Taguchi Optimization Technique Research Articles

Optimizing machining efficiency: a comprehensive study on PVD cathodic arc evaporation coated turning tool inserts with TiAlN/AlCrN multilayer coatings

Abstract The effectiveness of turning processes in manufacturing depends on the efficiency of cutting tool inserts. Coating these inserts is one common method that has been used to prolong their life span, reduce friction and increase wear resistance. The main purpose of the present study was to enhance the efficiency of turning tool inserts by exploring different combinations of coating substances such as TiAlN, AlCrN, and TiAlN/AlCrN. Cutting speed, feed rate, cutting depth and type of coating material were important input parameters for optimization. It was observed that tools with coatings like TiAIN and AlCrN had higher performance than those with single-layered ones. The use of multilayer coated inserts comprising TiAlN/AlCrN increased the hardness but reduced the wear thereby enhancing machining effectiveness. For Taguchi Grey Relation Analysis (GRA) optimization technique with L27 array for hardness and flank wear output parameters aimed at enhancement of input process parameters in turning operations. The coatings’ crystalline structure, phase composition and other crucial details for their performance were analyzed using Energy Dispersive (EDS) Spectroscopy and Scanning Electron (SEM) Microscopy techniques. The TiAlN/AlCrN coatings showed greater machinability than those with only TiAlN or AlCrN, even at high spindle speeds. The best processes were identified using the Taguchi and Grey relational optimization techniques. Some of these parameters include a speed of 600 m/min, a feed rate of 0.10 mm/rev, a depth of 1.5 mm, and a TiAlN/AlCrN coating. This meant that the hardness was at 3772 HV while flank wear is 6.45 mm for optimum parameters among others obtained from experiments. Various relationships can be displayed using contour plots which are usually visual representation between several factors in an experiment such as hardness and wear resistance which is shown by multilayer coating compared to single-layer coatings.

Application of Machine Learning and Grey Taguchi Technique for the Development and Optimization of a Natural Fiber Hybrid Reinforced Polymer Composite For Aircraft Body Manufacture

Abstract The rapid expansion of the air transport industry raises significant sustainability concerns due to its substantial carbon emissions and contribution to global climate change. These emissions are closely linked to fuel consumption, which in turn is influenced by the weight of materials used in aircraft systems. This study extensively applied machine learning tools for the optimization of natural fiber-reinforced composite material production parameters for aircraft body application. The Taguchi optimization technique was used to study the effect of sisal fibers, glass fibers, fiber length, and NaOH treatment concentration on the performance of the materials. Multi-objective optimization methods like the grey relational system and genetic algorithm (using the MATLAB programming interface) were employed to obtain the best combination of the studied factors for low fuel consumption (low carbon emission) and high-reliability structural applications of aircraft. The models developed from regressional analysis had high accuracy of prediction, with R-Square values all > 80%. Optimization of the grey relational model of the developed composite using the genetic algorithm showed the best process parameter to achieve low weight material for aircraft application to be 40% sisal, 5% glass fiber at 35mm fiber length, and 5% NaOH concentration with grey relational analysis at the highest possible level, which is unity.

Optimization of FDM printing parameters for square lattice structures: Improving mechanical characteristics

Integrating lattice structures into the design of products manufactured using Fused Deposition Modeling (FDM) can enhance the weight and strength ratio of printed models. In this research, the square lattice structure widely employed planar lattice structure is implemented, and Polylactic Acid (PLA) filament is utilized as the feedstock material for FDM printing due to its favorable properties, including biocompatibility, biodegradability, controlled degradation, sterilization, and mechanical characteristics. The Taguchi optimization technique is utilized to optimize the printing parameters for the square lattice structure. Design of experiment is developed based on the factors that have the most significant impact on the 3D printed product, which they determine through a literature survey of similar work. L9 orthogonal array is utilized from the design of experiments, with the requirement of three factors and three levels each: layer height (0.1, 0.2, and 0.3 mm), printing temperature (190, 200, and 210 °C), and printing speed (50, 75, and 100 mm/s). This research aims to optimize FDM printing parameters for the square lattice structure, focusing on enhancing the weight and strength ratio of printed samples with the help of S/N ratio and ANOVA. The optimal combination of design factors includes a smaller layer height of 0.1 mm, a printing temperature of 190 °C, and a printing speed of 100 mm/s shows improvement of 25.4 % of tensile strength. The research improves productivity and material utilization and holds relevance in automobile and medical applications. The advancements achieved through this research can benefit industries that require exceptionally lightweight and durable products.

