Towards a framework for energy-aware information systems in manufacturing

Environmental concerns, stricter legislation and inflated energy costs, together yield energy efficiency as an important pillar for virtually every industrial sector. Mindful of this challenge, ISs can act as enablers of energy-based management and intelligent decision support. Based on empirical evidence through two case studies combined with the design of a system prototype, this paper identifies those major functionalities that suffice to characterize an IS as ‘energy-aware’ in manufacturing. The functionalities are classified into two broad categories: (a) energy monitoring and (b) energy-aware analytics and are then combined into a high-level architecture. As a prerequisite for deploying such functionalities, this research presents also an approach integrating energy and operational information flows. Beyond that, the technologies that support the real-time and large-scale handling of energy data are provided. Our effort scales up to introduce a generic framework of a case-independent energy-aware IS.     

System construction for comprehensive industrial ecosystem oriented networked collaborative manufacturing platform (NCMP) based on three chains

In industrial manufacturing, with the deep integration and development of advanced digital technologies such as industrial big data, industrial Internet and industrial artificial intelligence with manufacturing industry, the manufacturing model is gradually developing and evolving from the direction of networking, platform, integration, collaboration and ecology. Therefore, for industrial manufacturing process, the research of construction of comprehensive industrial ecosystem oriented Networked Collaborative Manufacturing Platform (NCMP) system is great industrial application value by integrating network characteristics, platform elements, integrated mechanism, collaborative model and ecological format. In this paper, the system model of NCMP is constructed from four perspectives, including network perspective, collaborative manufacturing perspective, platform perspective, and industrial ecosystem perspective. Then, a system framework of NCMP based on three chains (manufacturing chain, value chain, and industrial chain) is proposed. Three collaborative subsystems of NCMP (vertical collaboration subsystem from multi perspective, horizontal collaboration subsystem from multi process, end to end collaboration subsystem from multi operator) are constructed. At last, a comprehensive system construction for NCMP in automobile industry is giving. The research results show that the most important elements to construct NCMP are purchasing department collaboration, demand department collaboration, design collaboration, data integration between enterprises and factories, etc.     

ManufAg: a multi-agent-system framework for production control of complex manufacturing systems

In this paper, we present a framework for the implementation of multi-agent-systems for production control of complex manufacturing systems. We present the results of a requirement analysis for production control systems for complex manufacturing systems; then we describe the framework design criteria. Our framework supports the inclusion of distributed hierarchical decision-making schemes into the production control. Furthermore, in order to increase the coordination abilities of multi-agent-systems, we follow the decision-making and staff agent architecture suggested in the PROSA reference architecture. We indicate the usage of the framework for designing and implementing an agent-based production control system for semiconductor manufacturing processes in a case study.     

蚂蚁算法在面向零件的网络化制造中的应用研究*

为了有效地实现网络制造环境下资源共享与优化配置,提出了协同制造链的概念,指出协同制造链是一种围绕零件制造过程的网络化制造动态联盟.在此基础上给出了协同制造链的定义和形式化描述,并以某航空发动机关键零件为具体应用研究对象,详细分析了协同制造链的构建和演化过程;同时,对协同制造链构建和演化过程中的关键问题--协同制造链排序进行了重点研究,建立了该问题的数学描述模型,设计并实现了一个基于蚂蚁算法的协同制造链排序策略.最后通过实例验证了该策略的有效性.     

Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation

Cloud-based design manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are enabled to configure, select, and utilize customized product realization resources and services ranging from computer-aided engineering software to reconfigurable manufacturing systems. An ongoing debate on CBDM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, communication and collaboration processes, crowdsourcing processes, information and communication infrastructure, programming models, data storage, and new business models pertaining to CBDM. One question, in particular, has often been raised: is cloud-based design and manufacturing actually a new paradigm, or is it just “old wine in new bottles”? To answer this question, we discuss and compare the existing definitions for CBDM, identify the essential characteristics of CBDM, define a systematic requirements checklist that an idealized CBDM system should satisfy, and compare CBDM to other relevant but more traditional collaborative design and distributed manufacturing systems such as web- and agent-based design and manufacturing systems. To justify the conclusion that CBDM can be considered as a new paradigm that is anticipated to drive digital manufacturing and design innovation, we present the development of a smart delivery drone as an idealized CBDM example scenario and propose a corresponding CBDM system architecture that incorporates CBDM-based design processes, integrated manufacturing services, information and supply chain management in a holistic sense.     

