天津市农业物联网标准体系研究

近年来,随着物联网技术在农业生产中的广泛应用,农业物联网技术的标准问题已引起了社会的普遍关注。为了保证此项技术在天津市农业生产中运用得当,开展农业物联网标准化工作势在必行。本文针对目前这种情况,构建了一整套科学完整的农业物联网标准体系,用于强化标准实施监督,夯实标准化技术基础,促进农业物联网有序发展,为天津在农业现代化产业发展方面提供重要的标准技术支撑。     

Dynamic performance modelling and measuring for machine tools with continuous-state wear processes

In this paper, we consider the problem of using empirical continuous-state wear data of machine tools to estimate the dynamic lifetime distribution and to measure the performance of a machining process subject to stochastic tool-wear evolution. Machining systems are dynamic processes whose performance variable is usually characterised by the amount of tool wear that advances gradually with a continuous range of values. To accurately capture the performance of these continuous-state wear processes, neither traditional models such as the binary-state models nor multi-state models are suitable. In this paper, an exponential mixed-effects (EME) model is first developed. The EME model is subsequently transformed into a linear mixed-effects (LME) model to enhance the fit and predictability of the wear process data. The LME models take into consideration the correlations among repeated wear measurements collected at different time points within each subject. We then implement the expectation-maximisation (EM) algorithm to obtain the full maximum likelihood estimates (MLEs) of the parameters of the LME models whose asymptotic normal distributions can be used to acquire approximate confidence intervals and a testing hypothesis for the parameters. In addition, to measure the dynamic performance of tools, the amount of wear over time estimated from LME models is compared with a given tool-failure threshold. Consequently, we obtain the reliability of the tool and the estimation of its residual-lifetime distribution, which is critical information for the tool replacement or maintenance strategy. Finally, the lower and upper wear prediction limits of the 95% confidence level are presented. A practical application of the proposed methodology is illustrated throughout the paper.     

Estimation and monitoring of key performance indicators of manufacturing systems using the multi-output Gaussian process

Recently, the estimation and monitoring of manufacturing key performance indicators (KPIs) have drawn significant attention. In this article, a KPI estimation and monitoring method using a multi-output Gaussian process (MGP) is proposed. The Gaussian process (GP) is an effective non-parametric flexible tool for data-driven statistical modelling for various systems. The unique features of the proposed method is that the MGP enjoys the high flexibility and desirable analytical properties of the GP while also capturing the correlation between different KPIs, thus providing better estimation accuracy and error quantification. The advantageous features of the proposed method are demonstrated through a numerical study as well as a case study with real world data in the estimation and monitoring of throughput for a multiclass production operation.     

Impacts of using a performance measurement system in supply chain management: a case study

The study examines how the utilisation of a new performance measurement system (PMS) influences supply chain management (SCM) and what kind of impacts the new system has on the performance of the supply chain. The paper utilises a longitudinal research setting where the data was gathered in two semi-structured interview studies after an action research project in which a new measurement system was designed and developed. The findings show how a PMS serves as a catalyst of inter-organisational knowledge transfer and promotes shared learning. The results also show how knowledge transfer and shared learning led to improved performance of the supply chain. The paper contributes by opening up the practical mechanisms through which performance measurement provides value for SCM and by showing how inter-organisational transfer of performance information catalyses learning and performance improvement. The paper looks beyond the design of performance measures and provides a view on the practice of supply chain performance management. The paper illustrates how sharing performance information amongst supply chain companies improves managers’ awareness of shared targets and the status of network operations. This also resulted in improved performance in the studied case network. Overall, the results encourage organisations to engage in network-level performance measurement and share performance information with their network partners.     

Development of a financial management system in a CIMS environment

This research is based on the Anshan Project, a cool strip millwork computer integrated manufacturing system (LZ-CIMS). The study describes the design and completion of a LZ-CIMS financial management system that was developed using an Oracle database with client/server architecture and Developer/2000. During the development of the system, the study explores the use of both software engineering and database theory and Oracle RDBMS to discuss the integrating methods of financial information.     

Design and application of Internet of things-based warehouse management system for smart logistics

Warehouse operations need to change due to the increasing complexity and variety of customer orders. The demand for real-time data and contextual information is requried because of the highly customised orders, which tend to be of small batch size but with high variety. Since the orders frequently change according to customer requirements, the synchronisation of purchase orders to support production to ensure on-time order fulfilment is of high importance. However, the inefficient and inaccurate order picking process has adverse effects on the order fulfilment. The objective of this paper is to propose an Internet of things (IoT)-based warehouse management system with an advanced data analytical approach using computational intelligence techniques to enable smart logistics for Industry 4.0. Based on the data collected from a case company, the proposed IoT-based WMS shows that the warehouse productivity, picking accuracy and efficiency can be improved and it is robust to order variability.     

