Efficiency of optimization algorithms on the adjustment of process parameters for geometric accuracy enhancement of denture plate in single point incremental sheet forming

2019 ◽  
Vol 32 (13) ◽  
pp. 8829-8846 ◽  
Author(s):  
Manel Sbayti ◽  
Riadh Bahloul ◽  
Hedi Belhadjsalah
Keyword(s):  
Process Parameters ◽  
Single Point ◽  
Optimization Algorithms ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Geometric Accuracy ◽  
Accuracy Enhancement ◽  
Denture Plate

Parameter optimization and texture evolution in single point incremental sheet forming process

2019 ◽  
Vol 234 (1-2) ◽  
pp. 126-139 ◽  
Author(s):  
Shamik Basak ◽  
K Sajun Prasad ◽  
Amarjeet Mehto ◽  
Joy Bagchi ◽  
Y Shiva Ganesh ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Regression Models ◽  
Incremental Forming ◽  
Single Point ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Single Point Incremental Forming ◽  
Input Process ◽  
Truncated Cone

Prototyping through incremental sheet forming is emerging as a latest trend in the manufacturing industries for fabricating personalized components according to customer requirement. In this study, a laboratory scale single-point incremental forming test setup was designed and fabricated to deform AA6061 sheet metal plastically. In addition, response surface methodology with Box–Behnken design technique was used to establish different regression models correlating input process parameters with mechanical responses such as angle of failure, part depth per unit time and surface roughness. Correspondingly, the regression models were implemented to optimize the input process parameters, and the predicted responses were successfully validated at the optimal conditions. It was observed that the predicted absolute error for angle of failure, part depth per unit time and surface roughness responses was approximately 0.9%, 4.4% and 6.3%, respectively, for the optimum parametric combination. Furthermore, the post-deformation responses from an optimized single point incremental forming truncated cone were correlated with microstructural evolution. It was observed that the peak hardness and highest areal surface roughness of 158 ± 9 HV and 1.943 μm, respectively, were found near to the pole of single-point incremental forming truncated cone, and the highest major plastic strain at this region was 0.80. During incremental forming, a significant increase in microhardness occurred due to grain refinement, whereas a substantial increase in the Brass and S texture component was responsible for the increase in the surface roughness.

scholarly journals Cranial Reconstruction Using Double Side Incremental Forming

2015 ◽  
Vol 639 ◽  
pp. 535-542 ◽  
Author(s):  
Bin Lu ◽  
Dong Kai Xu ◽  
Run Zhe Liu ◽  
Heng An Ou ◽  
Hui Long ◽  
...  
Keyword(s):  
Tool Path ◽  
Incremental Forming ◽  
Thickness Distribution ◽  
Single Point ◽  
Pure Titanium ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Geometric Accuracy ◽  
Backing Plate ◽  
Cranial Implant

Incremental sheet forming (ISF) is a highly versatile and flexible process for rapid manufacturing of complex sheet metal parts. Comparing to conventional sheet forming processes, ISF is of a clear advantage in manufacturing small batch or customized products such as cranial implant. Although effort on cranial reconstruction by using incremental sheet forming approach has been made in recent years, research has been mostly based on the single point incremental forming (SPIF) strategy and there are still considerable technical challenges for achieving better geometric accuracy, thickness distribution and complex cranial shape. In addition, the use of a backing plate or supporting die reduces the process flexibility and increases the cost. To overcome these limitations, double side incremental sheet forming (DSIF) process is employed for forming Grade 1 pure titanium sheet by using different toolpath strategies. The geometric accuracy and thickness distribution of the final part are evaluated so the optimized tool path strategies are developed. This leads to an assessment of the DSIF based approach for the application in cranial reconstruction.

scholarly journals A Novel Tool to Enhance The Lubricant Efficiency On Induction Heat-Assisted Incremental Sheet Forming of Ti-6Al-4V Sheets

2022 ◽  
Author(s):  
Weining Li ◽  
Khamis Essa ◽  
Sheng Li
Keyword(s):  
Surface Quality ◽  
Single Point ◽  
Water Channel ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Water Cooling ◽  
Geometric Accuracy ◽  
Molybdenum Disulphide ◽  
Roughness Analysis ◽  
Pass Through

Abstract For heat-assisted single point incremental sheet forming (SPIF) works of Ti-6Al-4V sheets, the use of lubricant has shown significant effects on surface quality and geometric accuracy at higher temperatures. Molybdenum disulphide (MoS2) is a common lubricant widely used in SPIF works, however, it usually indicates ineffective performance at high temperatures. This article has studied different lubricants of MoS2 lubricants and proposed a novel mixture of MoS2 to provide better surface quality and improve geometric accuracy. A forming tool with a ball-roller and water channel was designed to enable the MoS2 mixture to pass through the tool tip, allowing easy application of the lubricant on the localised area and reduce the thermal expansion on the ball-roller. Surface roughness analysis has revealed that the water-cooling MoS2 mixture performed well in reducing friction effects and achieved better geometric accuracy. Forming forces measurements, scanning electron microscope (SEM), energy dispersive X-ray Analysis (EDX) and micro-hardness tests also indicated that a higher strain hardening behaviour was detected for the water-cooling MoS2 mixture.

