Central Warehouse Research Articles

Inventory Control in a Spare Parts Distribution System with Emergency Stocks and Pipeline Information

Motivated by collaboration with a global spare parts service provider, we consider a two-echelon inventory system with multiple local warehouses, a so-called support warehouse, and a central warehouse with ample capacity. In case of stock-outs, the local warehouses can receive emergency shipments from the support warehouse or the central warehouse at an extra cost. Our focus is on using information on orders in the replenishment pipeline, i.e., pipeline information, to achieve cost-efficient policies for requesting emergency shipments. We introduce a policy where the request for an emergency shipment is based on the time until an outstanding order will reach the stock point considered. The goal is to determine how long one should wait for stock in the replenishment pipeline before requesting an emergency shipment, and the cost effects of using pipeline information in this manner. The analysis utilizes results from queuing theory and provides a decomposition technique for optimizing the policy parameters that reduces the complex multiechelon problem to more manageable single-echelon problems. The performance of our policy indicates that there can be a significant benefit in using pipeline information.

Fertilizer supply chain in Ethiopia: structure, performance and policy analysis

In Ethiopia, less than 40% of farmers use fertilizer and those who do, apply rates significantly below those recommended. This low fertilizer use is primarily due to prices being two to three times higher than prices on the world markets. Reducing the price of fertilizer requires a sound understanding of the product´s supply chain. This study investigates whether fertilizer is delivered to farmers in an efficient way and at the lowest possible costs using an institutional economics framework. It was conducted in the Arsi zone and relied on secondary data as well as primary data collected through interviews. The findings point out the presence of several formal and informal institutions regulating the market. A market monopoly at each stage of the supply chain and a striking correspondence between the central organization of the chain and the rise in left-over stocks were observed. This pinpoints the imperfect structure of the chain and a misallocation of resources locked up in fertilizer stockholding. In order to improve the demand estimation procedure, this study suggests that incentives should be instituted to enhance the reliability of the information transferred along the process. Additionally, expert knowledge used in the process should be well documented, stock inventories should not be limited to central warehouses and stockholding needs to be reduced.

Two parameter tuned multi-objective evolutionary algorithms for a bi-objective vendor managed inventory model with trapezoidal fuzzy demand

This paper presents a bi-objective vendor managed inventory (BOVMI) model for a supply chain problem with a single vendor and multiple retailers, in which the demand is fuzzy and the vendor manages the retailers’ inventory in a central warehouse. The vendor confronts two constraints: number of orders and available budget. In this model, the fuzzy demand is formulated using trapezoidal fuzzy number (TrFN) where the centroid defuzzification method is employed to defuzzify fuzzy output functions. Minimizing both the total inventory cost and the warehouse space are the two objectives of the model. Since the proposed model is formulated into a bi-objective integer nonlinear programming (INLP) problem, the multi-objective evolutionary algorithm (MOEA) of non-dominated sorting genetic algorithm-II (NSGA-II) is developed to find Pareto front solutions. Besides, since there is no benchmark available in the literature to validate the solutions obtained, another MOEA, namely the non-dominated ranking genetic algorithms (NRGA), is developed to solve the problem as well. To improve the performances of both algorithms, their parameters are calibrated using the Taguchi method. Finally, conclusions are made and future research works are recommended.

Fertilizer supply chain in Ethiopia: structure, performance and policy analysis

In Ethiopia, less than 40% of farmers use fertilizer and those who do, apply rates signi cantly be- low those recommended. This low fertilizer use is primarily due to prices being two to three times higher than prices on the world markets. Reducing the price of fertilizer requires a sound un- derstanding of the product ́s supply chain. This study investigates whether fertilizer is delivered to farmers in an ef cient way and at the lowest possible costs using an institutional economics framework. It was conducted in the Arsi zone and relied on secondary data as well as primary data collected through interviews. The ndings point out the presence of several formal and informal institutions regulating the market. A market monopoly at each stage of the supply chain and a striking correspondence between the central organization of the chain and the rise in left-over stocks were observed. This pinpoints the imperfect structure of the chain and a misallocation of resources locked up in fertilizer stockholding. In order to improve the demand estimation pro- cedure, this study suggests that incentives should be instituted to enhance the reliability of the information transferred along the process. Additionally, expert knowledge used in the process should be well documented, stock inventories should not be limited to central warehouses and stockholding needs to be reduced.

