P2P Web Service Based System for Supporting Decision-Making in Cellular Manufacturing Scheduling
With the increase of the Internet and Virtual Enterprises (VEs), interfaces for web systems and automated services are becoming an emergent necessity. In this paper we propose a Peer-to-peer (P2P) web-based decision-support system for enabling access to d
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P2P Web Service Based System for Supporting Decision-Making in Cellular Manufacturing Scheduling Maria Leonilde R. Varela, Rui Barbosa, and Susana Costa
Abstract With the increase of the Internet and Virtual Enterprises (VEs), interfaces for web systems and automated services are becoming an emergent necessity. In this paper we propose a Peer-to-peer (P2P) web-based decision-support system for enabling access to different manufacturing scheduling methods, which can be remotely available and accessible from a distributed knowledge base. The XMLbased modeling and communication is applied to manufacturing scheduling. Therefore, manufacturing scheduling problems and methods are modeled using XML. The proposed P2P web-based system works as web services, under the SOAP protocol. The system’s distributed knowledge base enables sharing information about scheduling problems and corresponding solving methods in a widened search space, through a scheduling community, integrating a VE. Running several methods enables different results for a given problem, consequently, contributing for a better decision-making. An important aspect is that this knowledge base can be easily and continuously updated by any contributor through the VE. Moreover, through this system once suitable available methods, for a given problem, are identified, it enables running one or more of them, for enabling a better manufacturing scheduling support, enhanced though incorporated fuzzy decision-making procedures. Keywords Cellular Manufacturing Scheduling • Web Services • Distributed Knowledge Base • Virtual Enterprise • Fuzzy Decision-making
M.L.R. Varela (*) • R. Barbosa • S. Costa Department of Production and Systems, School of Engineering, University of Minho, Azure´m Campus, 4800-058 Guimara˜es, Portugal e-mail: [email protected]; [email protected]; [email protected] A. Madureira et al. (eds.), Computational Intelligence and Decision Making: Trends and 155 Applications, Intelligent Systems, Control and Automation: Science and Engineering 61, DOI 10.1007/978-94-007-4722-7_15, # Springer Science+Business Media Dordrecht 2013
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Introduction
In today’s knowledge-based economy, the competitiveness of enterprises and the quality of work life are directly tied to the ability of effective creation and share of knowledge both, within and across organizations. Manufacturing scheduling is a complex task that involves a wide range of knowledge. Slight differences on the manufacturing environment originate distinct problems, which even though being closely related, require different solving methods to be applied. The effective and efficient resolution of those problems begins with the identification of suitable scheduling methods for solving them. When there are alternative methods for solving a problem we can obtain alternative solutions, which should be evaluated against specified criteria or objectives to be reached. Thus, users are able to properly solve a problem, through the execution of one or more schedulin
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