Cold working is a process that involves deforming a material at a room temperature. This process results in increased strength, hardness, and resistance to wear and fatigue, but it may also decrease the material’s ductility and toughness. To quantify the degree of cold working, the reduction in cross-sectional area expressed as a percentage is used. In contrast, age hardening utilizes a series of heat treatments to encourage the precipitation of small particles in the material’s microstructure, which hinder dislocation motion, making plastic deformation more difficult. Age hardening enhances the material’s strength and hardness while preserving its ductility and toughness. The effects of cold working and age hardening on mechanical properties are complex and dependent on various factors, including the material type, degree of cold working, temperature range and time of age hardening, and cooling rate after the heat treatment. Both cold working and age hardening can increase yield strength, tensile strength, and hardness, but this comes at the cost of reduced ductility and toughness. The extent of improvement is contingent on specific treatment conditions. Finding the optimal cold working and age hardening conditions for a material depends on the application’s specific requirements and desired balance between strength, hardness, ductility, and toughness. Achieving a careful balance of these properties is critical to ensure that the material can withstand the anticipated loading and environmental conditions without premature failure.

Design methods can greatly aid the engineering design process in developing new products or improving existing ones. Various techniques exist in materials processing to design and optimize processing parameters, including the Taguchi Method (Palani and Murugan, 2008; Tzeng et al., 2009), Response Surface Methodology (RSM) (Choudhury and El-Baradie, 1997; Noordin et al., 2004), Materials Informatics (Risanti et al., 2009; Reilly et al., 2013) and Design of Experiments (DOE) (Montgomery, 1997). The Taguchi method is a statistical approach to design a robust product or process that is insensitive to variation in the input factors, while achieving desired output specifications. This method is widely used in industries such as manufacturing, engineering, and design to improve product quality and reduce costs. Its benefits include improved product reliability, reduced development time, and reduced costs associated with product failures and warranty claims (Yang and Tarng, 1998; Venugopal et al., 2012). Response Surface Methodology (RSM) is a statistical technique used to model and analyze the relationship between a response variable and multiple input variables in order to optimize the response. The method involves building mathematical models of the response surface and then using optimization techniques to identify the optimal input settings that maximize or minimize the response (Choudhury and El-Baradie, 1997). Materials informatics involves using data-driven approaches, such as machine learning algorithms, to predict the properties of materials based on their composition, structure, and processing history. This can be used to design new materials or optimize the processing of existing materials (Tamura et al., 2020). Process modeling involves creating a mathematical model of the processing equipment and conditions, which can be used to optimize the processing parameters to achieve desired outcomes. It can be used to optimize the processing of materials and to predict the behavior of materials under different processing conditions (Risanti et al., 2009; Reilly et al., 2013). Design of Experiments (DOE) is a statistical approach used to systematically vary the processing parameters of a material and measure the resulting properties. It is a powerful method for determining the optimal combination of input factors that can produce the desired output response. By varying the processing parameters and measuring the resulting properties, the optimal combination of parameters can be identified to achieve the desired outcome (Kadaganchi et al., 2015). The same method is presented herein to vary the input parameters of the aluminium alloy 6061. In this study, the effect of cold work, along with aging temperature and time has been taken into consideration to be investigated in knowing the mechanical properties of AA6061 such as maximum yield strength, maximum UTS and minimum required elongation.

Researchers have utilized various design techniques to investigate and improve the mechanical properties of different materials. Tzeng et al. (Tzeng et al., 2009) found that the depth of cut has the largest effect on the overall surface roughness. On the contrary, changes in cutting speed have the largest impact on the highest peak-to-valley height and the roundness of the machined surface. Based on the ANOVA results, they found that the depth of cut is the most significant controlled factor for achieving the desired surface finish and roundness in turning operations. Noordin et al. (2004) studied the performance of a tool made of multilayer tungsten carbide when turning AISI 1045 steel using RSM. The input variables considered in the analysis include cutting speed, feed rate, and the side cutting edge angle (SCEA) of the cutting edge. The response variable of interest was the tangential force and surface roughness. They observed that changes in the feed rate will have the greatest impact on these performance indicators. They found that in the case of surface roughness, both the side cutting edge angle and the interaction of feed and SCEA are significant factors that contribute to the performance indicator. In contrast, for tangential force, it appears that the SCEA, the interaction of feed and SCEA, and the cutting speed are all factors that contribute to the performance indicator.

