Model Penentuan Ukuran Batch Produksi dan Bufferstock untuk Sistem Produksi Mengalami Penurunan Kinerja dengan Mempertimbangkan Perubahan Order Awal

This study develops a model that involves information the preliminary order. At first, the manufacturer provides the preliminary order for the coming week (five days) varies from day to day and is received on Friday. Change in the preliminary order for a given day is announced one day before and this is viewed as it occurs randomly. Moreover, production systems experience performance degradation (deterioration). Status of the production process shifts from in control to out of control that is identified by the last inspection. Inspection is done by sampling. At the time of the status of out of control the probability of producing non-conforming system component that is charged to the restoration cost and warranty costs.This paper is looking for a solution for determining the production batch size and the buffer stock to reduce total cost. The decision variables are production run period (T) and buffer factor (m). Having obtained the variables T and m, then the variable production batch size (QT) and the buffer stock (BT) can be determined sequentially. Heuristic methods used are Silver-Meal (SM) and Least Unit Cost (LUC) to obtain a solution for each model. Numerical examples are given to demonstrate the performance of the models. From the numerical results, it appears that LUC method is better than SM method.

Cost and Quantity Inventory Analysis in the Garment Industry: A Case study

This study aims to evaluate how effective and efficient inventory is in the fashion industry by using the EOQ method. This research is a quantitative study of WKB companies. The data used in this study are data for 2017 and 2018 covering the number of purchases and use of raw materials, data on ordering costs, data on holding costs, raw material prices, and Lead time. The results of this study indicate that, the level of frequency of purchases made more than 100 times resulting in high ordering costs. By using the EOQ method inventory becomes more effective and efficient, with order frequency being 15 times a year and ordering costs being less. The number of efficient inventories for one order based on EOQ in 2017 is 647 kg and in 2018 is 809 kg. For inventory costs using the EOQ method in 2017, the cost will be IDR 594,867.69 per year and in 2018 the cost will be IDR 612,956.26 per year. Costs that can be saved after using EOQ in 2017 are IDR 10,811,247.31 or 94.78%. Costs that can be saved after using EOQ in 2018 will cost IDR 11,066,168.74 or 94.75%. Keywords: Inventory, Economic Order Quantity

Cost and Quantity Inventory Analysis in the Garment Industry: A Case study

This study aims to evaluate how effective and efficient inventory is in the fashion industry by using the EOQ method. This research is a quantitative study of WKB companies. The data used in this study are data for 2017 and 2018 covering the number of purchases and use of raw materials, data on ordering costs, data on holding costs, raw material prices, and Lead time. The results of this study indicate that, the level of frequency of purchases made more than 100 times resulting in high ordering costs. By using the EOQ method inventory becomes more effective and efficient, with order frequency being 15 times a year and ordering costs being less. The number of efficient inventories for one order based on EOQ in 2017 is 647 kg and in 2018 is 809 kg. For inventory costs using the EOQ method in 2017, the cost will be IDR 594,867.69 per year and in 2018 the cost will be IDR 612,956.26 per year. Costs that can be saved after using EOQ in 2017 are IDR 10,811,247.31 or 94.78%. Costs that can be saved after using EOQ in 2018 will cost IDR 11,066,168.74 or 94.75%

Inventory management strategies propensity toward supply chain management in the aerospace industry in Malaysia : the moderating effect of financial risk consideration

This thesis examined the relationship between inventory management strategies (IMS) and supply chain management (SCM) performance in the aerospace industry, an advanced and high technology industry that is characterized by a high working capital with potential huge losses if something goes wrong. The IMS dimensions of stock holding, safety stock, storage policy and inventory risk were tested against the SCM performance dimensions of on-time delivery (OTD), balance score card (BSC), inventory turn and factors related to inventory-financial risks. The quantitative research methodology was opted for this study. Data collection was performed from January to May 2016, involving 81 respondents related to the aerospace industry in Malaysia. This accounted for 40.5% of the population in the country. The Statistical Package for the Social Sciences (SPSS) was used to assist in the analysis. The findings indicated that only two dimensions of the IMS are used as predictors for the SCM performance. It also revealed that every dimension of the SCM performance is significant with only one dimension of the IMS. The most important dimension of SCM performance is the inventory risk dimension. Contrary to the initial expectation, storage policy is found to be insignificant for the theoretical relationship in this industry and the financial risk factor is found to be a weak moderator in the proposed relationship. The findings also suggested the need to examine financial risk consideration as the independent variable when examining the SCM performance in the aerospace industry. Moreover, these findings can be considered unique as they offer different contributing dimensions to the SCM performance and these should be the eye-opener to the organizations that have different attributes, in particular the high technology industry that involves high working capital

Inventory control for a perishable product with non-stationary demand and service level constraints

We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at lowest cost. Every production run a set-up cost is incurred. Moreover, the producer has to deal with unit production cost, unit holding cost and unit cost of waste. The production plan for a finite time horizon specifies in which periods to produce and how much. We formulate this single item – single echelon production planning problem as a stochastic programming model with a chance constraint. We show that an approximate solution can be provided by a MILP model. The generated plan simultaneously specifies the periods to produce and the corresponding order-up-to levels. The order-up-to level for each period is corrected for the expected waste by explicitly considering for every period the expected agedistribution of the products in stock. The model assumes zero lead time and backlogging of shortages. The viability of the approach is illustrated by numerical experiments. Simulation shows that in 95.8% of the periods the service level requirements are met with an error tolerance of 1%