Warehouse Inventory Research Articles

SERVICE LEVEL IN MODEL OF INVENTORY LOCATION WITH STOCHASTIC DEMAND

In this paper we consider the influence of the safety factor on the decision of the inventory location. This decision is done based on the model which centralizes or decentralizes the safety stock. In this model we have to choose between the location of the inventory in the regional warehouses or the location in the central warehouse. The decision is made due to the minimizing the holding costs and the supply costs of the safety stock from the central warehouse to the customer. The main assumption is that the customers have the stochastic demands on the inventory items. Moreover, the customers’ demands have the known distribution with the known parameters. The complex analysis of the influences of possible probabilistic demands' distributions on the safety factors is conducted. The numerical computations for the safety factors used in the facility location model are also presented. In numerical examples we take into considerations the demands’ distributions the most often used in practice like the normal, the Poisson, the Gamma and the exponential distribution. Some graphs for the safety factors of these distributions are also drawn. Moreover for the mentioned demands’ distributions the model of the safety stock location depends on the specific factors. Among other things these factors are the mean and the variance of the demand, the number of the regional warehouses, the assumed service level, and some cost factors like the holding costs and the transportation costs. Some graphs which illustrated the dependence of the model elements on some listed before parameters are presented and their influence on the location decision is studied also.

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The Warehouse Management System is an Information Technology (TI) which helps companies in their warehouse operations and inventory, giving a more appropriate use to the space of distribution centers (DCs). Even though the operational and financial results of the implementation of IT, such as the WMS, are positive and clear, results related to safety and other technical issues need to be assessed more accurately, considering that IT demands high investments. Thus, to evaluate the WMS, this paper presents a literature review on technologies, IT, IS, and WMS, and then applies the method of Ribeiro and Carvalho to companies that offer logistics services such as Logistics Operators. A case study method will be used for that, following a qualitative approach based on semi-structured interviews with Logistics Operators. Among the results, it was found that these companies still give greater emphasis to the economic analysis of IT and must therefore improve the assessment of new software by involving variables that account for organizational, safety and other technical issues, in addition to the financial variables currently in use.

REPLACEMENT SPARE PART INVENTORY MONITORING USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

Abstract The amount of inventory is determined on the basis of the demand. So that users can know the demand forecasts need to be done on the request. This study uses the data to implement a replacement parts on the electronic module production equipment in the telecommunications transmission systems, switching, access and power, ie by replacing the electronic module in the system is trouble or damaged parts of a good electronic module spare parts inventory, while the faulty electronic modules shipped to the Repair Center for repaired again, so that the results of these improvements can replenish spare part inventory. Parameters speed on improvement process of electronic module broken (repaired), in the form of an average repair time at the repair centers, in order to get back into the electronic module that is ready for used as spare parts in compliance with the safe supply inventory warehouse. This research using the method of Adaptive Neuro Fuzzy Inference System (ANFIS) in developing a decision support system for inventory control of spare parts available in Warehouse Inventory taking into account several parameters supporters, namely demand, improvement and fulfillment of spare parts and repair time. This study uses a recycling input parameter repair faulty electronic module of the customer to immediately replace the module in inventory warehouse, do improvements in the Repair Center. So the acceleration restoration factor is very influential as the input spare parts inventory supply in the warehouse and using the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. Keywords: ANFIS, inventory control, replacement

Equation Chapter 1 Section 1A Two Warehouse Inventory Model for Deteriorating Items with an Exponential Demand and Shortage

In this paper, the two warehouse inventory problem for deteriorating items with exponentially increasing time demand rate and shortages is considered. Here existing storage is known as own warehouse OW and the other is hired on rental basis known as rented warehouse RW. The model allows different levels of item deterioration in both warehouses. Here replenishment rate is finite. The stock is transferred from RW to OW in continuous release pattern and the associated transportation cost is taken into account. Shortage in OW is allowed and excess demand is backlogged. An attempt is made to incorporate the different preservation facilities in own and rented warehouses for deteriorating items with exponentially time dependent demand. It is also assume that the preservation facility in RW is better than OW. For the general model, we give the equations for the optimal policy and cost function and we discuss some special case. A numerical example is given to illustrate the solution procedure of the model.

Optimization of ‘Milk Run’ of JCB India Ltd. (Ballabhgarh Plant)

JCB India Ltd. is a construction equipment manufacturer. Every production day, required materials in manufacturing of equipments produced at their Ballabhgarh Plant are brought in by Milk Runs, or from warehouse inventory. This paper is an attempt to minimize cost of Milk Runs for JCB India Ltd. The system is mathematically modeled to minimize total time for milk runs, followed by formulation and solution of a 'Bin- packing problem' to fit requisite number of trips into minimum possible number of trucks. 

