Comparative study of ultrasonic and laser assisted machining for sustainable leather cutting in greener industry practices

Abstract

Sustainable production strategies are becoming more essential in the leather industry to minimize environmental impact and enhance process efficiency. The proposed study investigates the comparative analysis of ultrasonic assisted machining and CO₂ laser assisted machining for leather cutting focusing on sustainable leather processing. In recent times the ultrasonic cutting has emerged as a promising alternative for precision leather cutting. This technique makes use of high frequency vibrations to cut through leather materials with minimum resistance that improves edge quality and significantly reduces the material waste. The cutting trials were carried out on buffalo leather with a thickness of 1.4 mm. The surface roughness and kerf width were analyzed as a key process parameter for this investigation to produce optimal input parameters. The proposed study also explores image processing techniques to quantify surface roughness. Experimental results in leather cutting demonstrate that ultrasonic cutting was performed by varying delay time of (0.1–0.4 s), cutting time (0.02–0.12 s) and shaking time (0.02–0.08 s) significantly reduces thermal damage and maintaining average surface roughness of 0.008 μm and narrow kerfwidth of 0.2899 mm. CO₂ laser cutting was carried out by varying power (20–30 W), cutting speed (10–30 m/min) and Standoff Distance (1.5–1.9 mm) produces significant thermal damage evident by carbonization at cut edges with an average surface roughness of 0.012 μm and kerf width of 0.1391 mm. The ultrasonic cutting consumes less energy compared to laser machining resulting in lower overall emissions and significantly reduced carbon footprint. As sustainability becomes an essential concern in the global industrial sector this study highlights the benefit and drawbacks of each technique emphasizing the adaptability of ultrasonic machining for greener industrial practices. These findings contribute to the sustainable manufacturing by demonstrating the potential of ultrasonic cutting for cleaner more efficient leather processing with reduced environmental impact.

Introduction

Leather is a unique biomaterial that has been utilised by humans for thousands of years throughout a broad variety of applications. The machinability of the leather material has not improved significantly over time. Laser Beam Machining (LBM) provides an efficient alternative for leather machining for rapid production and maintaining a constant quality throughout the machining process¹. Leather industries generate substantial hazardous waste which contributes to the escalating levels of soil and air pollution². The leather industry generates a wide variety of goods. The market demand for those goods is quite exceedingly effective across multiple sectors. The leather production process generates significant waste that leads to several forms of pollution³. Cutting, engraving and marking are the various processes used in leather machining that typically involve high energy consumption and material loss⁴. The important productivity difficulties in machining operations are material utilisation and cutting sequence both of which are critical for increasing efficiency and minimising waste. These challenges become more complicated as the number of parts grows, necessitating advanced planning and optimisation approaches⁵. The Leather Nesting Problem (LNP) is a complex optimization challenge in leather cutting process that aims to find the optimal arrangement of leather pieces on a single material sheet to minimize waste and maximize material utilization⁶. The extreme heat produced during the cutting process causes carbonization in leather that has been processed with Carbon di oxide (CO₂) lasers⁷. The laser cutting of leather results in carbonization at the edges, particularly noticeable in lighter-coloured leathers, manifesting as visually discernible darkened edges due to thermal effects⁸. The laser cutting of leather produces carbonized edges through the thermal decomposition leading to the formation of carbon deposits⁹. The Fourier Transform Infrared Spectroscopy (FTIR) analysis confirmed the presence of carbon-related functional groups indicative of such thermal decomposition. Despite its advantages such as precision and reduced material wastage laser cutting technology inherently generates carbonised cut edges. During the cutting process when chromium-tanned leather is involved, this leads to the presence of chromium oxides and other carbon-related compounds, raising potential concerns about toxic emissions if appropriate filtration or emission control technologies are not employed¹⁰. Therefore, this confirm that CO₂ laser processing of leather significantly contributes to carbonization, resulting in environmental implications through the formation of carbon deposits and potentially hazardous emissions¹¹.

This carbonization affects leather aesthetic and structural qualities¹². This leads to potential discolouration of charred edges on the leather contour necessitating further post-processing¹³. The excessive carbonisation might lower the quality of the final product by affecting downstream processes like stitching or bonding¹⁴. The leather cutting industry has the potential to produce an adverse impact on the environment by emitting toxic gaseous pollutants such as ammonia, hydrogen sulphide and volatile organic compounds. The emissions produced during the CO₂ laser may affect air quality and harm the environment health risk¹⁵. The ultrasonic cutting (USC)¹⁶ of leather overcome the carbonization issue typically seen in CO₂ laser¹⁷ by eliminating the heat induced decomposition of leather¹⁸. In recent developments the simulation-based approaches have provided insights into the fundamental mechanisms of ultrasonic assisted processes. This underscore the importance of optimizing process parameters that are crucial for achieving precision and sustainability in leather cutting¹⁹. The tool wear and durability are the key considerations in the assisted machining processes²⁰. The USC in leather demonstrates superior tool sustainability contributing to reduced maintenance frequency, lower operational costs and alignment with greener manufacturing practices. In USC high frequency vibrations²¹ are used instead of heat treatment²² for minimizing thermal effects and preventing carbonization. The ultrasonic cutting system combines mechanical and ultrasonic energy²³ to improve cutting performance. By combining high-frequency vibrations with pneumatic pressure²⁴ the system provides great accuracy, decreased friction and increased cutting efficiency²⁵ making it perfect for complicated materials such as leather. The USC approach produces clean cuts and prevent carbon residue formation. Effective management is critical for reducing the environmental footprint²⁶. Although there is different physical, chemical and biological ways for treating emissions, sustainable alternatives like as biofilters provide environmentally acceptable solutions, assisting in the development of greener leather processing processes²⁷ and pollution reduction. The USC has emerged as a promising alternative reducing defects and improving machining quality²⁸. Surface roughness measurement has evolved from traditional offline methods to modern real time inline measurement. The quality of the leather cut assessed through the critical indicator arithmetic mean roughness (Ra). The surface roughness impacted by both static and dynamic parameters of the cutting process. The implementation of non-contact techniques has gained extensive traction due to several critical benefits such as speed, accuracy, flexibility and assess surface quality in real time²⁹. Recent developments in non-traditional machining emphasized the importance of understanding the tool material interactions under assisted processes. This contributes to deeper understanding of material properties and machining modes that impact the final cutting quality³⁰.

