[PDF] Managing Intermittent Demand eBook

Author : John E. Boylan
Publisher : John Wiley & Sons
Page : 403 pages
File Size : 22,47 MB
Release : 2021-06-02
Category : Medical
ISBN : 1119135303

GET BOOK

INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute.

Author : John E. Boylan
Publisher : John Wiley & Sons
Page : 403 pages
File Size : 15,34 MB
Release : 2021-06-08
Category : Medical
ISBN : 1119976081

GET BOOK

INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute.

Author : Torben Engelmeyer
Publisher : Springer
Page : 167 pages
File Size : 41,45 MB
Release : 2016-05-02
Category : Business & Economics
ISBN : 3658140623

GET BOOK

This work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extensive simulation study the new model is compared with a wide range of conventional forecast/inventory model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters.

Author : Nezih Altay
Publisher : Springer Science & Business Media
Page : 315 pages
File Size : 48,2 MB
Release : 2011-03-24
Category : Technology & Engineering
ISBN : 0857290398

GET BOOK

With the pressure of time-based competition increasing, and customers demanding faster service, availability of service parts becomes a critical component of manufacturing and servicing operations. Service Parts Management first focuses on intermittent demand forecasting and then on the management of service parts inventories. It guides researchers and practitioners in finding better management solutions to their problems and is both an excellent reference for key concepts and a leading resource for further research. Demand forecasting techniques are presented for parametric and nonparametric approaches, and multi echelon cases and inventory pooling are also considered. Inventory control is examined in the continuous and periodic review cases, while the following are all examined in the context of forecasting: • error measures, • distributional assumptions, and • decision trees. Service Parts Management provides the reader with an overview and a detailed treatment of the current state of the research available on the forecasting and inventory management of items with intermittent demand. It is a comprehensive review of service parts management and provides a starting point for researchers, postgraduate students, and anyone interested in forecasting or managing inventory.

Author : Ngan Ngoc Chau
Publisher :
Page : 64 pages
File Size : 10,67 MB
Release : 2020
Category :
ISBN :

GET BOOK

Managing intermittent demand is a challenging operation in many industries since this type of demand is difficult to forecast. This challenge makes it hard to estimate inventory levels and thus affects service levels. The purpose of this study is to examine the impact of multiple levels of data aggregation on forecasting intermittent demand, and subsequently, on inventory control performance. In particular, we propose a procedure that integrates lead-time and customer heterogeneity into the forecasting using temporal and cross-sectional aggregation. Using data from a real-world setting and simulation, our analysis revealed that when high service levels were important for the company operations, the forecasting approach using temporal aggregation that incorporates lead-time information yielded a higher level of inventory efficiency in terms of both the holding cost and the realized service level. It appeared that when forecasts using temporal aggregation were augmented with information about customer behavior, their purchase patterns might be a helpful consideration for enhancing inventory performance. These findings allow us to provide useful recommendations for improving the current forecasting procedure and inventory control to the sponsor company of this project.

Author : Alp Akçay
Publisher :
Page : 30 pages
File Size : 18,46 MB
Release : 2016
Category :
ISBN :

GET BOOK

We consider a single-product discrete-time inventory model with intermittent demand. In every period, either zero demand or a positive demand is observed with an unknown probability. The distribution of the positive demand is assumed to be from the location-scale family with unknown mean and variance. The functional form of the optimal inventory target is available but it is a function of the unknown intermittent demand parameters that must be estimated from a limited amount of historical demand data. We first quantify the expected cost associated with implementing the optimal inventory policy using the point estimates of the unknown parameters by ignoring the uncertainty around them. We then minimize this expected cost with respect to a threshold variable that factors the statistical estimation errors of the unknown parameters into the inventory decision. We find that the use of an optimized threshold leads to a significant reduction in the a priori expected cost of the decision maker.

Author : Colin Lewis
Publisher : Routledge
Page : 172 pages
File Size : 35,88 MB
Release : 2012-05-23
Category : Business & Economics
ISBN : 113634683X

GET BOOK

This practical book covers the forecasting- and inventory control methods used in commercial, retail and manufacturing companies. Colin Lewis explains the theory and practice of current demand forecasting methods, the links between forecasts produced as a result of analysing demand data and the various methods by which this information, together with cost information on stocked items, is used to establish the controlling parameters of the most commonly used inventory control systems. The demand forecasting section of the book concentrates on the family of short-term forecasting models based on the exponentially weighted average and its many variants and also a group of medium-term forecasting models based on a time series, curve fitting approach. The inventory control sections investigate the re-order level policy and re-order cycle policy and indicate how these two processes can be operated at minimum cost while offering a high level of customer service.