中小型制造类企业的可靠性管理研究

以IEC 60 300 <可信性管理>系列标准为依据,分析了国内中小型制造类企业的实际特点,并在此基础上对其可靠性管理工作进行了研究.探讨了建立健全中小型制造类企业可靠性管理的组织机构,包括阐述可靠性保证组织机构的设置原则和机构设置与机构职能;对可靠性管理工作的各个环节包括可靠性计划、可靠性设计、可靠性数据资料管理、可靠性设计评审及可靠性监督和保证等各方面的工作内容及程序逐一进行了描述.在科学的基础上对中小型制造类企业可靠性管理的具体应用进行了探索.     

A Methodology for Developing Maintenance Policy for Automated Manufacturing Plants

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面向制造的设计系统中的可制造性评价方法与应用

对面向制造的设计系统中的可制造评价进行了深入地探讨，     

对精益企业制造和维修的要求

维修是为制造业服务的。它保证达到产品的数量和质量，并为保障制造设备和环境保护服务。在精益企业中，必须将制造和维修融合在一起。人们必须考虑维修的不同投入部门和不同行业的结构。本文对要求和方法进行了描述。     

Reliability assessment for a stochastic manufacturing system with reworking actions

This article evaluates the system reliability of a manufacturing system with reworking actions, where the system reliability is an essential indicator to determine whether the manufacturing system is capable or not. Based on the path concept, we transformed the manufacturing system into a stochastic-flow network in which the capacity of each machine is stochastic (i.e., multistate) due to failure, partial failure, and maintenance. In such a manufacturing network, the input flow (raw materials/WIP; work-in-process) processed by each machine might be defective and thus the output flow (WIP/products) would be less than the input amount. To analyze the different sources processed by the manufacturing network, we decomposed the network into one general processing path and several reworking paths by a graphical technique. Subsequently, an algorithm for the manufacturing network was proposed to generate the lower boundary vector which allows sufficient products to satisfy the demand. In terms of such a vector, the system reliability can be derived easily.     

面向维修的机械系统可靠度预测与仿真研究

机电产品在服役期间因零件失效而产生故障,重组维修破坏了原有的系统可靠性模型,因而需要对设备可靠性问题重新进行研究和评价。基于机电系统中零件的失效时间分布密度函数,研究了在重组维护过程中机电系统服役期间零件年龄结构的分布规律,发展了机电系统可靠性数学模型。通过仿真研究,探讨了系统服役期间年龄结构、可靠度和失效率的发展规律,定量地研究了失效时间分布密度函数的参数对系统可靠度的影响。这对于评估机械系统的可靠性和全生命周期的失效率,制定合理的维修策略具有重要意义。     

Reliability evaluation and opportunistic maintenance policy based on a novel delay time model

The delay time concept is widely adopted in literature to model the two‐stage failure process of most industrial systems which can be divided into normal stage (from new to an initial point of a defect) and defective stage (from defect arrival point to failure). Most existing delay time models assume that the normal and defective stages are independent. A generalized delay time model is proposed in this paper by considering the dependence between the normal and defective stages which is reflected in the fact that they share the same external shock process. According to the definition of shot‐noise process, external shocks will incur random hazard rate increments in the two stages. The failure state is self‐announcing, whereas the defective state can only be detected by block‐based inspection or opportunistic inspection offered by unexpected shutdown due to unavoidable external factors. The system is correctively replaced upon the occurrence of a system failure or preventively replaced at the detection of a defective state. Based on the stochastic failure model and maintenance policy, this paper evaluates system reliability performance and average long‐run cost rate via a Markov‐chain based approach. Finally, a case study on a steel convertor plant is given to demonstrate the applicability of the proposed model.     

俄罗斯乳化炸药生产工艺与设备

文章论述了俄罗斯乳化炸药之现状、生产工艺、生产设备和产品性能.     

Reliability analysis of maintenance data for complex medical devices

This paper proposes a method to analyze statistically maintenance data for complex medical devices with censoring and missing information. It presents a classification of the different types of failures and establishes policies for analyzing data at the system and component levels taking into account the failure types. The results of this analysis can be used as basic assumptions in the development of a maintenance/inspection optimization model. As a case study, we present the reliability analysis of a general infusion pump from a hospital. Copyright © 2010 John Wiley & Sons, Ltd.     

钢铁企业实现可持续发展的途径

可持续发展战略是中国钢铁企业的必然选择。实施这一战略可以从环保、节能、资源的综合利用起步，以技术进步、环保投资为支撑，推进循环经济，从而为实现企业与社会长期和谐、协调一致的发展承担起应有的责任。     

新制造环境下的装备质量与可靠性研究

中国制造业大而不强的主要瓶颈之一是产品质量不高。而制约产品质量提高的重要因素是产品的可靠性。本文通过对产品可靠性形成机理的分析,提出应在产品设计阶段引入可靠性设计;为应对激烈的市场竞争,为提高可靠性设计的效率,提出了基于信息化的协同可靠性设计理论框架。     

Optimal reliability and maintainability allocation in manufacturing systems

In this article an attempt has been made to solve an important task in the reliability management of manufacturing systems: the definition of reliability and maintainability specifications of parts, the general objective being to increase productivity while maintaining costs low. An analytical approach has been considered to evaluate an average index of production capability in series-parallel systems. A heuristic optimization procedure has been developed to solve the following problems: (a) determine the optimal reliability and maintainability allocation of parts to achieve the maximum production index at a given cost; and (b) determine the optimal reliability and maintainability allocation of parts which minimizes the total cost of investments, subject to the constraint of meeting a system production requirement. Numerical examples prove the effectiveness of the proposed procedure and show that the application of optimization analyses can provide large gains in terms of either productivity or total cost.     