The implementation of image processing techniques emerged as a powerful approach for non-contact measurement in leather cutting. This online process measurement allows real time surface characterization and enables immediate quality assessment with potential process adjustments. This technique handles and analyze visual data extracting intricate surface details that might be impossible by traditional measurement techniques³¹. Adjusting Standoff Distance (SOD) used to improve kerf width in leather cutting and this achieve narrower and more uniform kerf width³². The width of the kerf influences the precise dimensions³³ of the leather cut. The kerfwidth is a crucial technical parameter³⁴ in leather manufacturing for evaluating the precision and quality of the leather cutting process. The varying individual effects on kerfwidth and surface roughness³⁵ has been identified using main effect plots. This provides initial understanding of each parameter individual contribution to the response variable³⁶. After analyzing the main effects, the interaction plots help to refine insights by identifying parameter combinations and lead to significant changes. The interaction plot shows the input parameters interact and jointly influence the response variable. This helps to cover unexpected effects that occur when parameter combinations are varied together.USC represents an advanced technological approach³⁷ in the field of leather cutting those addresses both manufacturing precision and environmental sustainability. The ultrasonic vibration technology creates high quality leather cuts with significant ecological benefits. Recent investigations in ultrasonic assisted material processing have demonstrated not only shows surface improvements but also significant microstructural and mechanical transformations induced by ultrasonic energy³⁸. The advancements in sustainable manufacturing emphasized the effectiveness of modern techniques in machining to enhance machining quality and to minimize energy consumption and operational costs³⁹. Energy consumptions play a crucial role in evaluating the overall environmental impact of machining technologies. The predictive modelling specific cutting energy consumption under eco-benign lubricating environments significantly improves machining sustainability by optimizing parameters and reducing energy usage⁴⁰. USC minimizes material waste and contributes to sustainability by lowering carbon footprint, minimizing emissions and supports circular economy principles in leather cutting. USC produces clean edges without the need for post processing to remove carbonization in the case of laser cutting also it reduces the risk of scorching, ensuring better product quality and eliminating the negative impacts on downstream processes like stitching or bonding.

The drive for sustainability in leather cutting has accelerated the adoption of advanced technologies⁴¹. Sustainable production strategies are critically important within modern manufacturing practices reflecting global environmental goals such as the United Nations Sustainable Development Goals (SDGs) and industry commitments to green manufacturing. This aligns with the growing global emphasis on sustainable manufacturing practices. The traditional manufacturing methods such as manual cutting, rotary cutting and die pressing in leather cutting industry involve significant environmental impacts⁴². There is a need to adopt cleaner and more efficient technologies to meet evolving regulatory standards and consumer demands for sustainable products. A structured comparative framework is crucial to evaluate the performance of different assisted machining strategies⁴³. The proposed study addresses these challenges by presenting a quantitative comparative analysis between CO₂ laser and ultrasonic leather cutting for sustainable leather processing. This study highlights the advantages and limitations of both methods, emphasizing the potential of ultrasonic cutting as a more sustainable and eco-friendlier alternative in leather manufacturing. The lower operational temperatures and reduced emissions observed in USC offer the benefits seen with eco-benign strategies⁴⁴ emphasizing ultrasonic processing as an eco-friendlier and more durable alternative for sustainable manufacturing practices. The lower energy consumption, minimal thermal damage and extended tool life observed in USC for leather could be further justified not only from a sustainability standpoint but also through cost minimization metrics, strengthening the case for both an eco-friendly and economically superior alternative to conventional laser-based methods⁴⁵. The application of ultrasonic machining is revolutionising leather cutting by improving both operational efficiency and sustainability. This technological development not only boosts production but also promotes eco-friendly manufacturing processes. These findings provide valuable insights for adopting greener industrial practices, balancing operational efficiency with environmental responsibility. The monitoring strategies inspired by LIBS (Laser Induced Breakdown Spectroscopy) based technologies represents a significant opportunity to further enhance the environmental and process performance advantages demonstrated in this comparative study⁴⁶.

As a result of detailed literature survey, it was inferred that only limited existing literature explored laser assisted and ultrasonic assisted leather cutting. A critical research gap exists on comparative study of laser cutting and ultrasonic cutting of leather using Taguchi design approach. Minimal attention has been given to evaluating environmental impacts of leather cutting processes. The proposed study undertakes a significant effort to evaluate leather machinability through laser and ultrasonic cutting techniques. The adaptation of USC on leather cutting offer more sustainable and precise cutting solutions for the leather industry. Hence an attempt was undertaken in this study to support sustainable manufacturing by demonstrating the potential of ultrasonic cutting for cleaner and more efficient leather processing with reduced environmental impact. This investigation introduces both ultrasonic and laser cutting techniques for leather cutting that presents the results for each method with discussion on the effects of process parameters and concludes with key findings.

Materials and methods

Ultrasonic assisted leather cutting

Figure 1 shows the ultrasonic assisted leather cutting system. The combination of mechanical and ultrasonic energy used to enhance the precision and efficiency of the leather cutting. The proposed cutting system integrates high frequency vibrations with a cutting tool to improve the cutting performance. The high frequency vibrations are utilized to reduce friction and improve precision. This approach minimizes the heat generation and leather deformation. The ultrasonic generator delivers electrical energy to the cutting system and converts it into high frequency vibrations. The generator controls the frequency of the horn in the range of 19,850 Hz to 20,250 Hz.The piezoelectric transducer responsible for the conversion of mechanical vibrations to ultrasonic frequencies.

Fig. 1.

Schematic representation for ultrasonic cutting.

