Warehouse Stock Research Articles

Spare Parts inventory reduction: a multi-attribute approach

Abstract The paper aims to define a multi-attribute model allowing to re-design spare parts (SPs) inventory. The model helps in evaluating the inventory configuration compliant with both production and storage costs requirements. The model is based on SPs attributes to be considered critical for a production system. For each SP a reduction index is computed as a function of the attributes values expressed by the judgments of different decision-makers. A transform function is defined to convert reduction indexes into SPs stock reduction quantities. The transform function is consistent with a set of reduction policies to be adopted on the base of internal (i.e. system utilization) and external (i.e. supply quality) variables affecting system behaviour. The model has been tested and validated on a catalogue of a SPs supplier of an automotive components company. Due to the crisis of the automotive sector of the last two years, the management of the plant shifted the focus from high technical availability level of production system to the reduction of production costs and SPs stock in the local warehouse. Data collection and data mining required for SPs inventory reduction by traditional management policy revealed as time and resource consuming task. Results obtained by the proposed approach revealed the effectiveness of the model in reducing SPs inventory, as well as a reduced effort in carrying out the analysis.

Lower Bounds and Heuristics for Supply Chain Stock Allocation

Assume that m periods with stochastic demand remain until the next replenishment arrives at a central warehouse. How should the available inventory be allocated among N retailers? This paper presents a new policy and a new lower bound for the expected cost of this problem. The lower bound becomes tight as N → ∞ . The infinite horizon problem then decomposes into N independent m-period problems with optimal retailer ship-up-to levels that decrease over the m periods, and the warehouse is optimally replenished by an order-up-to level that renders zero (local) warehouse safety stock at the end of each replenishment cycle. Based on the lower bound solution, we suggest a heuristic for finite N. In a numerical study it outperforms the heuristic by Jackson [Jackson, P. L. 1988. Stock allocation in a two-echelon distribution system or what to do until your ship comes in. Management Sci. 34(7) 880–895], and the new lower bound improves on Clark and Scarf's [Clark, A. J., H. Scarf. 1960. Optimal policies for a multi-echelon inventory problem. Management Sci. 6(4) 475–490] bound when N is not too small. Moreover, the warehouse zero-safety-stock heuristic is comparable to Clark and Scarf's warehouse policy for lead times that are not too long. The suggested approach is quite general and may be applied to other logistical problems. In the present application it retains some of the risk-pooling benefits of holding central warehouse stock.

Warehouse management technologies

PurposeAims to discover the different technologies used in warehouse stock control.Design/methodology/approachThe paper begins with a review of optical and radio‐frequency product‐labelling technologies, and then examines various devices and systems for reading these labels and integrating stock control into back‐office databases. It then looks at techniques for finding the goods within the warehouse, from simple address labels to radar positioning and inertial navigation, considering both operator‐based and guided vehicle handling systems.FindingsLabelling technologies facilitate automatic product identification. Rugged handheld computers with wireless communications give real‐time capability and integrate stock control into wider software systems for efficient resource management. Speech synthesis provides one man‐machine interface enabling workers to order‐pick under database control. Automated readers record products entering and leaving the warehouse, theoretically removing the need for stock taking. Automatic guided vehicles are now available to stack and retrieve goods in the warehouse.Originality/valueProvides engineers with an overview of the diversity of solutions employed in warehouse stock handling.

Cultural Biography of Haute Couture: The Story of Aleksandar Joksimović's "Vitraž" Collection

The term »grandiose pseudo-clasicism«, introduced to the study of fashion in socialism by Djurdja Bartlett, does not hold ground in the case of Yugoslav/Serbian offical fashion industry. Instead, I claim that a more appropriate term would be »grandiose exotism«, since Yugoslav/Serbian fashion did not build its identity on the pseudo-classical esthetical models, but on the incorporation of exotic motives and patterns form the national thesaurus. »Grandiose exotism« was a part of the wider project of »national-style« fashion that dominated the history of Yugoslav/Serbian fashion during the 1960s. This form of fashion production was a convenient means for the presentation of Yugoslav idiosyncrasies. Since it corresponded with the characteristics of the social and political milieu of the Yugoslav state, »national-style« fashion symbolically represented the aspects of the identity of Yugoslavia as a socialist and non-aligned country. Therefore, the socialist regime gave a highly representative and commercialized role to grandiose exotism, as an exclusive style in national fashion. However, in the domain of everyday practices, exclusive fashion production was denied high cultural value, since its products were subjected to processes of commoditization and exchanged for very low sums of money. Parallel to the processes of commoditization, there was the process of informal singularization carried out by groups who had access to warehouse stocks of haute couture. Unfortunately, the lack of data on the further cultural biography of these objects disables us to fully study the destiny of exclusive pieces of Yugoslav fashion production in socialism.
 

