HEURISTIC APPROACHES FOR LOADING PROBLEMS IN FLEXIBLE MANUFACTURING SYSTEMS

Flexible manufacturing systems (FMSs) are able to process a wide variety of operations, but the specific mix of operations that can be performed at any point in time depends upon the combination of tools loaded onto the machines. The machines have tool magazines with finite capacities. We consider the problem of assigning operations and their associated tools to machines (or groups of machines) to maximize the throughput for a specified steady-state mix of orders. Since this objective is difficult to deal with directly, we use an intermediate objective of meeting workload targets for each machine group as closely as possible. A certain form of this intermediate objective has been shown to correlate highly with the original objective.

Since it is computationally intractable to find optimal solutions for problems with more than 20 operations, fast heuristic algorithms are developed. These algorithms are adapted from multi-dimensional bin-packing algorithms. Computational results are reported.     

Micromachined piezoelectric force sensors based on PZT thin films

A micromachined lead zirconate titanate (PZT) force sensor for scanning force microscope (SFM) is conceptualized by its piezoelectricity. The fabrication procedure is interpreted, and mechanical characteristics of the micromachined PZT force sensors with various lengths are studied in this paper. A compact SFM is constructed by using the piezoelectric PZT sensor. A very clear image is taken by this SFM. The current study of the micromachined PZT force sensor can be considered as a breakthrough of design of SFM as well as a good example of integrated piezoelectric microdevices     

Reliability and performance analysis of time – space – time switching networks with multiple separated space switches

Since electronic switching systems usually require very strict reliability requirements as well as good performance objectives, we need to jointly analyse the performance and reliability of switching systems. In this paper, we compare conventional time–space–time switches with single space switches with those with multiple separated space switches, from the viewpoints of reliability and performance. We consider time–space–time switching networks which consist of N incoming time switches, i.e. one NxN space switch, two (N/2)x(N/2) space switches, and four (N/4)x(N/4) space switches. We introduce a Markov reliability model to study the effect of failures and analyse the reliability and performance of three different types of switching networks in terms of average blocking probability and the mean time to unreliable operation, as we vary the offered traffic. As a result, T–S–T switching networks with multiple separated space switches exhibit better performance and reliability than those with single space switches.     

Modified atmosphere packaging of a mixed prepared vegetable salad dish

The aim of this study was to design a modified atmosphere package for a mixed vegetable salad consisting of 75 g of cut carrot, 55 g of cut cucumber, 20 g of sliced garlic and 50 g of whole green pepper. Respiration data of all the components were combined with film permeability data to predict package atmospheres and design optimal packages for experimental testing for improved shelf-life of the produce. The optimal package avoided minimum O₂ and maximum CO₂ tolerance limits, and chilling injury temperatures for any component. A pouch form package made of 27 mm low density polyethylene developed a modified atmosphere of 2.0–2.1% O₂ and 5.5–5.7% CO₂, which was beneficial for all components and provided better quality retention than other test packages.     

A neural network-based power system stabilizer using power flowcharacteristics

A neural network-based power system stabilizer (neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The use of power flow dynamics provides a PSS for a wide range of operation with reduced size neural networks. The neuro-PSS consists of two neural networks: neuro-identifier and neuro-controller. The low-frequency oscillation is modeled by the neuro-identifier using the power flow dynamics, then a generalized backpropagation-through-time (GBTT) algorithm is developed to train the neuro-controller. The simulation results show that the neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS     

Laser scanning path generation considering photopolymer solidification in micro-stereolithography

It is essential to automate the scanning path generation process to effectively implement the micro-stereolithography. However, a scanning path that is generated based only on a 3D CAD model introduces dimensional inaccuracies. In micro-stereolithography, the photopolymer solidification is affected by fabrication conditions, such as the optical properties (laser power, laser scanning speed, laser scanning pitch focusing condition, etc.) and material properties of the photopolymer. Thus, the photopolymer solidification phenomena must be considered when generating a laser scanning path. In this paper, a scanning path generation algorithm that uses 3D CAD data and considers the photopolymer solidification phenomena is proposed to improve the dimensional accuracy in micro-stereolithography. Multi-line photopolymer solidification experiments were performed for various laser scanning conditions to examine the photopolymer solidification phenomena. From these experiments, linear relations between the solidification length (width) and scanning length (width) were acquired and stored in a database. Subsequently, these data were utilized to compensate the scanning path of the laser beam. In addition, experiments for determining the layer thickness in the z-direction were performed and these results were also used in the scanning path generation algorithm.This research was supported by the Highly Advanced National Project (http://www.most.go.kr), which performs some of the National R&D Program, and sponsored by the Korean Ministry of Science and Technology under the contract project code M10214000116-02B1500-02010.     

Rapid and comprehensive indicator for evaluation of performance of treatment processes and of river waters.

Naturally occurring UV active compounds, commonly present in almost all source waters, can be rapidly monitored by their ultraviolet absorbance at 260 nm (E260). Herein, the extent of correlation between the E260 and the removal efficiency of the hazardous contaminants, endocrine disrupters and dioxins, were investigated using various treatment and river source waters. The detection of various types of hazardous contaminants using sophisticated analytical methods, such as high resolution gas chromatography (HRGC)/high resolution mass spectrometry (HRMS) and high performance liquid chromatography (HPLC)/inductively coupled plasma (ICP)/mass spectrometry (MS), as well as various short-term bioassays, can require hours or even days for results to be obtained. The removal of the E260 correlated well with those of individual contaminants, such as endocrine disruptor chemicals and dioxins, with the various treatment processes employed. In the plots of the endocrine disrupters against the DOC/E260, a correlation was found with the endocrine activity of the Korean/Japanese river waters employed in this study.     

Formation of C4 species in the deactivation of a Pd/SiO2 catalyst during the selective hydrogenation of acetylene

The deactivation characteristics of Pd/SiO₂ in the selective hydrogenation of acetylene were correlated with changes in the amount of the C4 species produced. The amounts of butenes produced changed in parallel with the catalyst activity, indicating that the rate limiting step for butene production was the same as that for acetylene hydrogenation. On the other hand, the amount of 1,3-butadiene produced changed, showing a maximum with catalyst deactivation because 1,3-butadiene is an intermediate in the sequential reaction process which involves both the production and consumption of 1,3-butadiene. This was verified by a simultaneous TG/reaction experiment showing that 1,3-butadiene was a precursor of green oil. The catalyst showed a self-regenerative behavior in its activity and the amounts of C4 species produced during the early stage of deactivation because two opposite factors, which contributed to either the lowering or the promotion of activity, were involved in the process. A specific type of polymer species, produced during the initial period of deactivation, is proposed to be responsible for the promotion of catalyst activity.     

StoryGrid [educational computing]

The StoryGrid project undertook studying the role new interface technologies might play in education, particularly at the high school level. Unfortunately, technology often seizes center stage in high school classrooms; i.e., it becomes the topic of instruction. We believe that learning about technology would be most successful when technology is not the topic, but simply a tool used during instruction. StoryGrid, therefore, was designed to support and to enhance existing narrative activity in classrooms by adhering to the following goals: trigger reflection and interpretation, accommodate individual expression and encourage student discourse.     

Visual insights into high-resolution earthquake Simulations.

This study focuses on the visualization of a series of large earthquake simulations collectively called TeraShake. The simulation series aims to assess the impact of San Andreas Fault earthquake scenarios in Southern California. We discuss the role of visualization in gaining scientific insight and aiding unexpected discoveries.