Applied Mechanics and Materials Vols. 752-753

Abstract: To realize the optimum parameters combination of product-service systems, a method based on the customer demands was referred. Firstly the customer demands and characteristic were divided into three types. Secondly using the combination of quantitative and qualitative method, the model of different customer satisfaction function to meet the various demands was established through data fitting. Finally more accurate and reasonable parameter combination model was achieved by building the optimal design model to meet the customer demands. Taken the grader company as an example, the validity of this method was proved.

Abstract: The purpose of this paper is to study a ink surface morphology, quantify the chemical composition involved in processing of graphite ink printed by flexographic printing. The methodology is to use surface sensitive technique, X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) and Field Emission Scanning Electron Microscopy (FESEM). As a finding we successfully achieved 25 micron lines array using PDMS printing plate. The Originality and value of this work is surface sensitive techniques like XPS, AFM and FESEM were exclusively used in order to characterize graphite inks printed by flexographic method, using PDMS printing plate.

Abstract: With application of intelligence technology in the manufacturing industry, the supply chain of manufacturing industry is more and more competitive. Strategic supplier is becoming more and more key element for the success of manufacturing enterprise. At present, there are many methods on selection and evaluation of strategic supplier of manufacturing enterprise. Analytical hierarchy process and grey correlation analysis is method which is used to choose strategic supplier of manufacturing enterprise by building optimum reference date and solving grey correlation degree. These have great effects in the enterprise practice in the aspects of qualitative diagnosis, quantitative diagnosis and grey information processing.

Abstract: With the market competition aggravating, strategic supplier of manufacturing enterprise is becoming more and more critical for the success of manufacturing enterprise. It plays decisive role in the areas of product quality, date of delivery, service, etc. At present, there are many methods on selection and evaluation of strategic supplier of manufacturing enterprise. But, there lacks of integral system. Through the establishment of outsourcing criteria to supplier classification based on products, this paper builds selection and evaluation standard system of strategic supplier of manufacturing enterprise in order to provide reference to manufacturing enterprise on choosing strategic supplier.

Abstract: Model design and rapid prototyping are utilized to manufacture push-ups frame. Point cloud data can be obtained by scanning parts with hand-held laser scanner, and imported into the Imageware to process. The varied points are removed, the missing points are repaired, and then the 3D model is designed through the Pro/E. Finally, the frame model is completed by rapid prototyping printers. The manufacturing period is shorten through the way of putting two technologies in the field of manufacturing together, the production requirements are met, and the business efficiency is improved.

Abstract: In modern industry, the nondestructive testing of printed circuit board (PCB) can prevent effectively the system failure and is becoming more and more important. As a vital part of the PCB, the via connects the devices, the components and the wires and plays a very important role for the connection of the circuits. With the development of testing technology, the nondestructive testing of the via extends from two dimension to three dimension in recent years. This paper proposes a three dimensional detection algorithm using morphology method to test the via. The proposed algorithm takes full advantage of the three dimensional structure and shape information of the via. We have used the proposed method to detect via from PCB images with different size and quality, and found the detection performances to be very encouraging.

Abstract: Energy efficiency is a key factor to improve WSNs’ performance, and hierarchical routing algorithms are fitter in large scale networks and have more reliability, so they are mostly used to improve the nodes’ energy efficiency now. In this paper, mainly existing hierarchical routing algorithms are introduced, and based on these researches, a new energy efficient hierarchical routing algorithm designed based on energy aware semi-static clustering method is proposed. In this algorithm named EASCA, the nodes’ residual energy and cost of communication would both be considered when clustering. And a special packet head is defined to update nodes’ energy information when transmitting message; to rotate cluster head automatically, a member management scheme is designed to complete this function; and a re-cluster mechanism is used to dynamic adjust the clusters to make sensor nodes organization more reasonable. At last, EASCA is compared with other typical hierarchical routing algorithms in a series of experiments, and the experiments’ result proves that EASCA has obviously improved WSNs’ energy efficiency.

Abstract: The article deals with problems of traffic simulation at cross intersection with cranked priority. For traffic simulation was used microsimulation software PTV VISSIM. In the article there is shown the brief description of traffic model creation and results of evaluation of travel times and delay times occurring during transit through the observed intersection.

Abstract: Classifying inventories into different groups based on the importance of each category of material is necessary for inventory management when there are a large number of inventories to be managed. In order to plan and determine effective policies in the management of each material, it is essential that the inventories be properly classified. One of the most popular methods used in classifying inventories is the ABC analysis, which is the classification of inventories based on their actual values. In the food-processing industry, for example, where inventories are often of perishable goods, the quality of inventories will decrease with storage time. Storage time is therefore considered a major factor when managing this inventory. In this research, the criterion of storage time was considered alongside others, including prices of materials per unit, amount of use, worth of use, and duration. However, since the classification of the inventories in this study was based on various complicated criteria, neural networks were applied. By using previous classifications as the input variables, we were able to apply a neural network to produce output variables and classify each inventory category into group A, B, or C. Neural networks were used to manage 105 inventories of the processing and product developing plant of the Royal Project Foundation. The findings showed that the neural network could effectively classify those inventories into groups A, B, and C, and that the accuracy of this classification was 84.35%.

Abstract: This study was conducted to investigate the research trends in water resource management using authors' keywords of papers in this area. For this purpose, networks of keywords were constructed through the analysis of social networks and the degree centrality was used as a measure for analyzing the water resource management areas in which research is being conducted most actively. Based on this analysis, the research trends in water resource management during the 1990s, 2000s, and after 2010 were investigated. As a result, the most active research areas in water resource management were found to be integrated water resource management system, water policies, and the development of programs for optimizing water resources. As a result of the analysis by period, the central subjects of research that emerged as new trends were found to be the acquisition of water resources such as ground water development during the 1990s, water resource management during the 2000s, and water resource management measures and government policies to cope with climate change after 2010. The significance of the present study is that the research trends were examined around the correlations among keywords by using social network analysis, rather than analyzing research trends simply by using the frequencies of papers and citations in water resource-related papers.