Manufacturing complexity and its measurement based on entropy models

Information-theoretic modeling of manufacturing organizations has led to the development of measures on the information of states of manufacturing systems. This paper provides an information-theoretic framework for the definition, measurement, and control of the states of manufacturing systems. Based on the information-theoretic entropy, the models of the static entropy and the dynamic entropy of manufacturing systems are developed, respectively. Scheduling is introduced to measure the manufacturing complexity and the feasible concepts of maximum schedule horizon and schedule adherence are advanced to quantitatively evaluate the effectiveness of schedules. Finally, an example is used to demonstrate the validity of the proposed methodology.     

制造系统复杂性度量方法研究

在对四种基于熵的制造系统复杂性定量方法及其应用性进行综合分析和比较的基础上，提出评价制造系统结构和过程复杂性的熵模型。该方法既可评价制造系统内每一独立维度的复杂性及其成本收益，也可对各维度之间的相互关系进行评价。随着系统维度及其相互关系的增加，评价的成本会按指数规律增加。通过成本收益评价．可以发现低效率的生产或加工过程，并明确改进方案的优先次序。     

Assessing the structural complexity of manufacturing systems configurations

Modern manufacturing systems are increasingly required to be flexible and adaptable to changing market demands, which adds to their structural and operational complexity. One of the major challenges at the early design stages is to select a manufacturing system configuration that both satisfies the production functional requirements and is easy to operate and manage. A new metric for assessing the structural complexity of manufacturing system configurations is presented in this paper. The proposed complexity metric incorporates the quantity of information using an entropy approach. It accounts for the complexity inherent in the various modules in the manufacturing system through the use of an index derived from a newly developed manufacturing systems classification code. The code captures the effect of various component types and technologies used in a manufacturing system on the system’s structural complexity. The presented metric would be helpful in selecting the least complex manufacturing system configuration that meets the requirements. An engine cylinder head production system is used to illustrate the application of the proposed methodology in comparing feasible but different manufacturing system configurations capable of producing the cylinder head based on their structurally inherent complexity.     

Data driven uncertainty evaluation for complex engineered system design

Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate structure decomposition, which limits their practical application. The rapid expansion of data makes utilizing data to guide and improve system design indispensable in practical engineering. In this paper, a data driven uncertainty evaluation approach is proposed to support the design of complex engineered systems. The core of the approach is a data-mining based uncertainty evaluation method that predicts the uncertainty level of a specific system design by means of analyzing association relations along different system attributes and synthesizing the information entropy of the covered attribute areas, and a quantitative measure of system uncertainty can be obtained accordingly. Monte Carlo simulation is introduced to get the uncertainty extrema, and the possible data distributions under different situations is discussed in detail. The uncertainty values can be normalized using the simulation results and the values can be used to evaluate different system designs. A prototype system is established, and two case studies have been carried out. The case of an inverted pendulum system validates the effectiveness of the proposed method, and the case of an oil sump design shows the practicability when two or more design plans need to be compared. This research can be used to evaluate the uncertainty of complex engineered systems completely relying on data, and is ideally suited for plan selection and performance analysis in system design.     

Object-oriented methods for manufacturing information systems

Object-oriented programming (OOP) is now widely used in application software development. OOP has advantages connected with handling complexity, reusability, extendability, modularity and data abstraction, enabling it to handle modern programming requirements more effectively than conventional programming methods. Successful advanced manufacturing systems demand increasing complexity, flexibility and integration between computer applications. An object-oriented approach is particularly promising for the design and development of manufacturing information systems. This paper outlines the concepts of object-oriented methods, and describes an object-oriented application development methodology for manufacturing information systems. A CASE (Computer-Aided Software Engineering) tool is used for system modelling and for direct source-code generation. A case study describing the development of a quality management information system is presented, which was implemented using a C++ development environment. Although the research described here is concerned with quality management information systems, the proposed design methodology is applicable to other areas of manufacturing, and conclusions are drawn concerning the uses of OOP in manufacturing information systems generally.     

