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The light guide plate (LGP) is a very important component of the backlight module; however, the electroforming process parameters for making LGP molding stampers are often based on accumulated experience and trial and error, which does not ensure that the set parameters are the best factor level combination and often results in increased manufacturing costs and product defect rates. In this article, eight factors, including boric acid concentration, pH value, temperature, current density, consistency of nickel ion, cathode size, anode size, and stirring speed, were selected by cause-and-effect analysis. Next, the Taguchi method was used to obtain the optimal process parameters in the electroforming process by the minimum number of experiments of the L18 orthogonal array. Finally, through actual process verification, in addition to meeting the target value of the nickel layer thickness of the LGP molding stampers, while improving the surface roughness, dot uniformity, and stress, the accuracy and process robustness are obtained. [ABSTRACT FROM AUTHOR]

Due to the upgrading of industrial technology and the maturity of electronic technology, product development technology, incorporating complex designs, has become highly sophisticated. Computer-aided engineering (CAE) has become a key procedure of high-tech industry. In this paper, CAE was used to simulate heat flow with CAE simulation software on the heat removal of a central processing unit (CPU) of a notebook computer component. A regression model was then obtained by using response surface methodology with the Box–Behnken design experimental matrix and by using different levels of experimental combinations. In addition, the optimal value of mean time between failures (MTBFs) was obtained by using the system response at unit cost as the response value. Finally, optimal settings were found to maximize the MTBF of a CPU. [ABSTRACT FROM AUTHOR]

The purpose of this study is to conduct a concurrent product and process parameters determination for further cost reduction and quality enhancement. The process design-related parameters, such as process mean, process tolerance and product design-related parameters, such as product tolerance, are considered simultaneously in the proposed approach. To reflect the response from these three key controllable characteristics: process mean, process tolerance and product tolerance, the key measurement score, which is the sum of the mean cost, tolerance cost, quality loss and failure cost, is used to evaluate the present model. Two examples are provided for demonstrating the application of single and multiple quality characteristics. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to concurrently perform a product and process design for quality and cost consideration. Conventionally, product design and process plan are completed in separate stages. However, there is an opportunity for further cost reduction and quality enhancement if product specification limits are narrowed to make them equal to the process specification limits. Then, this common limit becomes a combined decision variable in the concurrent product and process design. In addition, when the process deteriorates, to create a concurrent process and product design, it is still necessary to consider both process compensation and periodic resetting to alleviate the negative impact caused by process deterioration as much as necessary. Thus, the decision variables will include initial values (process means), process tolerances, combined limits, and the resetting cycle. The measurement score for evaluating these decision variables is the total cost: that is, the sum of mean cost, tolerance cost, quality loss, inspection cost, and failure cost. Because the nature of the above cost items, the model is much appropriate for off-line application, that makes concurrent product and process design become possible before process actualization. An example is presented to demonstrate the proposed approach. [Copyright &y& Elsevier]

The article presents a study which employed mathematical programming to create a model for operating room scheduling in hospitals through the use of optimization software. It claims that the scheduling model meets patient demands, lessen turnover rate, and allows for the effective utilization of the operating room. The study was conducted in Taiwan.

This paper introduces a mathematical model of tolerance chart balancing for machining process planning under complete inspection. The criteria considered in this study are based on the combined effects of manufacturing cost and quality loss, under constraints such as process capability limits, product design specifications, and product quality requirements. Manufacturing costs include the machining cost, part cost, inspection cost, reworking cost, and replacement cost. The machining cost is expressed in geometrical decreasing functions, which represent tolerances to be assigned. Process variability is expressed in quadratic loss functions, which represent the deviation between the part measurement and the target value. An example is presented to demonstrate the proposed model. A comparison made with previous methods shows that the proposed model minimizes the total cost of manufacturing activities and quality-related issues in machining process planning, particularly in the early stages. Moreover, the applications are not be limited to machining process planning but can also be used in other forms of production planning. [ABSTRACT FROM AUTHOR]

Abstract: This study intends to determine the optimal cutting parameters required to minimize the cutting time while maintaining an acceptable quality level. Usually, the equation for predicting cutting time is unknown during the early stages of cutting operations. This equation can be determined by studying the output cutting times vs. input cutting parameters through CATIA software, with assistance from the statistical method, response surface methodology (RSM). Then, the equation is formulated as an objective function in the form of mathematical programming (MP) to determine the optimal cutting parameters so that the cutting time is minimized. The formulation in MP also includes the constraints of feasible ranges for process capability consideration and surface roughness for quality concerns. The important ranking obtained from the statistical method in cooperation with the optimal solutions found from MP can also be used as references for the possibility of robust design improvements. [ABSTRACT FROM AUTHOR]