The mechanical vibrations essential for the ultrasonic cutting process to reduce the cutting force and to enhance cutting accuracy. The pneumatic piston arrangement applies the constant force to the cutting tool with the help of transducer assembly. The pressure applied by the piston arrangement regulate the cutting depth and ensure uniform cutting across the leather samples. The vibration generator amplifies the mechanical vibrations generated by the transducer to improve the cutting process. The converter changes the vibration mode from longitudinal to axial for efficient energy transfer to the cutting tool and the booster amplifies the vibrational energy to ensure the tool receives ultrasonic energy to perform precise cuts. The anvil absorbs some of the ultrasonic energy and provides a stable platform to cut leather and remains in place for uniform cutting. The horn assists as a mechanical amplifier transmits the ultrasonic vibrations from the booster and converter arrangement to the cutting tool. It is used to maintain the vibration frequency and amplitude during the leather cutting process. The 18 mm cutting tool attached in the horn used to perform leather cutting. It is fixed in a way to withstand ultrasonic vibrations while maintaining a sharp edge to precise leather cuts. The leather cut performed with assistance from ultrasonic vibrations and the mechanical pressure from the pneumatic piston arrangement. The ultrasonic vibration energy generated during the leather cutting process creates a unique interaction between the cutting tool and leather samples allowing for a more controlled and efficient mechanism. The anvil provides a stable platform to support the leather material during the cutting process. It absorbs some of the ultrasonic energy and ensures that the leather remains in place for uniform cutting.

The three critical input process variables in ultrasonic cutting of leather are Delay time (DT), Cutting time (CT) and Shaking time (ST) due to its importance in ultrasonic cutting process. The control parameters fixed as shown in Table 1. DT is the time of the horn down and the time from turning on the switch to having the ultrasonic wave. CT is the actual time to generate ultrasonic waves.ST refers to the duration were the ultrasonic vibrations applied to the cutting tool when it is in contact with the leather material.

Table 1.

Control factors and levels according to experiment using USC.

Sl.No.	Parameters	Unit	Level 1	Level 2	Level 3
1.	Delay time	Seconds	0.1	0.25	0.4
2.	Cutting time	Seconds	0.02	0.07	0.12
3.	Shaking time	Seconds	0.02	0.05	0.08

Figure 2 shows the ultrasonic generator, main view of experimental setup and cutting tool attached with horn for leather cutting. The main interface in ultrasonic generator used to set the frequency, amplitude and current and this also includes the time parameter adjustments for different levels of input process variables. The horn attached to the cutter controls the vibration frequency and amplitude during the leather cutting process, whereas the anvil serves as a solid base to hold the leather material. The input and output process parameters influence productivity measurement. Table 2 shows the design layout for the ultrasonic cutting process. Based on experienced ultrasonic machining operators the following parameters for the cutting process were chosen.

Fig. 2.

Experimental setup.

Table 2.

Design layout for the ultrasonic cutting process.

Trial No	Delay time (s)	Cutting time (s)	Shaking time (s)
1	0.1	0.02	0.02
2	0.1	0.07	0.05
3	0.1	0.12	0.08
4	0.25	0.02	0.05
5	0.25	0.07	0.08
6	0.25	0.12	0.02
7	0.4	0.02	0.08
8	0.4	0.07	0.02
9	0.4	0.12	0.05

CO₂ laser assisted leather cutting

Buffalo leather has been taken as specimens in the present study owing to higher usage among the leather material. The leather cuts have been performed using the GL-1680 CO₂ laser cutter as the rectangular specimens. The minimum achievable laser spot diameter was approximately 2 mm. Based on this, the spot area was calculated using the formula for a circular cross-section, resulting in an area of 0.0314 cm². The corresponding laser power density was then determined as approximately 3822 W/cm². The positioning accuracy is within ± 0.05 mm and the laser operate at a wavelength of 10.6 μm. The Surface quality has been evaluated using microscope. Laser power (W), cutting speed (m/min) and Standoff Distance (SOD) have been taken as input process parameters to access the surface quality. The process variables of cutting process have been chosen on expert knowledge of experienced machining operator in the present study. The cutting experiments have been performed using CO₂ LBM under the design of experiments as per Table 3.

Table 3.

Control factors and levels according to experiment using CO₂ LBM.

Sl.No.	Parameters	Unit	Level 1	Level 2	Level 3
1.	Power	Watt	20	25	30
2.	Cutting speed	m/min	10	20	30
3.	Standoff distance	mm	1.5	1.7	1.9

Table 4 shows the design layout for the CO₂ laser cutting process. The table corresponds to a Taguchi L₉ orthogonal array for experimental design to optimize parameters with minimal trials. The L₉ array allows for three factors each at three levels ensuring efficient cutting of all combinations.

Table 4.

Design layout for the CO₂ laser cutting process.

Trial No	Power (W)	Cutting speed (m/min)	SOD (mm)
1	20	10	1.5
2	20	20	1.7
3	20	30	1.9
4	25	10	1.7
5	25	20	1.9
6	25	30	1.5
7	30	10	1.9
8	30	20	1.5
9	30	30	1.7

This experimental design is used for determining optimal settings to improve CO₂ laser cutting performance including surface roughness and kerf width.

Results and discussion

The buffalo leather machined using the ultrasonic cutting and laser cutting is depicted in Fig. 3. The samples were examined under a microscope with appropriate illumination to assess surface quality. The cross-sectional surface morphology of the machined leather was captured using a Kruss Optronic MSL series stereo microscope. The leather samples were firmly secured in the microscope to acquire accurate cross section of leather contour edges in the form of images. The recorded images were trimmed by cropping unnecessary sections to focus on the vital areas. A Taguchi L₉ experimental design was utilized to determine the ideal balance between the response parameters.

Fig. 3.

Machined leather specimens.

Table 5 shows the Taguchi L₉ orthogonal array with results of surface roughness and kerfwidth in ultrasonic leather cutting with the experiment conducted. Delay time influences the system stability and energy transfer. The cutting time impact material removal and overall process efficiency. The shaking time impact surface quality and kerf characteristics.

Table 5.

Taguchi L₉ orthogonal array with results of surface roughness and Kerfwidth in USC.

