Date of Award

2018

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

First Advisor

Azab, Ahmed

Second Advisor

Baki, Fazle

Keywords

Mill-turn; Mixed Integer Linear Programming; Multitasking; Parallel Machining; Scheduling; Simulated Annealing

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 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.

Share

COinS