Stock Rationing in a Continuous Review Two-Echelon Inventory Model

In this paper we consider a 1-warehouse, N-retailer inventory system where demand occurs at all locations. We introduce an inventory model which allows us to set different service levels for retailers and direct customer demand at the warehouse. For each retailer a critical level is defined, such that a retailer replenishment order is delivered from warehouse stock if and only if the stock level exceeds this critical level. It is assumed that retailer replenishment orders, which are not satisfied from warehouse stock, are delivered directly from the outside supplier, instead of being backlogged. We present an analytical upper bound on the total cost of the system, and develop a heuristic method to optimize the policy parameters. Numerical experiments indicate that our technique provides a very close approximation of the exact cost. Also, we show that differentiating among the retailers and direct customer demand can yield significant cost reductions.

Balancing Retailer Inventories

This paper examines the optimality of inventory “balancing” in a one-warehouse N-retailer distribution system facing stochastic demand for a single product over T successive time intervals. In particular, we consider the division of predetermined quantities of warehouse stock among retailers in each interval. Balancing attempts to bring the retailer-inventories to the same (normalized with respect to first-interval demand) net inventory level. When the demand distribution over the T periods is symmetric with respect to all pairs of retailers, and retailer cost over the T-intervals is a convex function of the T shipments, we show that balancing divisions are optimal. The required convexity condition is shown to be satisfied for some familiar cost functions when shortages are backordered and lost. However for other cost functions, the convexity condition is satisfied under backordering, but not under lost sales. We also consider the nonidentical-retailer (demands are not symmetric) case and provide examples to show that balancing is generally not optimal, even for relatively common, simple cost functions.

Two-Interval Inventory-Allocation Policies in a One-Warehouse N-Identical-Retailer Distribution System

For a system of N-identical-retailers we construct a model for determining warehouse inventory-allocation policies which minimize system lost sales per retailer between system replenishments. An allocation policy is specified by: (a) the number of withdrawals from warehouse stock; (b) the intervals between successive withdrawals; (c) the quantity of stock to be withdrawn from the warehouse in each interval; and (d) the division of withdrawn stock among the retailers. We show that in the case of two withdrawals, available stock in each interval should be divided to “balance” retailer inventories. We also develop an infinite-retailer model and use it to determine two-interval allocation heuristics for N-retailer systems. Simulation tests suggest that the infinite-retailer heuristic policies are near-optimal for as few as two retailers. Simulation tests indicate that the risk-pooling benefits of allocation policies with two well-chosen intervals are comparable to those of base-stock policies with four equal intervals.

Allocating Warehouse Stock in a Retail Chain

The context is that of a retail chain where stock is purchased into a central warehouse from which branch stocks are replenished. This paper considers possible methods of allocating limited warehouse stock to branches, and uses simulation to quantify the resulting benefits.

Allocating Warehouse Stock in a Retail Chain

The context is that of a retail chain where stock is purchased into a central warehouse from which branch stocks are replenished. This paper considers possible methods of allocating limited warehouse stock to branches, and uses simulation to quantify the resulting benefits.

Allocating Warehouse Stock in a Retail Chain

Allocating Warehouse Stock in a Retail Chain

Stochastic inventory model for two-echelon distribution systems

This paper presents a heuristic treatment of a stochastic inventory model for a two-echelon distribution system, in which one central warehouse stocks goods for distribution to retailers. An iterative algorithm is developed to find an optimal or near optimal inventory policy minimizing the total variable system cost per year. Numerical experience with 15 randomly generated problems shows that the algorithm converges rapidly. A numerical example is given to illustrate the savings in annual cost by the two-echelon inventory model compared to the situation where the suboptimal inventory policies are determined sequentially, from the retailer level to the central warehouse.

Distributing imported goods to British customers

Interest in international physical distribution in Britain has traditionally focused on the problems exporters experience in transporting their goods to overseas customers. Very little consideration has been given to the way in which foreign manufacturers distribute their products in the home market. In a country such as Britain, where import penetration has reached a high level, foreign produced goods accounts for a large proportion of total freight movement and warehouse stock. Foreign manufacturers have invested heavily in distribution facilities in the UK and many are major clients of specialist distribution companies. The quality and efficiency of foreign manufacturers' distribution operations in the UK also affect their ability to compete with indigenous producers and to meet wholesalers' and retailers' delivery requirements. This article examines the nature and extent of foreign manufacturers' involvement in physical distribution in the UK.

A supermarket group's use of a computer bureau

Buying your own computer is not necessarily the only answer. One of the alternatives is to use the services of a computing bureau, and this is what has been done by Hillards, the successful north country‐based supermarket group. They have built up a partnership with Baric Computing Services which provides them, on the management reporting side of the system, with the handling of branch accounting and gives details of margins and information on suppliers. It also looks after warehouse stock control, payroll information and costings.

Application of the Cube-Per-Order Index Rule for Stock Location in a Distribution Warehouse

Consider a distribution warehouse divided into reserve storage and staging areas. The warehouse stores a variety of items and receives orders for any combination of items. Goods are moved from reserve storage to staging area, where they are selected to fill the given orders. The problem is to locate items in the staging area in order to minimize the expected labor costs of order selection. Several years ago, J. L. Heskett [Heskett, J. L. 1963. Cube-per-order index—A key to warehouse stock location. Transportation and Distribution Management 3 (April) 27–31.] proposed a criterion, called the cube-per-order index (CPO) rule, for solving this problem. The criterion was justified heuristically by means of numerical examples. Recently [Kallina, C. 1976. Optimality of the cube-per-order index rule for stock location in a distribution warehouse. Working paper, American Can Company, March.], one of the authors has shown that the class of problems considered by Heskett can be formulated as a linear program, and that the CPO rule is in fact the optimal solution. In this present paper, we will (1) summarize some basic background material, (2) describe the computational steps for implementation of the CPO rule, and (3) discuss some practical conclusions gathered from experience in actually applying the rule to assist in warehouse layout.

On Base-Stock Level Inventory Control

Mathematical models are used to discuss the following inventory situation customer demands on the warehouse stock of an item fluctuate independently and randomly during successive discrete time periods (e.g., weeks), demands that cannot be satisfied from stock on hand are “lost,” e.g., are satisfied elsewhere. There is a one-period lag in warehouse replenishments, and a base-stock-level policy determines the sizes of warehouse replenishment orders. Under these conditions available stock at the beginning of a period is a Markov chain, of Morse [Morse, P. M. 1959. Solutions of a class of discrete-time inventory problems. Opns Res. 7 67–78 (in particular pp. 76–78).]. This chain is discussed, and its probabilities are used to evaluate stock-out and inventory carrying costs associated with the end of a period. The above costs are also evaluated for the easily analyzed case in which disappointed demands backorder. A numerical example indicates that optimum base-stock-levels determined on the backordering assumption may be nearly identical with those determined assuming impatience.

FOR YOUR PROCESS NEEDS... Oxalic Acid From Coast-to-Coast Warehouse Stocks!

FOR YOUR PROCESS NEEDS... Oxalic Acid From Coast-to-Coast Warehouse Stocks!

Fat and oil data for second quarter 1931

Oil and Fat IndustriesVolume 8, Issue 9 p. 350-352 Article Fat and oil data for second quarter 1931 Production, consumption, exports and imports with factory and Warehouse Stocks, June 30, 1931 First published: 01 September 1931 https://doi.org/10.1007/BF02574446AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume8, Issue9September 1931Pages 350-352 RelatedInformation

Fat and oil data for fourth quarter 1930

Oil and Fat IndustriesVolume 8, Issue 3 p. 115-117 Article Fat and oil data for fourth quarter 1930 Production, consumption, exports and imports with factory and warehouse stocks December 31, 1930 First published: 01 March 1931 https://doi.org/10.1007/BF02574908AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume8, Issue3March 1931Pages 115-117 RelatedInformation

Fat and oil data for third quarter 1930

Oil and Fat IndustriesVolume 7, Issue 12 p. 467-471 Feature Article Fat and oil data for third quarter 1930 Production, consumption, exports and imports with factory and warehouse stocks September 30, 1930 First published: 01 December 1930 https://doi.org/10.1007/BF02588033AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume7, Issue12December 1930Pages 467-471 RelatedInformation

Fat and oil data for second quarter 1930

Oil and Fat IndustriesVolume 7, Issue 9 p. 355-357 Census Report for Second Quarter Fat and oil data for second quarter 1930 Production, consumption, exports and imports with factory and warehouse stocks June 30, 1930 First published: 01 September 1930 https://doi.org/10.1007/BF02564112AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume7, Issue9September 1930Pages 355-357 RelatedInformation