Trial No	Delay time (s)	Cutting time (s)	Shaking time (s)	Surface roughness (µm)	Kerfwidth (mm)	S/N Surface roughness (µm)	S/N Kerfwidth (mm)
1	0.1	0.02	0.02	0.011	0.4736	39.1721	6.4918
2	0.1	0.07	0.05	0.005	0.1632	46.0206	15.7456
3	0.1	0.12	0.08	0.007	0.2120	43.0980	13.4733
4	0.25	0.02	0.05	0.012	0.6176	38.4164	4.1859
5	0.25	0.07	0.08	0.010	0.3525	40.0000	9.0568
6	0.25	0.12	0.02	0.006	0.2012	44.4370	13.9274
7	0.4	0.02	0.08	0.008	0.2304	41.9382	12.7504
8	0.4	0.07	0.02	0.009	0.2912	40.9151	10.7162
9	0.4	0.12	0.05	0.004	0.0672	47.9588	23.4526

The lower delay times of 0.1s in trial 2 tend to produce lower kerf widths 0.1632 mm and better surface roughness 0.005 μm. The higher delay times 0.4s show slightly varied outcomes likely depending on cutting and shaking time. The Shorter cutting time 0.02s result in higher kerf widths 0.4736 mm in trial 1 but are faster. The longer cutting times 0.12s in trial 9 allow more precise cuts reducing kerf width 0.0672 mm and improving surface roughness of 0.004 μm. The Shorter shaking times 0.02s lead to better kerf width precision and smoother surfaces in some trials. The longer shaking times 0.08s may reduce precision but increasing kerf width and roughness. This helps to identify optimal ultrasonic leather cutting parameters to achieve high quality leather cuts with minimal surface roughness and kerf width. This can also be used to improve the efficiency of the ultrasonic cutting process for leather cutting applications. The mean standard deviation (S/N ratio) has been used for smaller is better according to the following Eq. (1). And the analysis of variance (ANOVA) was done using Minitab Software.

1

Where n is No. of observations and R is Observed data for each response.

The analysis of variance (ANOVA) was performed to evaluate the contribution of three factors Delay Time, Cutting Time and Shaking Time on the observed process performance. From Table 6 cutting time was identified as the most influential factor, contributing 51% to the total variation, followed by Delay Time (13%) and Shaking Time (7%). The residual error accounted for 19%, indicating the presence of some unexplained variability, potentially due to uncontrolled factors or experimental noise.

Table 6.

ANOVA results for surface roughness in ultrasonic cutting.

Source	Degree of freedom	Sum of squares	Mean squares	% Contribution
Delay time (s)	2	11.03	5.515	13
Cutting time (s)	2	42.56	21.282	51
Shaking time (s)	2	12.93	6.466	7
Residual error	2	16.57	8.286	19
Total	8	83.10

From Table 7 it was observed that cutting time again contributing 51% to the overall variance. However, the delay time exhibited a greater influence (25%) compared to the first trial, while shaking time accounted for 10% of the total variation. The residual error decreased to 14%, suggesting a better model fit. It was observed that the cutting time consistently emerged as the dominant factor affecting the process, while the contributions of delay time and shaking time were relatively smaller but still noteworthy. These findings underscore the importance of optimizing cutting time to improve process efficiency.

Table 7.

ANOVA results for Kerfwidth in ultrasonic cutting.

Source	Degree of freedom	Sum of squares	Mean squares	% Contribution
Delay time(s)	2	65.40	32.70	25
Cutting time (s)	2	125.94	62.97	51
Shaking time (s)	2	25.88	12.94	10
Residual error	2	35.77	17.89	14
Total	8	252.99		100

Table 8 shows the Taguchi L₉ orthogonal array with results of surface roughness and kerfwidth in CO₂ laser assisted leather cutting with the experiment conducted. Increased power range from 20 W to 30 W tends to reduce surface roughness and kerf width especially at higher cutting speeds. Increasing the cutting speed from 10 m/min to 30 m/min generally results in lower surface roughness and narrower kerf widths. There is a slight variation in surface roughness and kerf width with different standoff distances but the trends are not strongly dependent on this factor alone. The lowest surface roughness of 0.008 μm and kerf width of 0.0202 mm were observed in Trial 9. The highest surface roughness of 0.015 μm and kerf width of 0.3248 mm occurred at Trial 4.

Table 8.

Taguchi L₉ orthogonal array with results of surface roughness and Kerfwidth in LBM.

Trial No	Power (W)	Cutting speed (m/min)	Standoff distance (mm)	Surface roughness (µm)	Kerfwidth (mm)	S/N surface roughness (µm)	S/N Kerfwidth (mm)
1	20	10	1.5	0.015	0.2659	36.4782	11.5056
2	20	20	1.7	0.011	0.0673	39.1721	23.4397
3	20	30	1.9	0.016	0.1272	35.9176	17.9103
4	25	10	1.7	0.014	0.3248	37.0774	9.7677
5	25	20	1.9	0.013	0.1718	37.7211	15.2995
6	25	30	1.5	0.012	0.0905	38.4164	20.8670
7	30	10	1.9	0.010	0.0864	40.0000	21.2697
8	30	20	1.5	0.009	0.0982	40.9151	20.1578
9	30	30	1.7	0.008	0.0202	41.9382	33.8930

ANOVA was conducted to assess the impact of power, cutting speed, and Standoff Distance on the process performance. From Table 9, Power was found to be the most dominant factor, accounting for 74% of the total variation. Standoff Distance and Cutting Speed contributed 10% and 9%, respectively, indicating relatively minor influences. The residual error was limited to 7%, reflecting a strong model fit and minimal unexplained variation.

Table 9.

ANOVA of surface roughness for laser cut.

Source	Degree of freedom	Sum of squares	Mean squares	% Contribution
Power (W)	2	24.775	12.387	74
Cutting speed (m/min)	2	3.092	1.546	9
Standoff distance (mm)	2	3.451	1.726	10
Residual error	2	2.289	1.144	7
Total	8	33.606		100

Table 10 revealed a more balanced distribution of factor contributions. Power and Cutting Speed had comparable impacts, contributing 39% and 37%, respectively, while Standoff Distance maintained a modest influence at 10%. The residual error increased to 13%, suggesting a slight reduction in the model’s predictive accuracy compared to the first case. Overall, the findings highlight the critical role of Power in determining process outcomes, particularly in the first experiment, while also emphasizing the growing influence of Cutting Speed under varying experimental conditions.

Table 10.

ANOVA of Kerfwidth for laser cut.