基于业务服务的企业遗留系统集成框架

企业应用集成(EAI)是当前企业进行业务扩展的一项主要技术,基于SOA实现EAI面临着一个重要的问题,如何将遗留系统无缝地连接到不断变化的新业务需求中.利用面向服务的架构来解决企业遗留系统应用集成.结合业务服务的概念和传统企业应用集成解决方案,讨论了基于业务服务的遗留系统应用集成框架,使用IBM平台对一个遗留销售系统集成案例进行了实现.     

Complex networks in advanced manufacturing systems

In recent years, with the rapid development of manufacturing, information, and management technology, advanced manufacturing systems (AMSs) have become increasingly more and more complex, which hinders the wider applications of many key theories and technologies in AMSs. Fortunately, in the last two decades, some dramatic advances have been made in the field of statistical physics theories, along with the extensive applications of complex network. It has provided an alternative approach to analyze AMSs. Many recent studies have focused on the theory of complex networks to describe and solve complicated manufacturing problems. Based on a great number of relevant publications, this paper presents an up-to-date literature review with the identified outstanding research issues, future trends and directions. Three critical issues are summarized after this investigation: (a) the focused areas of AMSs that have deployed the theory of complex networks, (b) the addressed issues and the corresponding approaches, and (c) the limitations and directions of the existing works.     

虚拟制造企业的Petri网建模/仿真

为降低Petri网建模难度并增强模型的可读性,提出一种通过消息序列表（Message Sequence Chart,MSC）模型对虚拟制造（Virtual Manufacturing,VM）企业的生产经营过程进行Petri网建模的新方法．建立冲突消解机制,给出从MSC模型到Petri网模型的转换算法,在不改变Petri模型活性、安全性和有界性等特性的基础上对其进一步优化,并对Petri网模型进行分析与评估．     

Agent learning in autonomic manufacturing execution systems for enterprise networking

In enterprise networks, companies interact on a temporal basis through client–server relationships between order agents (clients) and resource agents (servers) acting as autonomic managers. In this work, the autonomic MES (@MES) proposed by Rolón and Martinez (2012) has been extended to allow selfish behavior and adaptive decision-making in distributed execution control and emergent scheduling. Agent learning in the @MES is addressed by rewarding order agents in order to continuously optimize their processing routes based on cost and reliability of alternative resource agents (servers). Service providers are rewarded so as to learn the quality level corresponding to each task which is used to define the processing time and cost for each client request. Two reinforcement learning algorithms have been implemented to simulate learning curves of client–server relationships in the @MES. Emerging behaviors obtained through generative simulation in a case study show that despite selfish behavior and policy adaptation in order and resource agents, the autonomic MES is able to reject significant disturbances and handle unplanned events successfully.     

Object-oriented specification of automated manufacturing systems

The design of automated manufacturing systems (AMSs) requires an effective system specification that helps designers to deal with the changes in system requirements. This paper presents an object-oriented rule-based methodology for the specification of AMSs, which extends the capability of the existing object-oriented specification methods to support system integration and the explicit representation of control policies. The methodology is characterised by the use of rule-based modelling techniques to specify object behaviours in terms of processes. The application of the methodology is illustrated by the specification of a flexible manufacturing system.     

A methodological framework for evaluating environmentally conscious manufacturing programs

The evaluation of environmentally conscious manufacturing programs is similar to many strategic initiatives and their justification methodologies. This similarity arises from the fact that there are multiple factors that need to be considered, many of which have long-term and broad implications for an organization. The types of programs that could be evaluated range from the appropriate selection of product designs and materials to major disassembly programs that may be implemented in parallel with standard assembly programs. The methodology will involve the synthesis of the analytical network process (ANP) and data envelopment analysis (DEA). We consider some of the more recent modeling innovations in each of these areas to help us address a critical and important decision that many managers and organizations are beginning to face. An illustrative example provides some insights into the application of this methodology. Additional issues and research questions within are also identified.     

