Ubiquitous conceptual design of a ubiquitous application: A textile SME case study for real time manufacturing monitoring

Advances in Information and Communication Technologies (ICT), computing, networking, mechanics and electronics are changing the people’s way of life. Several research efforts are leading the design and development of Artifact and Service Combination (ASC) with the implementation of Ubiquitous Technologies (UTs) in multidisciplinary sectors. However, the design process of such systems often ends in the implementation of conventional approaches and tools. A Ubiquitous Design Support Environment (UDSE) comprising an application intended to guide the different activities, tools and resources applied at the conceptual design stage is presented. After needs analysis, multidisciplinary collaborations are also required in order to generate innovative conceptual solutions, focusing this approach in the conceptual design stage of traditional design methods. Some activities from the conceptual design stage are enhanced through the use of the UDSE as well as through the use of a novel ubiquity assessment tool for concept selection and validation of Ubiquitous Products and Services. Finally, a case study on a Small and Medium Enterprise (SME) from textile sector, in a developing country, is presented to analyze and validate the presented concepts.     

Robust strategies for diagnosing manufacturing defects

We describe several strategies used by expert troubleshooters performing a manufacturing screening task, the diagnosis of defects on a computer board. These strategies use "inexact models" of the components and connections on the board. A prototype expert system has been implemented that uses the strategies and models. The strategies and models are robust because they are applicable to a wide range of problems, including problems not previously encountered. The system saves useful data acquired during problem solving to assist in future problems. We also describe how the above strategies and models can be used in a sensorbased system that acquires information about the board through a vision camera and other sensing devices. This will further increase the productivity of human troubleshooters.     

Tool-provisioning strategies for flexible manufacturing systems

The difficulties encountered in managing the tool flow in flexible manufacturing systems for the manufacture of prismatic parts indicate the requirement to handle operational issues such as tool assignment. The choice of operational strategy and its relationship to machine specification, work and tool loading, scheduling and specific mode of tool management may significantly enhance machine utilization and work throughput. In this paper, strategies are presented aimed at improving system efficiency and minimizing tooling costs by considering tool provision as work-orientated, where the tooling is changed to suit the production task, or tool-orientated, where resident tools dictate the work flow, or a combination of the two. This paper draws on evidence from current industrial practice and recent developments.     

Semi-supervised adaptive feature analysis and its application for multimedia understanding

Multimedia understanding for high dimensional data is still a challenging work, due to redundant features, noises and insufficient label information it contains. Graph-based semi-supervised feature learning is an effective approach to address this problem. Nevertheless, Existing graph-based semi-supervised methods usually depend on the pre-constructed Laplacian matrix but rarely modify it in the subsequent classification tasks. In this paper, an adaptive local manifold learning based semi-supervised feature selection is proposed. Compared to the state-of-the-art, the proposed algorithm has two advantages: 1) Adaptive local manifold learning and feature selection are integrated jointly into a single framework, where both the labeled and unlabeled data are utilized. Besides, the correlations between different components are also considered. 2) A group sparsity constraint, i.e. l _2?,?1-norm, is imposed to select the most relevant features. We also apply the proposed algorithm to serval kinds of multimedia understanding applications. Experimental results demonstrate the effectiveness of the proposed algorithm.     

Optimal search strategies for speech understanding control

This paper describes two algorithms for finding the optimal interpretation of an unknown utterance in a continuous speech understanding system. These methods guarantee that the first complete interpretation found will be the best scoring interpretation possible. Moreover, unlike other optimal strategies, they do not make finite-state assumptions about the nature of the grammar for the language being recognized. One of the methods, the density method, is especially interesting because it is not an instance of the ‘optimal’ $\text{A1}$ algorithm of Hart, Nilsson, and Raphael, and appears to be superior to it in the domains in which it is applicable. The other method, the shortfall method, is an instance of the $\text{A1}$ algorithm using a particular heuristic function. Proofs of the guaranteed discovery of the best interpretation and some empirical comparisons of the methods are given. The relationship of these methods to strategies used in existing speech understanding systems is also discussed. Although presented in the speech context, the algorithms are applicable to a general class of optimization and heuristic search problems.     

Novel strategies for global manufacturing systems interoperability

This paper reviews some of the most recently reported research into novel strategies for global manufacturing systems interoperability. Such research can be categorised as addressing four broad topic areas: the sensing manufacturing enterprise; semantics and knowledge management in manufacturing; service orientation and the need for negotiation; and business interoperability. Thus we identify a spectrum of research from the management of hardware and virtual sensing devices, through the semantic interpretation of the data and information generated by these, and its utilisation to support the collaborative manufacturing network lifecycle through service oriented software, and ultimately the provision of effective business interoperability. This study includes conceptual, theoretical, empirical and technological contributions, illustrated by real examples and demonstrating the novelty in comparison with previously reported results. The paper concludes elaborating final considerations on novel strategies for global manufacturing systems interoperability.     

