Dar-Yuan Chang

Cost-tolerance analysis model based on a neural networks method

The purpose of tolerance design in product components is to produce a product with the least manufacturing cost possible, while meeting all functional requirements of the product. The product designer and process planner must fully understand the process accuracy and manufacturing cost of all kinds of manufacturing process to perform a good process plan job. Usually, the cost-tolerance model is constructed by a linear or non-linear regression analysis based on the data of the cost-tolerance experiment and to derive the correlation curve between the two. Though these correlation curves can show the relationship between manufacturing cost and tolerance, a fitting error is inevitable. In particular, there is considerable discrepancy in terms of the non-experimental data. A cost-tolerance analysis model based on a neural networks method is proposed. The cost-tolerance experimental data are used to set the training sets to establish a cost-tolerance network. Three representation modes of the cost-tolerance relationship are presented. First, the cost-tolerance relationship is derived from the grid points setting by the required tolerance accuracy. Second, a reasonable manufacturing cost of an unknown cost-tolerance experimental pair can be derived by the simulation of a cost-tolerance network. Third, an inference model based on a networks output is proposed to express the scope of the cost variation of various tolerances by means of a cost band. Comparison is also made with the high-order polynomial power function and exponential function cost-tolerance curves adopted by Yeo et al . Analytical results prove that the application of the cost-tolerance analysis model based on neural networks yields better performance in controlling the average fitting error than all conventional fitting models. The representation model using a cost band can identify precisely the possible cost variation range and reduce the chances of error in the tolerance design and cost estimation. It can thus provide important references for tolerance designers and process planners.

Tool Wear, Hole Characteristics, and Manufacturing Tolerance in Alumina Ceramic Microdrilling Process

Microdrilling is an essential process in the electronics, aviation, and semiconductor industries. Since microdrills have low rigidness and a high aspect ratio, precise drilling parameters are required to prevent tool breakage from excessive thrust force or torque. This study implements thousand-micron grade microdrilling experiments in alumina ceramic to investigate the effects of drilling parameters on hole characteristics. Because ceramic has poor machinability, the holes must be fabricated by peck-drilling at shallow depths and continuous cooling. The drilling parameters analyzed included the spindle revolution speed, drill feed rate, peck-drilling return distance, and centering drill depth. Characteristics of the hole diameter and roundness were measured by a computer numerical control (CNC) image measurement device. The optimal parameters combination was derived by a two-stage Taguchis experiment. This study also observes tool wear on chisel edge and generalizes manufacturing tolerance to obtain stable quality characteristics. This article presents valuable process data for thousand-micron grade microholes drilled in sintered alumina ceramic.

Process Simulation–Assisted Fabricating Micro-Herringbone Grooves for a Hydrodynamic Bearing in Electrochemical Micromachining

This study presents the process simulation of fabricating a herringbone groove in a hydrodynamic bearing by electrochemical micromachining (EMM) process. The finite element simulation involved the multiphysics of a chemical reaction, a static electrical field, and electric current density. A dedicated EMM system was established for this study. The groove pattern on the cathode tool was transferred to the internal side of the bearing (anode) by anodic dissolution. The width of the microgroove was selected as a quality index to explore the effects of the process parameters, such as cathode tool, interelectrode gap, voltage intensity, and the pulse rate of the applied voltage, on the electric field distribution and groove fabrication. The experimental results show that the proposed micromachining system has an electrochemical processing rate of k = 1 × 10−11 m3/C, and could complete the micro-herringbone groove fabrication of 11 µm depth in 0.85 seconds. The simulation results were comparable to those of the experiment. The numerical simulation can be used to design the cathode tool and the parametric selection for the microgroove fabrication of hydrodynamic bearings.

Relationship between the Punch–Die Clearance and Shearing Quality of Progressive Shearing Die

This study performed experiments for the progressive shearing die of thin phosphorous bronze sheet to investigate effects of punch materials, punch–die clearance, sheared angle, and number of shearing strokes on burnish band of a sheared surface and burr width of shearing corner. It also analyzed the relationship between height of the burnish band and gravimetric wear rate. The concept of manufacturing tolerance was applied to establish an analytical model of the dimensional tolerance between punch and punch base. It was concluded that after assembling the punch and punch base under the worst conditions, the possible offset of the punch center and the punch–die clearance can be analyzed, and the burr width of the shearing corner can be accessed. Based on the experimental data, four linear predictive models elucidating the characteristics of shearing qualities such as punch–die clearance, punch gravimetric wear rate, and height of the burnish band of a sheared surface can be deduced. Besides, a predictive model of burr width was built by using the least-square method, exponential method, and polynomial regressive method. The result is highly referential to the assessment of sheared products as well as the prediction of tool life.