Underwater friction stir welding of ultrafine-grained laminated composites produced through accumulative roll bonding process

In this work, ultrafine-grained (UFG) plates of AA2024/AA5083 laminated composite with alternating layers of heat-treatable aluminum AA2024 and strain-hardening aluminum AA5083 were fabricated through accumulative roll bonding (ARB) technique and were subsequently joined using underwater friction stir welding (UFSW). Friction stir welding (FSW) is a solid-state welding method which is suitable for the joining of similar and dissimilar UFG alloys of AA2024 and AA5083, which are mainly used in aerospace and aviation industries. Welding variables, such as pin profile, rotational speed, welding speed, and tilt angle were optimized using the Taguchi optimization technique. Different zones of UFSWed joints including stir zone (SZ), thermo-mechanically affected zone (TMAZ), and heat affected zone (HAZ) were investigated through OM, TEM, and SEM. The results showed that the tapered cylindrical pin, 1000 rpm rotational speed, 110 mm.min−1 welding speed, and 2.5° tilt angle were the optimal welding variables in terms of tensile strength. The microstructural results showed the formation of nano-size, recrystallized equiaxed grains with a size of 500 nm (the same size as that in the UFG base metal) in the optimal sample. The hardness in the weldment of the optimal UFSW sample decreased slightly, so that the efficiency of 85% was presented and the minimum hardness location (MHL) disappeared. The ultimate tensile strength (UTS) of 425 MPa and 64% efficiency were observed in the optimal conditions. Due to the presence of very fine grains and large dislocations, and the uniform distribution of precipitates in the underwater state, high strength and elongation were obtained.

Experimental investigation and optimization of process parameters on digital light processing (DLP) 3D printing process based on Taguchi-grey relational analysis

Additive manufacturing technology, specifically Digital Light Processing (DLP), offers a unique approach to fabricating intricate objects without the need for traditional molds or machining. The technique described entails the incremental construction of layers through the curing process polymer, facilitated by a projection light source. Digital Light Processing 3D printing is particularly suited for creating complex structures with small cross-sections, requiring high surface polish and durability. In this study, DLP-printed test coupons were produced using an Ultraviolet-sensitive resin, and the investigation focused on examining the impact of surface quality and toughness, adhering to guidelines outlined by the ASTM specifications. To optimize the DLP printing process, Taguchi and Grey relational optimization techniques were employed to find the best values for multiple factors. The parameters considered in this study were speed, layer thickness, orientation, and pattern type. By employing these techniques, the optimal parameters were identified as follows: The printing process is conducted at a speed of 3 mm per second, with each layer being 0.05 mm thick and the orientation of the printed object is set at 90 degrees, and the pattern employed is of the square type. Experimental results revealed that utilizing these parameters yielded a surface roughness of 2.58 µm and an impact strength of 9.1J. The results showed that the Grey relational grade improved from 0.6244 to 0.7974, with a deviation of 0.173 and 27.71%, indicating a significant enhancement in the optimization process. Additionally, contour plots depicting the relationships between speed and orientation, speed and layer thickness, and orientation and layer thickness were generated for surface roughness, impact strength, and the Grey relational grade. This research offers valuable insights into optimizing DLP 3D printing processes to achieve enhanced surface quality, toughness, and material efficiency while reducing costs and production time.

Experimental Analysis Using Taguchi Optimization Technique on Wear Properties of AL-356 Alloy MMC Reinforced with SiC

Experimental Analysis Using Taguchi Optimization Technique on Wear Properties of AL-356 Alloy MMC Reinforced with SiC

Taguchi Parametric Optimization of Mild Steel Weld-Strength in Arc Welding Process

Abstract—In the welding process, the major factors whose selection contributes to the welded product as they all affect the strength and quality of the weld strength to a larger extent are hardness, electrode diameter and weld design (edge preparation). The purpose of this thesis is to efficiently determine the optimum welding operation parameters for achieving the highest breaking strength in the range of parameters. In order to meet the purpose in terms of both efficiency and effectiveness, this study will utilize the Taguchi parameter design methodology. The study includes selection of parameters, utilizing an orthogonal array, conducting experimental runs, data analysis, determining the optimum combination, verification experimentally finally the Modelling of input parameters (Hardness, Diameter of Electrode & Weld Design) and output parameter (Breaking Strength) is done using Taguchi optimization technique. Key words: Welding Parameters, Electric Arc Welding, Taguchi Method, welding design, hardness.