Managing inventory through (Q, r) policy for a VMI programme with freshness clause

This paper considers the inventory management in a VMI programme consisting of a vendor, a retailer and a VMI warehouse near the retailer. Specifically, the vendor is authorised to manage the inventory of the VMI warehouse through (Q, r) policy, and the retailer controls the service level of the warehouse by setting a minimum inventory level z. Besides, to reduce the vendor’s high inventory cost, a freshness clause is introduced. Our main finding is that under a given freshness clause, there exist the optimal (Q*, r*) for the vendor, and z* for the retailer. Based on this, we derive the conditions satisfied with (Q*, r*) and propose an iterative algorithm for solving z*. Furthermore, the freshness clause’s impact on each participant’s optimal decisions and the managerial implications are illustrated via numerical analysis.

Analisis Penerimaan dan Pengeluaran Barang Umum Non Curah Pada Gudang Perbekalan PT. Semen Padang

Inventory has its advantages and disadvantages. The advantage of this inventory is to beable to anticipate the urgent needs of the company, meet the demand from users. But thisstock has a loss, which can increase the costs to be incurred by the company so as to reducethe advantage held by the company. The more the amount of inventory in warehouse, themore the cost of inventory that must be removed and inventory turnover (ITO) whichproduced the lower. One way to do inventory control is to determine the optimal orderquantity. The method used to determine the optimal number of reservations is to use theEOQ method by considering the amount of safety stock and reorder point when done. Basedon the calculations have been performed for the optimal order quantity are 2,019 bottles ofoxygen, welding wirerod is 14,795 stems, and 185 stem of pipe metal. By doing of EOQ toinventory control obtained by the method of ITO increases the weld wire and pipe metalfrom 0.0392 to 1.1010 at the welding wire and from 0.2949 to 0.8627 on a pipe metal.However, the oxygen has decreased from 1.9238 to 1.6094 so that it can be concluded thatthe EOQ method can not be applied to the oxygen, but can be applied to the weldingwire and pipe metal.

Should feed mills go beyond traditional least cost formulation?

Due to the pressure to become more competitive, feed mills coordinate closely with their suppliers and customers by forward purchasing raw materials and integrating with downstream units such as animal producers. To integrate downstream units and forward purchase raw materials, the mill must explore new paradigms for managing integrated information. The close relationship between customers, suppliers and the feed mill allows the feed manager to access information that was not previously available, such as the price of raw materials and the demand for feed products, which creates a more deterministic environment. In the present study, to exploit information from the integration of production units, an extended planning horizon was evaluated by developing a mathematical model and a heuristic algorithm for multiple period planning. The simulated results indicated that feed mills are likely to benefit from expanding the planning horizon. On average, the costs obtained from multiple-period planning were approximately 2.55% lower than those of single-period planning. Moreover, because recipe costs fluctuate dramatically, mills benefit from multiple-period planning by accounting for variations in recipe costs. However, the savings of multiple period planning are limited by other factors such as inventory holding costs and the warehouse inventory of the feed mill.

Lot sizing for a single product recovery system with variable setup numbers

Inventory systems for joint remanufacturing and manufacturing have recently received considerable attention. In such systems, used products are collected from customers and are kept at the recoverable inventory warehouse for future remanufacturing. In this paper a production–remanufacturing inventory system is considered, where the demand can be satisfied by production and remanufacturing. The cost structure consists of the EOQ-type setup costs, holding costs and shortage costs. The model with no shortage case in serviceable inventory is first studied. The serviceable inventory shortage case is discussed next. Both models are considered for the case of variable setup numbers of equal sized batches for production and remanufacturing processes. For these two models sufficient conditions for the optimal type of policy, referring to the parameters of the models, are proposed.

