多载具自动化存取系统货位分配优化

根据多载具自动化存取系统运行的特点,统筹考虑存货货位和取货货位分配两方面内容,建立了多载具自动化存取系统货位分配优化的通用模型.该模型以最小化指令周期内存取货物的行程时间为优化目标,适应于不同载具数量和货化规模情形下的货位优化.设计了一种结合启发式算法的混合遗传算法来求解这一非确定多项式完全问题,并通过算例验证了该算法的有效性.     

Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming

A closed-loop supply chain (CLSC) network is composed of both forward and reverse flows. An essential issue to be considered in designing any supply chain network is determination of number and locations of facilities in each layer of the network. Such a problem is a challenging job, since it contains sub-problems which are proven to be nondeterministic polynomial time complete. This paper proposes a CLSC distribution network design problem in which reverse flows are imported into forward model proposed by Selim and Ozkarahan (Int J Adv Manuf Technol 36:401–418, 1). Such a model is considered assuming forward covering (model I) and backward covering (model II) objectives, and then results are compared against the model incorporating covering of both forward and backward networks (model III). Our aim is to accentuate on the role of considering backward parameters in design of a CLSC network and to show how results differ from considering sub-problems separately. To model and solve the problem, a fuzzy goal programming approach is developed for network design in an interactive manner between decision maker and the model. To validate the presented model and the proposed solution approach, a test problem is presented and comparison of results is made using this problem. The results show that the proposed model can solve the CLSC problems in a manageable time. Moreover, outputs of the three models differ significantly. Therefore, the role of incorporating backward flows into the network design problem has been shown using our experiments.     

Robust topology optimization of multi-material lattice structures under material and load uncertainties

Frontiers of Mechanical Engineering - Enabled by advancements in multi-material additive manufacturing, lightweight lattice structures consisting of networks of periodic unit cells have gained...     

A mathematical programming model for recycling network design under uncertainty: an interval-stochastic robust optimization model

The development of mathematical and optimization models for reverse supply network design has concerned considerable interest over the past decades. However, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of these developed tools. The aim of this paper is to propose a new mathematical programming model for recycling network design in the iron and steel industry. The considered recycling network is multi-echelon, multi-facility, multi-product, and multi-supplier. Moreover, another objective of this research is to introduce an interval-stochastic robust optimization methodology to deal with various uncertainties in the proposed model. Computational experiments are provided to demonstrate the applicability of the proposed model in recycling network design.     

基于 WinCC 的自动化配方管理系统设计与实现

为实现多项生产管理功能,在现有视窗控制中心自动化生产系统基础上进行二次开发,系统整体方案设计包括整体框架设计、系统模块设计和工作流程设计等。该系统方案已经在生产自动化监控中具体应用,成功实现提高生产效率、提升管理水平和降低能耗等目的。     

Quality monitoring of a closed-loop system with parametric uncertainties and external disturbances: a fault detection and isolation approach

Due to aging and environmental factors, system components may either fail or not function as expected, which causes unprecedented changes in the quality of the system. A timely detection of the onset of a fault in a component is crucial to a quality monitoring of a process if costly failures are to be avoided. However, finding the source of the failure is not trivial in systems with a large number of components and complex component relationships. In this paper, an efficient scheme to detect adverse changes in system reliability and find the failed component is proposed in order to have an effective process quality monitoring. The monitoring scheme has been made effective by implementing first the techniques of fixed-parameter Shewhart, MEWMA and Hotelling’s T² control chart, and then the adaptive versions of Shewhart Chart, MEWMA and T² control chart for counter checking the precision of quality reports. Once detected, the fault isolation scheme uses a Bayesian decision strategy based on the maximum correlation between the residual and one of a number of hypothesized residual estimates to generate a fault report. By doing so, the critical information about the presence or absence of a fault, and its isolation, is gained in a timely manner, thus making the quality monitoring system an effective tool for a variety of maintenance programs, especially of the preventive type. The proposed scheme is evaluated extensively on simulated examples, and on a physical fluid system exemplified by a benchmarked laboratory scale two-tank system to detect and isolate faults including sensor, actuator, and leakage ones.     