Taguchi’s optimization technique for water deflouridation through electrocoagulation

Excess fluoride in drinking water is posing serious health concern to humankind. Electrocoagulation is an emerging technique for water defluoridation, and recent research is focused on the optimization of process variables for achieving maximum fluoride removal. As such, the Taguchi optimization technique is adopted to arrive at optimum values process parameters which can provide maximum fluoride removal with more accuracy and fewer experimental runs. In the present research a laboratory-scale batch EC reactor with four aluminum electrodes (98% pure) connected to a DC supply for a wide range of fluoride concentrations which were not studied in earlier researches. Taguchi’s L 16 orthogonal array was applied for optimization of the process variable It revealed maximum efficiency of 86.67% for defluoridation at optimum conditions of process variables with pH: 6 ± 0.1, initial adsorbate concentration: 5 mg/L, EC time: 45 min, voltage: 25 V, and IED: 2 cm. The percentage contribution of process variables was obtained by ANOVA in descending order as initial adsorbate concentration (45.31%) > pH (33.83%) > voltage (13.68%) > EC time (4.2%) > IED (2.98%). Freundlich isotherm and second-order kinetic models were found to be the best suitable for water defluoridation using the EC process. FTIR and XRD analysis for EC sludge also confirmed the fluoride sorption onto A l ( O H ) 3 flocs. The electrode consumption of 0.263 kg/ m 3 , and total operational cost of USD 0.6004/ m 3 were estimated for water defluoridation using the EC process.

An Evaluation of Mechanical Properties of Nano GGBFS in Concrete with Statistical Validation

Concrete, the most extensively utilized construction material, maintains its high demand owing to the swift urbanization and population expansion worldwide. However, cement manufacturing consumes considerable energy and emits substantial CO2 into the atmosphere. To ensure the construction industry’s sustainability, it is imperative to use eco-friendly and cost-effective products. As an additional cementitious ingredient in concrete, nano-based GGBFS (NGGBFS) is therefore employed to provide sustainable environmental impacts. The main purpose of this study is to assess the compressive strength, tensile strength, and Young’s modulus of NGGBFS, considering various replacement percentages (2%, 4%, 6%, 8%, 10%, and 12%) compared to conventional cement. The maximum compressive strength (72.68 MPa) and tensile strength (6.12 MPa) were obtained at 365 days for GB4 concrete. The Taguchi optimisation technique was employed to determine the interaction between mineral admixture and curing days on the mechanical properties of concrete; it reveals that GB4 mineral admixture and 365 days of curing days have good interaction between the factors taken for the study. The ANOVA quadratic regression model provided the optimisation process response. According to principal component analysis, the compression strength and Young’s modulus significantly influence the components because their loadings are so close (0.722 and 0.68). As a result, optimal combinations with equivalent strengths can be successfully created by substituting 8% nano-based GGBFS (GB4) in cement, offering an alternative path toward sustainable development.

Bio-sorptive remediation of crude oil polluted sea water using plantain (Musa parasidiaca) leaves as bio-based sorbent: Parametric optimization by Taguchi technique, equilibrium isotherm and kinetic modelling studies

