New Shop Floor Control Approaches for Virtual Enterprises

The virtual enterprise paradigm seems a fit response to face market instability and the volatile nature of business opportunities increasing enterprise’s interest in similar forms of networked organisations. The dynamic environment of a virtual enterprise requires that partners in the consortium own reconfigurable shop floors. This paper presents new approaches to shop floor control that meet the requirements of the new industrial paradigms and argues on work re-organization at shop floor level.virtual enterprise; networked organisations

Achieving manufacturing excellence through the integration of enterprise systems and simulation

This paper discusses the significance of the enterprise systems and simulation integration in improving shop floor’s short-term production planning capability. The ultimate objectives are to identify the integration protocols, optimisation parameters and critical design artefacts, thereby identifying key ‘ingredients’ that help in setting out a future research agenda in pursuit of optimum decision-making at the shop floor level. While the integration of enterprise systems and simulation gains a widespread agreement within the existing work, the optimality, scalability and flexibility of the schedules remained unanswered. Furthermore, there seems to be no commonality or pattern as to how many core modules are required to enable such a flexible and scalable integration. Nevertheless, the objective of such integration remains clear, i.e. to achieve an optimum total production time, lead time, cycle time, production release rates and cost. The issues presently faced by existing enterprise systems (ES), if properly addressed, can contribute to the achievement of manufacturing excellence and can help identify the building blocks for the software architectural platform enabling the integration

Recent developments and future trends of industrial agents

The agent technology provides a new way to design and engineer control solutions based on the decentralization of control over distributed structures, addressing the current requirements for modern control systems in industrial domains. This paper presents the current situation of the development and deployment of agent technology, discussing the initiatives and the current trends faced for a wider dissemination and industrial adoption, based on the work that is being carried out by the IEEE IES Technical Committee on Industrial Agents

Application of auto-ID in agent-based manufacturing control

Conference Theme: Soft Computing Techniques for Advanced Manufacturing and Service SystemsSession - MA-Ha Manufacturing Technologies 1: cie177hk-1A feasibility study has been established to integrate agent and auto-ID technologies in manufacturing control applications. A multi-agent system (MAS) framework for intelligent manufacturing has been established. The intelligent MAS environment attempts to exploit the potential of Auto-ID (RFID in particular) technology in manufacturing applications. The aim is to evaluate the applications of Auto-ID, especially with RFID technology, in manufacturing control. This involves the establishment of the hardware and software interfaces to enable production and process data to be recorded and written in the Auto-ID devices. Experiments are being conducted to study the working requirements and parameters of the Auto-ID devices in the shopfloor environments. Subsequently, the RFID technology is adopted in a flexible assembly cell (FAC) to evaluate the feasibility of integrating the RFID devices in a multi-agent based manufacturing control system. A MAS infrastructure for FAC control has been developed to incorporate the coordination of the RFID devices.published_or_final_versionThe 40th International Conference on Computers & Industrial Engineering (CIE40), Awaji City, Japan, 25-28 July 2010. In Proceedings of the International Conference on Computers and Industrial Engineering, 2010, p. 1-

Scheduling Algorithms: Challenges Towards Smart Manufacturing

Collecting, processing, analyzing, and driving knowledge from large-scale real-time data is now realized with the emergence of Artificial Intelligence (AI) and Deep Learning (DL). The breakthrough of Industry 4.0 lays a foundation for intelligent manufacturing. However, implementation challenges of scheduling algorithms in the context of smart manufacturing are not yet comprehensively studied. The purpose of this study is to show the scheduling No.s that need to be considered in the smart manufacturing paradigm. To attain this objective, the literature review is conducted in five stages using publish or perish tools from different sources such as Scopus, Pubmed, Crossref, and Google Scholar. As a result, the first contribution of this study is a critical analysis of existing production scheduling algorithms\u27 characteristics and limitations from the viewpoint of smart manufacturing. The other contribution is to suggest the best strategies for selecting scheduling algorithms in a real-world scenario

Coordinating complex problem-solving among distributed intelligent agents

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet

Agent-based real-time assembly line management for wireless job shop environment

Recent developments in wireless technologies have created opportunities for developing next-generation manufacturing systems with real-time traceability, visibility and interoperability in shop floor planning, execution and control. This paper discusses how to deploy wireless and intelligent technologies to convert physical objects in manufacturing systems into smart objects to introduce and improve the interoperability and visibility between them and thus with manufacturing decision support systems. A reference architecture for wireless manufacturing (WM) is proposed where three types of smart objects are identified. At the same time, the concept of smart object agent (SOA) is presented and the corresponding framework of smart objects management system (SOMS) is constructed. Under this framework and the concept of SOA, a SOA-based WM environment is studied and demonstrated using a near real-life simplified product assembly line for the collection and synchronization of the real-time field data from manufacturing workshops. © 2010 IEEE.published_or_final_versionThe IEEE International Conference on Mechatronics and Automation (ICMA) 2010, Xi'an, China, 4-7 August 2010. In Proceedings of the IEEE International Conference on Mechatronics and Automation, 2010, p. 2013-201

Literature review on the ‘Smart Factory’ concept using bibliometric tools

The objective of this paper is to depict a landscape of the scientific literature on the concept of the ‘Smart Factory’, which in recent years is gaining more and more attention from academics and practitioners because of significant innovations in the production systems within the manufacturing sector. To achieve this objective, a dynamic methodology called "Systematic Literature Network Analysis (SLNA)" has been applied. This methodology combines the Systematic Literature Review approach with the analysis of bibliographic networks. The adopted methodology allows complementing traditional content-based literature reviews by extracting quantitative information from bibliographic networks to detect emerging topics, and by revealing the dynamic evolution of the scientific production of a discipline. This dynamic analysis allowed highlighting research directions and critical areas for the development of the "Smart Factory". At the same time, it offers insights on the fields on which companies, associations, politicians and technology providers need to focus in order to allow a real transition towards the implementation of large-scale Smart Factory