Troubleshooting Generator Sets using Expert System

Nopendri Nopendri, D. Nasien
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Abstract

PT. Zaman Teknindo (PT. ZT) is a company engaged in Mechanical and Engineering field which is registered as one PT. Telkomsel vendors. The problems that occur at PT. ZT, if the power outage and generator set (generator) does not start automatically. The corrective team on duty at that time will go to the field and find a solution to the problem. With a lack of knowledge from the corrective team, they need help from the mechanical team. The mechanical team is an external team of PT. ZT. To bring a mechanical team requires an enormous cost and a relatively long time needed to get to the location. Based on the problem above, this study proposes a forward chaining expert system that is by depth-first search using the certainty factor method. To prove whether a fact is certain or not, it must be in the metric form in generator troubleshooting. The research methodology used the Software Development Life Cycle (SDLC) starting from problem identification, analysis, design, coding, testing and maintenance. This system is web-based, so users can easily access and choose symptoms of the damage. With this system makes it easy for PT. ZT especially the corrective team in the field can easily find out the damage symptoms without having to meet with experts directly.
使用专家系统排除发电机组故障
PT. Zaman Teknindo (PT. ZT)是一家从事机械和工程领域的公司,是一家注册的PT. Telkomsel供应商。在PT. ZT发生的问题,如果停电和发电机组(发电机)不能自动启动。当时值班的纠正小组将前往现场寻找问题的解决方案。由于纠正小组缺乏知识,他们需要机械小组的帮助。机械团队是PT. ZT的外部团队。带一个机械团队需要巨大的成本和相对较长的时间才能到达现场。针对上述问题,本文提出了一种采用确定性因子法进行深度优先搜索的前向链专家系统。在发电机故障排除中,为了证明一个事实是否确定,它必须是度量形式的。研究方法采用软件开发生命周期(SDLC),从问题识别、分析、设计、编码、测试和维护开始。该系统是基于web的,因此用户可以方便地访问和选择损坏的症状。有了这个系统,PT、ZT特别是现场的纠正团队可以很容易地发现损坏的症状,而不必直接与专家见面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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