A New Tool Wear Examination Model by Least Square Method for Shearing Process of Thin Metal Sheet

A new method that accounts for material loss in the normal direction has been developed. Most research applied wear length and wear area to present the status of the tool. Nevertheless, these methods cannot detect the wear in the normal direction of the contact surface between tool and material, and cannot make accurate judgments in precision machining process. In the proposed model, both of the least square lines of the inspected positions and the least square planes of the examined flanks calculating by the wear depth of measuring points are used to infer the relative wear indices, such as flank wear angle, wear depth of punch top face, straightness error, area loss, and volume loss of punch flanks. By using these indices more objective estimations can be acquired than that of wear length and wear area. A series of shearing experiments of thin phosphor bronze sheet are executed to explore the effects of shearing parameters on punch flank wear, and several regressive equations are derived to express the relationships between the wear indices and number of shearing strokes.

The selection system for sheet bending tooling

Sheet metal working is one of the earliest techniques to develop in manufacturing industry. Machine specifications such as pressure capacity and bending length have to be considered in the selection of bending tooling in order to reach the best choice for the needs of the decision maker. The purpose of this paper is to use the ID3 model of inductive-learning knowledge acquisition to construct a product-type rule base, and to complete an expert system of the selection of sheet bending tooling, which may help the user to choose the appropriate bending tooling.

Laser scanning probe with multiple detectors used for sculptured surface digitization in reverse engineering

This paper presents a single-point laser probe with multiple detectors for scanning of a sculptured surface for digitization by reverse engineering. The probe consists of a point laser source and four linear high-resolution PSDs (Position Sensitive Devices). Its target scanning distance is 180 mm from the probe to the measured surface, with a measurable range of 90 mm. Assuming a diffusive surface, the displacement from the light spot on the measured surface to the probe along the light-axis can be derived by the Lambert model. In addition, the inclination angle of the measured point from the vertical axis of the light beam is also calculated. In this study, the probe is mounted on the NC machine integrating the three-axis controller, personal computer and A/D card to conduct the digitization process. Functions of the probe are verified by a standard half-sphere model. The test results show that the displacement resolution is reaching 50 μm and the measurable range of the inclination angle is 80 degrees. A mask model is digitized to demonstrate the scanning results.

In situ monitoring of voltage and temperature in lithium batteries

Lithium batteries are commonly used in mobile phones, personal digital assistants (PDA), notebooks and other computer, communication and consumer electronics (3C) products. Lithium batteries in 3C products or electric vehicles must rapidly charge and discharge. Thus, the inner temperature increases rapidly, which is a safety issue. Conversely, over charging results in unstable voltage and current. Hence, timely monitoring and safety management of data for temperature and voltage inside a lithium battery have become a popular issue. In this work, flexible micro temperature and voltage sensors were integrated in a coin cell using the micro-electro-mechanical systems (MEMS) process for in situ monitoring of temperature and voltage.

Process Parameter Experiments on Vacuum Casting Using a Silicone Rubber Mold for ABS Plastic Parts

Silicone rubber mold is one of soft mold processes for rapid tooling. Based on a master pattern, it can be used for casting the materials of wax, plastic, and low-melting metals directly during a short developing time, very suitable for sample fabrications. This paper conducts vacuum casting experiments by Taguchi’s method to derive the optimal parameter selections on ABS plastic vacuum casting using a silicone rubber mold. The factor that affects pouring characteristics maximally is the mold vacuuming time.

Tool Wear in a Ceramic Microdrilling Processing Using Image Processing Methods

A microhole array is a critical feature on a probe head for microprobe positioning in vertical probe cards. The precision of fabricating microholes affects the final positions of needle tips, and has a significant influence on the correctness of testing results. In the industry, the probe head is made of ceramic and the microhole array is mainly machined by a mechanical microdrilling process. Thus, measuring tool wear and the precision of the microhole is an important task in probe head fabrication. Only then can the functions of probe card be mastered effectively. This study presents a computer vision system that uses image processing methods to evaluate the microdrill wear. Five experiments with different drilling length and two trials of long-drilling were implemented. Wear measurements of the cutting lip and wear land discussed by image methods provide practical references for ceramic microdrilling.