基于模糊综合评判的MIE需求诊断方法

研究了制造业信息化工程需求分析的现状，提出并设计了基于模糊综合评判的制造业信息化工程需求诊断方法，实现了由定性分析向定量分析的转变，指出了该方法的研究重点在于建立需求评价指标体系和模糊关系矩阵，并围绕这一过程建立了最终判断制造企业信息化工程能力的逻辑关系模型。     

“制造强国”评价指标体系构建及初步分析

制造业是实体经济的主体、国民经济的支柱。本文描述了我国制造业"大而不强"的现实状况,借鉴国内外制造业产业评价体系的研究经验,确定了"制造强国"的内涵和特征,构建了包括四个一级指标和18个二级指标在内的"制造强国"综合评价体系,并以此为基础,对中国和其他几个国家的制造业指标横向对比进行了初步分析。     

Manufacturing lines under surplus-based control: multiple products and bounded buffers

Challenged by the scheduling complexity for production flow processes in industrial facilities, we study the performance of multi-product producing lines. We analyse the performance of multi-product lines that consist a number of machines and bounded buffers with preselected base stock levels. It is assumed that each manufacturing machine in the line is capable of working with several product types, but only operate on one product at a time. The network is operated under a surplus-based production control policy in the presence of perturbations and production demand fluctuations. We derive bounds on the demand tracking accuracy for each product type, regardless its flow direction in the multi-product line. In addition, for a multi-product line with unidirectional product flow, we obtain a quantitative relation between demand tracking accuracy, its inventory levels, numbers of product types, buffer capacity limits and perturbations. The accuracy of the obtained demand tracking bounds is illustrated by numerical simulations. By means of simulation experiments, we show that the obtained results have a valuable meaning and can be used as a reference tool in practice.     

Fuzzy adaptive preventive maintenance in a manufacturing control system: a step towards self-maintenance

In this paper, a framework of integrating preventive maintenance (PM) and manufacturing control system is proposed. Fuzzy-logic control is used to enable an intelligent approach of integrating PM and a manufacturing control system. This will contribute to the novel development of an integrated and intelligent framework in those two fields that are sometimes difficult to achieve. This idea is based on combining work on an intelligent real-time controller for a failure-prone manufacturing system using a fuzzy-logic approach (Yuniarto, M.N. and Labib, A.W., Optimal control system of an unreliable machine using fuzzy logic control: from design to implementation. Int. J. Prod. Res. (in press a); Yuniarto, M.N. and Labib, A.W., Intelligent real time control of disturbances in manufacturing systems. Integr. Manuf. Syst.: Int. J. Manuf. Technol. Manage. (in press b) and the work on PM proposed by Labib et al. (Labib, A.W., Williams, G.B. and O’Connor, R.F., An intelligent maintenance model (system): an application of analytic hierarchy process and a fuzzy logic rule-based controller. J. Oper. Res. Soc., 1998, 49, 745–757)). The aim of the research is to control a failure-prone manufacturing system and at the same time propose which PM method is applicable to a specific failure-prone manufacturing system. The mean time to repair and mean time between failures of the system are used as integrator agents, by using them to couple the two areas to be integrated (i.e. a maintenance system and manufacturing system).     

Analysis and improvement of multi-product assembly systems: an application study at a furniture manufacturing plant

In this paper, we introduce an application study of modelling, analysis and continuous improvement of an assembly system at a furniture manufacturing plant using production systems engineering methods. Analytical models have been developed to characterise the assembly system making multiple products, and recursive procedures have been derived to evaluate line production rate. Lot size analysis is carried out, and bottleneck analysis methods are introduced to identify the bottlenecks, whose improvement can lead to the largest improvement in system performance. Such methods provide a quantitative tool for plant engineers and managers to operate and improve assembly line with high productivity, and are also applicable to other large-volume manufacturing systems.     

