TY  - BOOK
AU  - Sarin,Subhash C.
AU  - Jaiprakash,Puneet
ED  - SpringerLink (Online service)
TI  - Flow Shop Lot Streaming
SN  - 9780387476889
U1  - 670 23
PY  - 2007///
CY  - Boston, MA
PB  - Springer US
KW  - ENGINEERING
KW  - INDUSTRIAL ENGINEERING
KW  - ENGINEERING ECONOMY
KW  - BUSINESS LOGISTICS
KW  - INDUSTRIAL AND PRODUCTION ENGINEERING
KW  - OPERATIONS RESEARCH/DECISION THEORY
KW  - ENGINEERING ECONOMICS, ORGANIZATION, LOGISTICS, MARKETING
KW  - PRODUCTION/LOGISTICS
N1  - Introduction -- Introduction to the Lot Streaming Problem. Introduction. Terminolog. Assumption, Notation and Classification Scheme. Dominance in Lot Streaming Model. Potential benefits of Lot Streaming. Brief Historical Perspective. Applications of Lot Streaming. Chapter Summary -- Generic Mathematical Models of the Flow Shop Lot Streaming Problem. Introduction. Some Generic Mathematical models for Lot Streaming Problem.Mathematical Models for special Cases. Chapter Summary -- 2-Machine Shop Lot Streaming Problems -- 3-Machine Flow Shop Lot Streaming Problems -- m-Machine Flow Shop Lot Streaming Problems
N2  - Lot streaming is a process of breaking a batch of jobs into smaller lots, and then processing these in an overlapping fashion on the machines. This important concept can significantly improve the overall performance of a production process, and thereby make the operation of a manufacturing system lean. Flow Shop Lot Streaming introduces the reader to this significant production process, presents various analysis techniques, and allows the reader to quickly become conversant with the state-of-the-art techniques necessary to embark on new research directions. This text begins with an introduction to and a brief historical perspective of the lot streaming problem, and continues with generic mathematical models for this problem. Flow Shop Lot Streaming presents systematic analysis, algorithms, key ideas and illustrative examples using 2-machine, 3-machine, and the general m-machine flow shop lot streaming problems. Flow Shop Lot Streaming will appeal to production and operations management engineers, researchers, and academics interested in implementing the latest models, analysis, and algorithms in the study of manufacturing systems
UR  - http://dx.doi.org/10.1007/978-0-387-47688-9
ER  -