This study investigated the potential of employing plantain leaves as a natural bio-based sorbent for crude oil spill polluted seawater remediation. Type L9(34) Taguchi orthogonal array technique was used to evaluate the effect of four independent bio-sorption factors at three different levels (crude oil initial concentration (X1 7.8, 11.5 and 15.6 g/L), seawater-crude oil temperature (X2 25, 35 and 45 °C), bio-sorbent dosage (X3 1, 2 and 3 g) and bio-sorbent particle size (X4 1.18, 2.36 and 4.72 mm) on two response indices (bio-sorption efficiency (%) and bio-sorption capacity (g/g)). Taguchi optimization technique, numerical-desirability index function optimization technique and a proposed optimization method were utilized to determine the optimum bio-sorption factors needed for the optimum bio-sorption efficiency and bio-sorption capacity. The results demonstrated that the crude oil bio-sorption efficiency of the plantain leaves was significantly influenced by X1, X3 and X4 and the bio-sorption capacity was mainly influenced by X1 and X3. The optimum bio-sorption efficiency and the optimum bio-sorption capacity were 99.05 % and 12.82 g/g, respectively, obtained at optimum combination of factors and levels of X11 (7.8 g/L), X33 (3 g) and X41 (1.18 mm) for bio-sorption efficiency and X13 (15.6 g/L) X31 (1 g) for bio-sorption capacity. The Freundlich and Dubinin-Rudeshkevich isotherm models best explain the equilibrium bio-sorption data, while the pseudo-second order kinetic model best describes the bio-sorption kinetics. The bio-sorptive remediation mechanism followed dual mechanism of physical and chemical bio-sorption and the mass transfer controlled by film diffusion. The maximum bio-sorption capacity (Kf) was 14.0 gg-1.

Energy and exergy analysis of gasification of solid fuels by optimization of chemical kinetics

A three-zone kinetic model is developed for thermodynamic analysis of the gasification of two solid fuels, rubber wood and refused devised fuel (RDF), by optimizing the chemical kinetics for five reduction zone reactions. With the help of the kinetic model, syngas composition and temperatures are determined for pyrolysis, oxidation, and reduction reactions. The chemical kinetics for reduction zone reactions are considered as control variables in the Taguchi optimization technique with the objective functions of maximum calorific value and maximum exergy efficiency. Optimization results obtained for refused derived fuel (RDF) indicate that the methanation reaction has the most influence, with a 65 % contribution on calorific value and a 71 % contribution for maximizing exergy efficiency. However, for rubber wood, the Boudouard reaction was found to have the most influence on calorific value with a 49 % contribution, while the water-gas reaction had the most influence on exergy efficiency with a 46 % contribution. Based on the findings from Taguchi optimization on the influential chemical kinetics coefficients, further analysis is carried out on the relevant equilibrium constants for both materials. The research outcome of the study is helpful for understanding the relative influence of biomass composition and reaction conditions on the chemical kinetics of gasification for maximizing energy output from the process.

3D biomimetic scaffold’s dimensional accuracy: a crucial geometrical response for bone tissue engineering

Abstract Additive manufacturing has emerged as a trending methodology for producing different simple to complex geometries in minimum lead time, which in turn gives better quality attributes when compared to conventional manufacturing procedures. Fabrication of polylactic acid-based porous scaffold prototypes by 3-dimensional printing has been extensively performed successfully by many researchers. The dimensional accuracy of the 3-dimensional printed part is a very crucial aspect of bone tissue engineering. Dimensional precision of 3-dimensional biomimetic scaffolds has been a response characteristic somehow less focused on by researchers, though it is essential as it acts as a stereotype for defect recuperation while consequently developing extracellular matrix and bone regeneration. The present paper fosters re-tuning the process parameters of a fused deposition modeling based 3-dimensional printer while considering the dimensional precision as a response parameter by the Taguchi optimization technique using a full factorial design L27 orthogonal array set of design of experiments. The crystallinity of the polylactic acid filament material was assessed using differential scanning calorimetry and X-ray diffraction. The thermal breakdown of filament material was investigated utilizing a thermogravimetric analyzer. According to Taguchi’s signal-to-noise ratios, the optimum values were 0.14 mm of layer thickness, 20 mm s−1 of printing speed, and 80 % of infill percentage. In order to justify the results, response surface methodology was employed. R-square values for Taguchi and the response surface models were 88.61 % and 68.71 %, respectively.

Topological design factor optimization in the development of periodic‐type honeycomb lattice structure on the carbon fiber reinforced polyethylene terephthalate glycol composite