转向架自动化立体仓库机械系统设计

铁路是我国国民经济的动脉、交通运输系统的骨干。为实施跨越式发展,满足国民经济和社会快速发展对交通运输日益不断增长的需求,我国铁路确立了铁路快速客运网发展规划。针对规划的要求,铁道部加快了铁路装备现代化的步伐,引进了4种动车组。     

Straightness and flatness tolerance evaluation: an optimization approach

This paper presents an optimization approach that could be used to calculate exact values of straightness and flatness errors as defined by the ANSI Y14.5M standards on geometric dimensioning and tolerancing. The straightness and flatness error evaluation problems are formulated as nonlinear optimization problems with linear objective function and nonlinear constraints. Because of the special structure of the problem, a linear search method is developed that reduces the nonlinear problem to a linear programming problem with only two constraints. Examples are presented to compare the optimization approach with the least-squares method and some exact methods. The results show that the optimization procedures presented in this paper provide exact values of straightness and flatness errors and are superior to the existing methods in terms of computation time.     

Sustainable cultivation location optimization of the Jatropha curcas L. under uncertainty: A unified fuzzy data envelopment analysis approach

Second-generation biodiesel production from non-edible high oil content feedstocks such as Jutropha curcas L. (JCL) has been found as a suitable alternative for the fossil diesel which is mostly consumed in transportation sector. Second-generation biodiesel eliminates the drawbacks of the first generation such as food-energy challenge and provides opportunity for rural development. Location optimization of JCL plays a vital role in the success and prosperity of JCL projects. In this study, sustainability and ecological indicators are defined to evaluate the performance and efficiency of the candidate locations for JCL cultivation under uncertainty. The values of defined indicators are highly tainted with uncertainty in real-life situation. To optimize the candidate locations for JCL cultivation under uncertainty, an efficient Unified Fuzzy Data Envelopment Analysis (UFDEA) model is developed. The proposed UFDEA model is verified and validated through investigating a real case study in Iran and the associated results are compared to those obtained by the crisp Unified Data Envelopment Analysis model under different levels of uncertainty. The obtained results show the applicability of the proposed UFDEA model in selecting suitable areas for JCL cultivation under uncertainty.     

Electrical resistivity as a measure of change of state in substrates: Design, development and validation of an automated system

Intrinsically smart structural composites are materials, which can perform function such as sensing strain, stress damage or temperature. Electrical resistance could potentially serve as an indicator of structural well-being or damage in the structure. To this end, the development of an automated resistance measurement system is desired. An automated nodal electrical resistance acquisition circuitry (NERAC) was designed, and interfaced to a laptop for measurement of electrical resistance/impedance from the substrate of interest. Measurements were carried out using DC/AC method with four-point probe technique. Baseline reading before damage was noted and compared with the resistance measured after damage. The device was calibrated and validated on three different substrates: PVDF samples, composite panels and smart concrete. Results conformed to previous work done on these substrates, validating the effective working of the NERAC device. Change of state of the substrate, after damage was assessed by measurement of resistance/impedance.     

PLC功能块图编程系统的设计与实现

本文简述了PLC功能块图FBD的基本概念、功能和编程方法。针对功能块图FBD编程系统的设计要求,基于IEC61131—3国际标准制定的编程规则,采用面向对象的方法,设计出了一套全新的完整实用的数据结构。同时介绍了功能块图编程系统的设计方案及其基于VC＋＋集成开发环境的方案实现。     

PLC结构化文本编程系统的设计与实现

本文简述了PLC结构化文本ST的基本概念、讲述其编程方法。针对结构化文本ST编程系统的设计要求,基于IEC61131-3国际标准制定的编程规则,采用面向对象的方法,设计出了一套完整实用的数据结构,与此同时介绍结构化文本在基于VC++集成开发坏境下的方案设计与实现过程。     

面向规范化数控编程系统的设计与研究

针对模具企业数控编程工作没有规范体系、数控编程流程不统一、对数控编程经验依赖性强及优良的加工工艺未得到有效继承等问题,设计出一款规范化数控编程系统。该系统以规范化数控系统为开发目标,研究工艺知识库的构建,建立基于实例与加工规则的综合推理机制,采用PowerMILL二次开发技术开发基于规范化流程设计的数控编程系统,实现工艺数据库与CAM软件的数据交互。结果表明：该系统可有效缩短模具数控编程时间,提高工艺设计和数控加工效率。     

An approach for automated fault diagnosis based on a fuzzy decision tree and boundary analysis of a reconstructed phase space

Although reconstructed phase space is one of the most powerful methods for analyzing a time series, it can fail in fault diagnosis of an induction motor when the appropriate pre-processing is not performed. Therefore, boundary analysis based a new feature extraction method in phase space is proposed for diagnosis of induction motor faults. The proposed approach requires the measurement of one phase current signal to construct the phase space representation. Each phase space is converted into an image, and the boundary of each image is extracted by a boundary detection algorithm. A fuzzy decision tree has been designed to detect broken rotor bars and broken connector faults. The results indicate that the proposed approach has a higher recognition rate than other methods on the same dataset.     