Non-centralised control strategies for energy-efficient and flexible manufacturing systems

The manufacturing industry is transforming towards smart, energy-efficient, and flexible manufacturing systems. In this regard, this work deals with the design of non-centralised control architectures to improve the energy efficiency of such systems and to promote their flexibility. Based on both the configuration of manufacturing systems and their coupling dynamics, these systems are divided into sub-systems, from which smaller control problems can be stated. Thus, control/management strategies can also be modularised to confer more flexibility to manufacturing systems. Then, by using suitable distributed optimisation techniques, and properly defining the consensus stages among the local controllers, the outputs from such controllers are optimally coordinated to minimise the total energy consumption of the whole system. The proposed control strategies are tested in simulation for a typical process line of automotive parts manufacturing industry, in which the main processing units are machine tools. Based on the obtained results, manufacturing systems and their control strategies could be suitably modularised using non-centralised control schemes, from which a closed-loop performance similar to its centralised counterpart can be achieved.     

A framework for variation visualization and understanding in complex manufacturing systems

This paper provides a framework that allows industrial practitioners to visualize the most significant variation patterns within their process using three-dimensional animation software. In essence, this framework complements Phase I statistical monitoring methods by enabling users to: (1) acquire detailed understanding of common-cause variability (especially in complex manufacturing systems); (2) quickly and easily visualize the effects of common-cause variability in a process with respect to the final product; and (3) utilize the new insights regarding the process variability to identify opportunities for process improvement. The framework is illustrated through a case study using actual dimensional data from a US automotive assembly plant.     

制造执行系统柔性应用框架研究

针对制造执行系统应用开发的复杂性,提出了一个制造执行系统的柔性应用框架。在多层服务体系结构的基础上,该应用框架通过运用面向过程的对象分析技术、基于规则的事件服务机制和业务工程分析技术,提供可重构的组织结构、可伸缩的业务流程和可定制的业务规则,使得系统开发和实施的柔性得以提高。同时,运用该柔性框架,对一个实例进行分析和实现。     

基于云平台的共享制造模式定价策略

在共享制造背景下,设备制造商可以通过两种方式向消费者提供服务:直接出售生产型设备给消费者,通过云平台提供制造服务:在购买模式下,讨论消费者的决策行为以及设备制造商的最优定价策略;在服务模式下,采用逆向归纳法分别求解基于商业性云平台(最大化自身收益)和基于公益性云平台(最大化社会总效益)的多阶段动态博弈问题.通过比较两种...     

中小企业适用的防火墙方案

中小企业是一个庞大的群体,许多业务或生产流程非常紧密地依赖于网络来实现,网络安全对它们来说是可能是一个攸关生存的问题.针对中小企业网络的具体特点,寻求一个技术合理,稳定可靠的防火墙方案,对解决网络安全问题非常重要.     

Agile MPC system linking manufacturing and market strategies

Increasing complexity and interdependency in manufacturing enterprises require an agile manufacturing paradigm. This paper considers a dynamic control approach for linking manufacturing strategy with market strategy through a reconfigurable manufacturing planning and control (MPC) system to support agility in this context. A comprehensive MPC model capable of adopting different MPC strategies through distributed controllers of inventory, capacity, and WIP is presented. A hierarchical supervisory controller (referred to as decision logic unit, DLU) that intakes the high-level strategic market decisions and constraints together with feedback of the current manufacturing system state (WIP, production, and inventory levels) and optimally manages the distributed controllers is introduced. The DLU architecture with its three layers and their different functionalities is discussed showing how they link the higher management level to the operational level to satisfy the required demand. A case study for an automatic PCB assembly factory is implemented to demonstrate the applicability of the whole approach. In addition, a comparative cost analysis study is carried out to compare between the developed agile MPC system and classical-inventory- and capacity-based MPC policies in response to different demand patterns. Results showed that the developed agile MPC policy is as cost effective as the inventory-based MPC policy in demand patterns with steady trends, as cost effective as capacity-based MPC in turbulent demand patterns, and far superior than both classical MPC polices in mixed-demand patterns.     