AbstractIn most of the automobile and aerospace materials, cellular structures are extensively used due to their lightweight and high energy absorption capabilities. Naturally available animal bones and plant stems are light in weight due to their natural cellular structures. This may inspire various researchers for integrating the various lattice structures such as beam, planar, triply periodic minimal surfaces, and voronoi structures on the various structural materials. The development of lattice structures using 3D printing technology has opened up major attention towards fabricating lightweight components without any complications. In this study, the detailed crashworthiness responses such as compressive strength was optimized in terms of varying the topology‐related factors on the carbon fiber reinforced polyethylene terephthalate glycol (CF/PETG) composite. The experimentation was conducted concerning variable topology factors such as shell thickness, unit cell type, wall thickness (WT), unit cell orientation (UCO), skewing angle, and unit cell size. The model was examined and optimized by means of the Taguchi optimization technique. The crashworthiness response was analyzed using the compression test and moreover, this experimental response is used for the optimization processes. From the observation, the topology factors which contributed more for the higher compressive strength will be UCO of 65.47% and WT of 15.20%. Results of the regression study show that the R square value with concern to the compressive strength will be 92.74%. The optimized design parametric condition for CF/PETG composite established a higher compressive strength of 41.179 MPa, From the overall results, it is clear that the variation in the topology factors has developed a huge and favorable impact on the mechanical characteristics of the lattice‐structured CF/PETG polymer composite.Highlights Hexagonal Lattice structure incorporation on the carbon fiber reinforced PETG composite. Design optimization on the compressive properties. Taguchi optimization is performed on design‐based lattice structures. Unit cell orientation has higher percentage contribution on compressive strength.

Experimental investigation and Taguchi optimization of FDM process parameters for the enhancement of tensile properties of Bi-layered printed PLA-ABS

Additive manufacturing (AM) technology has gained significant popularity, among which Fused Deposition Modeling (FDM) has emerged as the predominant technique for 3D printing. FDM offers the unique ability to achieve the desired and tailored engineering properties required for specific applications. This experimental study investigates the influence of varying FDM process parameters on the mechanical properties and highlights the optimal set of parameters for better tensile strength for a bi-layered composite of PLA-ABS (polylactic acid and acrylonitrile butadiene styrene). Also, it investigates the most-to-least influential printing parameters. Four process parameters were played out i.e., Infill density (50%, 75%, and 100%), number of layers (20,25 and 30), printing speed (20 mm sec−1, 40 mm sec−1, and 60 mm sec−1), and bed temperature (90 °C, 95 °C, and 100 °C), while keeping other parameters constant. Taguchi optimization technique was used for optimization and experiments were designed according to Taguchi orthogonal array L9 (3 4). After printing, the samples were evaluated for tensile properties and the results were analyzed. It is found that the infill density is the most influential parameter while bed temperature is the least influential. Infill density of 75%, 30 layers per part, a printing speed of 20 mm sec−1, and a bed temperature of 100 °C are the optimal set of parameters for better tensile strength. Alongside, percent elongation, printing time, and strength-to-weight ratio were also analyzed and correlated.

Analyzing the Tribological Behavior of Titanium Dioxide (TiO2) Particulate Filled Jute Fiber Reinforced Interpenetrating Polymer Network (IPNs) Composite by using Taguchi Optimization Technique

Analyzing the Tribological Behavior of Titanium Dioxide (TiO2) Particulate Filled Jute Fiber Reinforced Interpenetrating Polymer Network (IPNs) Composite by using Taguchi Optimization Technique

Appraisal on mechanical, durability and ecological performance of sustainable cementitious mortar by using Taguchi optimization technique

This research investigated the performance of ternary blended cement mortars containing recycle brick powder, ground granulated blast furnace slag and nano-silica experimentally and statistically. The Taguchi method was employed to create a design of experiment with L16 Taguchi array for blended mixes. Analysis of the experimental results was evaluated by analysis of variance and used to determine the statistical effect of parameters. In the construction industry, the major portion of demolition contains brick waste that requires a huge area for disposal and also causes environmental pollution. In this study, various blended mortar samples with different levels of recycled brick clay (0%, 5%, 10% and 15%), ground granulated blast furnace slag (0%, 20%, 40%, 60%) and nano silica (0%, 2%, 4% and 6%) were produced and their compressive strength, ultrasonic pulse velocity, dynamic young modulus, water absorption and permeable pores were determined. Recorded parameters revealed that mixtures blended with 10% RBP, 20% GGBFS and 6% NS (MR10G20NS6) give maximum compressive strength; whereas, mixtures blended with 15% RBP, 60% GGBFS and 0% NS (MR15G60NS0) exhibit minimum embodied energy, carbon emission and cost involved in production. Based on the findings, it is recommended that the Taguchi optimization analysis approach could be employed efficiently in such research.

