A generalized machine requirements planning algorithm for serial flow machining systems

The machine requirements planning problem is one which is applicable throughout the manufacturing industry. The use of automation and computer technology makes the use of machine requirements modelling particularly attractive, and the vast capital investment in machining equipment offers significant opportunity for savings through optimization. The machine requirements problem must be modelled as a mixed integer linear program. However, a dynamic programming solution procedure with linear programming postoptimality techniques at each stage of the machining process is utilized to provide an efficient, flexible algorithm. The machine requirements model is capable of optimizing any type of machining system, whether of a discrete or continuous operating mode. Through discretizing the machine parameters problem, by limiting tool changes to between passes of a tool, any continuous mode system is approximated as discrete for optimization purposes and a direct interface with the machine requirements planning model is provided. The dynamic programming solution procedure is compared with a mixed integer procedure. The DP formulation is not only more efficient in both time and core but provides sensitivity information and offers a broad spectrum of further application into more complex aspects of manufacturing systems.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Industrial Engineering and Operations Research

Department dc:contributor.department

Industrial Engineering and Operations Research

Grantor dc:publisher

Virginia Polytechnic Institute and State University

Year dc:date.issued

1978

Author dc:creator

• Hayes, Glenn M.

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10919/64747

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/64747