOLOGIES – PERSPECTIVES AND POSSIBILITIES

The selection of orders means to find a number of products in the warehouse matching a number of independent orders of several customers. It is an important part of the supply and distribution chain, accounting for 65% of the total operating costs of a typical warehouse. The emphasis of this work is on the synchronization of all activities within the manufacturing system, which is a permanent challenge for both a successful manufacture and business in general. For the realization of this research task it is necessary to start with the structure of the manufacturing system and to theemphasis the hierarchy of objectives and also the strategies which should be employed for their realizations. Thevalidity of the concept suggested is estimated out by computer simulation, using the initial data from theindustry. The SAP orPerftech.Largo ERP is a simple and technically updated software for creating effective comprehensive business information systems that can at any time provide users with the desired status information in the company. The most commonly used modules are: finance, human resources management, sales and procurement, external operations, production, material operations.The simulation program starts with a temporary presumption that the materials needed for reproduction are available in the input data of the warehouse. All work orders are processed and sent to the data entry of the warehouse.The program starts the data at the time of occurrence of any work order within the system at the time required for its realization and automatically takes into account the priorities of each working order. The user has an intermediateor material warehouse that enables normal operation of the production process and optimal supply time.

Production planning in industrial townships modeled as hub location–allocation problems considering congestion in manufacturing plants

In this paper, we aim to develop optimal production plans in industrial townships modeled as hub location–allocation problems (HLAP) taking congestion into account. In the proposed model, hub nodes are considered as industrial townships where manufacturing plants and a central distribution warehouse are located, and two objectives are targeted. The first is to minimize the total costs, which includes the cost of hub deployment, factories and warehouses, transportation, and so forth. The second is to minimize the total elapsed time of products in manufacturing plants and warehouses modeled as queues. Due to the ambiguity in estimating the model’s parameters, they are considered as fuzzy parameters to make model closer to reality. The fuzzy model is then converted into an equivalent crisp model by combining the expected value (EV) and the fuzzy chance constrained programming (FCCP) approaches. Subsequently, the bi-objective crisp model is converted into a single aggregated objective model. In order to validate the proposed model, six numerical examples are solved, and the sensitivity of the proposed model with regard to changes in model’s parameters is investigated.