A discrete dynamic programming approach towards optimal outsourcing policy in supply chain management

PurposeAs global markets become more customer oriented, rapid response rates are now often among the most important metrics in business. To achieve the required agility, many companies are forced to take decisions of whether to vertically integrate a value chain or to outsource some of its operations. The purpose of this paper is to develop a sequential decision modeling process to enable determination of optimal outsourcing policy decisions with respect to the variables such as warehouse inventory, in‐house manufacturing capacity and the ordering cost to the outsource supplier.Design/methodology/approachIn this paper, a discrete dynamic programming‐based modeling framework is developed for analyzing outsourcing policies for supply chain management problems. Specifically, the assumed situation entails a dynamic decision between in‐house production vis‐à‐vis outsourcing, which is contingent upon several factors such as demand during the period under consideration, available inventory, available production capacity of the firm, ordering cost to the outsourced supplier and the fixed capital cost of machine capacity enhancement.FindingsThe framework enables the determination of a time‐based outsourcing policy, which is a prescription regarding: the optimum quantities to be produced in‐house vs those to be outsourced, and the level of capacity to be set in each period.Originality/valueThe problem investigates useful managerial decisions that are relevant to a real life dynamic situation within a manufacturing industry when effecting outsourcing decisions.

Inventory control in a two-echelon dual-channel supply chain with setup of production and delivery

This paper considers a two-echelon dual-channel supply chain model with setup of production and delivery and develops a new inventory control policy for the supply chain. Previously, a two-echelon supply chain model without setup of production and delivery is considered and a one-for-one inventory control policy is applied to the supply chain. In the inventory control policy, production is stopped when the warehouse inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. Moreover, delivery to the retailer is stopped when the store inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. The total cost that consists of inventory holding costs and lost sales cost is considered, and setup costs are not considered in the total cost. Once setup costs are introduced, the one-for-one inventory control policy is no longer appropriate. Then, this paper develops a new control policy for the two-echelon dual-channel supply chain with setup of production and delivery. As performance measure, the total cost that consists of inventory holding costs, lost sales cost, and production and delivery setup costs is considered, and the total cost calculated on the basis of Markov analysis demonstrates the effectiveness of the proposed control policy.

Optimal Control of Production and Remanufacturing in a Reverse Logistics Model with Backlogging

Reverse logistics activities have received increasing attention within logistics and operations management during the last years, both from a theoretical and a practical point of view. The field of reverse logistics includes all logistics processes starting with the take-back of used products from customers up to the stage of making them reusable products or disposing them. In this paper, a single-product recovery system is studied. In such system, used products are collected from customers and are kept at the recoverable inventory warehouse in view to be recovered. The constant demand rate can be satisfied either by newly produced products or by recovered ones (serviceable inventory), which are regarded as perfectly as the new ones. Excess demand is completely backlogged. Following an exact analytical approach, the optimal set-up numbers and the optimal lot sizes for the production of new products and for the recovery of returned products are obtained. A numerical cost comparison of this model with the corresponding one without backordering is also performed.

Assessing the impact of inventory inaccuracies within a Newsvendor framework

This paper examines a Newsvendor framework in which a wholesaler who sells products to retailers is subject to inaccuracies in inventory data. The wholesaler’s decision regarding the management of his warehouse inventory is based on inventory data recorded in the information system. We assume that the wholesaler uses barcode labels and scanners in order to gather information concerning the available inventory in the warehouse. Because of errors arising during the manual barcode scanning process, the information on the available inventory level can deviate from the physical quantity and can result in an additional cost. This paper quantifies the economic impact of having uncertainty on the inventory level. We first analyze the case of a wholesaler that is not aware of inventory errors or chooses to ignore them in order to evaluate the efficiency loss due to errors compared with an error free situation. We then assess the effect of various actions enabling to tackle the inventory inaccuracy issue with a particular focus on actions such as the deployment of a new data capture technology.

Perancangan Sistem Informasi Inventori Gudang Berbasis Intranet

PT Duta Mas Satu Pasuruan which be active in area produce of plywood, in activity documentation of data relating with inventory product still be done in a manual so that the problem which often faced was report access inventory limited to space and time where sales department didn’t know number supply of product in warehouse because doesn’t have information access connected. Arrangement of good inventory must always can answer question how much the product available in warehouse and when the product is required. So, for know the product stock especially product become then required by Information Inventory Warehouse System (SIGA) bases on Intranet. This implementation used scripting language discharged at HTML for enables checking and supervision directly through computer tissue system. Information Inventory Warehouse System (SIGA) made with software open source using program language of PHP and management of data base MySQL, and then used server computer bases on Windows. Information data of stock product which is available in warehouse has 4 kinds of product type, there are DF (4' × 8') 15000 slabs, MDF component design 18000 slabs, Plywood 24000 slabs and Fancywood 9000 slabs.