Kadaganchi et al. (2015) introduced a mathematical model to forecast the yield strength, tensile strength, and ductility of friction stir welds of AA 2014-T6. They focused on the most significant process parameters, including spindle speed, welding speed, tilt angle, and tool pin profile, in the context of friction stir welding of aluminium alloys. They observed that the use of a hexagonal tool pin profile in the fabrication of welds resulted in the highest tensile strength and elongation, indicating that this tool profile produces the strongest and most ductile welds. On the other hand, the welds made with a conical tool pin profile have the lowest tensile strength and elongation, suggesting that this tool profile results in weaker and less ductile welds. Bui et al. (2011) performed experiments to investigate how reducing the cross-sectional area of variable thickness of aluminium tubes affects their microstructure and mechanical properties. Two distinct position-controlled mandrel techniques were employed to draw the tubes, and their mechanical properties were assessed in relation to the cross-sectional reduction. The experiments involved cold drawing tubes with different outer diameters and cross-sectional reductions ranging from 11% to 41%. To determine the mechanical properties at specific locations, specimens were extracted from the tubes parallel to their axes, and tensile tests were performed on them. They have observed, an increase in cross-sectional reduction resulted in higher microhardness, yield strength, and ultimate tensile strength of the deformed samples. However, this was accompanied by a decrease in corresponding elongation. Additionally, the anisotropy in microstructure and mechanical properties became more significant with increasing cross-sectional reduction. It was found that the mechanical properties of the drawn tubes varied depending on the mandrel shapes used and the initial tube outer diameter.

Mirzakhani and Mansourinejad (Mirzakhani and Mansourinejad, 2011) investigated the tensile properties of AA6061 alloy under varying conditions of precipitation hardening and cold working. They found that increasing the aging time and temperature resulted in higher tensile strength, but a lower elongation. Additionally, an increase in reduction in area led to decreased ductility and increased tensile strength for two distinct sample types: those that underwent a single aging process at 180°C for 4 h and those that were solutionized and subsequently cold-rolled. Oritz et al. (2007) studied the strain limits of aluminium alloys 6061, 2024, and 7075 subjected to plastic strain using a tensile testing machine. The strain limit was expressed as the UTS, which varies depending on the temper and the amount of plastic strain applied. They applied heat treatment to improve the mechanical properties of these alloys, particularly their strength and ductility. They observed that forming of aluminium alloys should be done in low-strength, high-ductility tempers to minimize the risk of cracking and increase the formability of the material. They also observed that hardened tempers such as T6 and T8 of aluminium alloys are less ductile and more brittle, which means they have a lower tolerance for plastic deformation. As a result, only small amounts of strain, typically in the range of 2%–3%, should be applied to these tempers before they are at risk of cracking or other forms of failure.

Masounave et al. (1997), observed that the three-way interactions between the variables feed rate, cutting speed, depth of cut, tool nose radius, and tool length have significant effects on the surface roughness. It has been found that the optimal surface roughness can be achieved by utilizing a low feed rate, a large tool nose radius, and a high cutting speed in combination. It has been found that when machining mild carbon steel at certain feed rates, tool nose radius, and cutting speeds, the formation of a built-up edge can negatively impact surface roughness. Liang et al. (2021) studied how the heat from welding affects the properties of an Inconel 625 alloy. They observed that the grains became more rounded, and carbides became more visible. They also found that the metal became weaker when it was exposed to high temperatures. They discovered that when the metal is heated, it changes in ways that make it harder for it to resist being bent or deformed. Zhang et al. (2022a) conducted isothermal compression tests to understand how to control the way grains form in metals. They found that if they heat the metal to a certain temperature and then press it at a certain speed, they can get the grains to be the right size and shape. They studied what happens to the metal at different temperatures and found that if they heat it too much, the grains become too big. They also studied what happens to the metal when it is being pressed and found that two different processes are happening at the same time to control the grain size. One process involves the edges of the grains bulging out, and the other involves the grains rotating. Zhang et al. (2023) conducted experiments to test the corrosion resistance of the AA7A04 when cut in different ways. They treated some samples of the metal at different temperatures and then cut them at high speeds using different cutting techniques. They measured how well the metal resisted corrosion in each case by looking at various factors, such as the size of capacitance arc radius and the amount of corrosion products that formed. They found that certain combinations of cutting speed, depth, and feed rate made the metal more resistant to corrosion. They also noticed that surface scratches made the metal more likely to corrode, while other types of damage didn't have as much of an impact. They identified a chemical called Al(OH)3 insolubles as being the main element that caused the metal to corrode. Finally, they found that the metal treated at a higher temperature was more resistant to corrosion when cut using the same parameters.

Zhang et al. (2022b) used heat to break down Ni-glycolate@RGO complexes, which resulted in the creation of Ni-decorated reduced graphene oxide (Ni-RGO) nanosheets. They discovered that the Ni particles were evenly distributed on both sides of the RGO nanosheets. They also found that when more Ni-RGO was added, the thickness of the interfacial intermetallic compounds (IMCs) decreased, and the grain size in the xNi-RGO/SAC305 composite solders became much smaller. They found that adding small amounts of Ni-RGO nanosheets (0.03 wt%) significantly improved the bonding strength and solderability of the solder joint. Djavanroodi et al. (2012) conducted a study on commercial pure aluminum that underwent up to 8 passes of the Equal Channel Angular Pressing (ECAP) process. They examined how the strain distribution behaved in the ECAPed material by testing four different die channel angles. They used two methods to measure strain homogeneity—inhomogeneity index (Ci) and standard deviation (S.D.). The study revealed that Ci was not the best way to measure uniformity of the strain distribution. The researchers suggested that designing the ECAP die geometry to achieve optimal strain distribution homogeneity is more important than achieving the optimal effective strain magnitude. Ebrahimi et al. (2019) used computer models to investigate how different factors, such as angles, friction, and speed, affect the deformation of aluminum during pressing. They found that the angle of the die channel had the greatest impact on both the strain and the force required, while friction had a smaller effect on strain but still affected the required force. The speed of the press didn't appear to have a significant effect. Based on their findings, the researchers recommend using a die with a steep channel angle and a large corner angle to achieve the desired strain behavior, and minimizing friction to reduce the required force without affecting the strain behavior too much.

