Training Material Decision Making for Mechanics Using Analytic Hierarchy Process (AHP): A Case Study of PT United Tractors Tbk.

Anggi Febrianto, A. Pratama, T. D. Sofianti
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引用次数: 1

Abstract

United Tractors is committed to providing total solutions for products and services that customers need to provide the best satisfaction for customers in using products and services. In order for products and service quality to always meet customer specifications and expectations, we provide excellent service through the after-sales service quality assurance program, namely UT Guaranteed Product Support (UT GPS) [1]. In order to maximize On-Time in full Machine maintenance period, improving mechanical competence is one of the main things that must be done. To determine the right material of training, we need to make the right decisions using the Multi-Criteria Decision Making (MCDM) method by the Analytical Hierarchy Process (AHP) application. In this research, decision making is based on business criteria with parameters of population, the number of job orders and the number of parts orders and combined with job frequency criteria by job classification criteria with Preventive Maintenance (PM) parameters, Machine Trouble Shooting (MTS) and Component Overhaul (OVH). In this paper data matrix is inputted to the application super decision for getting the result. Rank of training based on business criteria is a result for get the decision making for start training based on priority number at PT United Tractor Tbk.
基于层次分析法的力学训练材料决策——以PT联合拖拉机Tbk为例。
联合拖拉机致力于为客户所需的产品和服务提供整体解决方案,为客户在使用产品和服务时提供最佳的满意度。为了使产品和服务质量始终满足客户的规格和期望,我们通过售后服务质量保证计划,即UT保证产品支持(UT GPS)[1],提供优质的服务。为了在全维修周期内最大限度地提高机器的正点率,提高机械能力是必须做的主要事情之一。为了确定合适的培训材料,我们需要应用层次分析过程(AHP)的多准则决策(MCDM)方法做出正确的决策。在本研究中,决策基于以人口、作业订单数量和零件订单数量为参数的业务准则,并结合以预防性维护(PM)、机器故障排除(MTS)和部件检修(OVH)为参数的作业分类准则的作业频率准则。本文将数据矩阵输入到应用程序超级决策中以获得结果。在PT United Tractor Tbk,基于业务标准的培训排名是获得基于优先级编号的开始培训决策的结果。
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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