Cyber-based design for additive manufacturing using artificial neural networks for Industry 4.0

Additive Manufacturing (AM) requires integrated networking, embedded controls and cloud computing technologies to increase their efficiency and resource utilisation. However, currently there is no readily applicable system that can be used for cloud-based AM. The objective of this research is to develop a framework for designing a cyber additive manufacturing system that integrates an expert system with Internet of Things (IoT). An Artificial Neural Network (ANN) based expert system was implemented to classify input part designs based on CAD data and user inputs. Three ANN algorithms were trained on a knowledge base to identify optimal AM processes for different part designs. A two-stage model was used to enhance the prediction accuracy above 90% by increasing the number of input factors and datasets. A cyber interface was developed to query AM machine availability and resource capability using a Node-RED IoT device simulator. The dynamic AM machine identification system developed using an application programme interface (API) that integrates inputs from the smart algorithm and IoT interface for real-time predictions. This research establishes a foundation for the development of a cyber additive design for manufacturing system which can dynamically allocate digital designs to different AM techniques over the cyber network.     

环境模拟器低温泵测试系统设计

大口径低温泵测试系统可为环模设备低温泵提供完整的性能参数.本文介绍了一种大口径、大抽速低温泵的测试系统,对各分系统结构功能进行了详细描述.其使用流量法和流导法两种方法提供在1×10-6Pa至10 Pa范围内的抽速、预冷时间、极限真空度等参数的测量.此系统同时具有加热烘烤和可调节气体流量的功能.     

Changing role of maintenance in business organisations: measurement versus strategic orientation

The purpose of this study is to examine the nature of performance measures utilised by the maintenance function in today’s business organisations. In the process, the increasing variety and significance of these measures are addressed from operational and strategic perspectives. A survey-based research method was utilised to gather the research data. Several statistical procedures were utilised to analyse the data. The findings of this study point to the multifaceted nature of the maintenance measures and measurement. Multiple categories of maintenance measures were identified. These categories varied from the machine-specific, to measures impacting organisational performance. The relative lack of emphasis placed on the environment and strategic facets of maintenance is noted. The findings of this study have direct implications to organisations, which are attempting to measure the effectiveness of their maintenance efforts. The need to align the maintenance performance efforts with the organisational strategic direction is emphasised. In this context, the integration of the maintenance performance information systems with the overall organisational performance management information system might facilitate the needed alignment. This study utilises 120 maintenance measures. As such, it represents a comprehensive view of the maintenance effort.     

物联网技术在制冷空调行业中的应用

针对物联网技术在制冷空调行业中三个方面的应用进行分析,介绍了物联网技术在食品冷藏储运及实时监控中、制冷空调系统远程控制中、中央空调系统计费系统等方面的应用情况。     

Analysis and approximation for the performance of a workstation with various types of setups

Setups commonly exist in flexible manufacturing systems. Modelling the queue time correctly is of fundamental importance in evaluating the performance of manufacturing systems. An insightful classification is the first step towards correct modelling. Through the observation of practical production lines, two types of setups are classified: state-induced setups and product-induced setups. The product-induced setups can be a changeover setup or a replacement setup. Changeover setups are induced by switching manufacturing processes between products, whereas replacement setups are caused by changing components or consumables. Approximate models for the mean queue time of different setup types are proposed based on their distinct properties. The proposed models are validated with simulations and perform well in the examined cases.     

Dependability and performance stochastic modelling of a two-unit repairable production system with preventive maintenance

In this paper, a two-unit multistate repairable production system is considered in which preventive maintenance (PM) is implemented in order to improve its dependability and performance. A general model is provided for the production system using a semi-Markov process, for examining system’s limiting behaviour. Apart from combining redundancy with PM, we introduce scenarios like imperfect and failed maintenance which are usually met in real life production systems. For the proposed model, we calculate the availability, the mean time to failure and the total operational cost and we formulate optimisation problems settled with respect to the system’s inspection times. The main aim of our work is to determine the optimal inspection times and consequently the optimal PM policies to be adopted in order to optimise system’s dependability and performance.     

基于Web技术的IP网络性能测量系统的研究与实现

在分析了网络性能测量系统的功能和层次结构的基础上,设计并实现了一个利用Web技术测量IP网络性能的系统。系统基于分布式B／S架构,有效地简化了部署并增强了移植性,降低了开发和维护的成本。在模拟网络环境中的试验结果显示,系统测量结果准确可靠,测量速度快,代价低。     

Proactive environmental strategies and performance: role of green supply chain processes and green product design in the Chinese high-tech industry

Though many firms still believe that passive environmental strategies are sufficient, it is pertinent that they move beyond this belief and take a proactive supply chain-wide environmental stance so as to create a sustainable environment. In this paper, we seek to extend current work within green supply chain management by considering multiple green supply chain capabilities and performance measures. We hypothesise the linkage between environmental orientation, green supply chain capabilities and performance by drawing upon stakeholder theory and natural resource-based view. More importantly, our study is the first to distinguish between product and process-related capabilities in the green supply chain area and study their direct and mediating role with respect to environmental and financial performance measures. Using survey data collected from 256 Chinese-based high-tech firms, we analyse several hypothesised relationships. Our results provide strong support for the significant role that green product design and green supply chain processes can play in improving firms’ environmental and financial performance. Interestingly, our results also suggest that green product design may not have a direct impact on financial performance.     

