Multi objective optimization of plasma arc cutting of AISI 304 Stainless Steel using Taguchi and Grey Rational Analysis method
Plasma arc cutting is one of the best non-conventional machining process, which is popular for cutting various materials that were difficult for cutting and also produces sophisticated geometries. Optimization of plasma arc cutting (PAC) is required to obtain products of good physical and mechanical
2025-06-28 16:34:12 - Adil Khan
Multi objective optimization of plasma arc cutting of AISI 304 Stainless Steel using Taguchi and Grey Rational Analysis method
Project Area of Specialization Mechanical EngineeringProject SummaryPlasma arc cutting is one of the best non-conventional machining process, which is popular for cutting various materials that were difficult for cutting and also produces sophisticated geometries. Optimization of plasma arc cutting (PAC) is required to obtain products of good physical and mechanical properties that is why optimization of plasma arc cutting has always been an open field for research purposes. This work investigates the influence of plasma arc cutting variables such as current, voltage, torch height, and speed on response variables, Surface Roughness, Material removal rate, and dross of AISI 304 stainless steel. Design of experiment techniques is extensively used for optimization purposes. Optimization is referred to the controlling of some particular set of parameters of a process subject to certain constraints in order to obtain optimized results. Multi-objective optimization is one that deals with the optimization of more than one objective function. It is performed to have immense control over cost factors, production, and quality. Commonly Taguchi method, grey rational analysis, and ANOVA is used for the optimization of the manufacturing process. Taguchi’s methods are techniques that aim to improve product and process quality. Taguchi’s parameter design involves adjusting process parameters to obtain desired objective functions with minimal variability. Control of variability is achieved by signal to noise (S/N) ratio. Taguchi based Grey relational analysis is a well-organized and systematic technique for multi-objective optimization. GRA is the best fit for solving problems involving little information and which involves multi parameters and response variables.
Project ObjectivesObjectives:
- To improve the quality of the plasma arc cutting process
- To analyze the influence of effective process parameters on response variables of AISI304
- Optimization of dross formation and surface roughness by optimizing process parameters of plasma arc cutting
- Optimization of process parameters to maximize material removal rate
First of all plasma arc cutting is studied in the local industry. Significant process parameters that influence plasma arc cutting and response variables of AISI 304 will be identified from the literature review. Taguchi OA is to be used for designing the experiments and the experimentation will be carried out at local industry PCSIR. Data collection is to be done by measurement of samples. ANOVA will be used for finding out the effectiveness of each parameter. Signal to Noise (S/N) ratio will be calculated for each level. Taguchi method along with GRA will be used for multi-objective optimization.
Benefits of the ProjectThis research work will be helpful to learn about the multi-objective optimization of a manufacturing process (PAC). It will also be beneficial to know about the application of DOE techniques such as Taguchi, GRA, and ANOVA for optimization purposes. Furthermore, learn about plasma arc cutting its parameters and response variables. This work will also aid in improving technical writing and will also help to learn about various software’s like Minitab, endnote, Grammarly, Visio, etc.
This research will help every sector of the community which is involved in the material removal process by PAC. It will help to improve the quality of cut by optimization of cutting parameters and as a result, the product quality and productivity will be maximized while minimizing the total production cost.
The world is moving towards lean manufacturing. This research work will be significant because it will reduce rework and scrap and can be implemented in the practical field to achieve better product quality.
Technical Details of Final Deliverable1. Mono-objective optimization of material removal rate.
2. Mono-objective optimization of surface roughness.
3. Mono-objective optimization of dross formation.
4. Mono-objective optimization of kerf width.
5. Mono-objective optimization of chamfer.
6. Multiobjective optimization of material removal rate, surface roughness, dross formation, kerf width and chamfer simultaneously.
7. Providing a Sustainable solution from plasma Arc cutting.
Before our works mostly works are done in a single/mono objective optimization of plasma arc cutting and in our research work we are working on multi-objective optimization of PAC.
From the literature review, it can be concluded that a lot of work has been carried out on PAC but there is still room for improvement in optimization. From research work, it can be observed that current, standoff distance, and speed are effective to process parameters that can be optimized. In this work we consider these parameters to optimize them for dross formation, surface roughness, and MRR in AISI 304. The effect of process parameters on multi-objective optimization of the stated responses in Plasma arc cutting on AISI 304 has not been investigated yet. In our work we will use Taguchi L9 OA coupled with GRA for optimization purposes and ANOVA will be used to analyze data, also Minitab software will be used to find out the effect of each parameter.
Final Deliverable of the Project Hardware SystemCore Industry ManufacturingOther IndustriesCore Technology Clean TechOther Technologies OthersSustainable Development Goals Decent Work and Economic GrowthRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 30520 | |||
| Material charges | Equipment | 9 | 1000 | 9000 |
| Cutting charges | Equipment | 9 | 850 | 7650 |
| Testing charges | Equipment | 9 | 750 | 6750 |
| Ball points | Miscellaneous | 12 | 10 | 120 |
| Pencils | Miscellaneous | 6 | 10 | 60 |
| Sharpener | Miscellaneous | 3 | 10 | 30 |
| Printing | Miscellaneous | 7 | 410 | 2870 |
| Ruler + Protector | Miscellaneous | 2 | 30 | 60 |
| Metal marker | Miscellaneous | 2 | 30 | 60 |
| Cover Binding | Miscellaneous | 7 | 60 | 420 |
| Ring Binding | Miscellaneous | 7 | 50 | 350 |
| Thesis Binding | Miscellaneous | 7 | 450 | 3150 |