Thermal Friction Drilling Process Parametric Optimization for AISI 304 Stainless Steel Using an Integrated Taguchi-Pareto–Grey Wolf-Desirability Function Analysis Optimization Technique

Thermal friction estimations are presently essential on steel for manufacturing applications as they predict the aggregated energy required for the required process. However, the current thermal friction estimates are inaccurate as they exclude the optimized thresholds of both the input and output quantities. In this article, the optimization of the drilling operation process is accounted for by introducing a new method of combined Taguchi-Pareto–grey wolf-desirability function analysis applied on the AISI 304 stainless steel. An objective function was formulated using the delta values developed from the average signal-to-noise into the response table of the Taguchi method. Besides, the ranks of the parameters through the response table are taken in the reciprocal mode to evaluate the values of the linear program formulated according to the objective function and some constraints taken from the system. Six input parameters were considered tool cylindrical region diameter, friction angle, friction contact area ratio, mouthpiece thickness, feed rate and reciprocal speed. The outputs are the axial force, radial force, hole diameter dimensional error, roundness error and bushing length. These inputs and outputs were analyzed for the optimization process. Based on the results, which were solved using the C++ software, the best value converges in iteration 8 with the starting value of 1699.2. Iteration 1 drops to 11016.3 in six iterations (iterations 2 to 7) and finally converges at 11015.9 in iterations 8 through 20. The usefulness of the effort is to help process engineers to execute cost-effective energy conservation decisions in optimization that could be obtained using optimized thermal friction values

Optimization and scale-up of fermentation of glucansucrase and branched glucan by Pediococcus pentosaceus CRAG3 using Taguchi methodology in bioreactor

The present investigation focuses on screening and optimization of media components to enhance glucansucrase and glucan production by Pediococcus pentosaceus CRAG3 at shake-flask and bioreactor level using Taguchi orthogonal array design. A three-level Taguchi orthogonal array layout of L27 (33) was employed, in which six variables were studied for their influence on glucansucrase and glucan production. The results showed that sucrose, K2HPO4 and Tween-80 were the most significant factors to improve glucansucrase production while the glucan production was mostly affected by sucrose, peptone and K2HPO4. The optimized medium composition for maximum glucansucrase and glucan production were: sucrose 3.5% and 5%; yeast extract 0.2% and 2.0%; beef extract 0.5% and 0.5%; peptone 3.0% and 1.0%; K2HPO4 0.2% and 0.2%, and Tween-80 1.0 and 0.1%, respectively. The optimized medium gave 10.1 U/ml and 10.2 U/ml glucansucrase activity while glucan concentrations were 56 mg/ml and 80 mg/ml in shake flask and bioreactor level, respectively which were in good agreement with predicted values (10.1 U/ml and 54.5 mg/ml). The optimized medium gave 2 fold enhancement in enzyme activity and 4 fold increase in glucan concentration as compared to non-optimized medium (4.5 U/ml and 15 mg/ml, respectively) at shake flask level

The Optimization of Packaging System Process Parameters Using Taguchi Method

Packaging systems constitute substantially to product cost, its safety, and optimization. Unfortunately, no previous optimization studies have examined the packaging system in a bottling process plant for the unique, developing country environment. Consequently, the Taguchi method is applied to optimize a process plant's packaging system in a Nigerian plant's real-life situation. Optimal combinations of packaging system parameters that minimize product waste are created. An L4 (23) Taguchi orthogonal array was selected to analyze the data, and signal-to-noise ratios were computed for each experiment's run. Since the aim was to minimize beer waste, the ‘the-smaller-the-better’ signal-to-noise ratio was chosen in the analysis. S/N ratio plots revealed the optimum settings to obtain minimal product waste, namely, A2, B1, and C2 from the main effects plot for signal-to-noise ratios. A two-way ANOVA was performed on the significant factors to determine their percentage contributions to the response (product waste). Through Taguchi's innovative approach, the feasibility of optimizing the packaging process parameters was demonstrated and validated

Multi-Objective Optimization in Machining (Turning) Of Brass

The present study highlights a multi-objective optimization problem by applying both TOPSIS and Utility concepts coupled with Taguchi method through a case study in machining (turning) of pure Brass. The study aimed at evaluating the best process environment which could simultaneously satisfy multiple requirements of quality and productivity. In view of the fact, the traditional Taguchi method cannot solve a multi-objective optimization problem; to overcome this limitation, TOPSIS and Utility concepts have been coupled with Taguchi method. The 2 concepts have been adopted to convert a multi-response optimization problem into a single response optimization problem; in which CC (Closeness Coefficient) and U (Utility Index) respectively serve as the representative single objective function for optimization. The study combined TOPSIS/Utility and Taguchi method for predicting optimal setting. Based on Taguchi’s Signal-to- Noise ratio (S/N), analysis has been made on the CC/U and optimal process environment has been selected finally which corresponds to highest S/N Ratio of the CC/U. Optimal result has been verified through confirmatory test. The case study indicates application feasibility of the aforesaid methodology proposed for multi-response optimization and off-line control of multiple quality and productivity characteristics in Brass machining

Multi-objective optimization of carbon/glass hybrid composites with newly developed resin (NDR) using gray relational analysis