Akbarpour et al. (2019) investigated how the microstructure of copper powder was affected by the duration of milling. They observed that longer milling times resulted in smaller grain size and increased lattice strain, leading to greater powder hardness. However, this also caused the powder to have lower density since it didn’t pack together as tightly. Yamada et al. (2000), investigated the two-step aging behavior of Al-Mg-Si alloys. The investigation has involved several methods such as hardness and electrical resistivity measurements, adiabatic calorimetry, and transmission electron microscopy. They observed that the quenching conditions, especially step-quenching and first-aging, have a significant effect on the peak hardness of two-step aged specimens. The impact of different thermal processing parameters on both physical and mechanical properties of 7075 T⁶ aluminium alloy was studied by Clark Jr et al. (2005). This involved varying the solution treatment temperatures, quenching media, and artificial aging conditions. They found a significant relationship between the tensile strength and hardness which suggests that changes in the microstructure that affect the hardness also affect the tensile strength.

Optimizing the properties of aluminium alloys is crucial to enhance their performance in various applications. The mechanical properties, such as yield strength, ultimate tensile strength, and elongation, play a critical role in determining the suitability of aluminium alloys for different purposes. Hence, cold working and age hardening techniques are used to optimize these mechanical properties and improve the overall performance of the alloy. The present study investigates the effects of input factors on the output response variable, including yield, ultimate tensile strength, and elongation. The objective of this research is to establish a correlation between the input parameters of aging temperature, time, and cold work and the output response variables of yield, ultimate tensile strength (UTS), and elongation. The test results are summarized using ANOVA tables. The key finding is that temperature is the most significant effects on yield and UTS but also there is combine effects of input factors on mechanical properties.

Figure 1 shows the conceptual diagram of aluminium tube manufacturing. The production process begins with melting and casting of aluminum alloys in a furnace. The resulting molten metal is then poured into a mold to create ingots and billets. The extrusion process is utilized to form desired shape from the ingots. The required shape formed from extrusion are then subjected to annealing to enhance their workability and decrease internal stresses. During annealing, the metal is heated to a specific temperature and then cooled at a gradual pace, resulting in an increase in the metal’s ductility and toughness.

Once the annealing process is complete on the aluminium alloy undergoes additional processing of cold working using a draw bench. This process enhances the metal strength and the required surface finish and dimension. The final step in aluminium alloy production is quenching and aging. Quenching is the rapid cooling of the alloy to room temperature. The alloy is then aged by heating it to a specific temperature for a certain duration. This process enhances the metal’s strength, toughness, and corrosion resistance. These processes along with the corresponding process parameters values of the input factors, is illustrated in Figure 2. To enhance the properties of AA6061, designed experiments prove to be a powerful technique. The selected process parameters include cold work (10% and 30%). Subsequently, the AA6061 tubes were quenched at 535°C, and age hardening was conducted for 10 and 18 h at temperatures ranging from 160°C to 190°C. Afterward, samples of the alloy were fabricated using an ASTM E8 2004 machine, and tensile testing was performed utilizing an ASTM B557 technique. Finally, the results were subjected to statistical analysis using Design Expert software.

The results from the cold working and aging trials performed as per the experimental plan are shown in Table 6. The “Std Order” column refers to the standard order of the experimental runs. The “Run order” column indicates the sequence of the experimental runs performed. The experimental data for yield strength, UTS, and elongation are presented in the last three columns of the Table 6. The data obtained from the experiments were subsequently analyzed using the Design Expert software (Montgomery, 1997).

This paper reports on an experimental study that investigated the effects of cold work percentage, aging time, and aging temperature on the yield strength, ultimate tensile strength, and percentage elongation of AA 6061. It was revealed that temperature factor is found the most significant factor. The empirical models obtained through DOE and subsequently reduced exhibited a reasonable level of accuracy and can be utilized for prediction within the range of the factors that were investigated. We have found that the preferable temperature ranges from 155 to 172 ℃ , the preferable cold work is 10% or more, and the preferable time is 10 h, but can be extended up to overage time. We noted that all input factors are significant for yield, whereas for UTS, temperature and Cold Work, along with their interaction, are significant. In future work, we can optimize temperature and time using Response Surface Methodology (RSM).