A Production Planning Model for a Steel Plate Fabrication Plant with Flexible Customization and Manufacturing
(2014) 19th IFAC World Congress, 2014- Abstract
- With increased market competition and advances in modern manufacturing technologies, requirements on customer orders and manufacturing conditions have become more diversified. This paper addresses a dynamic production planning problem for a steel plate fabrication plant with practical flexibility of both customers and manufacturing, such as steel slab-plate matching rules, plate substitution options, production line assignment. These flexibility factors can provide the decision maker with auxiliary options to satisfy customer requirements through realizable production planning. The steel slab-plate matching rules combined with plate substitution options are visualized by a networked graph and formulated by a set based design. A... (More)
- With increased market competition and advances in modern manufacturing technologies, requirements on customer orders and manufacturing conditions have become more diversified. This paper addresses a dynamic production planning problem for a steel plate fabrication plant with practical flexibility of both customers and manufacturing, such as steel slab-plate matching rules, plate substitution options, production line assignment. These flexibility factors can provide the decision maker with auxiliary options to satisfy customer requirements through realizable production planning. The steel slab-plate matching rules combined with plate substitution options are visualized by a networked graph and formulated by a set based design. A mixed-integer nonlinear programming (MINLP) model that incorporates various manufacturing constraints and the flexibility is proposed to simultaneously optimize production strategy and provide practical managerial information such as backlogging/inventory level, capacity availability, and also steel slab demand. Linearization methods are used to transform the original MINLP problem into mixed integer linear programming (MILP) model resulting in easier and quicker solutions. A real industrial steel plate fabrication plant is used as a case and illustrates the effectiveness and applicability of the proposed method. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7760731
- author
- Lu, Shan ; Su, Hongye ; Johnsson, Charlotta LU and Xie, Lie
- organization
- publishing date
- 2014
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- mixed-integer linear programming, Production planning
- pages
- 6 pages
- conference name
- 19th IFAC World Congress, 2014
- conference location
- Cape Town, South Africa
- conference dates
- 2014-08-24 - 2014-08-29
- external identifiers
-
- scopus:84929833689
- language
- English
- LU publication?
- yes
- id
- cb671ae1-bcb4-403e-935c-db536b99c28d (old id 7760731)
- date added to LUP
- 2016-04-04 13:03:06
- date last changed
- 2024-01-13 05:46:06
@misc{cb671ae1-bcb4-403e-935c-db536b99c28d,
abstract = {{With increased market competition and advances in modern manufacturing technologies, requirements on customer orders and manufacturing conditions have become more diversified. This paper addresses a dynamic production planning problem for a steel plate fabrication plant with practical flexibility of both customers and manufacturing, such as steel slab-plate matching rules, plate substitution options, production line assignment. These flexibility factors can provide the decision maker with auxiliary options to satisfy customer requirements through realizable production planning. The steel slab-plate matching rules combined with plate substitution options are visualized by a networked graph and formulated by a set based design. A mixed-integer nonlinear programming (MINLP) model that incorporates various manufacturing constraints and the flexibility is proposed to simultaneously optimize production strategy and provide practical managerial information such as backlogging/inventory level, capacity availability, and also steel slab demand. Linearization methods are used to transform the original MINLP problem into mixed integer linear programming (MILP) model resulting in easier and quicker solutions. A real industrial steel plate fabrication plant is used as a case and illustrates the effectiveness and applicability of the proposed method.}},
author = {{Lu, Shan and Su, Hongye and Johnsson, Charlotta and Xie, Lie}},
keywords = {{mixed-integer linear programming; Production planning}},
language = {{eng}},
title = {{A Production Planning Model for a Steel Plate Fabrication Plant with Flexible Customization and Manufacturing}},
year = {{2014}},
}