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Modeling and optimization in turning of PA66-GF30% and PA66 using multi-criteria decision-making (PSI, MABAC, and MAIRCA) methods: a comparative study

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Abstract

Semi-crystalline polymers are widely used in modern industry. Indeed, they are highly demanded because of their excellent compromise between advantageous mechanical properties, high lightness, good productivity, and low cost. In this work, a modeling study of performance parameters such as (Ra), (Fz), (Pc), and (MRR) was carried out using the response surface methodology (RSM). Dry machining operations were performed on two polyamides (PA66-GF30% and PA66) following the L9 (33) orthogonal array. The results were used to perform a mono-objective optimization based on the Taguchi signal-to-noise ratio (S/N). In addition, a comparative study between three multi-objective optimization methods MCDM (PSI, MABAC, and MAIRCA) coupled with the Taguchi approach was realized. The target objective is to reduce (Ra, Fz, and Pc) and maximize (MRR) simultaneously. The results found are original and can help researchers working in the field of machining polyamides with and without reinforcement.

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Abbreviations

Vc:

Cutting speed (m/min)

f:

Feed rate (mm/rev)

ap:

Depth of cut (mm)

Ra:

Surface roughness (μm)

Fz:

Tangential cutting force (N)

Pc:

Power consumption (W)

MRR:

Material removal rate (cm3/min)

ANOVA:

Analysis of variance

RSM:

Response surface methodology

MCDM:

Multi-criteria decision-making methods

PSI:

Preference selection index

MABAC:

Multi-attributive border approximation area comparison

MAIRCA:

Multi-attributive ideal-real comparative analysis

EDM:

Electrical Discharge Machining

DF:

Desirability Function

ANN:

Artificial neural network

PMEDM:

Powder mixed electrical discharge machining

ESM:

Ultrasonic Machining

MRS:

Material-removal speed (g/h)

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Acknowledgements

The present research was undertaken by the “Metal Cutting Research Group” of the Structures and Mechanics Laboratory (LMS) of the 8 May 1945-Guelma University, Algeria.

Funding

The present research was undertaken by the “Metal Cutting Research Group” of the Structures and Mechanics Laboratory (LMS) of the 8 May 1945-Guelma University, Algeria, and received funding from the General Directorate of Scientific Research and Technological Development (DGRSDT) under the PRFU research project A11N01UN240120190001.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Mechanics and Structure Laboratory (LMS), Universite 8 Mai 1945, 401, 24000, Guelma, BP, Algeria

    Sabrina Haoues, Mohamed Athmane Yallese, Salim Belhadi & Salim Chihaoui

  2. Department of Mechanical Engineering, Yildiz Technical University, 34349, Istanbul, Besiktas, Turkey

    Alper Uysal

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  1. Sabrina Haoues
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  2. Mohamed Athmane Yallese
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Correspondence to Sabrina Haoues.

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Haoues, S., Yallese, M.A., Belhadi, S. et al. Modeling and optimization in turning of PA66-GF30% and PA66 using multi-criteria decision-making (PSI, MABAC, and MAIRCA) methods: a comparative study. Int J Adv Manuf Technol 124, 2401–2421 (2023). https://doi.org/10.1007/s00170-022-10583-8

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