Date of Award
2018
Publication Type
Master Thesis
Degree Name
M.A.Sc.
Department
Mechanical, Automotive, and Materials Engineering
Keywords
Mill-turn; Mixed Integer Linear Programming; Multitasking; Parallel Machining; Scheduling; Simulated Annealing
Supervisor
Azab, Ahmed
Supervisor
Baki, Fazle
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
Multitasking is an important part of today’s manufacturing plants. Multitask machine tools are capable of processing multiple operations at the same time by applying a different set of part and tool holding devices. Mill-turns are multitasking machines with the ability to perform a variety of operations with considerable accuracy and agility. One critical factor in simultaneous machining is to create a schedule for different operations to be completed in minimum make-span. A Mixed Integer Linear Programming (MILP) model is developed to address the machine scheduling problem. The adopted assumptions are more realistic when compared with the previous models. The model allows for processing multiple operations simultaneously on a single part; parts are being processed on the same setup and multiple turrets can process a single operation of a single job simultaneously performing multiple depths of cut. A Simulated Annealing algorithm with a novel initial solution and assignment approach is developed to solve large instances of the problem. Test cases are presented to assess the proposed model and metaheuristic algorithm.
Recommended Citation
Yavari, Saleh, "Machine Scheduling for Multitask Machining" (2018). Electronic Theses and Dissertations. 7409.
https://scholar.uwindsor.ca/etd/7409