Production scheduling in ERP systems: An AI-based approach to face the gap

Production scheduling in ERP systems: An AI-based approach to face the gap
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ERP 系统中的生产调度:基于人工智能的方法来应对差距

DOI:
10.1108/14637150310468416
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发表时间:
2003
期刊:
Bus. Process. Manag. J.
影响因子:
--
通讯作者:
K. Ergazakis
K. Ergazakis
中科院分区:
--
文献类型:
--
作者:
K. Metaxiotis;J. Psarras;K. Ergazakis

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在当前的竞争环境中,每个公司都面临着许多挑战:快速响应客户需求,高质量的产品或服务,客户满意度,可靠的交货日期,高效率等。因此,在过去五年中,许多公司开始采用企业资源规划(ERP)解决方案。ERP是一个打包的软件系统,它通过通用的数据处理和通信协议实现了运营、业务流程和功能的集成。然而,大多数,如果不是全部,这些系统不支持生产调度过程,这是至关重要的,在今天的制造业和服务业。在本文中,作者提出了一个基于知识的生产调度系统,可以作为自定义模块集成到ERP系统中。该系统使用在工业环境中的主要条件,以便动态地选择,并提出最合适的调度算法从许多候选算法库。
In the current competitive environment, each company faces a number of challenges: quick response to customers’ demands, high quality of products or services, customers’ satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data‐processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today’s manufacturing and service industries. In this paper, the authors propose a knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.
2005 年未来集成系统五年展望
DOI: --
发表时间: 2005
期刊:
影响因子: --
作者:
S.Oda;D.F.Moore;Y.Majima et al.
通讯作者: Y.Majima et al.