A new procedure for spare parts inventory management in ETO production: a case study

Rinaldi, Marta; Fera, Marcello; Macchiaroli, R.; Bottani, Eleonora

doi:10.1016/j.procs.2022.12.233

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…Proper spare part management is essential for enhancing vessel reliability, ensuring safety, and reducing maintenance costs. Rinaldi et al conducted research demonstrating a correlation between the total cost and the maximum number of spare parts storages, underscoring the significance of spare part management in the broader context of asset management [20].…”

Section: Spare Part Managementmentioning

confidence: 99%

Optimizing spare part management for vessels in liner shipping

Bisadi,

Zare,

Magnus Hvattum

2024

Recent Topics in Maintenance Management

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Seagoing vessels require regular maintenance. Preventive maintenance can be planned ahead of time, and can be executed either at sea or while visiting a port. The spare parts used when performing maintenance can come from warehouses that store the parts until needed at a port, but they can also come from on-vessel storages. Some spare parts must be available on a vessel at all times, in the case that corrective maintenance is required. This chapter considers liner shipping, where each vessel follows a pre-planned itinerary and a number of preventive maintenance tasks have been scheduled over time. A mathematical model is proposed that can be used to decide where to store spare parts, how many spare parts to keep in inventory, when to order spare parts from suppliers, and when and where to perform the scheduled maintenance tasks. Numerical experiments show that the model can be solved very quickly. The model can thus be used as a tool to support making decisions related to inventory management for spare parts.

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Section: Spare Part Managementmentioning

confidence: 99%

Optimizing spare part management for vessels in liner shipping

Bisadi,

Zare,

Magnus Hvattum

2024

Recent Topics in Maintenance Management

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“…Di tingkat nasional, pemerintah dan asosiasi industri berperan dalam mengatur dan mengembangkan kegiatan terkait pengendalian persediaan suku cadang alat berat (Ye et al, 2022). Mereka dapat menyelenggarakan seminar, pelatihan, atau forum diskusi untuk membahas praktik terbaik dalam manajemen persediaan (Rinaldi et al, 2023). Selain itu, perusahaan-perusahaan dalam industri alat berat juga dapat menjalin kemitraan dengan produsen suku cadang lokal atau internasional untuk memastikan ketersediaan suku cadang yang handal dan dengan harga yang kompetitif (Nandi et al, 2021).…”

Section: Pendahuluanunclassified

Optimisasi Pengendalian Persediaan Spare Part Alat Berat Menggunakan Metode Continuous Review: Studi Kasus PT. Kasmar Tiar Raya di Kabupaten Kolaka Utara

Rafsanjani,

Lamatinulu Ahmad,

Nurul Chairany

et al. 2024

JIEI

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Spare part memiliki peran yang sangat penting dan menjadi kebutuhan dalam industri alat berat. PT. Kasmar Tiar Raya, perusahaan tambang nikel, mengalami masalah dengan pesanan spare part yang berlebihan sehingga terjadi penyimpanan berlebihan (overstock), yang menyebabkan biaya penyimpanan tinggi dan memiliki risiko kerusakan. Tujuan dari penelitian ini adalah untuk mengoptimalkan pengendalian persediaan spare part alat berat di perusahaan. Metode yang digunakan dalam penelitian ini adalah Metode Continuous Review. Hasil penelitian menunjukkan titik pemesanan ulang atau reorder point (ROP) untuk beberapa spare part, seperti oil seal sebanyak 75 unit, tooth sebanyak 27 unit, bearing sebanyak 30 unit, hose sebanyak 60 unit, dan oil filter sebanyak 78 unit. Dengan mengetahui titik pemesanan ulang ini, perusahaan dapat mengelola persediaan dengan lebih efisien, mengurangi biaya penyimpanan yang tinggi, dan menghindari risiko kerusakan. Dengan menerapkan Metode Continuous Review, PT. Kasmar Tiar Raya dapat meningkatkan efektivitas operasional dan menghindari kerugian yang tidak perlu terkait dengan persediaan spare part alat berat.

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“…Most of them are conducted to aim for several objectives such as cost minimization, profit maximization, service level improvement, and planning accuracy. To achieve those goals, the studies did experiments on several aspects such as inventory or ordering policy and strategy for perishable items (Gioia et al, 2023;Guo et al, 2018;Gong et al, 2022), retail products (Rios and Vera, 2023;Sridhar et al, 2021), and spare parts or OEM items (Rinaldi et al, 2023;Zhang et al, 2019). The other aspects that are being changed include inventory level (Wolbert, 2013;Ohmori and Yoshimoto, 2020), inventory allocation (Bretthauer et al, 2010), product pricing (Rios and Vera, 2023), and supplier selection (Wibowo et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Guo et al (2018) utilized a risk management framework and used conditional value at risk (CVaR) in their study. Some other more popular approaches to solve inventory problems are optimization through various methods (Gong et al, 2022;Zhang et al, 2019;Dong et al, 2011), simulation (Sridhar et al, 2021;Rinaldi et al, 2023), and combination of simulation and optimization or Sim-Opt (Gioia et al, 2023;Wibowo et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Predictive Analytics to Improve Inventory Performance: A Case Study of an FMCG Company

Suwignjo,

Panjaitan,

Baihaqy

et al. 2023

OSCM: An Int. Journal

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Predictive analytics is a methodology used to predict the outcome of future events with the use of historical data. Predictive analytics comes in very handy in various fields such as finance, manufacturing, healthcare, and even supply chain. Not only in those fields, but predictive analytics is also useful in managing inventory. However, we find that there is a lack of studies focusing on the implementation of predictive analytics to predict inventory status (overstock, understock) by considering inventory level and demand forecast. This study is inspired by a real-world problem at one of the largest FMCG companies in Indonesia. With so many product types to manage, this company often faces problems of understocked and overstocked inventory. This study attempts to solve that problem by employing big data and predictive analytics approaches. The gradient boosting model is used because it is an improvement of the decision tree model. The data that are used as predictors are inventory level, inventory week cover, historical sales, and demand forecast. The target variable for classification is inventory status which is divided into three classes, namely understock, normal, and overstock. Meanwhile, the target variable for the regression model is the amount of understock/overstock. The result of the classification model has an accuracy of 0.84 for category 1 products, 0.76 for category 2 products, and 0.74 for category 3 products. While the result of the regression model is an R 2 of 0.89 for category 1 products, 0.76 for category 2 products, and 0.74 for category 3 products. The data that comes from the prediction model are visualized in a dashboard. The visualization dashboard displays the data using heatmaps and line graphs, so the information can be used for further analysis.

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A new procedure for spare parts inventory management in ETO production: a case study

Cited by 10 publications

References 18 publications

Optimizing spare part management for vessels in liner shipping

Optimizing spare part management for vessels in liner shipping

Optimisasi Pengendalian Persediaan Spare Part Alat Berat Menggunakan Metode Continuous Review: Studi Kasus PT. Kasmar Tiar Raya di Kabupaten Kolaka Utara

Predictive Analytics to Improve Inventory Performance: A Case Study of an FMCG Company

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