Selecting the suitable material handling equipment in the presence of vagueness

Selection of the suitable material handling equipment (MHE) is a very difficult task for the manufacturing companies because of the considerable capital investment required. There are many tangible and intangible factors for choosing the suitable MHE. Multiple criteria decision making (MCDM) has been found to be a useful approach to analyze these conflicting factors. The evaluation of MHE alternatives within the frame of various subjective criteria and the weights of the criteria are usually expressed in linguistic terms. This makes fuzzy logic a more natural approach to this kind of problems. This paper proposes a combined MCDM methodology for evaluation and selection of MHE types for a company in the steel construction industry in Istanbul, Turkey. Fuzzy analytic network process (FANP) is utilized for assigning weights of the criteria for MHE selection and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is used to determine the most proper system alternative using the criteria weights attained by FANP. The selection is based on the compatibility between MHE and production characteristics. Objective is to select the most efficient MHE considering also the cost efficiency. The study was followed by the sensitivity analyses of the results.     

Hourly River Flow Forecasting: Application of Emotional Neural Network Versus Multiple Machine Learning Paradigms

Water Resources Management - Monitoring hourly river flows is indispensable for flood forecasting and disaster risk management. The objective of the present study is to develop a suite of hourly...     

弹用数字舵控的系统设计与实现

文章介绍一种弹用双通道数字舵机控制器的系统设计与实现方案;该方案以DSP数字信号采样与处理技术为基础,将舵机驱动系统与控制系统进行一体化设计,通过SPI总线拓展技术扩充舵机控制通道数量,并运用位置式复合PI及PD控制算法设计控制软件,从而实现了对双通道舵机的一体化控制;所进行的阶跃及频率响应实验表明,基于该方案的舵机控制器具备性能稳定、控制参数一致性好、集成度高、抗干扰能力强等特点,且其主要动态性能指标满足设计与应用需求。     

Modeling of ferrofluid magnetic actuation with dynamic magnetic fields in small channels

One of the most important and promising research areas in biomedical and micropumping applications is magnetic actuation of ferrofluids with dynamic magnetic fields. For ensuring the use of ferrofluids in various applications in engineering fields, their flows generated by magnetic fields should be extensively investigated and simulated. In this study, simulations of ferrofluid actuation with dynamic magnetic fields were performed by modeling it using the COMSOL Multiphysics software, and iron oxide nanoparticle-based ferrofluids at different angles of rotating magnets were considered to provide insight into ferrofluid flow in small channels. Ferrofluid flows were modeled at different magnetic flux densities provided by rotating magnets, and velocity profiles inside the channel were analyzed. It was shown that ferrofluid actuation can be considered as a futuristic micropumping alternative, simulation results matched well with the experimental results of previous work, and the established model could serve as a tool to analyze ferrofluid flows generated by dynamic magnetic fields. The results of the model show that flow rates up to 100 µl/s can be reached at a rotation angle of 30° by using dynamic magnetic fields. Various applications including biomedical applications might be envisaged.     

Stochastic signaling in the presence of channel state information uncertainty

In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, stochastic signaling based on the available imperfect channel coefficient at the transmitter is analyzed, and it is shown that optimal signals can be represented by a randomization between at most two distinct signal levels for each symbol. Then, performance of stochastic signaling and conventional deterministic signaling is compared for this scenario, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Furthermore, under CSI uncertainty, two different stochastic signaling strategies, namely, robust stochastic signaling and stochastic signaling with averaging, are proposed. For the robust stochastic signaling problem, sufficient conditions are derived for reducing the problem to a simpler form. It is shown that the optimal signal for each symbol can be expressed as a randomization between at most two distinct signal values for stochastic signaling with averaging, as well as for robust stochastic signaling under certain conditions. Finally, two numerical examples are presented to explore the theoretical results.     

A Method for the Estimation of the Interface Temperature in Ultrasonic Joining

Ultrasonic joining of copper foil to 1100 aluminum sheet at nominal joining temperatures of 298 K to 413 K (25 °C to 140 °C) for 1.25 second caused significant copper diffusion into the aluminum sheet, indicating very high diffusivity (D) values of 1.54 × 10^?13 to 2.22 × 10^?13 m²/s. The D values reflect high excess vacancy concentrations caused by the rapid plastic deformation in the joining surfaces. A method is presented to estimate the actual values of interface temperature from the diffusion data and expected values of vacancy concentrations. The estimated values of interface temperature were about 390 to 410 deg below the equilibrium melting point of aluminum, and in agreement with reported experimental values.     

Conceptualizing manufacturing flexibility: An operational approach and a comparative evaluation

An operational approach to conceptualization and the measurement of manufacturing flexibility is presented. A critical review of selected measures from the literature is provided in the context of the operational approach. A flexibility measure is proposed. A formulation and the features of the proposed measure are discussed. An application of the measure is demonstrated through a hypothetical example. Using the same example, selected flexibility measures from the literature are evaluated. The performance of the measures and the proposed measure are compared.     

Organizational strategy development in distribution channel management using fuzzy AHP and hierarchical fuzzy TOPSIS

Distribution channel management not only consists of choosing distribution channels. In fact, probably the most difficult phase of the distribution management starts after this choice. Determining an appropriate organization strategy for distribution channel management is like a problem of concern to marketing practitioners and academics as well in this phase. In this study, the organization strategy of distribution channel management is developed using fuzzy analytic hierarchy process (FAHP) and hierarchical fuzzy TOPSIS (HFTOPSIS) for an edible-vegetable oils manufacturer firm operating in Turkey. The company distributes its products all over the country. Due to the complex structure of the distribution network, the company wants to decide the organization strategy to manage the distribution channels. In this paper, the methods of FAHP and HFTOPSIS for evaluating and selecting among the five organization strategy models for distribution channel management of vegetable oil manufacturer have been presented. The proposed models include determinants of distribution channel management for edible-vegetable oil industry; (i) customer profile, (ii) distributor reliability, (iii) the position of competitors in market, and (iv) managerial and financial perspective. Using FAHP and HFTOPSIS, hybrid based strategy (KBS), which has the greatest desirability index value after the evaluation among the five alternatives is found as the best choice. Thus, the case of the vegetable oil manufacturer company provides the researchers and practitioners to understand in a better way the importance of developing organization strategy in channel management from a practical point of view.