Purpose: It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle, stacking sequence, different resins and thickness of composite laminates has been carried out. The focus of this research work is on the optimization of the design variables like stacking angle, stacking sequence, different resins and thickness of composite laminates which affect the mechanical properties of hybrid composites. For this purpose, the Taguchi technique and the method of gray relational analysis (GRA) are used to identify the optimum combination of design variables. In this case, the effect of the abovementioned design variables, particularly of the newly developed resin (NDR) on mechanical properties of hybrid composites has been investigated. Design/methodology/approach: The Taguchi method is used for design of experiments and with gray relational grade (GRG) approach, the optimization is done. Findings: From the experimental analysis and optimization study, it was seen that the NDR gives excellent bonding strength of fibers resulting in enhanced mechanical properties of hybrid composite laminates. With the GRA method, the initial setting (A3B2C4D2) was having GRG 0.866. It was increased by using a new optimum combination (A2B2C4D1) to 0.878. It means that there is an increment in the grade by 1.366%. Therefore, using the GRA approach of analysis, design variables have been successfully optimized to achieve enhanced mechanical properties of hybrid composite laminates. Originality/value: This is an original research work

Robust Design Methodology for Sustainability

A key principle in Quality Management (QM) is customer focus and much research has aimed at techniques supportive of this principle. One example of a research area within QM focused on developing such techniques is Robust Design Methodology (RDM). Taguchi, an early proponent of robust design defined quality in a way that differs from others, i.e. as loss to the society caused by the product, thus not being restricted to an individual customer. Today, this definition seems to be well in line with the sustainability challenges in all disciplines. Thus, it is time to enhance RDM to again focus on preventing losses to the society and thereby contribute to sustainability. The purpose of this paper is to explore how RDM may support Sustainable Product Development (SPD) and thus propose a research agenda for enhancing quality practices towards sustainability. The house of quality is used as a research instrument; identifying linkages between RDM and SPD. Some examples of the findings include the strong relationship between clean manufacturing and all RDM strategies, and the need to broaden the scope of traditional RDM with respect to material use. Finally, a future research agenda towards RDM for sustainability is proposed

Optimization of multiple performance responses of a fish feed pelletizer machine

This study details the assembling of a prefabricated fish feed pelletizing machine and optimization of some operational parameters such as die thickness, number of die holes, shaft speed and feed rate to produce high-grade fish pellets. The Taguchi methodology and Grey relational analysis (GRA) have been utilized to evaluate the multi-objective functions of interest such as pelletizing efficiency, throughput, energy requirements and pellets bulk density (g/cm3). The pelletizer machine performance evaluation test was carried at 3 levels of die thickness (8, 6 and 12 mm), number of die holes (30, 25, and 35), and feed rates (145, 130 and 160 g/h). The test for the performance indicators was conducted using L9 orthogonal array experimental design. The test data were analyzed using the Taguchi scheme employing the signal-to-noise ratio response with effects deduced. The GRA was utilized to assess multiple responses by fusing the Taguchi technique with the GRA. Thus the multi-objective optimization was transformed to a single equivalent objective function. The results of Taguchi optimization revealed that die thickness was the most influential parameter for the various control factors. In addition, optimum parameter combination was obtainable at medium die thickness (8mm), medium number of die holes (30), low shaft speed (200rpm) and medium feed rate of 145g/h. Analysis of variance for grey relational grade (GRG) reveals that die thickness and feed rate are the dominant parameters. The confirmation test performed shows that the GRG is enhanced by 2.19%

Integration of mahalanobis-taguchi system and activity based costing in decision making for remanufacturing

Classifying components at the end of life (EOL) into remanufacture, repair or dispose is still a major concern to automotive industries. Prior to this study, no specific approach is reported as a guide line to determine critical crankpins that justifying economical remanufacturing process. Traditional cost accounting (TCA) has been used widely by remanufacturing industries but this is not a good measure of estimating the actual manufacturing costs per unit as compared to activity based costing (ABC). However, the application of ABC method in estimating remanufactured cost is rarely reported. These issues were handled separately without a proper integration to make remanufacturing decision which frequently results into uneconomical operating cost and finally the decision becomes less accurate. The aim of this work is to develop a suitable pattern recognition method for classifying crankshaft into three different EOL groups and subsequently evaluates the critical and non-critical crankpins of the used crankshaft using Mahalanobis-Taguchi System (MTS). A remanufacturability assessment technique was developed using Microsoft Excel spreadsheet on pattern recognition and critical crankpins evaluation, and finally integrates these information into a similar spreadsheet with ABC to make decision whether the crankshaft is to be remanufactured, repaired or disposed. The developed scatter diagram was able to recognize group pattern of EOL crankshaft which later was successfully used to determine critical crankpins required for remanufacturing process. The proposed method can serve as a useful approach to the remanufacturing industries for systematically evaluate and decide EOL components for further processing. Case study on six engine models, the result shows that three engines can be securely remanufactured at above 40% profit margin while another two engines are still viable to remanufacture but with less profit margin. In contrast, only two engines can be securely remanufactured due overcharge when using TCA. This inaccuracy affects significantly the overall remanufacturing activities and revenue of the industry. In conclusion, the proposed integration on pattern recognition, parameter evaluation and costing assists the decision making process to effectively remanufacture EOL automotive components as confirmed by Head of workshop of Motor Teknologi Industri Sdn. Bhd

Continuous improvement: A bibliography with indexes, 1989-1991

This bibliography contains 198 annotated references to reports and journal articles entered into the NASA Scientific and Technical Information Data base during 1989 to 1991