Source	Degree of freedom	Sum of squares	Mean squares	% Contribution
Power (W)	2	24.775	12.387	74
Cutting speed (m/min)	2	3.092	1.546	9
Standoff distance (mm)	2	3.451	1.726	10
Residual Error	2	2.289	1.144	7
Total	8	33.606		100

Measurement of surface roughness in leather cut performed by USC and LBM

The proposed study presents a comprehensive methodology for quantitative surface roughness analysis using MATLAB 2024a utilizing digital image processing techniques enabling precise measurement of surface topographical characteristics. Figure 4 depicts the functional flow diagram for the microscopic image analysis. The high-resolution images of leather cross section were acquired and converted to grayscale format to ensure uniformity in intensity representation. The captured images are normalized and preprocessed using Gaussian filter to effectively minimize noise artifacts to improve the surface texture. The surface profiles were extracted by averaging grayscale intensity values along horizontal and vertical directions subsequently translating pixel intensities to micrometre height data using the resolution of the captured images was consistently maintained at 0.5 μm per pixel determined through a calibration procedure using known reference dimensions. The arithmetic average roughness (Ra) represents the mean deviation from the mean line and the root mean square roughness (Rq) quantifies the statistical variance in height deviations.

Fig. 4.

Surface roughness analysis of leather cut surfaces using image processing.

Visualization through three-dimensional (3D) surface plots and detailed profile graphs were employed to verify the robustness of the processing algorithm and confirm accurate representation of the surface topology.

Surface roughness analysis in ultrasonic cutting

The conversion process from a captured microscopic image to a preprocessed grayscale image during ultrasonic cutting is shown in Fig. 5. The Gaussian filter is used to reduce noise and improve the image signal-to-noise ratio thereby improving the image reliable for further analysis. The image is then normalized to a double-precision format that stays in the 0–1 range standardizing pixel intensity values for consistent processing. The height profile extraction method calculates the mean pixel intensities across rows and columns to produce two distinct profiles for horizontal and vertical. This dual profile approach enables surface characterisation to adjust for variations in texture and orientation. The statistical techniques involved in height data processing derive the surface roughness parameters. Systematic fluctuations are removed using a linear trend removal process so that the analyses concentrate on local surface anomalies. The Ra and Rq are the two main surface roughness metrics that are acquired by the technique which also computes deviations and the mean line.

Fig. 5.

Conversion of captured microscopic image to preprocessed grayscale image in USC.

The Ra parameter is a fundamental measure of surface irregularity, representing the arithmetic mean of absolute deviations from the mean line. Rq provides a root mean square evaluation of surface variations that is particularly susceptible to localised height fluctuations. The 3D surface plot using a colour map and a height profile plot with a trend line. The proposed algorithm generates graphical representations including a 3D surface plot with a colormap and a height profile plot with a trend line. These visualisations not only offer intuitive representations of surface topography but also enable the qualitative interpretation of quantitative measurements. The calibration factor is a critical parameter in the analysis enabling the precise conversion between physical measurements and pixel dimensions. This method facilitates precise roughness quantification across a variety of imaging systems by establishing a connection between digital image representation and actual surface measurements through the inclusion of this factor.

Figure 6 illustrates the surface roughness and profile analysis of a poor cut obtained using ultrasonic leather cutting. The 3D surface plot illustrates the spatial distribution of the Ra in micrometres (µm) over the cut area. The plot indicates the maximum surface roughness in red region and minimum surface roughness in blue region. The surface roughness varies significantly with high peaks around the middle of the cut and lower roughness near the edges. The uneven distribution of roughness suggests improper ultrasonic frequency tuning and non-optimized input process parameter. The height profile graph indicates the variation of surface height (Rq) in micrometres along the length of the cut plotted in pixels. This shows the maximum height and minimum height in µm. The downward slope is observed in the red dashed trend line indicating a decline in surface height over distance. The surface roughness starts high at the initial state reflecting a rough and uneven cutting process at the beginning. In the intermediate state the surface height fluctuates but decreases slightly. The final Rq height drops further indicating better consistency but still poor quality due to high variability. The height profile oscillates significantly showing peaks and valleys along the length of the cut. The trend line slope is negative emphasizing a gradual reduction in surface height. This could indicate issues such as tool wear over the cutting path and uneven distribution of cutting pressure.

Fig. 6.

Poor leather cut performed using USC in trial 4.

Figure 7 illustrates the variation in the Ra across the cutting area showcasing a uniform and smooth cutting profile. The average Ra indicating an overall high-quality surface finish. The plot shows minimal fluctuations in surface roughness suggesting an even cutting action across the leather. The presence of smaller blue regions representing lower Ra values highlights the optimized cutting conditions minimizing material damage and defects. The height profile graph provides insight into the surface texture in terms of Rq along the length of the cut. The maximum Rq, minimum Rq and the average Rq reflecting a uniform height distribution. The trend line remains nearly horizontal indicating consistent material removal and negligible height deviation across the cutting path. The height variations are minimal signifying superior cutting precision with no abrupt irregularities. The steady height profile confirms that the ultrasonic cutter maintained consistent pressure and energy during the process. Peaks and valleys are evenly distributed without significant deviations highlighting well-calibrated ultrasonic settings. Table 11 summarizes and compares key metrics and observations for the poor cut and the best cut based on the provided images and analysis.

Fig. 7.

Best leather cut performed using USC in trial 9.

Table 11.

Key metrics and observations for the poor cut and the best cut in USC.

Sl.No	Feature	Poor cut in trial 4	Best cut in trial 9
1	Surface Roughness (Ra)	Noticeable fluctuations with irregular peaks and valleys	Uniform surface finish with minor fluctuations
2	Height Profile (Rq)	Trend line shows a decreasing slope, indicating irregular material removal	Nearly horizontal trend line with consistent material removal
3	Uniformity	Surface roughness and height profiles show considerable variation with uneven distribution of peaks and valleys	More uniform roughness and height profile with smooth and evenly distributed surface textures
4	Trend Line behaviour	Downward sloping trend line indicates inconsistent material removal over the cutting path	Flat trend line reflects consistent cutting with minimal deviations
5	Material Removal	Uneven material removal due to poor calibration or unstable ultrasonic settings	Smooth and consistent material removal due to optimized cutting parameters
6	Vibrations and Stability	Significant mechanical vibrations leading to irregular surface textures and height fluctuations	Minimal vibrations ensure a smooth and consistent cutting process
7	Overall Cut Quality	Poor, Visible defects, higher roughness and inconsistent height profile indicate suboptimal parameters	Best, Minimal defects, low surface roughness and consistent height profile highlight superior cutting precision

Surface roughness analysis in CO₂ laser cutting

The conversion of captured microscopic image to preprocessed grayscale image in CO₂ LBM is as shown in Fig. 8.

