Machining Parameters Optimization Based on Objective Function Linearization

Cristina Gavrus, Nicolae-Valentin Ivan and Gheorghe Oancea
Additional contact information
Cristina Gavrus: Department of Engineering and Industrial Management, Transilvania University of Brasov, 500036 Brasov, Romania
Nicolae-Valentin Ivan: Department of Manufacturing Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
Gheorghe Oancea: Department of Manufacturing Engineering, Transilvania University of Brasov, 500036 Brasov, Romania

Mathematics, 2022, vol. 10, issue 5, 1-15

Abstract: Manufacturing process optimization is an ever-actual goal. Within this goal, machining parameters optimization is a very important task. Machining parameters strongly influence the manufacturing costs, process productivity and piece quality. Literature presents a series of optimization methods. The results supplied by these methods are comparable and it is difficult to establish which method is the best. For machining parameters optimization, this paper proposes a novel, simple and efficient method, without additional costs related to new software packages. This approach is based on linear mathematical programming. The optimization mathematical models are, however, nonlinear. Therefore, mathematical model linearization is required. The major and difficult problem is the linearization of the objective function. This represents the key element of the proposed optimization method. In this respect, the paper proposes an original mathematical procedure for calculating the part of the objective function that refers to the analytical integration of the tool life into the model. This calculus procedure was transposed into an original software tool. For demonstrating the validity of the method, a comparison is presented among the results obtained by certain optimization techniques. It results that the proposed method is simple and as good as those presented by the literature.

Keywords: optimization; linear objective function; linear solving method; machining parameters; comparative results (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/5/803/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/5/803/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:5:p:803-:d:763200

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().