Conventional process capability indices, such as Cp, Cpk, and Cpm, have been used widely and successfully in most of today’s manufacturing sectors. These process capability indices, however, can only measure the process consequence resulting from various combinations of process mean and process variance on site by measuring the output without concern as to cost. Hence, the focus of this research was to develop a new process capability index, Cpmc, which not only considered the impact from process mean and process variance, as is conventionally done, but also considered the relevant quality and production costs incurred in a product’s life cycle. With these added aspects, the new process capability index, Cpmc, is considered as a response value which needs to be optimized to ensure that both an economical and a quality design can be achieved. The design constraints are the restrictions resulting from the process capability limits, the feasible process range, and the functionality requirements. An example of product assembly is introduced to demonstrate the applicability of the presented approach so that the optimal mean and tolerance values can be determined and so that the Cpmc value is maximized. By using the presented Cpmc, a high-quality but low-cost process design can be achieved during the early stages of product design and process planning. [ABSTRACT FROM AUTHOR]

Abstract: As quality values failed to meet customers’ requirements when the hot-bar soldering process (HBSP) was first introduced in the electronic manufacturing service (EMS) company, it is the intention of this study to combine quality function deployment (QFD) and the Taguchi method to analyze the produced quality characteristics and to optimize the process parameters. The product from HBSP is a gate board that transmits vertical signals in thin film transistor liquid crystal display (TFT-LCD) modules. To produce a gate board through HBSP, a film of flexible printed circuit (FPC) is soldered onto the pad of a printed circuit board (PCB) with the hot-bar (HB) which is heated by a pulse heater. When performing a problem analysis, the strength of the solder joints is considered a response value of quality characteristics for the process of HBSP. The critical factors are then identified via the Taguchi method. The results of this study will indicate whether or not the quality of the gate board can be improved significantly and thereby satisfy customers’ requirements. [Copyright &y& Elsevier]

In the past, the process capability index (PCI) was the only one used in on-line quality management; there were no researches on off-line applications, such as product design or process planning. In using conventional PCI for off-line application, designers normally established the process mean close to the design target, and minimized the process variance so that the PCI value would be maximized. The process variance is determined by the process tolerance, which affects the production cost. This factor must be considered because cost will increase as process tolerance is minimized. Simply averting small tolerance for the sake of cost reduction is not always a rational choice, because a great tolerance value generally results in poor quality. Hence, the conventional PCI value does not truly represent the measurement score for off-line applications during product design or process planning. In this regard, the off-line PCI expression is developed with consideration of the balance between product quality and production cost. The product quality is represented by quality loss function, and production cost is expressed by tolerance cost function. These two functions are simultaneously related to process mean and process tolerance. Thus, the new PCI expression can be used to determine appropriate process mean and process tolerance, as well as a measurement score for comparison and selection among candidates. Consequently, an economical and quality of product design and process planning can be achieved during off-line applications. [ABSTRACT FROM AUTHOR]

A hybrid neural network and selective allowance approach is proposed in this study for internal due date assignment in a wafer fabrication plant (wafer fab). In the first part, a look-ahead self-organization map-fuzzy back propagation network (SOM-FBPN) is constructed to estimate the completion time of a job. Subsequently, a selective allowance policy is established to determine the allowance that will be added to the estimated job completion time. Compared with traditional approaches, the look-ahead SOM-FBPN has many features (including incorporating the future release plan, classifying jobs, and incorporating expert opinions), and the selective allowance policy is novel by considering two different production control issues to avoid missing the due date. According to experimental results, the prediction accuracy of the look-ahead SOM-FBPN was significantly better than those of many existing approaches. Besides, the selective allowance policy considerably improved the due date related performance after adding some extra allowance. [ABSTRACT FROM AUTHOR]

Conventional process planning of manufacturing operations presets fixed process means and process tolerances for all operations and allows outputs to be distributed around these fixed values, as long as the final outputs meet acceptable specifications. Most of these approaches consider process means and process tolerances to be independent decision variables in process planning with the resultant process means equal or close to the design targets of the blueprint dimensions. Furthermore, these approaches assume that process variability is small in comparison to the quality requirement, and that the phenomena of process shifting or deterioration are not factors of manufacturing operations. For these reasons, conventional approaches to process planning are inappropriate for high value, and precision manufacturing process, particularly of a complex part. Hence, this study introduces a process optimization model which considers process means and process tolerances simultaneously, with sequential operation adjustment to reduce process variability, and with part compensation to offset process shifting. [ABSTRACT FROM AUTHOR]