基于精准识别的乡村振兴质量动态评价体系构建:逻辑框架与应用分析

乡村振兴战略的实施是破解我国“农业农村农民”问题的根本之策,构建一个可操作、科学的乡村振兴质量动态评价体系,则是更好地评价乡村振兴实施效果、部署乡村振兴各要素有效流动的重要基础。我国推进乡村振兴战略既要抓速度也要重质量,整齐划一的乡村振兴路径,可能会导致低质量的发展结果。《国家乡村振兴战略规划(2018—2022年)》第九章中,明确提出了“分类推进”乡村振兴的思想,就是为了充分考虑地区差异性,提出各具特色的乡村振兴路径。研究发现:第一,构建基于基础资源禀赋、区位资源禀赋、发展要素禀赋以及特色资源禀赋的前置乡村分类识别框架,并以县级数据进行测算,将全国1079个县按照前置指标识别分类;第二,应用前置分类的结果,提出了不同类型县域乡村振兴考核评价体系的权重建议,以引导不同地区主动探索符合自身特色的乡村振兴道路。研究进一步从政策制定、执行和评价三个方面为分类推进乡村振兴战略提出建议,不仅丰富了乡村振兴实践理论,也为中央和各级地方政府分类考核乡村振兴绩效提供了可操作的科学方法。     

基于DEA的制造系统全要素能源效率评价与优化

针对目前机械加工车间制造系统能源效率评价需要基于大量的机械加工试验来分析能量消耗,需要基于经验公式来获得能源效率指标,以及没有实现基于能效评价后的能效优化等问题,基于生产管理信息系统监测数据,提出一种制造系统全要素能源效率评价指标。用数据包络分析方法对机械加工车间制造系统全要素能源效率进行评价,使用能源效率优化分析方法构建能源效率函数关系,从而提出降低能耗和提高能源利用率的定量科学方法。最后以某变速箱装配车间为例,通过实例分析,验证该评价及优化方法的理论及应用价值。     

江西自然科学博物馆空调冷热源方案的技术经济分析

根据当地气候条件、空调负荷特性、自然环境、能源政策及政府文件资料,优选了两种空调冷热源方案,即水源热泵系统和水源热泵＋冰蓄冷系统。综合考虑方案特性、设备初投资、年运行费等因素,采用经济评价法对两种方案进行技术经济分析,并定量的计算了两种方案的能耗及其对环境的影响。最终确定水源热泵＋冰蓄冷系统为江西自然科学博物馆的空调冷热源方案。     

Analysis of Confidence Lower Limits of Reliability and Hazard Rate for Electronic Stability Control Systems

This article describes an evaluation method for reliability and hazard rate of lifetime distribution confidence lower limits for electronic stability control (ESC) system using test data from multistage and subsystems. This method provides estimation that can potentially and significantly reduce the amount of testing, without sacrificing the one‐sided confidence level of reliability. This also allows quicker design verification and validation for ESC systems. The method is derived under the assumption that the reliability parameter is a random variable with a given distribution function, and the product's reliability increases monotonously during the development process. This new method is applied to the analysis of reliability of an ESC system. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment of human reliability based on evaluation of plant experience: requirements and implementation

A major problem in assessment of human failures in probabilistic safety assessment is the lack of empirical data needed for human reliability analysis (HRA). This problem is aggravated by the fact that different HRA methods use different parameters for the assessment and that HRA is currently enforced to provide data and methods for assessment of human reliability in new technical environments such as computerized control rooms, in accident management situations, or in low-power and shut down situations. Plant experience is one source to deal with this problem. In this paper, a method is presented that describes how plant experience about human failures and human performance may be used to support the process of analyzing and assessing human reliability. Based on considerations of requirements of HRA, a method is presented first which is able to describe and analyze human interactions that were observed within events. Implementation of the approach as a database application is outlined. Second, the main results of the application of the method to 165 boiling water reactor events are presented. Observed influencing factors on human performance are discussed; estimates for probabilities are calculated and compared with the data tables of the THERP handbook. An outline is given for using the presented method for the analysis of cognitive errors or organizational aspects.     

Multivariate Statistical Process Control Based on Principal Component Analysis (MSPC-PCA): Some Reflections and a Case Study in an Autobody Assembly Process

In modern manufacturing processes, massive amounts of multivariate data are routinely collected through automated in-process sensing. These data often exhibit high correlation, rank deficiency, low signal-to-noise ratio and missing values. Conventional univariate and multivariate statistical process control techniques are not suitable to be used in these environments. This article discusses these issues and advocates the use of multivariate statistical process control based on principal component analysis (MSPC-PCA) as an efficient statistical tool for process understanding, monitoring and diagnosing assignable causes for special events in these contexts. Data from an autobody assembly process are used to illustrate the practical benefits of using MSPC-PCA rather than conventional SPC in manufacturing processes.