基于状态熵的制造系统结构复杂性建模与评价

针对现有结构复杂性建模方法存在的不足,在考虑中间缓冲区状态对制造系统状态影响的基础上,提出一种基于通用发生函数法和信息熵理论的非串行制造系统结构复杂性建模与评价方法,从系统角度对制造系统的复杂性进行测度。通过建立中间缓冲区的状态转移方程,定义缓冲区的状态,分析中间缓冲区状态对非串行制造系统各工位加工设备状态的影响,将原制造系统转化为等效系统;利用通用发生函数法描述各等效加工设备的性能及其发生概率,并将制造系统分解成若干并联和串联子系统,引入并联和串联复合算子求解整个系统的发生函数,得到系统的状态空间及其对应的概率空间;从系统角度出发,利用信息论中的信息熵模型建立非串行制造系统的结构复杂性模型。以某车间的非串行缸盖柔性加工线为例,验证该模型与评价方法的有效性。     

基于信息熵的制造系统复杂性测度及其在调度中的应用

制造系统的复杂性是指制造系统难以被理解、描述、预测和控制的状态。从信息论角度指出制造系统的复杂度是描述制造系统的状态所预期需要的信息量。将制造系统的复杂性描述为静态和动态两种形式:静态复杂性是描述制造系统在静止状态下各制造资源根据其调度方案所预期拥有的状态所需要的信息量,动态复杂性则指描述制造系统在运行过程中各资源的实际状态所需要的信息量。应用信息论中的信息熵理论研究制造系统的复杂性测度问题,分别建立了基于信息熵的静态和动态复杂性测度模型。将上述复杂性理论应用于调度研究,提出最大可行调度时限和调度依附度两个评价调度有效性的量化指标,为调度有效性的分析、评价及改善提供了重要工具。实例研究表明所提理论和方法的有效性。     

Advanced RFID application for a mixed-product assembly line

Due to its scale, complexity, and uncertainty of the processes, the management and control of automotive manufacturing systems have been very challenging. With the recent application of new technologies such as radio frequency identification (RFID) to manufacturing process, real-time information has become available in manufacturing systems through IT infrastructures. It is expected that RFID-based real-time information will increase timeliness and efficiency in decision making and drastically reduce uncertainty. That, in turn, will enhance both productivity and quality. This paper presents an advanced RFID application for automotive assembly processes, specifically, dynamic material dispatching (e.g., auto assembly parts). The application is uniquely advanced in that it integrates RFID technology with a real-time decision support system to ensure the accurate and efficient delivery of auto parts to mixed-product assembly lines. In this application, we have described the problem as a mixed-integer programming model, proposed a heuristic algorithm that incorporates the available RFID information, and assessed the value of RFID through a scenario-based analysis. We hope this paper may help contribute to a virtuous cycle of RFID innovation and applications in the manufacturing sector.     

测量与控制系统动态误差溯源熵方法

误差溯源方法主要是尽可能使“黑箱”系统得到“白化”。论文提出应用动态熵值方法对测控系统进行误差溯源,讨论了测量与控制系统的输入、干扰信号分别对输出信号熵值的贡献,并建立了求取多维测量与控制系统的动态熵方法不确定度分量表达式,力求建立比较简明通用的误差溯源数学模型,使静态误差和动态误差有统一的分析研究方法。     

Economic and strategic perspectives on investing in RMS and FMS

The evolution of manufacturing systems, according to changing internal and external conditions, requires design and assessment techniques that consider both strategic and financial criteria to evaluate the suitability of the Flexible and Reconfigurable system solutions in addressing these variations. In this paper, a fuzzy multi-objective mixed integer optimization model to evaluate RMS investments used in a multiple product demand environment is presented. The model incorporates in-house production and outsourcing options, machine acquisition and disposal costs, operational costs, and re-configuration cost and duration for the utilized modular machines. The resulting system configurations are optimized for lifecycle costs, responsiveness performance, and system structural complexity simultaneously. A complexity metric that incorporates the quantity of information using an entropy approach is used to represent the inherent structural complexity of the considered system configurations. It accounts for the complexity of the machine modules in a manufacturing system through the use of an index derived from a newly developed manufacturing systems classification code, which captures the effect machine types and technologies on the system’s structural complexity. A metric is proposed to measure the responsiveness ability and efficiency as well as the overall capability of each machine and effectiveness of machines changeover. The application of the developed planning and assessment model that incorporates these three criteria is illustrated with a case study where FMS and RMS alternatives were compared. The suitable conditions for investing in RMS are also discussed.

