Handbook Of Stochastic Models And Analysis Of Manufacturing System Operations
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Handbook of Stochastic Models and Analysis of Manufacturing System Operations
Author: J. MacGregor Smith
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-05-17
This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using analytical models to design and control manufacturing systems and their operations entail critical stochastic performance analysis as well as integrated optimization models of these systems. Topics deal with the areas of facilities planning, transportation, and material handling systems, logistics and supply chain management, and integrated productivity and quality models covering: • Stochastic modeling and analysis of manufacturing systems • Design, analysis, and optimization of manufacturing systems • Facilities planning, transportation, and material handling systems analysis • Production planning, scheduling systems, management, and control • Analytical approaches to logistics and supply chain management • Integrated productivity and quality models, and their analysis • Literature surveys of issues relevant in manufacturing systems • Case studies of manufacturing system operations and analysis Today’s manufacturing system operations are becoming increasingly complex. Advanced knowledge of best practices for treating these problems is not always well known. The purpose of the book is to create a foundation for the development of stochastic models and their analysis in manufacturing system operations. Given the handbook nature of the volume, introducing basic principles, concepts, and algorithms for treating these problems and their solutions is the main intent of this handbook. Readers unfamiliar with these research areas will be able to find a research foundation for studying these problems and systems.
Stochastic Processes
The aim of this special issue is to publish original research papers that cover recent advances in the theory and application of stochastic processes. There is especial focus on applications of stochastic processes as models of dynamic phenomena in various research areas, such as queuing theory, physics, biology, economics, medicine, reliability theory, and financial mathematics. Potential topics include, but are not limited to: Markov chains and processes; large deviations and limit theorems; random motions; stochastic biological model; reliability, availability, maintenance, inspection; queueing models; queueing network models; computational methods for stochastic models; applications to risk theory, insurance and mathematical finance.
Performance Analysis and Capacity Planning of Multi-stage Stochastic Order Fulfilment Systems with Levelled Order Release and Order Deadlines
Author: Mohring, Uta
language: en
Publisher: KIT Scientific Publishing
Release Date: 2022-09-15
Order fulfilment systems are forced to manage a volatile customer demand while meeting customer-required short order deadlines. To handle these challenges, we introduce the Strategy of Levelled Order Release (LOR) for workload balancing over time. The contributions of this work are (1) the workload balancing concept LOR, (2) a discrete-time Markov chain for performance analysis, and (3) an algorithm for capacity planning under performance constraints in order fulfilment systems with LOR.