Multi-class queueing models for performance analysis of computer systems

Queueing models, networks of queues in particular, have been found especially useful for estimating the performance of computer systems. Networks of queues with multiple customer classes provide a flexible framework for modelling computer systems, where a rich set of analytical results and techniques are available. When because of the complexity of the system being modelled the analytical results cannot be applied directly, they often point to fairly accurate approximation schemes. In this paper, we present a brief survey of some of the important results and techniques from the theory of multi-class queueing networks. We also present a case study to illustrate how these results and techniques are used in a real-life situation where many of the modelling constraints are violated.     

A framework with revised rough-DEMATEL to capture and evaluate requirements for smart industrial product-service system of systems

Smart industrial product-service system of systems (SiP-S3) is a new extension of industrial PSS via smart technology and SoS (system of systems) engineering. A framework with revised rough-DEMATEL method is proposed to capture and evaluate requirements for SiP-S3. From the various interactions in value stream mapping of SiP-S3, business, functional and non-functional requirements can be captured and converged into SiP-S3 requirements. Due to the interrelation between requirements of SiP-S3 and uncertainty of expert judgments, rough-DEMATEL is adopted but is revised in two aspects. Generally, SiP-S3 requirement items are plentiful, a set of programming code for rough set approximation is firstly given to reduce manual calculation burden. Moreover, compared to multiple operators of modified-CFCS (converting fuzzy values into crisp scores) plus SVL (single vector-length), a feasible and simpler operator of AVL (average vector-length) on rough-prominence and rough-relation is firstly devised to prioritise requirements. As such, roughness can be remained till at the end of calculation procedure to avoid uncertain assessment information loss. Surface mount technology (SMT) is not trivial in electronic manufacturing service industry, an illustrative case study of SMTE-S3 (SMT equipment-service system of systems) is demonstrated to verify feasibility and potential of proposal methodological framework.     

汽车制造企业制造过程质量管理信息系统的研究与开发

针对国内汽车制造企业在制造过程上存在质量信息管理工作无序、低效和成本较高的现象,以上海大众汽车有限公司为例,研究如何开发汽车制造过程的质量管理信息系统。根据汽车制造过程质量控制的特点分别阐述了系统需求分析、系统业务流程分析、系统数据流程分析和系统技术方案这4个关键开发环节的主要内容。     

Iot based laundry services: an application of big data analytics,intelligent logistics management,and machine learning techniques

The authors propose an innovative Internet of Things (IoT) based E-commerce business model Cloud Laundry for mass scale laundry services. The model utilises big data analytics, intelligent logistics management, and machine learning techniques. Using GPS and real-time update of big data, it calculates the best transportation path and update and re-route the logistic terminals quickly and simultaneously. Cloud laundry intelligently and dynamically provides the best laundry solutions based on the current state spaces of the laundry terminals through the user's specifications and thus offers local hotel customers with convenient, efficient, and transparent laundry services. Taking advantage of the rapid development of the big data industry, user interest modelling, and information security and privacy considerations, cloud laundry uses smartphone terminal control and big data models to maintain customers’ security needs. Different from the traditional laundry industry, cloud laundry companies have higher capital turnover, more liquidity, and stronger profitability. Therefore, this new generation of smart laundry business model could be of interest to not only academic researchers, but E-commerce entrepreneurs as well.     

客车空调系统性能测试方法设计

对原有焓差测试设备进行改进,利用焓差法实现客车空调性能测试,测试方法简单快捷、节约成本,且测试结果与设计值吻合较好。证明此方法可以在以后测试中继续使用。另外,在测试的同时,对电机温升情况进行观察,测试方法及试验间通风性能够满足电机绝缘等级要求。     

机械真空泵远程故障诊断系统研究与应用

真空精炼炉是一种用于生产高品质钢水的二次冶炼装置,其核心是机械真空泵系统.该系统能否长期稳定运行将直接影响到钢水冶炼效果和吨钢成本,因此对该系统进行在线监测和快速故障诊断尤为重要.本文以RH真空精炼炉为例,将各级机械真空泵与多种监控设备耦合,并引入远程物联网技术,创建了远程故障诊断系统,并得到国内某钢厂实践验证.