A reexamination of Rice Warrants in late premodern Osaka : The meaning of the 1761 Ban on Rice Warrants not confirmed by warehouse inventory

A reexamination of Rice Warrants in late premodern Osaka : The meaning of the 1761 Ban on Rice Warrants not confirmed by warehouse inventory

Using radio frequency identification in agent-based control systems for industrial applications

The radio frequency identification (RFID) is a technology for automatic identification of items, particularly in supply chain, but it is becoming increasingly important for industrial applications. Unlike barcode technology that detects the optical signals reflected from barcode labels, RFID uses radio waves to transmit the information from an RFID tag affixed to the physical object. In contrast to today most often use of this technology in warehouse inventory and supply chain, the focus of this paper is on the exploitation of RFID in industrial environments, particularly for the purposes of the real-time programmable logic controller (PLC)-based manufacturing control. The paper also presents a unique architecture integrating the RFID technology with the agent-based industrial control solutions by proposing special RFID agents as mediators between physical RFID readers and other agents. Integral part of this solution is the introduction of the work piece agents directly negotiating with the manufacturing resource agents about the details of production.

Building Relationship Network for Machine Analysis from Wear Debris Measurements

Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear debris analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self-organizing maps. This is achieved using relationship measurements among corresponding attributes of various measurements for wear debris. Finally, visualization technique is proposed that helps the viewer in understanding and utilizing these relationships that enable accurate diagnostics. ICROSCOPIC applications have been one of the important areas in the field of automation for on- line/off-line visual inspection systems in industry and for long-term availability of inventory in warehouses. These systems include analysis of microscopic wear debris. Any change in the steady state operation of the machine creates a change in the normal wear mechanism. This change once transported by a lubricant from wear sites carries important information relating to the condition of engines and other machinery. Researchers have used this information to diagnose wear-producing modes and thus attempt to predict wear failures in machines (1-2). For the purpose of objective diagnosis, the identification and analysis of these wear debris have been reported in literature using various automation techniques. The interested reader is referred to the work of authors in (3-5) for further study. The aim of the overall research has been to develop an image analysis and in some cases knowledge based system to classify wear debris for the objective under study. The authors in (6) have discussed an intelligent expert system via Internet using combination of an expert system and a neural network. The respective authors have only discussed classifications where desired ones are known and corresponding mapping is

Economic ordering policy for an item with imperfect quality subject to the in-house inspection

This article considers a production/inventory system where each lot of items received or produced contains a random proportion of defective units, items of imperfect quality. The purchaser contacts a 100% inspection in order to identify the perfect (acceptable) quality items. The model examines the following two options for the imperfect quality items: sell them to a secondary market, as a single batch and at a price lower to that of new ones, or rework them at some cost and then use them as new ones to satisfy demand. After inspection, the good quality items are sent to the working inventory warehouse in batches of equal size. For both of these cases, the optimal ordering lot size and the optimal number of batches are obtained. A numerical example illustrates the solution procedure and sensitivity analysis results are reported.

The inventory management system for automobile spare parts in a central warehouse

Because of the complex structure of spare parts supply chain, the conventional approaches, which do not consider the relationships between decision factors globally, cannot achieve the optimal performance. Therefore, this paper aims to develop an enhanced fuzzy neural network (EFNN) based decision support system for managing automobile spares inventory in a central warehouse. In this system, the EFNN is utilized for forecasting the demand for spare parts. However, without considering relevant domain knowledge, traditional neural networks are found to be suffered from the problem of low accuracy of forecasting unseen examples. Therefore, in our EFNN, the following improvement is made: First, it assigns connection weights based on the fuzzy analytic hierarchy process (AHP) method without painstakingly turning them. Second, by generating and refining activation functions according to genetic algorithm, our EFNN can provide comprehensive and accurate activation functions and fit a wider range of nonlinear models. Last, but not least, an adaptive input variable is introduced to decrease the impact of the bullwhip effect on the forecasting accuracy. The proposed system is evaluated with the real word data and experimental results indicate that our EFNN outperforms other five models in fill rate and stock cost measures.

Lot-sizing for a single-product recovery system with backordering

In this article, a single-product recovery system is studied. Used products are collected from customers and kept at the recoverable inventory warehouse for future recovery. The constant demand rate can be satisfied either by newly produced products or by recovered ones (serviceable inventory), which are regarded as perfectly as the new ones. Excess demand is completely backordered. Following an exact analytical approach, the optimal production and recovery policy is obtained. A numerical cost comparison of this model with the corresponding one without backordering is also performed. The results are general, as they were valid for finite and infinite production and recovery rates.