中小企业适用的防火墙方案

中小企业是一个庞大的群体,许多业务或生产流程非常紧密地依赖于网络来实现,网络安全对它们来说是可能是一个攸关生存的问题。针对中小企业网络的具体特点,寻求一个技术合理,稳定可靠的防火墙方案,对解决网络安全问题非常重要。     

Cultural dependency analysis for understanding speech emotion

Speech has been one of the major communication medium for years and will continue to do so until video communication becomes widely available and easily accessible. Although numerous technologies have been developed to improve the effectiveness of speech communication system, human interaction with machines and robots are still far from ideal. It is acknowledged that human can communicate effectively with each other through the telephony system. This situation motivates many researchers to study in depth the human communication system, with emphasis on its ability to express and infer emotion for effective social communication. Understanding the interlocutors’ emotion and recognizing the listeners’ perception is the key to boost communication effectiveness and interaction. Nonetheless, the perceived emotion is subjective and very much dependent on culture, environment and the pre-emotional state of the listener. Attempts have been made to understand the influence of culture in speech emotion and researchers have reported mixed findings that lead us to believe there are some common acoustical characteristics that enable similar emotion to be discriminated universally across culture. Yet there are unique speech attributes that facilitate exclusive emotion recognition of a particular culture. Understanding culture dependency is thus important to the performance of the speech emotion recognition system.In this paper three different speech emotion databases; namely: Berlin Emo-db, NTU_American and NTU_Asian dataset were selected to represent three different cultures of European, American and Asian respectively focusing on three basic emotions of anger, happiness and sadness with neutral acting as a reference. Different data arrangements with accordance to varying degree of culture dependency were designed for the experimental setup to provide better understanding of inter-cultural and intra-cultural effect in recognizing the speech emotion. Features were extracted using Mel Frequency Cepstral Co-efficient (MFCC) method and classified with neural network (Multi Layer Perceptron (MLP)) and fuzzy neural networks; namely: Adaptive Network Fuzzy Inference System (ANFIS) and Generic Self-Organizing Fuzzy Neural Network (GenSOFNN) representing precise and linguistic fuzzy rule conjuncts respectively. From the experimental results, it can be observed that culture influences the speech emotion recognition accuracy. 75% accuracy performance was recorded for generalized homogeneous intra-cultural experiments whereas the accuracy performance dropped to almost as low as chance probability (25% for 4 classes) for both homogeneous and heterogeneous mixed-cultural inter-culture experiments. The two-stage culture-sensitive speech emotion recognition approach was subsequently proposed to discriminate culture and speech emotion. Results of the analysis show potential of using the proposed technique to recognize culture-influenced speech emotion, which can be extended in many applications, for instance call center and intelligent vehicle. Such analysis may help us to better understand the culture dependency of speech emotion and as a result the accuracy performance of the speech emotion recognition system can be boosted.     

Evaluation of techniques for manufacturing process analysis

In the last 20 years, several methodologies, models and tools have been developed for the analysis and optimisation of manufacturing systems in order to propose general improvements. Many of these techniques make extensive use of data modelling, simulation, decision-making support, expert systems and reference models. This paper presents the first outcome of a piece of research work to integrate manufacturing process analysis into an integrated modelling framework covering all aspects related to the shop-floor as it really is. The main methodologies and software tools have been identified and evaluated and the results tested on industrial examples. As a result of this evaluation it has been possible to identify the inefficiencies of the techniques. These problems are connected with integrating the different types of data to be analysed—such as quality, time, costs, resource capacity, productivity, flexibility or improvements—into a single analysis environment. The inefficiencies detected enable us to present a general framework for making better use of modelling techniques for manufacturing process analysis. Received July 2005 / Accepted January 2006     

Mining transportation logs for understanding the after-assembly block manufacturing process in the shipbuilding industry

In the after-assembly block manufacturing process in the shipbuilding industry, domain experts or industrial managers have the following questions regarding the first step in terms of reducing the overhead transportation cost due to irregularities not defined in a process design: “What tasks are bottlenecks?” and “How long do the blocks remain waiting in stockyards?” We provide the answers to these two questions. In the process mining framework, we propose a method automatically extracting the most frequent task flows from transport usage histories. Considering characteristics of our application, we use a clustering technique to identify heterogeneous groups of process instances, and then derive a process model independently by group. Process models extracted from real-world transportation logs, are verified by domain experts and labelled based on their interpretations. Consequently, we conceptualize the “standard process” from one global process model. Moreover, local models derived from groups of process instances reflect unknown context regarding characteristics of blocks. Our proposed method can provide conceptualized process models and process (or waiting in stockyards) times as a performance indicator. Providing reasonable answers to their questions, it helps domain experts better understand and manage the actual process. With the extension of the conventional methodology for our application problem, the main contributions of this research are that our proposed approach provides insight into the after-assembly block manufacturing process, and describes the first step for reducing transportation costs.