Application of Multi-Criteria Decision Making Optimization Tool for Determining Mild Steel Weld Properties and Process Parameters Using the TOPSIS

Friction materials, mainly made of reinforced composites, should possess excellent physical and tribological properties, such as a higher coefficient of friction, minimum wear, adequate surface hardness, and higher porosity for various automotive brake applications. Attainment of those properties greatly depends on the settings of different input parameters, such as molding pressure, temperature and time, temperature and time of heat treatment/sintering, etc., during the processing of friction materials. In this article, four multi-criteria decision-making (MCDM) tools, i.e., technique for order of preference by similarity to ideal solution (TOPSIS), evaluation based on distance from average solution (EDAS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and multi-objective optimization on the basis of ratio analysis (MOORA) are applied to identify the optimal parametric combinations for two different friction materials. A comparative analysis of the derived results suggests the same optimal parametric mixes for all the MCDM techniques for both case studies. Thus, for the considered case studies, the optimal parametric combinations as molding time = 8 min, molding temperature = 175 °C, molding pressure = 27 MPa, sintering time = 10 h and sintering temperature = 225 °C, and molding pressure = 27.90 MPa, molding temperature = 170 °C, curing time = 8 min, and heat treatment time = 1 h, respectively, would help in attaining the most desired properties of friction materials. Improvements in the predicted response values prove the efficacy of the adopted MCDM techniques in determining the optimal combinations of various process parameters for friction materials.

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Application of MOORA to Optimize WEDM Process Parameters: A Multi-criteria Decision Making Approach

ICRRM 2019 – System Reliability, Quality Control, Safety, Maintenance and Management ◽

10.1007/978-981-13-8507-0_12 ◽

2019 ◽

pp. 73-78

Author(s):

Himadri Majumder ◽

Srimant Kumar Mishra ◽

Anil R. Sahu ◽

Anil Laxmanrao Bavche ◽

Mahadev Valekar ◽

...

Keyword(s):

Decision Making ◽

Process Parameters ◽

Multi Criteria Decision Making ◽

Wedm Process

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A multi-criteria decision making method for vapor smoothening fused deposition modelling part

Rapid Prototyping Journal ◽

10.1108/rpj-08-2020-0184 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Sugavaneswarn M. ◽

Prashanthi B. ◽

John Rajan A.

Keyword(s):

Decision Making ◽

Surface Roughness ◽

Process Parameters ◽

Surface Finish ◽

Orientation Angle ◽

Multi Criteria Decision Making ◽

Post Processing ◽

Dimensional Error ◽

Content Type ◽

Fused Deposition

Purpose This paper aims to enhance the surface finish of the fused deposition modeling (FDM) part using the vapor smoothening (VS) post-processing method and to study the combined effect of FDM and VS process parameters on the quality of the part. Design/methodology/approach Analysis of variance method is used to understand the significance of the FDM and VS process parameters. Following this, the optimized parameter for multiple criteria response is reported using the technique for order preference by similarity to ideal solution. The process parameters alternatives are build orientation angle, build surface normal and exposure time and the criteria are surface roughness and dimensional error percentage. Findings The result observed contradicts the result reported on the independent parameter optimization of FDM and VS processes. There is a radical improvement in the surface finish on account of the coating process and an increase in the exposure time results in the decrease of the surface roughness. Minimum surface roughness of 0.11 µm is observed at 1,620 build angle and the least dimensional error of 0.01% is observed at build orientation angle 540. The impact of VS on the up-facing surface is different from the down-facing surface due to the removal of support material burrs and the exposure of the surface to vapor direction. Originality/value A study on the multi-criteria decision-making to ascertain the effect of post-processing on FDM component surface normal directed both to downward (build angle 0°–90°) and to upward (build angle 99°–180°) are reported for the first time in this article. The data reported for the post-processed FDM part at the build angle 0°–180° can be used as a guideline for selecting the optimal parameter and for assigning appropriate tolerance in the CAD model.

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A Systematic Simulation-Based Multi-Criteria Decision-Making Approach for the Evaluation of Semi–Fully Flexible Machine System Process Parameters

Electronics ◽

10.3390/electronics11020233 ◽

2022 ◽

Vol 11 (2) ◽

pp. 233

Author(s):

Thirupathi Samala ◽

Vijaya Kumar Manupati ◽

Jose Machado ◽

Shubham Khandelwal ◽

Katarzyna Antosz

Keyword(s):

Decision Making ◽

Real Time ◽

Process Parameters ◽

Manufacturing Systems ◽

Entropy Method ◽

Multi Criteria Decision Making ◽

Machine Condition ◽

Simulation Approach ◽

Throughput Time ◽

Stay Time

Current manufacturing system health management is of prime importance due to the emergence of recent cost-effective and -efficient prognostics and diagnostics capabilities. This paper investigates the most used performance measures viz. Throughput Rate, Throughput Time, System Use, Availability, Average Stay Time, and Maximum Stay Time as alternatives that are responsible for the diagnostics of manufacturing systems during real-time disruptions. We have considered four different configurations as criteria on which to test with the proposed integrated MCDM (Multi-Criteria Decision-Making)-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)-based simulation approach. The main objective of this proposed model is to improve the performance of semi–fully flexible systems and to maximize the production rate by ranking the parameters from most influenced to least. In this study, first, the performance of the considered process parameters are analyzed using a simulation approach, and furthermore the obtained results are validated using real-time experimental results. Thereafter, using an Entropy method, the weights of each parameter are identified and then the MCDM-based TOPSIS is applied to rank the parameters. The results show that Throughput tTme is the most affected parameter and that Availability, average stay time, and max stay time are least affected in the case of no breakdown of machine condition. Similarly, Throughput Time is the most affected parameter and Maximum Stay Time is the least affected parameter in the case of the breakdown of machine condition. Finally, the rankings from the TOPSIS method are compared with the PROMETHEE method rankings. The results demonstrate the ability to understand system behavior in both normal and uncertain conditions.

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