Forecasting Model Number Production of Car Spare Parts at PT. Showa Katou Indonesia with Arima Method

Cici Emilia Sukmawati, Ayu Ratna Juwita
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Abstract

In the case of single part production planning at PT Showa Katou Indonesia The problem is the production plan is only a production schedule, the schedule is made only two times (morning and evening) in a day. The schedule is created after the Production Planning Inventory Control (PPIC) contacts the customer to ascertain what the customer needs. After knowing what the customer needs, a production schedule and planning are made. The impact of this erratic production schedule causes loss of production time because if there is no demand then nothing is done by workers and the machine stops production because they have to wait for an erratic production schedule. Another impact is the absence of stock in the warehouse and delays in delivery because they are only waiting for the production schedule from PPIC and waiting for finished goods to be produced. To reduce the bad impact, it is necessary to forecast production planning with data mining methods to help these problems. The method used is the ARIMA method with the model (p,d,q) (1,1,1). The results of testing using tools and manual testing showed significant values with MAD = 52.45, MSE = 3917.84, MAPE = 0.05.
用Arima方法预测印尼昭和卡托工厂汽车零配件产量模型
在印度尼西亚PT昭和卡头的单零件生产计划的情况下,问题是生产计划只是一个生产计划,计划在一天中只做两次(早上和晚上)。计划是在生产计划库存控制(PPIC)联系客户以确定客户需求之后创建的。在了解客户需求后,制定生产计划和计划。这种不稳定的生产计划的影响导致了生产时间的损失,因为如果没有需求,工人就什么都不做,机器就会停止生产,因为他们必须等待不稳定的生产计划。另一个影响是仓库没有库存和交货延迟,因为他们只是在等待PPIC的生产计划,等待成品生产出来。为了减少不良影响,有必要利用数据挖掘方法预测生产计划来帮助解决这些问题。使用的方法是ARIMA方法,模型为(p,d,q)(1,1,1)。工具检测和手工检测结果均有统计学意义,MAD = 52.45, MSE = 3917.84, MAPE = 0.05。
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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