• 반도체디스플레이기술학회지
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• 제16권2호
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• pp.79-84
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• 2017

This paper outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling when machining STS304 with TiAlN coated SKH59 tool under up and down end milling conditions. The end milling parameters evaluated are depth of cut, spindle speed and feed rate. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to analyze the effect of these end milling parameters. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. An orthogonal array of $L_9(33)$ was used. The most important input parameter for cutting force, however, is the feed rate, and depending on the cutter rotation direction. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
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• pp.225-229
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• 2000

Burrs formed during face milling operations are very hard to characterize like other machining burrs because there are many parameters which affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complicated combination effects between the parameters. In this paper, Taguchi method, which is a systematic optimization application of design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization. Optimized experimental conditions are provided to show the effectiveness of this approach.

• 한국정밀공학회지
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• 제18권12호
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• pp.130-136
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• 2001

Burrs formed during face milling operations are very hard to characterize because there are many parameters that affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complex combined effects between the parameters. In this paper, the Taguchi method, which is a systematic optimization application in design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization in face milling. Also, analysis of variance (AVOVA) is employed to study the performance characteristics in more detail. Experimental verifications are provided to show the effectiveness of this approach.

• Journal of Welding and Joining
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• 제35권1호
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• pp.74-78
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• 2017

In auto ancillary fabrication industry, GMAW is a very useful & important welding process and EN10025 S 235 Grade is common material used for manufacturing of two wheeler chassis. This research gives the detail influence of welding process parameters such as welding current, welding voltage, wire speed on the penetration in EN10025 S 235 Grade mild steel material. The experimentation of this research has been carried out by using three factors, three level Taguchi DOE method. To analyze & optimize the welding parameters & characteristics, analysis of variance, L9 orthogonal array & signal to noise ratio are used. Length of Penetration in addition to the depth of penetration is major concern in fillet welded joints, as the penetration decides the strength of the welded joint. After analysis of penetration in all 9 welded samples, optimize parameters readings verified & found probability value within 0.05.From this research it is come to know that welding current & welding voltage is major parameters which affects the penetration in welded joints.

• 대한기계학회논문집A
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• 제32권7호
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• pp.602-609
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• 2008

This paper presents experimental optimization of process parameters for a newly developed SFF(Solid Freeform Fabrication) system. Two critical process parameters, layering thickness and curing period, which have a large effect on the quality of the product, are optimized through experiments. Specimens are produced using layering thicknesses of 60, 80, 100, 120, 140, and $160\;{\mu}m$ and curing periods of 0, 10, 20, and 30 minutes under the same processing conditions, i.e., build-room temperature, feed-room temperature, roller speed, laser power, scan speed, and scan spacing. The specimens are tested to compare and analyze performance indices such as thickness accuracy, flatness, stress-strain characteristics, and porosity. The experimental result indicates that layering thickness of $80{\sim}100\;{\mu}m$ and curing period of $20{\sim}30$ minutes are recommended for the developed industrial SFF system.

• 한국정밀공학회지
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• 제13권3호
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• pp.70-79
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• 1996

In off-line process optimization, process parameters are controlled such that the process is robust against changes in equipment conditions and incoming materials. The off-line methods, however, are not effective when the changes are so large that process parameters need to be adjusted. On-line control can respond to such large changes, but process uniformity has not been controlled on-line due to the difficulties in modeling. This paper is aimed at developing a new on-line control methodology where the uniformity is controlled effectively. The process variability is categorized based on the physical considerations, and the process parameters are classi- fied considering their effects on the categorized process variabilities. On-line control is performed with the properly selected process parameters so that robustness may not be degraded. The developed methodology is applied to the single wafer plasma etching processes, which resulted in both higher within-a-wafer uniformity and compens- ation of the incoming material non-uniformity.

• 품질경영학회지
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• 제45권2호
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• pp.191-207
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• 2017

Purpose: To develop an interactive version of the conventional process capability-based approach, called 'Interactive Process Capability-Based Approach (IPCA)' in multi-response surface optimization to obtain a satisfactory compromise which incorporates a decision maker(DM)'s preference information precisely. Methods: The proposed IPCA consists of 4 steps. Step 1 is to obtain the estimated process capability indices and initialize the parameters. Step 2 is to maximize the overall process capability index. Step 3 is to evaluate the optimization results. If all the responses are satisfactory, the procedure stops with the most preferred compromise solution. Otherwise, it moves to Step 4. Step 4 is to adjust the preference parameters. The adjustment can be made in two modes: relaxation and tightening. The relaxation is to make the importance of one of the satisfactory responses lower, which is implemented by decreasing its weight. The tightening is to make the importance of one of the unsatisfactory responses higher, which is implemented by increasing its weight. Then, the procedure goes back to Step 2. If there is no response to be adjusted, it stops with the unsatisfactory compromise solution. Results: The proposed IPCA was illustrated through a multi-response surface problem, colloidal gas aphrons problem. The illustration shows that it can generate a satisfactory compromise through an interactive procedure which enables the DM to provide his or her preference information conveniently. Conclusion: The proposed IPCA has two major advantages. One is to obtain a satisfactory compromise which is faithful to the DM preference structure. The other is to make the DM's participation in the interactive procedure easier by using the process capability index in judging satisfaction/unsatisfaction. The process capability index is very familiar with quality practitioners as well as indicates the process performance levels numerically.

• Journal of Welding and Joining
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• 제29권6호
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• Korean Journal of Chemical Engineering
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• 제36권3호
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• pp.356-367
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• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• Smart Structures and Systems
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• 제18권3호
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• pp.425-448
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• 2016

In this paper, a new Pigeon Colony Algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution; the flying process is designed to search for the local and global optimum and improve the global worst solution; and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.