Fig. 8.

Conversion of captured microscopic image to preprocessed grayscale image in CO₂ LBM.

Figure 9 shows the poor leather cut performed using LBM in trail 3. The Ra exhibits regions of both moderate and high roughness with peaks indicating uneven material removal. The smoother regions correspond to areas of better process control whereas the rougher areas suggest possible fluctuations in laser power or inconsistent standoff distance. The Rq ranges with an overall downward trend. A significant peak is observed suggesting localized imperfections.

Fig. 9.

Poor leather cut performed using LBM in trial 3.

The decreasing trend of the Rq values along the cutting length implies progressive stabilization of the process. The analysis indicates a mixed quality cut with prominent roughness variations across the surface. The observed trends suggest the need for optimization of key parameters such as laser power, pulse duration and standoff distance to achieve uniform cutting quality. These findings underscore the importance of optimized control strategies to minimize imperfections and enhance the overall process efficiency.

Figure 10 provides a detailed analysis of best leather cut performed using LBM in trial 9. The Ra values show a mix of high and low roughness. The smoother zones suggest localized areas of effective laser cutting while rougher areas may be due to factors such as inconsistent laser power and standoff distance fluctuations. The Rq varies with the trend line indicating minimal surface irregularities along the cutting path. Peaks and troughs in the graph highlight regular surface patterns. This analysis highlights moderate variability in surface quality during laser beam cutting of leather. The trend line in roughness along the height profile indicates the optimized process parameters achieved uniform cutting quality and reduce imperfections. Table 12 summarizes and compares key metrics and observations for the poor cut and the best cut based on the provided images and analysis.

Fig. 10.

Best leather cut performed using LBM in trial 9.

Table 12.

Key metrics and observations for the poor cut and the best cut.

Sl.No	Feature	Poor cut in trial 3	Best cut in trial 9
1	Surface Roughness (Ra)	High variability and uneven distribution	More uniform and smoother overall
2	Height Profile (Rq)	Irregular peaks and troughs	Fewer peaks and smoother transitions
3	Uniformity	Poor and significant variations across the cut surface	Better and improved consistency with minimal variations
4	Trend Line behaviour	Downward trend and indicating improvement over time	Slight upward trend, suggesting minor degradation in uniformity
5	Material Removal	Non-uniform removal, leading to uneven kerf width	Consistent removal; well- defined kerf width
6	Thermal distribution	Unstable heat distribution	Better process stability
7	Overall Cut Quality	Poor, visible defects, irregular edges and poor consistency	High, smooth edges, fewer defects and better finish

Measurement of Kerfwidth

The kerfwidth plays a crucial role in ultrasonic and laser leather cutting for evaluating the quality of the leather cut. This parameter reflects the precision and effectiveness of the cutting process. The kerf width values were recorded by averaging 10 values determined using ruler function in microscope which was first calibrated by actual Vernier scale. Figure 11 compares kerf width measurements between two trials of best cut performed in USC and LBM.

Fig. 11.

Kerfwidth measurement.

Figure 11a shows the kerfwidth for leather cuts performed using USM is consistently measured at 0.0672 mm across the entire length of the cut. The uniformity of the kerf width indicates that USM delivers highly precise cuts with minimal variation in width. This suggests that the ultrasonic method maintains excellent control throughout the cutting process. A constant kerf width of 0.0672 mm means USM offers reliable and stable cutting performance making it suitable for applications demanding high precision. Figure 11b shows the kerfwidth for cuts performed using LBM is consistently measured at 0.0202 mm along the length of the cut. The kerf width of LBM is much smaller than USM suggests that LBM produce leather cuts with an extremely narrow width. The LBM process appears to deliver a very fine cut with a much smaller kerf width. Both USM and LBM show excellent consistency in their kerf widths with no significant variation across the length of the cuts. This indicates that both methods are highly reliable in terms of precision and stability. This significant difference highlights the differing nature of the two cutting processes. USM uses high frequency vibrations to cut the material typically resulting in a broader cut whereas LBM employs laser energy which can produce extremely fine cuts. Both USM and LBM demonstrate high precision and consistent kerf widths. However, LBM produces a significantly finer cut making it ideal for applications requiring very narrow cuts. The best cut in USC and LBM showcases the importance of parameter optimization to achieve consistent kerf widths, reduced material deformation, and high-quality finishes. These findings emphasize the critical need for process optimization in ultrasonic and laser leather cutting to enhance both precision and overall efficiency.

Effects of process parameters on surface roughness and Kerfwidth in USC

To measure the effect of process parameters the main effect plot for the surface roughness and kerf width graphs were plotted. The main effects plot for surface roughness and kerfwidth analyses the three different factors such as delay time, cutting time and shaking time. These factors affect the surface roughness and kerfwidth of a leather material when it is cut using an ultrasonic cutting process. In this study the main effect plot analysis was performed with the help of Minitab 17.1 version software package. Figure 12 indicates that as the delay time increases the mean surface roughness slightly increases suggesting that longer delay times lead to higher surface roughness. The cutting time increases the mean surface roughness increases significantly indicating that longer cutting times result in higher surface roughness. The shaking time increases the mean surface roughness also increases significantly suggesting that longer shaking times contribute to higher surface roughness.

Fig. 12.

Main effects plot analysis on surface roughness.

Figure 13 shows the main effects plot for kerfwidth which is a measure of the width of the cut made in the leather material during the ultrasonic cutting process. As the delay time increases the mean kerfwidth first decreases slightly and then increases. This suggests that an intermediate delay time may be optimal for minimizing the kerfwidth. The plot also indicates that as the cutting time increases the mean kerfwidth increases significantly. This means that longer cutting times result in a larger kerfwidth. As the Shaking Time increases the mean kerfwidth also increases significantly. This implies that longer shaking times contribute to a wider kerfwidth.

