Improvement Of Inventory Control Systems For Raw Material In A Make To Order Company
Robertus Willy Gunawan
Abstract
Robertus Willy Gunawan
Abstract
In any manufacturing industry, inventory is always an important part to be controlled; companies have to design a system that is able to avoid stock outs while keeping the stock at minimum. Nonetheless, to some extents, managing inventory is utterly complicated. In many cases, companies turn into fiasco when they design an efficient inventory control system, especially for make-to-order companies which deal with extremely high demand uncertainty. In this paper, several inventory control systems such as continuous review (s, Q system) and periodic review (R, s, S system) are investigated and compared to the existing inventory control system in the company. The objective is to obtain a better inventory control system for every raw material category in terms of total cost and service level. At the very first phase, considering usage volume and the coefficient of variance, several raw material samples are taken. This research develops a Monte Carlo simulation for generating probabilistic demand and shipment lead time. In carrying out simulation for generating demand, author uses several replications to evade improper results, which could lead to wrong decisions. Each scenario for inventory control system is evaluated in terms of total cost and service level. Heuristic methods for both continuous and periodic inventory control systems are also used to test the sensitivity of the parameters. This paper brings an important recommendation to the company as well as insight for make- to-order companies in general. Since cost is the ultimate output for profit-based companies including Karya Makmur Baru, Ltd., the proposed inventory control system for each raw material category could be implemented by the company as a means to reduce the total inventory cost while maintaining the service level target. The inventory cost reduction ranges from 39.69% to 72.85%, with the minimum service level of 98.48%.
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In any manufacturing industry, inventory is always an important part to be controlled; companies have to design a system that is able to avoid stock outs while keeping the stock at minimum. Nonetheless, to some extents, managing inventory is utterly complicated. In many cases, companies turn into fiasco when they design an efficient inventory control system, especially for make-to-order companies which deal with extremely high demand uncertainty. In this paper, several inventory control systems such as continuous review (s, Q system) and periodic review (R, s, S system) are investigated and compared to the existing inventory control system in the company. The objective is to obtain a better inventory control system for every raw material category in terms of total cost and service level. At the very first phase, considering usage volume and the coefficient of variance, several raw material samples are taken. This research develops a Monte Carlo simulation for generating probabilistic demand and shipment lead time. In carrying out simulation for generating demand, author uses several replications to evade improper results, which could lead to wrong decisions. Each scenario for inventory control system is evaluated in terms of total cost and service level. Heuristic methods for both continuous and periodic inventory control systems are also used to test the sensitivity of the parameters. This paper brings an important recommendation to the company as well as insight for make- to-order companies in general. Since cost is the ultimate output for profit-based companies including Karya Makmur Baru, Ltd., the proposed inventory control system for each raw material category could be implemented by the company as a means to reduce the total inventory cost while maintaining the service level target. The inventory cost reduction ranges from 39.69% to 72.85%, with the minimum service level of 98.48%.
Key concepts: Safety stock, Inventory control, Inventory theory, Cycle count, Inventory valuation, Lead time, Holding cost, Operations research