A framework using cluster-based hybrid network architecture for collaborative virtual surgery

Research on collaborative virtual environments (CVEs) opens the opportunity for simulating the cooperative work in surgical operations. It is however a challenging task to implement a high performance collaborative surgical simulation system because of the difficulty in maintaining state consistency with minimum network latencies, especially when sophisticated deformable models and haptics are involved. In this paper, an integrated framework using cluster-based hybrid network architecture is proposed to support collaborative virtual surgery. Multicast transmission is employed to transmit updated information among participants in order to reduce network latencies, while system consistency is maintained by an administrative server. Reliable multicast is implemented using distributed message acknowledgment based on cluster cooperation and sliding window technique. The robustness of the framework is guaranteed by the failure detection chain which enables smooth transition when participants join and leave the collaboration, including normal and involuntary leaving. Communication overhead is further reduced by implementing a number of management approaches such as computational policies and collaborative mechanisms. The feasibility of the proposed framework is demonstrated by successfully extending an existing standalone orthopedic surgery trainer into a collaborative simulation system. A series of experiments have been conducted to evaluate the system performance. The results demonstrate that the proposed framework is capable of supporting collaborative surgical simulation.     

A model-driven workflow fragmentation framework for collaborative workflow architectures and systems

This paper focuses on a workflow distribution methodology for rationally deploying workflow models onto a distributed workflow system running on cloud computing environments, and we particularly lay a stress upon that those workflow systems operable on cloud computing environments are dubbed collaborative workflow systems, which are not only built upon the collaborative workflow architectures proposed in the paper, but pursuing the so-called collaborative computing paradigm characterized by focusing collaboration over cloud computing environments. The essential idea of the workflow distribution methodology is about how to fragment a workflow model and how to allocate its fragments to each of the architectural components configuring the underlying collaborative workflow architecture and system. As a reasonable solution to realize the essential idea, the paper proposes a model-driven workflow fragmentation framework, which provides a series of fragmentation algorithms that semantically fragmentate a workflow model by considering the semantic factors - performer, role, control-flow, data-flow, etc. - of the ICN-based workflow model as fragmentation criteria. The algorithms are classified into the vertical fragmentation approach, the horizontal fragmentation approach, and the hybrid approach of both. Conclusively, this paper conceives a possible set of collaborative workflow architectures embedding the collaborative computing paradigm, and describes the detailed formalism of the framework and about how the framework works on those collaborative workflow architectures and systems.     

Category theory-based collaborative design methodology for mechatronic systems

Recent advances in companies are characterized by highly dynamic, knowledge-intensive and collaborative process. This has become primary concern for mechatronic systems since they involve multiple disciplines and knowledge. This requires a close exchange in order to share knowledge between the different design teams. The first step in knowledge sharing is to identify the most important knowledge that need to be capitalized, which we call “crucial knowledge”. During this exchange, heterogeneous knowledge and modelling languages are involved in the design process, which can lead to conflicts. Hence, the challenge is to continuously capture and handle such conflicts between expert models. Thus, the focus of this paper is to propose a new collaborative design model suitable for mechatronic concurrent design. Our contribution lies in identifying crucial knowledge and resolving conflicts in a formal way in order to ensure efficient collaboration. Our methodology called Category Theory-based Collaborative Design (CaTCoD) is described with its associated meta-model. A demonstrator is also used to validate the proposed methodology using an example from the aeronautic field.     

Semantic communications between distributed cyber-physical systems towards collaborative automation for smart manufacturing

Machine-to-machine (M2M) communication is a crucial technology for collaborative manufacturing automation in the Industrial Internet of Things (IIoT)-empowered industrial networks. The new decentralized manufacturing automation paradigm features ubiquitous communication and interoperable interactions between machines. However, peer-to-peer (P2P) interoperable communications at the semantic level between industrial machines is a challenge. To address this challenge, we introduce a concept of Semantic-aware Cyber-Physical Systems (SCPSs) based on which manufacturing devices can establish semantic M2M communications. In this work, we propose a generic system architecture of SCPS and its enabling technologies. Our proposed system architecture adds a semantic layer and a communication layer to the conventional cyber-physical system (CPS) in order to maximize compatibility with the diverse CPS implementation architecture. With Semantic Web technologies as the backbone of the semantic layer, SCPSs can exchange semantic messages with maximum interoperability following the same understanding of the manufacturing context. A pilot implementation of the presented work is illustrated with a proof-of-concept case study between two semantic-aware cyber-physical machine tools. The semantic communication provided by the SCPS architecture makes ubiquitous M2M communication in a network of manufacturing devices environment possible, laying the foundation for collaborative manufacturing automation for achieving smart manufacturing. Another case study focusing on decentralized production control between machines in a workshop also proved the merits of semantic-aware M2M communication technologies.     