Fig. 13.

Main effects plot analysis on Kerfwidth.

The observation provided in these main effects plot can be useful for optimizing the ultrasonic cutting process to achieve the desired surface roughness and kerfwidth characteristics for the leather material.

Figure 14a shows the 3D plot that depict the variation of surface roughness during ultrasonic leather cutting under delay time and cutting time parameter combinations. It was observed that the surface roughness varies based on the interaction between delay time and cutting time.

Fig. 14.

(a) Surface roughness as a function of delay time and cutting time. (b) Surface roughness as a function of delay time and shaking time. (c) Surface roughness as a function of cutting time and shaking time.

The colour gradient indicates the magnitude of surface roughness with red representing the highest values and blue the lowest. This shows non-linear behaviour with regions of sharp peaks and troughs suggesting that surface quality is sensitive to specific combinations of delay and cutting times.

Figure 14b examines the variation of surface roughness as a function of delay time and shaking time. A similar non-linear relationship is observed where certain delay and shaking time combinations lead to either increased or decreased roughness. The surface features sharp gradients indicating the parameters strong influence on the surface quality.

Figure 14c shows the relationship between surface roughness, cutting time and shaking time. The surface appears smoother in certain regions with fewer extreme peaks indicating moderate sensitivity to these parameters. However specific combinations still result in sharp increases or decreases in roughness requiring careful optimization of cutting and shaking times. All three plots emphasize the intricate dependency of surface roughness on process parameters in ultrasonic leather cutting. The colour-coded variation underscores the critical need for parameter optimization to minimize surface roughness and enhance cutting quality. The sharp transitions in surface roughness highlight the importance of maintaining precise control over delay time, cutting time, and shaking time during the process.

Figure 15a shows a non-linear relationship with sharp peaks and valleys. Kerf width increases as both delay time and cutting time increase. A lower kerf width region is observed at specific combinations of low delay time and moderate cutting time.

Fig. 15.

(a) Kerfwidth as a function of delay time and cutting time. (b) kerfwidth as a function of delay time and shaking time. 15 (c) Kerfwidth as a function of cutting time and shaking time.

Figure 15b shows higher delay time and shaking time led to larger kerf width values. The surface reveals sharp transitions with lower kerf width occurring at lower delay times regardless of shaking time. The interaction between the parameters shows distinct peaks and troughs.

Figure 15c shows kerfwidth is highest when both cutting time and shaking time are at their maximum. Lower kerfwidth is consistently observed at lower cutting times across different shaking times. The surface demonstrates a complex interplay between cutting and shaking times with variations forming ridges and depressions. The higher values of delay time, cutting time and shaking time generally result in increased kerf width. The kerf width response is non-linear with regions of sudden increases and decreases based on parameter combinations. Fine-tuning the parameters can help achieve lower kerf widths, enhancing cutting precision and surface quality.

Effects of process parameters on surface roughness and Kerfwidth in LBM

Figure 16 illustrates the main effects plot for surface roughness in CO₂ LBM focusing on three control parameters. As laser power increases the mean surface roughness increases linearly. Laser power has a strong positive effect on surface roughness indicating that higher power levels lead to rougher surfaces. Cutting speed has a moderate effect on surface roughness with the highest roughness occurring at medium speed levels. SOD has an inverse relationship with surface roughness, suggesting that increasing the stand-off distance leads to smoother surfaces. The main effects plot reveals that laser power has the strongest positive effect on surface roughness, cutting speed has a moderate effect and stand-off distance has an inverse effect with higher SOD values resulting in lower surface roughness.

Fig. 16.

Main effects plot analysis on surface roughness in LBM.

Figure 17 represents the main effects plot for kerfwidth in LBM analyzing the impact of three control parameters. Laser power has a strong positive effect on kerfwidth indicating that higher power levels lead to larger kerfwidth. Cutting speed has a moderate effect on kerfwidth, with the highest kerfwidth occurring at medium speed levels. SOD has an inverse relationship with kerfwidth suggesting that increasing the stand-off distance leads to smaller kerfwidth. The main effects plot reveals that laser power has the strongest positive effect on kerfwidth, cutting speed has a moderate effect and SOD has an inverse effect with higher SOD values resulting in smaller kerfwidth.

Fig. 17.

Main effects plot analysis on Kerfwidth in LBM.

Figure 18a examines the relationship between surface roughness and two independent process parameters power and cutting speed. Surface roughness increases significantly at high laser power and low cutting speeds which may indicate over burning or material charring. Lower laser power combined with higher cutting speeds results in reduced surface roughness, likely due to more controlled ablation.

Fig. 18.

(a) Surface roughness as a function of power and cutting speed. (b) Surface roughness as a function of power and SOD. (c) Surface roughness as a function of Cutting speed and SOD.

Figure 18b shows the surface roughness increases when standoff distance is either too small or too large indicating the importance of maintaining an optimal SOD. High laser power amplifies the surface roughness effect, especially when combined with extreme SOD values.

Figure 18c shows high cutting speeds combined with moderate SOD yield lower surface roughness suggesting efficient cutting conditions. Extremely high or low SOD values, irrespective of cutting speed, result in increased roughness due to inconsistent focus and energy delivery.

Laser power has a significant impact on surface roughness, and its interaction with other factors is crucial for achieving a smooth cut. Cutting speed and SOD need careful optimization to minimize surface roughness while preventing material defects. These insights guide parameter tuning in CO₂ leather cutting to achieve higher quality results with minimal surface defects.

Figure 19a depicts the Kerfwidth as a function of power and cutting speed. At high power and low cutting speeds the kerf width increases significantly due to excessive energy leading to overcutting. Lower power and higher cutting speeds result in narrower kerf widths, indicating precise cutting with minimal material removal.

Fig. 19.

(a) Kerfwidth as a function of power and cutting speed. (b) Kerfwidth as a function of power and SOD. (c) Kerfwidth as a function of cutting speed and SOD.

Figure 19b depicts the kerfwidth as a function of power and SOD. Higher power combined with extreme low or high SOD values results in wider kerf widths. The optimal SOD combined with moderate power minimizes kerf width, achieving precise and clean cuts.