Modeling of large-scale complex re-entrant manufacturing systems by extended object-oriented Petri nets

In this paper we propose an extended object-oriented Petri nets (EOPNs) for effective modeling of large-scale complex re-entrant manufacturing systems (ReMSs). To cope with their complexity because of the re-entrant process route and the mixed production mode, a special type of transition called a main-bus gate (MBG) is introduced, which can cause products to undergo every re-entrant manufacturing stage. A hierarchical approach is also applied to cope with the complexity. As a typical large-scale complex ReMS, the semiconductor wafer fabrication system (SWFS) is taken as an example for demonstrating the proposed EOPNs. A case study is provided to show the modelling procedures, and the resulting model validates that the EOPNs can cope well with the modelling complexity of large-scale complex ReMSs.     

Modeling and application of mixed model assembly system complexity introduced by auto-body personalization

Assembly system complexity, especially welding system complexity introduced by auto-body product personalization is regarded as a major contributor of uncertainty in the system planning and designing. The welding system complexity is defined based on information entropy theory, the station-level integrated complexity model, and system-level complexity flow model are established to obtain the complexity source of welding system. Complexity source sensitivity indices are proposed to indentify key station and key equipment that contribute most to the complexity. Based on the application of auto-body side welding line case, the result indicates that the proposed complexity model and key complexity source identifying and diagnosing process can be used as the decision support tool of auto-body welding system.     

Manufacturing process modelling using process specification language

The manufacturing process is one of the important processes in a product??s life cycle. The sharing of manufacturing process information among different functional application systems, such as process planning, manufacturing simulation, manufacturing execution and project management, has become difficult to implement due to the growing complexity of the manufacturing information of product, process, resource and plant. A unified representation of manufacturing process information for all applications can enable convenient integration between different application systems. The development of manufacturing-related ontology and the Process Specification Language (PSL) has provided a formal definition and structure of semantic concepts for the capture and the exchange of manufacturing information. This paper presents a manufacturing process information modelling method which builds a standard, complete and exact definition of manufacturing process data by applying current PSL specifications. New extensions of the concepts of the manufacturing process and the types of relationship for describing activities, materials and resources in a process are identified and developed. The completeness and adaptability of activity relation of the proposed manufacturing process information representation is verified using mathematical induction under a variety of complex manufacturing process situations. The ability of the modelling method in expressing complex process information is demonstrated by a machining process example.     

Object-based knowledge bases in automatic manufacturing environments

A manufacturing system is a very complex network of physical activities, decision making and information flows. Hence the complexity of the design and the integration of such a system increases with increases in the degree of automation. In this paper the authors propose to use the framework of an object-oriented knowledge base as the basis to, organise the knowledge in an automatic manufacturing environment. Such systems can provide significant advantages in terms of knowledge management, integrity control, object abstraction, design abstraction, and very high level programming. The power of this framework is illustrated in detail in the context of process planning, which is one of the major components of an automatic manufacturing environment. This research is supported by the National Science Foundation under grant number CDR-85-00022.     