Process design involves process mean and process tolerance determination. Process mean determination is finding the best settings for product quality, without affecting manufacturing cost. However, process tolerance determination is a manufacturing process selection which generally affects manufacturing cost and product quality. In this study, asymmetric quality loss is considered in measuring product quality, and tolerance cost is adopted in representing manufacturing cost. To reflect the combined effect of process mean and process tolerance completely, failure cost is added to the category of manufacturing cost. Then, based on the sum of these three costs, a simultaneous optimization of process mean and process tolerance is determined for process planning in the early stages of development. [ABSTRACT FROM AUTHOR]

Most tolerance design optimization problems have focused on developing exact methods to reduce manufacturing cost or to increase product quality. The inherent assumption with this approach is that assembly functions are known before a tolerance design problem is analyzed. With the current development of CAD (Computer-Aided Design) software, design engineers can address the tolerance design problem without knowing assembly functions in advance. In this study, VSA-3D/Pro software, which contains a set of simulation tools, is employed to generate experimental assembly data. These computer experimental data will be converted into other forms such as total cost and Process Capability Index. Total cost consists of tolerance cost and quality loss. Then, empirical equations representing two variables can be obtained through a statistical regression method. After that, mathematical optimization and sensitivity analysis are performed within the constrained ‘desired design and process’ space. Consequently, tolerance design via computer experiments enables engineers to optimize design tolerance and manufacturing variation to achieve the highest quality at the most cost effective price during the design and planning stage. Copyright © 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study presents a tool replacement model which determines the optimal initial tool setting, tool adjustment cycle and tool replacement time with regard to quality loss, adjustment cost, replacement cost and penalty cost for possible tool failure. A quadratic loss function is employed to characterize the costs representing part quality. The Bernstein probability density function (BDF) is applied to describe the usual characteristics of tool life and the tool wear process. Then, based on the considered costs, the best strategy for tool replacement can be determined. A possible application of the model is given that provides a method of off-line tool management in a production environment. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Producing high-quality products at low cost is one of the key factors to survival for manufacturing sectors in today's intense global competition environment. One way to gain competitiveness is to integrate product design and process planning into one activity. This study attempts to determine optimal process parameters for a manufacturing process under given design parameters. The process parameters to be determined in this study include process means and process tolerances for particular manufacturing process sequences. The problem is formulated in constrained non-linear optimization, considering both quality- and manufacturing-related costs. The proposed application evaluates alternative product designs and process sequences so that the best associated process parameters can be determined during the early stages of design and planning. This makes the link between CAD and CAM systems more useful and effective. As a result, optimal integration of product design and process planning with minimal production costs and maximal product quality is possible. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper provides a mathematical model for tolerance chart balancing for machining process planning. The formulation of the proposed model is based on the graphic 'rooted tree' representation technique in describing the sequence of the machining process. The criteria considered in the presented study are based on the combined effects of manufacturing cost and quality loss under constraints such as process capability limits. design functionality restrictions. and product quality requirements. Applications of these models include minimizing the total cost of manufacturing activities and quality related issues with process selection and tolerance allocation in machining process planning, particularly in the early stage of planning. [ABSTRACT FROM AUTHOR]

This paper provides a few general mathematical models for determining product tolerances which minimize the combined manufacturing costs and quality loss. The models contain quality cost with a quadratic loss function and represent manufacturing costs with geometrical decay functions. The models are also formulated with multiple variables which represent the set of characteristics in a part. Applications of these models include minimizing the total cost with effective tolerance allocation in product design. [ABSTRACT FROM AUTHOR]

This paper provides a general approach for determining tolerances for machined parts which minimizes the combined machining cost and quality cost. We derive a mathematical model which takes into consideration both machining cost and quality cost, which depend on tolerance specifications and the distribution of the machined part dimension produced by a chosen machining process. The model represents the quality cost with a loss function and represents the machining cost with a fitted curve based on some original data. The distribution of the machined part characteristic is taken to be either normal or triangular, depending on model assumptions. By applying this model, designers can determine the tolerance which provides the minimum expected total cost. [ABSTRACT FROM AUTHOR]