Costing the supply chain for delivery of ACT and RDTs in the public sector in Benin and Kenya

BackgroundStudies have shown that supply chain costs are a significant proportion of total programme costs. Nevertheless, the costs of delivering specific products are poorly understood and ballpark estimates are often used to inadequately plan for the budgetary implications of supply chain expenses. The purpose of this research was to estimate the country level costs of the public sector supply chain for artemisinin-based combination therapy (ACT) and rapid diagnostic tests (RDTs) from the central to the peripheral levels in Benin and Kenya.MethodsA micro-costing approach was used and primary data on the various cost components of the supply chain was collected at the central, intermediate, and facility levels between September and November 2013. Information sources included central warehouse databases, health facility records, transport schedules, and expenditure reports. Data from document reviews and semi-structured interviews were used to identify cost inputs and estimate actual costs. Sampling was purposive to isolate key variables of interest. Survey guides were developed and administered electronically. Data were extracted into Microsoft Excel®, and the supply chain cost per unit of ACT and RDT distributed by function and level of system was calculated.ResultsIn Benin, supply chain costs added USD 0.2011 to the initial acquisition cost of ACT and USD 0.3375 to RDTs (normalized to USD 1). In Kenya, they added USD 0.2443 to the acquisition cost of ACT and USD 0.1895 to RDTs (normalized to USD 1). Total supply chain costs accounted for more than 30% of the initial acquisition cost of the products in some cases and these costs were highly sensitive to product volumes. The major cost drivers were found to be labour, transport, and utilities with health facilities carrying the majority of the cost per unit of product.ConclusionsAccurate cost estimates are needed to ensure adequate resources are available for supply chain activities. Product volumes should be considered when costing supply chain functions rather than dollar value. Further work is needed to develop extrapolative costing models that can be applied at country level without extensive micro-costing exercises. This will allow other countries to generate more accurate estimates in the future.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-014-0530-1) contains supplementary material, which is available to authorized users.

Criticality analysis of spare parts management: a multi-criteria classification regarding a cross-plant central warehouse strategy

Today an efficient warehouse and inventory management of spare parts for production machinery is essential for service organizations. Optimal strategies in procurement, stocking and supply play an important role for serviceability in spare parts management. In this context, individual item criticality should be considered, which describes how crucial a spare part is. This paper presents a three-dimensional classification approach for spare parts regarding a cross-plant central warehouse strategy of a service network. The approach uses two dimensions to estimate value and predictability of spare parts with aid of an ABC and XYZ analysis. The third dimension VED analyses a multi-criteria criticality classification and six feasible criteria are identified to describe item criticality. The methodology of the analysis is based on a decision tree, which represents the defined criteria by nodes. In addition, the analytic hierarchy process is used to solve the multi-criteria decision problems at the different nodes of the decision tree. The approach is developed in a research project and evaluation of spare parts is performed based on real inventory and transaction data in cooperation with an industrial company. As a result 15,000 out of 50,000 items could be classified as suitable for central warehousing.

Kanban-driven parts feeding within a semi-automated O-shaped assembly line: a case study in the automotive industry