Taguchi optimized sliding wear behavior and hardness of novelGrewia optiva/Basalt fiber reinforced hybrid polyester composites

AbstractThis research paper investigated the hardness and tribological performance of novelGrewia optiva/Basalt fiber reinforced hybrid polymer composites. Two different configuration of hybrid composite that is, woven and chopped fiber reinforced composite are considered for the study. The chopped fiber configuration of the composite is further divided into two types based on fiber length and wt%. The fiber lengths studied are 6 and 12 mm while the wt% studied are 0, 6, and 12 wt%. Woven fiber reinforced composite is divided into five configurations based on wt% ofG. optivafiber with 0, 3, 6, 9, and 12 wt%. In all configurations, maximum fiber content of 12 wt% is maintained. B6/GO6 composite exhibits minimum specific wear rate and maximum hardness among all the compositions. Wear experimental results are analyzed by Taguchi optimization technique and based on the five levels and four control factors (sliding velocity, fiber loading, sliding distance, and normal load) L25partial orthogonal array was suggested for the woven fiber reinforced composites. Fiber content is the main control parameter for hardness testing and L9orthogonal array was suggested according to four control factors and three levels.

Optimizing the shoulder diameter for double side friction stir welding of medium-thick TC4/AA2024 dissimilar alloys by Taguchi optimization technique

Optimizing the shoulder diameter for double side friction stir welding of medium-thick TC4/AA2024 dissimilar alloys by Taguchi optimization technique

Production and optimization of the refractory properties of blended Nigerian clay for high-temperature application; a non-stochastic optimization approach

High-performance materials, systems, and processes have necessitated the exploration of very high-temperature environments. Materials, particularly ceramics, which can withstand these high temperatures, have been extensively studied, even though enough emphasis has not been given to clays sourced locally in Nigeria, where there is an abundance. Also, stochastic optimization techniques has been employed to improve on system or carry out experimentation with minimal spend of resources and very high accuracy. This work extensively explored the refractory properties of blends developed from locally sourced clays (Mayo Ndaga and kachalla Sembe and Kona). The Taguchi optimization technique was employed to determine the effect of various quantities of the clays on the loss on ignition (LOI), refractoriness (RF), and firing shrinkage (FS) of the blends. It was discovered that the optimum (lowest) LOI, highest RF, and lowest FS were 11%, 1333 °C, and 0.48%, respectively. Analysis of variance also proved the significance of Mayo Ndaga on the RF and FS of the blends, with P-values of 0.038 and 0.000 at a 95% confidence level.

Enhancing manufacturing excellence with Lean Six Sigma and zero defects based on Industry 4.0

Improving quality, enhancing productivity, redesigning machining tools, eliminating waste in production, and shortening lead time are all objectives aimed at improving customer satisfaction and increasing profitability for manufacturing companies. This study combines lean manufacturing and six sigma techniques to form a technique called Lean Six Sigma (LSS) by using the DMAIC (Define-Measure-Analysis-Improve-Control) model. This study proposes to use statistical test models to analyze real data collected directly from the operator. The study proposes to use the Taguchi optimization technique to determine the optimal conditions for oil dipping tanks of molybdenum materials. In addition, the study also proposes a computer vision technique to recognize objects using color recognition techniques running on the LABVIEW software platform. This study builds a digital numerical control (DNC) model operating on digital signal processing techniques, linking the data of each process together. The results reduced the rate of defective parts in the whole processing stage from 6.5 % to zero defects, the whole processing line production capacity increased by 7.9 %, and the profit of the whole production line was USD 35762 per year. As a valuable external outcome, the conclusion of the LSS project fostered a spirit of continuous improvement. The utilization of research results from the research environment in the actual production setting is significantly enhanced for the operator. The LSS model is deployed with specific tasks and targets for each member of the LSS project team, and the processing conditions for each specific stage are optimized, such as the oil dipping process and hole grinding process. Industry 4.0 techniques, including computer vision, digital numerical control, and commercial software such as LabVIEW and MINITAB, are optimized for use, simplifying machining operations. Some proposed directions for future research are also presented in detail. For example, studying the improvement of the quality of the 220 V power supply through harmonic mitigation in processing factories is an intriguing area of investigation. Additionally, exploring data security for big data in the context of Industry 4.0 would be a valuable study to enhance customer satisfaction with big data technology in the future.