Dispatching for make-to-order wafer fabs with machine-dedication and mask set-up characteristics

This paper develops a dispatching algorithm to improve on-time delivery for a make-to-order semiconductor wafer fab with two special characteristics: mask set-up and machine dedication. A new algorithm is proposed for dispatching series workstations. Simulation experiments show that the algorithm outperforms the previous methods both in on-time delivery rate, cycle time, and only slightly less than the best benchmark in throughput. The experiments are carried out in 10 test scenarios, which are created by the combination of two product-mix ratios and five mask set-up times.     

A combined dispatching criteria approach to scheduling dual flow-shops

This study investigates a dual flow-shops scheduling problem. In the scheduling context, there are two flow shops and each shop involves three processing stages. The two shops are functionally identical but their stage processing times for a job are different. While sequentially going through the three processing stages, each job is allowed to travel between the two shops. That is, for a job, each of its three stages could be processed in any of the two shops. Such a context is called dual flow-shops in the sense that the two flow shops’ capacities are completely shared. The scheduling problem involves two decisions: (1) route assignment (i.e. assigning the processing stages of a job to a shop), and (2) job sequencing (i.e. sequencing the jobs waiting before each stage). The scheduling objective is to minimise the coefficient of variation of slack time (CV_S ), in which the slack time (also called lateness) denotes the difference between the due date and total completion time of a job. We propose five genetic-algorithm-based (GA-based) solution methods to solve the scheduling problem, which are called GA-EDD, GA-FIFO, GA-SPT, GA-LFO, and GA-COMBO respectively. Numerical experiments indicate that GA-COMBO outperforms the other four methods.     

An energy‐based damage parameter for the life prediction of AISI 304 stainless steel subjected to mean strain

Abstract

This study extends the plastic strain energy approach to predict the fatigue life of AISI 304 stainless steel. A modified energy parameter based on the stable plastic strain energy density under tension conditions is proposed to account for the mean strain and stress effects in a low cycle fatigue regime. The fatigue life curve based on the proposed energy parameter can be obtained directly by modifying the parameters in the fatigue life curve based on the stable plastic strain energy pertaining to fully reversed cyclic loading. Hence, the proposed damage parameter provides a convenient means of evaluating fatigue life on the mean strain or stress effect. The modified energy parameter can also be used to explain the combined effect of alternating and mean strain/stress on the fatigue life. In this study, the mean strain effects on the fatigue life of AISI 304 stainless steel are examined by performing fatigue tests at different mean strain levels. The experimental results indicate that the combination of an alternating strain and a mean strain strongly influences the fatigue life. Meanwhile, it is found that the change in fatigue life is sensitive to changes in the proposed damage parameter under the condition of a constant strain amplitude at various mean strain levels. A good agreement is observed between the experimental fatigue life and the fatigue life predicted by the proposed damage parameter. The damage parameter proposed by Smith et al. (1970) is also employed to quantify the mean strain effect. The results indicate that this parameter also provides a reasonable estimate of the fatigue life of AISI 304 stainless steel. However, a simple statistical analysis confirms that the proposed damage parameter provides a better prediction of the fatigue life of AISI 304 stainless steel than the SWT parameter.     

Influence of operating parameters on photocatalytic degradation of phenol in UV/TiO2 process

The use of hydrogen peroxide (H₂O₂) for improved photocatalytic degradation of phenol in aqueous suspension of commercial TiO₂ powders (Degussa P-25) was investigated. Photodegradation was compared using direct photolysis (UV alone), H₂O₂/UV, TiO₂/UV, and H₂O₂/TiO₂/UV processes in a batch reactor with high-pressure mercury lamp irradiation. The effects of operating parameters such as catalyst dosage, light intensity, pH of the solution, the initial phenol, and H₂O₂ concentrations on photodegradation process were examined. It was shown that photodegradation using H₂O₂/TiO₂/UV process was much more effective than using either H₂O₂/UV or TiO₂/UV process. The effect of the initial phenol concentration on TOC removal was also studied, demonstrating that more than 8 h was required to completely mineralize phenol into water and carbon dioxide. For all the four oxidation processes studied, photodegradation followed the first-order kinetics. The apparent rate constants with 400-W UV ranged from 5.0 × 10⁻⁴ min⁻¹ by direct photolysis to 1.4 × 10⁻² min⁻¹ using H₂O₂/TiO₂/UV process. The role of H₂O₂ on such enhanced photodegradation of phenol in aqueous solution was finally discussed.     

Thermally and mechanically enhanced epoxy resin‐silica hybrid materials containing primary amine‐modified silica nanoparticles

In this article, a series of hybrid materials consisted of epoxy resin matrix and well‐dispersed amino‐modified silica (denoted by AMS) nanoparticles were successfully prepared. First of all, the AMS nanoparticles were synthesized by performing the conventional acid‐catalyzed sol–gel reactions of tetraethyl orthosilicate (TEOS), which acts as acceded sol–gel precursor in the presence of 3‐aminopropyl trimethoxysilane (APTES), a silane coupling agent molecules. The as‐prepared AMS nanoparticles were then characterized by FTIR, ¹³C‐NMR, and ²⁹Si‐NMR spectroscopy. Subsequently, a series of hybrid materials were prepared by performing in situ thermal ring‐opening polymerization reactions of epoxy resin in the presence of as‐prepared AMS nanoparticles and raw silica (RS) particles (i.e., pristine silica). AMS nanoparticles were found to show better dispersion capability in the polymer matrices than that of RS particles based on the morphological observation of transmission electron microscopy (TEM) study. The better dispersion capability of AMS nanoparticles in hybrid materials was found to lead enhanced thermal, mechanical properties, reduced moisture absorption, and gas permeability based on the measurements of thermo gravimetric analysis (TGA), differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and gas permeability analysis (GPA), respectively. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Application of backpropagation neural network for spindle vibration-based tool wear monitoring in micro-milling