Purpose – The aim of the present work is to provide a case study where lean production (LP) techniques are implemented in a semi-automated assembly line with O-shaped (closed-loop) layout configuration. The action research has been conducted within an assembly line for automotive components. The work aims to provide insights on the impact of loop layout features with respect to lean principles’ application; operative solutions related to some logistic limit of loop layout; and how kanban technique can be adapted to an O-shaped layout. Design/methodology/approach – The main research methodology is based on action research within an assembly line of oil pumps. The two research questions find answer through literature analysis and implementation of LP in the O-shaped layout. In the A3 step, we identify the main weak points of a loop layout also under the perspective of operators’ feeling. The analysis of the main constraints is conducted in this step, with respect to the most common layout used within LP adoption. Steps A4 and A5 answer to RQ2 by an on-field results’ analysis. Findings – The use of an O-shaped layout may allow to improve ergonomic conditions for workers; to better organize parts feeding through slides and chutes because of the presence of operators outside the line. The new approach to determine the number of withdrawal kanban potentially extends the findings of Tardif et al. (2012): the minimum of the objective function is reached with a higher number of withdrawal kanbans. Research limitations/implications – The approach is applied within a stand-alone line, while in several industrial contexts, we may find several of these lines in the same shop floor. In this case, LP implementation would cope with the several kanban cards circulating, the over-saturation of the logistic operator in supplying all the lines with smaller quantities of materials. Practical implications – The action research resulted in the introduction of a new concept of supermarket, conceived as a decoupling buffer that lies near the line and in the review feeding devices, with the adoption of bins and operators’ feeding chutes. Parts’ feeding systems is reorganized with a two levels of withdrawal kanban. The introduction of line supermarket and the change of supply policies from pallets to bins contributed to the strong reduction of average work-in-progress. Yet, the double-withdrawal kanban and the small quantities supplied may cause an increase of material handling times and meters covered by operators. Social implications – Better working condition of the line operators because of the presence of ergonomic chutes for parts’ feeding. In contrast, we observed a high saturation of logistic operator because of the small quantities of components supplied on the line, with an increased stress of this worker. Originality/value – A decoupled withdrawal kanban (DWK) is developed. In DWK, the first withdrawal is issued to the supermarket that serves the line. The second withdrawal kanban is issued from the supermarket to the central warehouse. Within DWK, we propose a modified dimensioning formula through minimization of the objective function Z(k). Parts’ feeding is now organized with sliding chutes on operators’ workstations to collect components in accordance to kanban dimensioning.

Abstract W P275: Validation of Stroke Meaningful Use Measures in a National EHR System

Background: The Affordable Care Act included eight stroke indicators in its Meaningful Use (MU) program. This project evaluated stroke MU measures in national VHA data and determined sources of error in using centralized electronic health record (EHR) data. Methods: We converted local SQL queries that generated stroke indicators to run on VA Central Data Warehouse (CDW) data, mapping each local data element to the corresponding CDW data element and table. Numerator (NM) and denominator (DN) results were generated from CDW data in a sample of 2200 ischemic stroke admissions in 11 VA hospitals. Local and CDW NM and DN results were compared to chart review. NM and DN mismatch reports were iteratively examined to identify, categorize, and correct sources of error. We calculated passing rates, sensitivity and specificity for the NMs and DNs, and an overall accuracy kappa statistic. Results: Results for two measures (VTE prophylaxis and antithrombotic (AT) by day 2) are shown in the Table. The most common error in VTE prophylaxis was failure to identify mechanical prophylaxis devices (171/185 NM false negative errors), and in the AT measure was failure to identify a contraindication to therapy (50/59 DN false positive errors). Errors impacting multiple indicators included difficulty identifying Comfort Care status, discrepancies between electronic and charted medication administration, and difficulty identifying medications given in the ER. Passing rates (chart review vs. EHR) were higher with chart review for VTE (87% vs 76%) but similar for AT (91% vs 90%). Conclusions: Stroke MU indicators can be relatively accurately generated from existing EHR systems but accuracy decreases in central compared to local data sources. To improve stroke MU measure accuracy, EHRs should include standardized data elements for devices, Comfort Care status, recording contraindications, and medications given in the ER.

Network-based interactive navigation and analysis of large biological datasets

Abstract Over the last decade, advances in high-throughput technologies have resulted in a flood of new biological data. Here, individual samples can extend up into terabyte size. While potential applications are broad, ranging from biotechnology to medical applications, the analysis of these datasets poses massive challenges. In order to make use of the produced terabytes of data, these datasets need to be integrated, need to be mapped onto existing biological knowledge, and need to be explored by experts. We present UniPAX and BiNA, a scalable system for the integration and analysis of high-throughput data (genomics, transcriptomics, proteomics, and metabolomics) in a network context. A central data warehouse holds the core dataset. A flexible middleware can execute custom queries on this dataset and communicate with our visual analytics tool BiNA, the Biological Network Analyzer. We demonstrate how the combination of these tools permits an efficient analysis of large-scale datasets for medical applications.

Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies.

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.

Key factors in successful online grocery retailing: empirical evidence from Tokyo, Japan

Recently, Japan has seen a proliferation of online grocery retailers. This study identifies the key attributes determining Japanese consumers' preferences when choosing an online grocery retailer. To identify the factors attracting consumers, we conducted an online consumer survey in the area including the Tokyo Metropolitan district (Tokyo Metropolis, Yokohama, Saitama and Chiba City), with over 400 respondents. We then employed conjoint analysis to estimate the relative importance of selected service characteristics on consumer preferences in online grocery retailing. The results indicate that consumers attached highest value to shipping charges, followed by availability of delivery time window ranges and receiving methods. The final is expedited shipment. We also found that these preference rankings support central warehouse model development, rather than ship-from-store model. These findings provide implications to be considered by online grocery retailers when devising their marketing activities to build a competitive advantage over large and small- and medium-sized enterprise retailers.

SchizConnect: Virtual Data Integration in Neuroimaging.

In many scientific domains, including neuroimaging studies, there is a need to obtain increasingly larger cohorts to achieve the desired statistical power for discovery. However, the economics of imaging studies make it unlikely that any single study or consortia can achieve the desired sample sizes. What is needed is an architecture that can easily incorporate additional studies as they become available. We present such architecture based on a virtual data integration approach, where data remains at the original sources, and is retrieved and harmonized in response to user queries. This is in contrast to approaches that move the data to a central warehouse. We implemented our approach in the SchizConnect system that integrates data from three neuroimaging consortia on Schizophrenia: FBIRN's Human Imaging Database (HID), MRN's Collaborative Imaging and Neuroinformatics System (COINS), and the NUSDAST project at XNAT Central. A portal providing harmonized access to these sources is publicly deployed at schizconnect.org.

A Robust Optimization of Capacity Allocation Policies in the Third-Party Warehouse

We study the capacity allocation policies of a third-party warehouse center, which supplies several different level services on different prices with fixed capacity, on revenue management perspective. For the single period situation, we use three different robust methods, absolute robust, deviation robust, and relative robust method, to maximize the whole revenue. Then we give some numerical examples to verify the practical applicability. For the multiperiod situation, as the demand is uncertain, we propose a stochastic model for the multiperiod revenue management problem of the warehouse. A novel robust optimization technique is applied in this model to maximize the whole revenue. Then we give some numerical examples to verify the practical applicability of our method.

DiXa: a data infrastructure for chemical safety assessment.

Motivation: The field of toxicogenomics (the application of ‘-omics’ technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available.Results: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal.Availability and implementation: http://www.dixa-fp7.euContact: d.hendrickx@maastrichtuniversity.nl; info@dixa-fp7.euSupplementary information: Supplementary data are available at Bioinformatics online.

Redesign of the supply of mobile mechanics based on a novel genetic optimization algorithm using Google Maps API

If a mobile mechanic has to travel for material, productive time is lost. This paper presents a novel method to reduce activities regarding material handling with extending of serving locations. The design of the supply system can be considered as a complex combinatorial optimization problem, where the goal is to find a route plan with minimal route cost, which services all the demands from the central warehouses while satisfying the capacity and other constraints. We present a multi-chromosome technique for solving the multiple Traveling Salesman Problem (mTSP). The new operators based on a problem-specific representation proved to be more effective in terms of flexibility, complexity and transparency, and also in efficiency than the previous methods. The proposed optimization algorithm was implemented in MATLAB and integrated with Google Maps to provide a complete framework for distance calculation, definition of the initial routes, and visualization. This integrated framework was successfully applied in the solution of a real logistic problem, in the supply of mobile mechanics at one of Hungary׳s biggest energy providers.

