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Academic Editor:Meikang Qiu
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China
Received 5 April 2015; Revised 24 April 2015; Accepted 27 April 2015; 19 January 2016
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Recently, the emerging technologies (e.g., Internet of Things (IoT) [1-3], wireless sensor networks [4, 5], big data [6], cloud computing [7-9], embedded system [10], and mobile Internet [11]) are being introduced into the manufacturing environment, which ushers in a fourth industrial revolution. Consequently, a strategic initiative called "Industrie 4.0" was proposed and was adopted as part of the "High-Tech Strategy 2020 Action Plan" of the German government [12]. The similar strategies were also proposed by other main industrial countries, for example, "Industrial Internet" [13] from USA and "Internet +" [14] from China. The Industrie 4.0 describes a production oriented Cyber-Physical Systems (CPS) [15-17] that integrate production facilities, warehousing systems, logistics, and even social requirements to establish the global value creation networks [18].
In order to preferably implement Industrie 4.0, the following three key features should be considered [12]: (1) horizontal integration through value networks, (2) vertical integration and networked manufacturing systems, and (3) end-to-end digital integration of engineering across the entire value chain. The setting for vertical integration is the factory, so the vertical integration means implementing the smart factory that is highly flexible and reconfigurable. Therefore, the smart factory is believed to be able to produce customized and small-lot products efficiently and profitably.
Prior to the smart manufacturing of Indusrie 4.0, many other advanced manufacturing schemes have already been proposed to overcome the drawbacks of the traditional production lines, for example, the flexible manufacturing and the agile manufacturing. Among these schemes, the multiagent system (MAS) is the most representative [19]. The manufacturing resources are defined as intelligent agents that negotiate with each other to implement dynamical reconfiguration to achieve flexibility. However, it is difficult for the MAS to handle the complexity of manufacturing system, so it still lacks a generally accepted MAS implementation. In our view, the cloud-assisted industrial wireless network (IWN) can suitably support the smart factory by implementing...