This study develops a micro-tool condition monitoring system consisting of accelerometers on the spindle, a data acquisition and signal transformation module, and a backpropagation neural network. This study also discusses the effect of the sensor installations, selected features, and the bandwidth size of the features on the classification rate. To collect the vibration signals necessary for training the system model and verifying the system, an experiment was implemented on a micro-milling research platform along with a 700?μm diameter micro-end mill and a SK2 workpiece. A three-axis accelerometer was installed on a sensor plate attached to the spindle housing to collect vibration signals in three directions during cutting. The frequency domain features representing changes in tool wear were selected based on the class mean scatter criteria after transforming signals from the time domain to the frequency domain by fast Fourier transform. Using the appropriate vibration features, this study develops and tests a backpropagation neural network classifier. Results show that proper feature extraction for classification provides a better solution than applying all spectral features into the classifier. Selecting five features for classification provides a better classification rate than the case with four and three features along with the 30?Hz bandwidth size of the spectral feature. Moreover, combining the signals for tool condition from both direction signals provides a better classification rate than determining the tool condition using a one-direction single sensor.     

Effect of electrochemical surface area on electroless copper deposition: Pd nanocubes as new activators

In this study, the electrochemical surface area (ESA) and specific activity are used to obtain a fair comparison of various activators used for electroless copper deposition (ECD). Different sizes (i.e., 27, 48, and 63 nm) of Pd nanocubes (NCs) enclosed by {1 0 0} facets were successfully synthesized for use as new activators. The results of an analysis based on mixed potential theory indicated that the specific activities in terms of deposition current densities for the 27, 48, and 63 nm NCs and 9 nm nanoparticles (NPs) were 0.31, 1.06, 0.93, and 0.13 mA cm^?2_ESA, respectively. From the results of electrochemical quartz crystal microbalance measurements, the specific activities calculated from the mean deposition rates of the 27, 48, and 63 nm NCs and 9 nm NPs were 29.62, 68.72, 54.77, and 9.72 μg cm^?2 s^?1, respectively. A specific activity order of 48 nm NC > 63 nm NC > 27 nm NC > 9 nm NP was obtained. The 48 nm Pd NCs exhibited the maximum activity towards the activation of the ECD bath.     

Finite element based fatigue life estimation of the solder joints with effect of intermetallic compound growth

This paper develops an analysis procedure to study the effects of intermetallic compound (IMC) growth on the fatigue life of 63Sn-37Pb (lead-rich)/96.5Sn-3.5Ag (lead-free) solder balls for flip-chip plastic ball grid array packages under thermal cycling test conditions. In this analysis procedure, the thickness of the IMC increased with the number of thermal cycles, and was determined using the growth rate equation. A series of non-linear finite element analyses was conducted to simulate the stress/strain history at the critical locations of the solder balls with various IMC thicknesses in thermal cycling tests. The simulated stress/strain results were then employed in a fatigue life prediction model to determine the relationship between the predicted fatigue life of the solder ball and the IMC thickness. Based on the concept of continuous damage accumulation and incorporated with the linear damage rule, this study defines the damage of each thermal cycle as the reciprocal of the predicted fatigue life of the solder joints with the corresponding IMC thickness. The final fatigue failure of the solder ball was determined as the number of cycles corresponding to the cumulative damage equal to unity. Results show that the solder joint fatigue life decreased as the IMC thickness increased. Moreover, the predicted thermal fatigue life of lead-rich solders based on the effects of IMC growth is apparently smaller than that without considering the IMC growth in the reliability analysis. Results also show that the influence of the IMC thickness on the fatigue life prediction of the lead-free solder joint can be ignored.     

Effect of silanes on the morphology,hydrophobicity, and dynamical mechanical properties of polyimide/silica hybrid membranes

Polyimide (PI)/silica hybrid membranes with high contact angles were prepared through the in situ sol–gel process. The precursor, poly(amic acid) with controlled block chain length, was synthesized using 4,4′‐diaminodiphenyl ether (ODA), 3,3′,4,4′‐benzophenone‐tetracarboxylic dianhydride (BTDA) and 3‐aminopropyl‐trimethoxysilane (APrTMOS) or 3‐aminopropyldimethylethoxysilane (APDiMOS). And then, phenyltrimethoxysilane (PTS) or tetramethoxysilane (TMOS) or methyltrimethoxysilane (MTrMOS) was respectively, added to the above polyamic acid and mixed thoroughly. Following curing reaction, the PI/silica hybrid membranes with different cross‐linkages, silica content, and hydrophobic properties were prepared. The effect on the formation of PI imide ring during imidization reaction is increased as the increase of silanes content and characterized by frequency shiftment and absorbance ratio of Fourier transform infrared (FTIR) measurements. All the hybrid membranes show high transparency though with high silica contents. The storage modulus, tan δ, and damping intensity by DMA measurements are all correlated with silane content or block chain length. And all these membranes with silane content possess high contact angle as compared to pure PI without any silanes added and the contact angles increase with increasing the silane content. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011