Demand satisfaction in supply chain management system using a full online optimal control method

In the business world, there are two key factors: customer satisfaction and cost. Delivery of goods from the manufacturer to customer is defined by supply chain management system systematically and the effect of the mentioned elements is seen in this structure. In this paper, current processes in a multi-product, multi-echelon supply chain are formulated as an updated discrete time dynamic model with work-in-process products. The model includes one raw material supplier, two plant (production unit) for manufacturing two types of products, one central warehouse, two local warehouses, and four retailers, and communication channels between the nodes are defined based on sharing possibility. Regarding advantages of decentralized control faced with multi-agent systems and functionality of predictive control to comply customer demand in a reasonable lead time according to predictive structure of supply chains and demands, a full online decentralized predictive control method with lot sizing is designed and applied to the model. The simulations show a trade-off between reduced cost based on lot sizing and customer satisfaction obviously.

Optimizing a vendor managed inventory (VMI) model considering delivering cost in a three-echelon supply chain using two tuned-parameter meta-heuristics

In the retailer-supplier partnerships, the vendor-managed inventory (VMI) is one of the important policies in the supply chain management (SCM) to reduce the bullwhip effect. As there is a lack of study on the central warehouse via delivering cost in VMI literature, this paper presents a VMI model in SCM including single-vendor, multi-retailer, and single-warehouse. While the vendor confronts with two constraints, namely the number of orders and budget, the purpose of this research is to find order size, the shortest possible route, and replenishment frequencies for the vendor and the retailers to minimize the total inventory cost. As the proposed model is an NP-hard problem, a meta-heuristics namely particle swarm optimization (PSO) is employed to optimize the proposed model. Since there is no available benchmark for evaluation of the proposed method, a genetic algorithm is used to validate and verify the solution presented by PSO. Moreover, Taguchi method in the design of experiments calibrates the parameters of the algorithm to provide the reliable solution. Finally, the conclusion and further studies are presented.

Security at the source: securing today’s critical supply chain networks

This paper focuses on the re-engineering of supply chain security processes of an international organization with global operations. This research project is based on a multimethod field study designed to evaluate, over a 12 month period, the implementation of a new security concept downstream of the central warehouse. During a 12 month field study, it was found that after new processes were in place, the organization was able to achieve substantial benefits, including increased velocity, enhanced security, and lower security costs. This research introduces the new concept of security at the source, which defines security as a fundamental criterion of quality; it borrows from quality management theory to implement a new perspective on supply chain security; and it offers a new avenue for researchers to further study this concept as a cost-effective solution to secure supply chains. The results of this research outline new processes for industries requiring enhanced security in their shipments due to the vulnerability of high-profile targets, such as high risers and transport systems, to terrorist or criminal activity.

Integration of a cancer registry dataset into a hospital-wide central data warehouse.

212 Background: The ability to link cancer registry data to clinical and administrative data sets for quality improvement has long been desired. We sought to integrate registry data into a central data warehouse in an effort to make available for the first time consistent and reliable diagnosis and staging data to a broad hospital user group. Methods: After a short period of data analysis, the tables for Cancer Registry data (Oracle) were modeled. The source data (SQL Server) was conformed and integrated using an ETL tool (Informatica). All ETL QA work was performed with SQL queries. Cancer registry data was integrated into reporting architecture (Microstrategy) to facilitate design of standardized and ad hoc reports. Results: 140 distinct fields on demographics, staging (clinical, pathological, collaborative), site specific categories, diagnosis, and treatment were integrated into the Dana-Farber Analytics Reporting Tool (DART) for historic Cancer Registry data beginning with January 2010 newly diagnosed cancers. All Cancer Registry data and patient files (new and old) are updated in DART on a monthly basis. Conclusions: Individuals across the hospital now have the ability to link clinical and administrative data from our EMR, institutional QI data from varied systems, and pharmacy data to Cancer Registry data in the DART tool. One example of the integration of these multiple data sets is the linkage of staging data from the Cancer Registry data set and time to referral data from the administrative data set by patient MRN. As DFCI aims to cohort its patients based on their primary diagnosis for quality improvement and other internal reporting needs, the ability to analyze patients in this way becomes critical. This project sets an example for other centers as they integrate Cancer Registry data into user friendly business intelligence systems to help meet federal reporting mandates and aid internal improvement work. [Table: see text]

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.