دانلود مقاله ISI انگلیسی شماره 1115
ترجمه فارسی عنوان مقاله

نمونه اولیه سیستم چند عاملی برنامه ریزی منابع سازمانی (ERP) : معماری یکپارچه و چارچوب مفهومی

عنوان انگلیسی
A prototype multi-agent ERP system: an integrated architecture and a conceptual framework
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
1115 2005 9 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Technovation, Volume 25, Issue 4, April 2005, Pages 433–441

ترجمه کلمات کلیدی
برنامه ریزی منابع سازمانی () - عامل نرم افزار - معماری  - پیاده سازی -
کلمات کلیدی انگلیسی
Enterprise resource planning ERP, Software agent, ERP architecture, ERP implementation
پیش نمایش مقاله
پیش نمایش مقاله  نمونه اولیه سیستم چند عاملی برنامه ریزی منابع سازمانی (ERP) : معماری یکپارچه و چارچوب مفهومی

چکیده انگلیسی

This paper proposes a prototype multi-agent enterprise resource planning (MAERP) system that utilizes the characteristics and capabilities of software agents to achieve enterprise wide integration. A software agent is a self-contained, autonomous software module that performs assigned tasks from the human user and interacts/communicates with other applications and other software agents in different platforms to complete the tasks. Four types of intelligent software agents (coordinating agents, task agents, data collecting agents, and user interface agents) are examined and discussed in the proposed MAERPS architecture. We demonstrate how the proposed prototype MAERP system takes advantage of existing information systems among various functional areas to achieve the system integration of commercially available enterprise resource planning (ERP) systems, while avoiding numerous problems encountered during a typical ERP implementation.

مقدمه انگلیسی

Modern businesses are too complex and dynamic to be managed optimally using traditional information systems or even rigidly structured enterprise resource planning (ERP) systems. Agent-based systems claim to be next generation software capable of adapting dynamically to changing business environment and of solving a wide range of business problems in areas such as supply-chain management (SCM), health care and patient monitoring, process control applications, and knowledge discovery (Papazoglou, 2001). Software agents are sophisticated computer programs that act autonomously on behalf of their users to solve complex problems, and a multi-agent system is a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver.

نتیجه گیری انگلیسی

In this paper, we present a multi-agent system that is capable of providing enterprise wide integration. With this approach, we demonstrate that a set of software agents with specialized expertise can be quickly assembled to gather relevant information and knowledge, and more importantly, to cooperate with each other (other agents, information systems, and managers) in order to arrive at timely decisions in dealing with various enterprise scenarios. We provide a simple illustration to show how the proposed MAERP system might work. Through our illustration, we show how numerous actions/commands are executed by various agents, resulting in a multiple phased and structured conversation among agents. The MAERP architecture presented in this research is only the first step toward agent-based ERP systems. Further research is needed to extend the current work and to address its limitations. In cooperation with industry partners, we intend to develop a prototype MAERP system and to demonstrate that more practical and relevant problems can be addressed successfully. We also intend to show that a systematic approach based on the theory of constraints can be used to develop an agent-based ERP system. Following the ideas proposed in Goldratt (2000), we believe that an agent-based ERP system can be developed with relative ease by focusing first on those components of an organization which are critical for identifying and optimizing the system’s constraints. The ERP system developed in this manner will show immediate impact on the financial performance of an organization. We would also like to extend the applications of the proposed MAERP system to the supply-chain environment where agents can be used to communicate and evaluate the performance of the supply-chain members based on new global performance measures such as throughput dollar days and inventory dollar days as suggested by Gupta (2003).