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All Journal International Journal of Industrial Engineering and Engineering Management
Ai, T.J.
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Industrial & Manufacturing Engineering

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Inventory Policy for Dependent Demand Where Parent Demand Has Decreasing Pattern Pratama, Y.N.A.; Darmawan, M.; Astanti, R.D.; Ai, T.J.; Gong, D.C.
International Journal of Industrial Engineering and Engineering Management Vol. 1 No. 1 (2019)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v1i1.2293

Abstract

When a product reaches its maturity in its life cycle, some innovations have to be put in that product in order to lengthen its life cycle. Otherwise, that product will be perceived as obsolete. It might affect the demand of that product i.e. the demand become decreasing. Based on the observation that we conducted over two smart phone brands, the phenomena that the demand has declining pattern really happened in the real situation. In addition, the observation shows that the product life cycle is getting shorter. This implies that the manufacturer has to deal with decreasing demand more often. A case study is presented in this paper, in which manufacturer experienced final product with decreasing demand pattern. Some lot sizing techniques, such as Lot for Lot, Silver Meal 1, Silver Meal 2, Least Unit Cost, Part Period Balancing, and Incremental, are tested to solve the inventory policy for both final product (parent) and its components (child). It is concluded that a company should not consider only one component or one level whenever deciding the inventory policy, i.e. production lot size. It is shown by the case study that the best lot sizing technique for a particular parent of product whenever the company only consider the parent is different with the best lot sizing technique whenever the company consider the parent and its child. For the case presented, it is shown that the smallest total cost of parent and child is most likely occurred whenever Silver Meal 2 lot sizing technique is applied in the parent with decreasing demand pattern. 
A Joint Replenishment Inventory Model to Control Multi-Item Medicines with Consideration of Space Requirements in the Hospital William, W.; Ai, T.J.; Lee, W.
International Journal of Industrial Engineering and Engineering Management Vol. 2 No. 2 (2020)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v2i2.4190

Abstract

Medicines can be considered the most widely used medical expenditures in hospitals. To reduce the medicines expenses in the hospital, the term of inventory control is applied. Medicines must be controlled by considering the expiry dates and the probabilistic demand from the customers. Therefore, it is necessary to develop an inventory model that can be suitable to control medicines by minimizing the expired medicines, total inventory costs, and dealing with unpredictable demand. The purpose of this research is to develop an inventory model for determining optimum replenishment time and order quantities and space requirements for multi-item medicines with consideration of expiry dates of the medicines and all medicines are being purchased in a single purchase order so that the total inventory costs in hospitals can be minimized. The result is that the proposed inventory model results in optimum space requirements and the lowest inventory costs. Therefore, hospitals must order medicines based on the optimum order quantity.
Predictive Maintenance in SCADA-Based Industries: A literature review Suryadarma, E.H.E.; Ai, T.J.
International Journal of Industrial Engineering and Engineering Management Vol. 2 No. 1 (2020)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v2i1.4368

Abstract

The purpose of this paper is to mapping and review what has been done on the topic of research on predictive maintenance in SCADA (Supervisory Control and Data Acquisition) based industries. In the research area of predictive maintenance, various methods for predicting damage or time to failure of a machine have been proposed and applied in various industries. This paper systematically categorizes predictive maintenance in SCADA-based industries research based on industry classifications according to ISIC (International Standard Industrial Classification of All Economic Activities). Furthermore, the research scope is explored its connection to the topics of Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Supervisory Control and Data Acquisition (SCADA). It is found that 81.5% of the research was conducted on the electricity, gas, steam, and air conditioning supply industries, 11.1% of research was conducted on the mining and quarrying industry, and 7.4% of the research conducted in the manufacturing industry. It is also found that 85.2% of studies used AI and ML, 18.5% of the studies used IoT, and 18.5% of research used AI/ML and IoT technology together.
Co-Authors Astanti, R.D. Darmawan, M Gong, D.C. Lee, W. Pratama, Y.N.A. Suryadarma, E.H.E. William, W.