scholarly journals Incremental sheet forming of thermoplastics: a review

2020 ◽  
Vol 111 (1-2) ◽  
pp. 565-587
Author(s):  
Hui Zhu ◽  
Hengan Ou ◽  
Atanas Popov
Keyword(s):  
Process Parameters ◽  
Flexible Manufacturing ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Metallic Materials ◽  
Processing Conditions ◽  
Geometric Accuracy ◽  
Significant Progress ◽  
Research Directions ◽  
Made In

Abstract Incremental sheet forming (ISF) is a promising flexible manufacturing process, which has been tested in sheet forming of various metallic materials. Although ISF-based forming of thermoplastics is relatively new, it has drawn considerable interests and significant progress has been made in recent years. This paper presents a review of concurrent research on the emerging trend of thermoplastic-focused ISF processes. Attention is given to the processing conditions including process setup, process parameters and forming forces. The deformation mechanism and failure behaviour during ISF of thermoplastics are evaluated, which leads to detailed discussions on the formability, effect of different process parameters and the forming quality such as geometric accuracy, surface finish and other consideration factors in ISF of thermoplastics. A comparison of important similarities and differences between ISF of thermoplastic and metallic materials is made. Finally, a brief discussion is provided on the technical challenges and research directions for ISF of thermoplastic materials in the future.

Customized cranial implant manufactured by incremental sheet forming using a biocompatible polymer

2018 ◽  
Vol 24 (1) ◽  
pp. 120-129 ◽  
Author(s):  
Isabel Bagudanch ◽  
María Luisa García-Romeu ◽  
Ines Ferrer ◽  
Joaquim Ciurana
Keyword(s):  
Incremental Forming ◽  
Raw Materials ◽  
Single Point ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Scanning System ◽  
Geometric Accuracy ◽  
Biocompatible Polymer ◽  
Content Type ◽  
Cranial Implant

Purpose The purpose of this paper is to demonstrate the feasibility of incremental sheet forming (ISF), using the most common variants, single-point incremental forming (SPIF) and two-point incremental forming (TPIF), to produce prototypes of customized cranial implants using a biocompatible polymer (ultrahigh molecular weight polyethylene, UHMWPE), ensuring an appropriate geometric accuracy and cost. Design/methodology/approach The cranial implant is designed based on computerized tomographies (CT) of the patient, converting them into a 3D model using the software InVesalius. To generate the toolpath for the forming operation computer-aided manufacturing (CAM) software is used. Once the cranial implant is manufactured, a 3D scanning system is used to determine the geometric deviation between the real part and the initial design. Findings The results corroborate that it is possible to successfully manufacture a customized cranial implant using ISF, being able to improve the geometric accuracy using the TPIF variant with a negative die. Originality/value This paper is one of the first research works in which a customized cranial implant is successfully manufactured using a flexible technology, ISF and a biocompatible polymer. The use of polymeric implants in cranioplasty is advantageous because of their lightweight, low heat conductivity and mechanical properties similar to bone. Furthermore, the cost of the implant has been calculated considering not only the raw materials and manufacturing time but also the environmental impact, revealing that it is a cheap process with a low lead-time.

Modeling Force Fluctuations in Incremental Sheet Forming

2020 ◽  
Author(s):  
Michael Prize ◽  
Douglas Bristow ◽  
Robert Landers
Keyword(s):  
Process Parameters ◽  
Tool Path ◽  
Single Point ◽  
Reaction Force ◽  
Three Dimensional ◽  
Geometric Error ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Forming Force ◽  
Manufacturing Method

Abstract Incremental Sheet Forming (ISF) is a versatile manufacturing method in which a three-dimensional part is fabricated by progressively deforming a metal sheet. This is typically done via a robot with a single point tool following a defined trajectory. During this process a reaction force between the forming tool and sheet is generated. This force, denoted the forming force and defined as the force acting perpendicular to the sheet, has been modeled in several studies. Given a part with homogenous material, a fixed part geometry, and constant process parameters, these models predict the forming force will be constant. However, many studies have shown that this force fluctuates during the process. This paper augments the model by accounting for changes in process parameters due to robot geometric errors to describe these fluctuations. The model is experimentally validated, and the fluctuations of the forming force are reduced by 51% by modifying the tool path based on the identified robot geometric error.