Figure 19c shows kerfwidth as a function of cutting speed and SOD. Increased cutting speed reduces kerf width particularly when combined with an optimal SOD. Low cutting speeds and extreme SOD values result in larger kerf widths. Laser power has a dominant influence on kerf width with higher power leading to wider cuts due to increased energy delivery. Cutting speed affects kerf width inversely with higher speeds producing narrower cuts and slower speeds causing excessive material melting. SOD must be optimized to balance kerf width ensuring the laser beam remains focused for clean and precise cutting. These findings used to guide the optimization of laser cutting parameters in CO₂ based leather cutting to achieve precise kerf widths enhancing material utilization and cutting efficiency.

Figure 20 shows the surface morphology of the cross section of the leather cut performed using USC and LBM. The images were captured using optical microscope Fig. 20a highlights the surface shows evident carbonization and thermal damage characterized by rough edges and a darkened charred appearance. The laser thermal effect results in material degradation and uneven surface morphology. Figure 20b shows the carbonization free surface with ultrasonic cutting. The surface appears smoother and more uniform with no visible signs of carbonization. Ultrasonic cutting produces a clean cut by avoiding thermal damage preserving the material integrity of leather. Laser cutting leads to carbonization and thermal effects degrading the leather surface quality. Ultrasonic cutting offers superior surface morphology eliminating thermal damage and providing a clean and precise cut.

Fig. 20.

Surface morphology of the cross section of the leather cut using optical microscope.

Figure 21 shows the SEM image of ultrasonic leather cut reveals a distinctly fibrous structure with minimal thermal damage. The fibers appear cleanly separated and display limited deformation, reflecting the non-thermal nature of ultrasonic cutting. The edges of fibers show well-defined, smooth surfaces without significant carbonization, indicative of efficient, precise cutting and reduced material damage. This microstructure highlights ultrasonic cutting potential for maintaining material integrity and reducing waste in leather processing applications.

Fig. 21.

Ultrasonic cutting machined leather surface.

Figure 22 shows the SEM image of leather cut using CO₂ laser reveals a highly irregular and carbonized surface morphology. The fiber structures appear fused together, with significant thermal degradation and rough, uneven texture. The presence of Pores and cracks indicating localized burning and material collapse due to intense heat exposure. This microstructure highlights the thermal damage associated with laser cutting, resulting in compromised material integrity and higher potential for surface defects compared to ultrasonic cutting.

Fig. 22.

CO₂ laser cutting machined leather surface.

Conclusion

An experimental investigation was performed to analyze the effect of ultrasonic leather cutting and CO₂ leather cutting. The performance measures such as surface roughness and kerf width were taken into consideration. The following conclusions were obtained from the experimental findings and discussions.

• The comparative study analysed the effects of delay time, cutting time and shaking time in ultrasonic cutting as well as power, cutting speed and SOD in CO₂ laser cutting on surface roughness and kerfwidth.

• Minimal delay time of 0.1s achieved narrow kerfwidth of 0.1632 mm and better surface roughness of 0.005 μm enhancing system stability and energy transfer.

• Minimal cutting time of 0.02s achieved faster processing but leads to higher kerfwidth of 0.4376 mm and the maximum cutting time of 0.12s allowed more precise cuts with a kerfwidth of 0.0672 mm and surface roughness of 0.004 μm.

• Minimal shaking time of 0.02s improve precision and surface roughness in some trials but maximum shaking time of 0.08s increasing kerfwidth and surface roughness.

• The delay time of 0.4 s, cutting time of 0.12 s and shaking time of 0.05 s produce optimal performance measures. Optimizing the delay time, cutting time and shaking time is crucial to achieve minimal surface roughness and consistent kerf width.

• High laser power of 30 W and cutting speed 30 m/min in CO₂ laser cutting of leather significantly improve surface roughness and kerfwidth.

• The standoff distance of 1.7 mm balancing leather material removal efficiency and cutting quality emerging as a near optimal distance from the tested range.

• In CO₂ laser cutting of leather 30 W laser power combined with higher cutting speed of 30 m/min and a mid-range SOD of 1.7 mm optimizes surface roughness and minimizes kerf width.

• The microscope captured leather cut morphology-based image processing approach quantify the surface roughness that generates graphical representations including a 3D surface plot with a colormap and a height profile plot with a trend line.

Ultrasonic leather cutting supports greener industry practices in several ways particularly in minimizing environmental impact, reducing waste and improving energy efficiency. Ultrasonic cutting is a non-thermal process avoids the carbonization and emission of volatile organic compounds (VOCs) and particulates associated with thermal processes, directly supporting greener manufacturing initiatives. Ultrasonic cutting typically requires less energy than laser cutting since it relies on mechanical vibration rather than high-powered lasers. This results in lower energy consumption reducing the carbon footprint of the cutting process. The precise nature of ultrasonic cutting minimizes material waste leading to efficient use of leather and reducing the amount of scrap that needs to be disposed. By avoiding thermal damage ultrasonic cutting preserves the natural properties of leather making it more durable and extending product life cycles. This supports sustainable manufacturing by improving the overall quality and usability of the material. Ultrasonic leather cutting aligns with greener industry practices by reducing energy consumption, emissions and material waste while delivering high precision and quality. Its eco-friendly advantages make it an excellent alternative for industries striving to achieve sustainable manufacturing goals.

Ultrasonic cutting technologies have notable potential for broader integration into smart manufacturing environments. Their compatibility with real-time monitoring, precise parameter control, and seamless automation could enhance their implementation in digitally interconnected production lines. However, challenges related to scaling up for large-volume production, integration with existing infrastructure, and initial capital investment remain critical factors. Further research should focus on overcoming these limitations and exploring hybrid systems combining ultrasonic and laser cutting, potentially leveraging the strengths of both technologies. Such integration would represent a significant step towards sustainable, high-efficiency leather processing within smart manufacturing ecosystems.

Author contributions

S.M.: Conceptualization, Data curation, Methodology, Formal analysis, Writing – original draft. V.S.: Data curation, Writing – original draft, Conceptualization, Methodology. I.C.: Data curation, Writing – original draft, Conceptualization. All authors have read and agreed to the published version of the manuscript.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.