Identification and Assessment of Factors Influencing Human Reliability in Maintenance Using Fuzzy Cognitive Maps

Human element forms an inevitable part of maintenance activity and gets affected by a variety of interacting factors, ranging from environmental, organizational, job factors, and so on to personal characteristics, which bring in inherent variability in its reliability. Assessment of impact of these factors is, therefore, critical for human reliability estimation in maintenance. In every probabilistic risk, safety or maintenance analysis, human reliability does act as an effective aspect to assess implications of various aspects of the human performance. But the main constraint with various human reliability analysis methods is in judging the important human performance influencing factors. Because of high degree of uncertainty and variability that characterizes the plant maintenance environment, it is proposed to use the soft computing technique of fuzzy cognitive maps in exploring the importance of performance shaping factors in maintenance scenario. For this purpose, the maintenance environment is modeled in terms of factors affecting human reliability using cognitive maps. The causal relationships among these factors are explored and simulations performed to quantify its effect on the human reliability. The applicability of the methodology is demonstrated through an example. Copyright © 2013 John Wiley & Sons, Ltd.     

制造业信息化评价指标体系和方法研究

在分析中国制造业信息化水平评价现状的基础上,提出了制造业信息化评价指标体系。运用信度分析和效度分析确定正式评价指标体系和调查问卷。给出了制造业信息化指数的计算方法。最后对信息化指数进行了分析研究。     

Reliability Analysis and Comparison Between Automatic and Manual Load Haul Dump Machines

Today's trend of replacing manually operated vehicles with automated ones will have an impact not only on machine design, working environment and procedures but also on machine breakdown and maintenance procedures. In the harsh environment of underground mines, the transition from manual to automatic operation is believed to fundamentally change the basis for break downs, maintenance and machine design. In this paper, differences and similarities between manual and automatic underground loading equipment is analysed from a reliability point of view. The analysis is based on a case study performed at a Swedish underground mine. In the contrary of common thoughts, this paper proves that there is a difference between the manual and semi‐automatic machines and in particular for the transmission, in favour of the manual one. This paper also shows a path for detailed reliability analysis, and the results may be used for improving maintenance programmes for other types of mobile equipment. Copyright © 2013 John Wiley & Sons, Ltd.     

Fundamental Theories and Key Technologies for Smart and Optimal Manufacturing in the Process Industry

Given the significant requirements for transforming and promoting the process industry, we present the major limitations of current petrochemical enterprises, including limitations in decision-making, production operation, efficiency and security, information integration, and so forth. To promote a vision of the process industry with efficient, green, and smart production, modern information technology should be utilized throughout the entire optimization process for production, management, and marketing. To focus on smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of the manufacturing process, operating mode, and supply chain management, we put forward several key scientific problems in engineering in a demand-driven and application-oriented manner, namely: ① intelligent sensing and integration of all process information, including production and management information; ② collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; ③ cooperative control and optimization of plant-wide production processes via human-cyber-physical interaction; and ④ life-cycle assessments for safety and environmental footprint monitoring, in addition to tracing analysis and risk control. In order to solve these limitations and core scientific problems, we further present fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Although this paper discusses the process industry in China, the conclusions in this paper can be extended to the process industry around the world.     

Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis

Predictive maintenance (PdM) is an effective means to eliminate potential failures, ensure stable equipment operation and improve the mission reliability of manufacturing systems and the quality of products, which is the premise of intelligent manufacturing. Therefore, an integrated PdM strategy considering product quality level and mission reliability state is proposed regarding the intelligent manufacturing philosophy of ‘prediction and manufacturing’. First, the key process variables are identified and integrated into the evaluation of the equipment degradation state. Second, the quality deviation index is defined to describe the quality of the product quantitatively according to the co-effect of manufacturing system component reliability and product quality in the quality–reliability chain. Third, to achieve changeable production task demands, mission reliability is defined to characterise the equipment production states comprehensively. The optimal integrated PdM strategy, which combines quality control and mission reliability analysis, is obtained by minimising the total cost. Finally, a case study on decision-making with the integrated PdM strategy for a cylinder head manufacturing system is presented to validate the effectiveness of the proposed method. The final results shows that proposed method achieves approximately 26.02 and 20.54% cost improvement over periodic preventive maintenance and conventional condition-based maintenance respectively.     

Opportunities and Challenges of Artificial Intelligence for Green Manufacturing in the Process Industry

Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process-safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging information technologies such as artificial intelligence (AI) are quite promising as a means of overcoming these difficulties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety; ② knowledge-based reasoning for process safety; ③ accurate fusion of heterogeneous data from various sources; and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.     

Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme.