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Logisticians in the worldwide industry are frequently faced with the problem of measuring the total cost of holding inventories with simple and easy-to-use methodologies. The purpose of this paper is to look at the problem, and in particular illustrate the inventory holding cost rate computation, when different kind of warehousing systems are applied.

A multiple case study analysis is here developed and supported by a methodological framework directly derived from the working group discussions and brainstorming activities. Two different field of application are considered: one related to five companies with manual warehousing systems operating with traditional fork lift trucks; the other is among five companies operating with automated storage/retrieval systems (AS/RS) to store inventories.

The multi-case study helps to understand how the holding cost parameter is currently computed by industrial managers and how much the difference between manual and automated/automatic warehousing systems impacts on the inventory cost structure definition. The insights from the ten case studies provide evidence that the kind of storage system adopted inside the factory can impact on the holding cost rate computation and permit to derive important considerations.

The final aim of this work is to help industrial engineers and logisticians in correctly understanding the inventory costs involved in their systems and their cost structure. In addition, the multi-case analysis leads to considerations, to be applied in different industrial contexts. As other industrial applications are identified, they may be analyzed by using the presented methodology, and with aid from the data from this paper.

The relevance of this work is to help industrial engineers and logisticians in understanding correctly the inventory costs involved in their logistics systems and their cost structure. In addition, the multi-case analysis lead to interesting final considerations, easily to be applied in different industrial contexts. As other industrial applications are identified, they may be analyzed by using the methodology and extrapolating the data from this paper.

In June 1998, the Bruce T. Halle Library opened on Eastern Michigan University’s campus and began using an automated storage and retrieval system for low‐use books and periodicals. Approximately one third of the library’s total collection was placed into this storage system, freeing floor space for many new activities in the library. This system, linked to the library’s online catalog, could retrieve items requested by a patron in less than ten minutes. While the Automated storage/retrieval systems (AS/RS) performed well, other start‐up problems of a new building and public perceptions of the AS/RS made its introduction a challenge. Planning, implementation, and public reaction and acceptance are discussed.

This study is concerned with evaluating the performance of different storage policies and tour construction procedures for multi‐command picking using automated storage‐retrieval systems (AS/RS). The AS/RS machine travel time for each storage policy is derived as a function of the shape of the storage area, the number of picking points and the sequencing algorithm used. The combination of these variables yields various solutions to the problem, thus providing a useful guide in designing effective picking systems. The average travel time of the AS/RS in each configuration is calculated by computer simulation in a full factorial experimental design. A subset of the results derived from this study has been successfully implemented in a case study, involving the BMW AG Italy spare parts distribution warehouse.

Automated material‐handling techniques have been successfully applied in industry for over a decade. The techniques and systems developed to automate warehouse operations directly apply to libraries. The problem of storing a growing mass of little used but “valuable” materials can be resolved by new material handling strategies, which will also generate improved library services. The characteristics of a miniload automated storage and retrieval system are described, and formulas are presented for calculating the size of system needed by a library. Also included are “rule‐of‐thumb” prices for calculating the approximate costs of a system of a specific size.

To develop a decision support system (DSS) and improved management criteria for operating dispenser‐based single‐piece automatic order picking systems (AOPS) in distribution centers, able to reduce the need for manual decision making based on personal experience or subjective judgement.

Simulation was utilized to analyze the relationships between stochastic demand, setup parameters and performances of an AOPS. A set of rules was then defined to cost‐effectively select the values of setup parameters. A DSS was built incorporating the heuristic rules to dynamically update the equipment setup.

Manual management of an AOPS can be poorly efficient even if largely practiced. Significant economic benefits may result from rule‐based equipment setup instead of the traditional manual decision approach. This was verified resorting to a case study referring to the distribution center of a leading pharmaceuticals distributor in Italy. Major performances improvements resulted regarding manual operation by an experienced logistic manager, including a 40 per cent reduction of the cost per picked order line.

The proposed DSS is able to monitor the system behaviour over a specified time window and automatically set the values of the state variables for the next period. It is able to automatically define the set of items to be allocated on to the machine, to select the number of storage locations allocated to each item and set reorder levels and maximum picking quantities for each item, thus greatly simplifying the task of the logistic manager. Utilization of this DSS enables one to maintain a high level of picking automation efficiency while drastically cutting the required support personnel, thus significantly improving profit margins of high‐volume high‐rotation distribution centers.

The paper addresses, with original methodology, a practically relevant issue which is neglected in the literature. The paper is aimed at distribution centers managers seeking to improve the performances of AOPS and reduce their operating costs.

This paper presents an overview on the Auto‐ID (Automatic Identification) technologies testbed that has been established at the University of Missouri‐Rolla (UMR) with the objective of supporting research, development, and implementation of Auto‐ID technologies in network‐centric manufacturing environments.

UMR's Auto‐ID testbed uses a unique hardware‐in‐the‐loop simulation methodology, which integrates decision‐making model development with the design of networking topology and data routing/scheduling schemes, in order to develop, test, and implement viable Auto‐ID solutions. The methodology is founded on a 3‐level integrated model: controller simulation, distributed controller simulation, and distributed controller simulation with hardware‐in‐the‐loop.

This paper discusses two case studies that highlight the effective use of RFID technology, its potential advantages, challenges, and deficiencies stemming from particular applications. These applications include dock doors, automated guided vehicles, conveyor and automated storage/retrieval systems, integration of RFID middleware with programmable logic controllers, and inventory management of time‐sensitive materials.

The paper presents an innovative idea: hardware‐in‐the‐loop simulation methodology to design automation systems. The approach has been implemented on a variety of applications, which are presented in the paper as case studies.

Of all first generation automated storage and retrieval (AS/R) systems installed in libraries in the United States, the most complex and ambitious installation was at the Health Sciences Library at Ohio State University. The system was designed to have twelve aisles, but only eight were installed, along with four calling stations/circulation desks located at both ends of the machine on each of two floors of the library. The system, which originally cost $811,799, required constant maintenance resulting in expenditures of $889,191 through June 1990, plus $139,575 for conversion/renovation of the system in recent years. In 1989, the university made the decision to remove the Randtriever in conjunction with anticipated expansion and renovation of the library. A sidebar by Eric Jayjohn compares the Rand‐triever with contemporary AS/R technology.

The process of bringing Lied Library’s automated storage and retrieval system (ASRS) online consisted of setting up the system and storing materials. Setting up the system required defining specifications, designing a user‐interface between the integrated online library system and the ASRS, training in operation, and preparing for maintenance. Storing materials required selecting and processing the items to be stored, loading them into bins, and retrieving them with the system. Library staff spent countless hours in planning, customizing, preparing data, supplementing existing data, testing, and learning the system. The time was well spent as the load process went smoothly with relatively few problems.

Two researchers suggest a new approach to the most fundamental warehousing operation of all.

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.