Research on group awareness of networked collaboration within the design team and between teams

Group awareness is the critical content of collaboration in a networked collaborative design team, and it is a meaningful way to study teamwork efficiency. However, existing methods that describe awareness information are not comprehensive. They all set an ideal collaborative environment of the single role and single activity, ignoring the bidirectional and overlapping of the collaboration process. To meet this gap, a novel group awareness method for the networked collaboration design team is proposed in this paper from the actual collaborative process. Firstly, the awareness information granularity in the joint work of the networked collaborative design team is described in detail, and the group awareness model is established. Then, the intra- and inter-team collaboration of networked collaborative design team is quantified, and correspondingly, combined with the degree of cooperation between members, a method for solving the group awareness ability of intra- and inter-team association by adopting awareness calculation is presented. Last, to illustrate the feasibility of the suggested approach, a vehicle interior collaborative design task is taken as an example. This study can provide practical guidance for a related design service platform to optimize team collaboration efficiency and select team members objectively and fairly.     

Absolute stability and stabilization for Lurie networked control systems

This paper investigates the problem of absolute stability and stabilization for networked control systems (NCSs) with the controlled plant being Lurie systems (Lurie NCSs), in which the network‐induced delays are assumed to be time‐varying and bounded. By considering the relationship between the network‐induced delay and its upper bound, an improved stability criterion for networked control system is proposed. Furthermore, the resulting condition is extended to design a state feedback controller by employing an improved cone complementary linearization (ICCL) algorithm. A numerical example is worked out to illustrate the effectiveness and the benefits of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

Online merchant resource allocation and matching for open community collaborative manufacturing (OCCM) in mass personalization model

In order to meet the requirements of customers' pursuit of personalized and diversified needs, enterprises need to change from the traditional mass manufacturing model to mass personalization manufacturing model. On the other hand, collaborative manufacturing based on stakeholders will effectively solve the problems of information asymmetry, low operational efficiency and insufficient resource utilization in the process of manufacturing. Moreover, the new model of open community manufacturing is conducive to the planning, allocation, optimization and management of various networked and social resources. Therefore, combined with above three innovative models of mass personalization manufacturing, collaborative manufacturing and open community manufacturing, this paper studies the online merchant resource allocation and matching of open community collaborative manufacturing (OCCM) for mass personalization (MP) model to realize the innovation of design model, improve design efficiency and save design resource cost. Firstly, the workflow for OCCM in MP model based on system engineering analysis method is studied. Secondly, online merchant resource allocation for OCCM based on social network analysis (SNA) and online merchant resource matching for OCCM based on fuzzy clustering are proposed. At last, a case study for OCCM in the automotive industry is given to verify the effectiveness of the proposed model and methods.     

Simulation aided design of organizational structures in manufacturing systems using structuring strategies

This paper presents a simulation aided approach for designing organizational structures in manufacturing systems. The approach is based on a detailed modeling and characterization of the forecasted order program, especially of elementary processes, activity networks and manufacturing orders. Under the use of the organization modeling system FORM, that has been developed at the ifab-Institute of Human and Industrial Engineering of the University of Karlsruhe, structuring strategies—e.g., a process-oriented strategy—can be applied in order to design organizational structures in manufacturing systems in a flexible and efficient way. Following that, a dynamical analysis of the created manufacturing structures can be carried out with the simulation tool FEMOS, that has also been developed at the ifab-Institute. The evaluation module of FEMOS enables to measure the designed solutions with the help of logistical—e.g., lead time degree—and organizational—e.g., degree of autonomy—key data. This evaluation is the basis for the identification of effective manufacturing systems and also of improvement potentialities. Finally, a case study is presented in this paper designing and analyzing different organizational structures of a manufacturing system where gear boxes and robot grip arms were manufactured.     

A belief-theoretic framework for the collaborative development and integration of para-consistent conceptual models

Merging and integrating different conceptual models which have been collaboratively developed by domain experts and analysts with dissimilar perspectives on the same issue has been the subject of tremendous amount of research. In this paper, we focus on the fact that human analysts’ opinions possess a degree of uncertainty which can be exploited while integrating such information. We propose an underlying modeling construct which is the basis for transforming conceptual models into a manipulatable format. Based on this construct, methods for formally negotiating over and merging of conceptual models are proposed. The approach presented in this paper focuses on the formalization of uncertainty and expert reliability through the employment of belief theory. The proposed work has been evaluated for its effectiveness and usability. The evaluators (a group of Computer Science graduate students) believed that the proposed framework has the capability to fulfil its intended tasks. The obtained results from the performance perspective are also promising.