An integrated fuzzy DEA–fuzzy C-means–simulation for optimization of operator allocation in cellular manufacturing systems

This paper presents an integrated fuzzy data envelopment analysis (FDEA), fuzzy C-means and computer simulation for optimization of operator allocation in cellular manufacturing systems (CMS). This is a challenging issue in flexible manufacturing systems in general and in CMS in particular. A computer simulation model, which considers various operators layout, is developed. For considering more information from computer simulation report, the output data is fuzzified. FDEA is utilized to assess simulation alternatives in various levels of uncertainty. In addition, FDEA ranking of decision-making units are clustered by fuzzy C-means method. Each of the clusters indicates a degree of desirability for operator allocation. Previous studies only utilize multivariate analysis methods and simulation, whereas this study uses an integrated simulation, fuzzy DEA, fuzzy C-means, and fuzzy indicators. Furthermore, previous CMS studies consider only one type of product, whereas this study considers multiproduct for CMS modeling through simulation. Moreover, more robust CMS assessment indicators are used in the proposed model. A practical case study illustrates the effectiveness and superiority of the proposed methodology. In addition, we compared the results of U shape with other production types, namely spiral, straight, L, W, zigzag, and Z. Moreover, we show that it dominates the other production types.     

基于多Agent的虚拟企业调度研究与实现

针对虚拟企业制造环境的不确定性、动态性和复杂性，运用多Agent技术实现生产调度系统的反应性和智能性．构建了虚拟企业生产调度系统体系结构；通过Agent能力匹配来实现任务分解；采用基于合同网的协商和多属性决策来解决虚拟企业调度问题中的任务分配和协作，利用集成的优化算法来自动处理调度优化问题，并进行了原型系统的开发。     

Makespan minimization for m-machine permutation flowshop scheduling problem with learning considerations

Increased complexity of current manufacturing systems together with dynamic conditions and permanent demands for flexible and robust functionality makes their management and control very difficult and challenging. Workflow simulation is an effective approach to investigate dynamic workflow scheduling policies and evaluate the overall manufacturing system performance. The results attained in simulation model can give directions on how to maximize system output when selecting an appropriate scheduling practice for a real system. In this paper, we investigate the abilities of multi-agent systems in combination with dynamic dispatching rules and failure handling mechanisms to manage dynamic environment conditions (such as machine failures) for systems in the production automation domain. We measure system robustness by systematically assessing the total system performance (e.g., number of finished products) in a number of representative test cases. We use an agent-based simulation environment, MAST, which has been validated with real-world hardware to strengthen the external validity of the simulation results. We investigated the performance of a re-scheduling component which uses four different policies that define how to adjust the system schedule in case of machine disturbances/failures. In the context of the empirical study the Complete Rerouting re-scheduling policy outperformed all other policies.     

基于数字孪生的复杂产品离散装配车间动态调度

面向多品种变批量生产的复杂产品离散装配车间是典型的复杂制造系统,其运行过程呈现高复杂性、强动态性和不确定性因素多等特征,为实现复杂产品离散装配车间的动态调度,提出一种基于数字孪生的复杂产品离散装配车间动态调度方法,通过物理空间和虚拟空间之间的数据交互进行更精确的动态调度.构建了基于数字孪生的复杂产品离散装配车间调度框架...     

冗余信标及其在Petri网结构控制中的应用

提出了冗余严格极小信标的概念 ,冗余信标是网拓扑的一种特殊结构。在保证网系统的所有信标不被清空时 ,只需要考虑那些非冗余的严格极小信标即可。这样便降低无死锁Petri控制器设计的复杂性 ,大大增强了Petri网处理复杂系统的能力。同时提出了一种死锁控制的迭代算法 ,使用冗余信标的概念可以大大简化Petri网的设计。以自动制造系统为例 ,说明了这种概念的应用。     

New criterion for evaluating the aptitude of measurement systems in process capability determination

In practice, carrying out statistical process control of manufacturing processes requires the use of measurement systems. These systems are not totally reliable because they are subject to inherent variability. This paper investigates the influence of measurement uncertainty on the analysis of manufacturing process capability. A new methodology is described that helps overcome the effect of measurement uncertainty in order to obtain a more accurate assessment of the capability of the production processes. This methodology presents a solution that ensures the metrological confirmation of the measurement processes, and it was developed for manufacturing processes centred at a nominal value and for off-centred processes. Moreover, an improved capability index integrated into the statistical process control is proposed for evaluating measurement systems. The index helps identify manufacturing process quality risks associated with uncertainty in measurement systems.