Optimization in single point incremental forming of Inconel 718 through response surface methodology

2020 ◽  
Vol 44 (1) ◽  
pp. 148-160
Author(s):  
S. Pratheesh Kumar ◽  
S. Elangovan
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Inconel 718 ◽  
Single Point ◽  
Optimization Technique ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Forming Process ◽  
Profile Accuracy

Incremental sheet forming is a flexible and versatile process with a promising future in the batch production and prototyping sectors. With decreased design time and negligible production time, incremental sheet forming provides reliability, flexibility, and quality, while being an economical option in contrast to the traditional forming process. In this paper, Inconel 718, a material that has extensive use in aircraft engines, is considered for experimental work to obtain the optimum combination of process parameters. Response surface methodology is used to optimize the process parameters, in particular feed rate, step depth, and lubricant viscosity. The output responses are surface roughness, profile accuracy, and wall thickness. Analysis of variance (ANOVA) is performed using the experimental results to predict the statistical influence of the process parameters. The optimal combination of process parameters is further predicted using a numerical optimization technique to achieve better profile accuracy and surface finish. The results obtained are experimentally validated and are in good agreement with the predicted values.

Multiobjective optimization of process variables in single-point incremental forming using grey relational analysis coupled with entropy weights

2021 ◽  
pp. 146442072110204
Author(s):  
Abdulmajeed Dabwan ◽  
Adham E Ragab ◽  
Mohamed A Saleh ◽  
Atef M Ghaleb ◽  
Mohamed Z Ramadan ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Incremental Forming ◽  
Single Point ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Numerical Control ◽  
Single Point Incremental Forming ◽  
Process Variables ◽  
Relational Analysis ◽  
Grey Relational

Incremental sheet forming is a specific group of sheet forming methods that enable the manufacture of complex parts utilizing computer numerical control instead of specialized tools. It is an incredibly adaptable operation that involves minimal usage of sophisticated tools, dies, and forming presses. Besides its main application in the field of rapid prototyping, incremental sheet forming processes can be used for the manufacture of unique parts in small batches. The goal of this study is to broaden the knowledge of the deformation process in single-point incremental forming. This work studies the deformation behavior in single-point incremental forming by experimentally investigating the principal stresses, principal strains, and thinning of single-point incremental forming products. Conical-shaped components are fabricated using AA1050-H14 aluminum alloy at various combinations of fundamental variables. The factorial design is employed to plan the experimental study and analysis of variance is conducted to analyze the results. The grey relational analysis approach coupled with entropy weights is also implemented to identify optimum process variables for single-point incremental forming. The results show that the tool diameter has the greatest effect on the thinning of the SPIF product, followed by the sheet thickness, step size, and feed rate.

scholarly journals Artificial neural network for modeling and investigating the effects of forming tool characteristics on the accuracy and formability of thin aluminum alloy blanks when using SPIF

2021 ◽  
Author(s):  
Sherwan Mohammed Najm ◽  
Imre Paniti
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Process Parameters ◽  
Single Point ◽  
Tool Material ◽  
Deformation Mode ◽  
Geometric Accuracy ◽  
Forming Process ◽  
Tool Shape ◽  
Artificial Neural

AbstractIncremental Sheet Forming (ISF) has attracted attention due to its flexibility as far as its forming process and complexity in the deformation mode are concerned. Single Point Incremental Forming (SPIF) is one of the major types of ISF, which also constitutes the simplest type of ISF. If sufficient quality and accuracy without defects are desired, for the production of an ISF component, optimal parameters of the ISF process should be selected. In order to do that, an initial prediction of formability and geometric accuracy helps researchers select proper parameters when forming components using SPIF. In this process, selected parameters are tool materials and shapes. As evidenced by earlier studies, multiple forming tests with different process parameters have been conducted to experimentally explore such parameters when using SPIF. With regard to the range of these parameters, in the scope of this study, the influence of tool material, tool shape, tool-end corner radius, and tool surface roughness (Ra/Rz) were investigated experimentally on SPIF components: the studied factors include the formability and geometric accuracy of formed parts. In order to produce a well-established study, an appropriate modeling tool was needed. To this end, with the help of adopting the data collected from 108 components formed with the help of SPIF, Artificial Neural Network (ANN) was used to explore and determine proper materials and the geometry of forming tools: thus, ANN was applied to predict the formability and geometric accuracy as output. Process parameters were used as input data for the created ANN relying on actual values obtained from experimental components. In addition, an analytical equation was generated for each output based on the extracted weight and bias of the best network prediction. Compared to the experimental approach, analytical equations enable the researcher to estimate parameter values within a relatively short time and in a practicable way. Also, an estimate of Relative Importance (RI) of SPIF parameters (generated with the help of the partitioning weight method) concerning the expected output is also presented in the study. One of the key findings is that tool characteristics play an essential role in all predictions and fundamentally impact the final products.

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