Design and implementation of an automated secondary cooling system for the continuous casting of billets

This paper describes a heat transfer model based automatic secondary cooling system for a billet caster. The model aims to minimize the variation in surface temperature and excessive reheating of the billet strands. It is also used to avoid the low ductility trough of the solidifying steel, which aggravates the tendency of steel to crack. The system has been designed and implemented in an integrated steel plant. A Programmable Logic Controller (PLC) based automation system has been developed to control the water flow in the secondary cooling zones of the strand. The results obtained through field trials have shown complete elimination of internal and off-corner cracks for the fifty billet samples that were monitored.     

Production planning of FMS under tool magazine constraints: A dynamic programming approach

Production planning is one of the most important activities for efficient operation of a flexible manufacturing system. This complex acivity is concerned with the decisions related to system set-up, involving solving the problems of selection of a set of part types for simultaneous processing, determining the production ratios, assigning the pallets and fixtures, and assigning operations and tools to machines. In this paper, a dynamic programming algorithm is developed to solve the above problems simultaneously by considering the flexibilities and constraints of the system in order to minimise the unbalanced workload of machines. In this context, various factors such as the tools required for operations, alternative routes available for operations, tool magazine capacity and the limited number of pallets and fixtures are considered. The method is validated with a case study.Notation B a large number - i part type,i=1,...,N - o operation,o=1,...,O _i - k machine,k=1,...,K - j stage,j=1,...,N (N is maximum number of stages required, i.e. equal to the number of part types) - n indicates the number of parts to be introduced into the system (represents the state in DP),n=j,...,nmax. In stagej at least one number of each part type should be introduced into the system. The maximum number of parts can be a user defined maximum,nmax. - P _iok processing time of part typei, operationo on machinek - OA _io set of operation alternatives available for part typei, operation - o an alternative consists of machine number, tool number along with its processing time - pw _ik average workload required by a part typei on machinek - a _i number of parts (ratio) of typei - f _i number of fixtures available to part typei - S(j) {S ₁(j),S ₂(j),...,S _p (j),...}, whereS _p (j) ispth set of selected part types with cardinalityj - |S(j)| ^N C _j - W _k a constant, indicating the average unbalanced workload on a machinek and is a user defined value - L _j,k (S _p (j),n,a _i ) load of machinek at stagej when selection isS _p (j), number of part types isn, and number of parts of type isa _i - L* _j,k (S _p (j),n) load of machinek in stagej at minimum unbalanced workload when selection isS _p (j) and number of parts in system isn - F _j (S _p )(j),n,a _i ) unbalanced workload of all machines at stagej, when selection isS _p (j), number of part types isn, and number of parts of type isa _i - F _j (S _p (j),n) minimum unbalanced workload of all machines, whenS _p (j) is the set of selected part types andn is the number of parts in the system     

基于神经网络的制冷模糊控制系统仿真与优化

针对制冷系统被控对象模型建立了一个基本模糊控制器,并给出一组较优量化因子,在此基础上建立和训练了一个模糊神经网络控制器,并在MATLAB仿真环境下对制冷模糊控制进行仿真和优化。根据得到的一系列仿真结果对所设计的制冷模糊控制系统性能进行了分析,探讨了神经网络训练样本数据对FNNC系统控制性能的影响,结果表明采用合理的样本数据可以优化模糊神经网络制冷控制系统。     

Deadlock-free scheduling of an automated manufacturing system using an enhanced colored time resource Petri-net model-based evolutionary endosymbiotic learning automata approach

Deadlock-free scheduling of parts is vital for increasing the utilization of an Automated Manufacturing System (AMS). An existing literature survey has identified the role of an effective modeling methodology for AMS in ensuring the appropriate scheduling of the parts on the available resources. In this paper, a new modeling methodology termed as Extended Color Time Net of Set of Simple Sequential Process with Resources (ECTS³PR) has been presented that efficiently handles dynamic behavior of the manufacturing system. The model is subsequently utilized to obtain a deadlock-free schedule with minimized makespan using a new Evolutionary Endosymbiotic Learning Automata (EELA) algorithm. The ECTS³PR model, which can easily handle various relations and structural interactions, proves to be very helpful in measuring and managing system performances. The novel algorithm EELA has the merits of both endosymbiotic systems and learning automata. The proposed algorithm performs better than various benchmark strategies available in the literature. Extensive experiments have been performed to examine the effectiveness of the proposed methodology, and the results obtained over different data sets of varying dimensions authenticate the performance claim. Superiority of the proposed approach has been validated by defining a new performance index termed as the ‘makespan index’ (MI), whereas the ANOVA analysis reveals the robustness of the algorithm.