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Multi objective optimization approach for multi-item inventory control: A case study in leather industry Nafisah, Laila; Prasetyo, Gigih Jono; Nursubiyantoro, Eko; Chaeron, Mochammad; Soepardi, Apriani; Suharsih, Sri
OPSI Vol 17, No 1 (2024): ISSN 1693-2102
Publisher : Jurusan Teknik Industri Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v17i1.11106

PT ASA is a leather tanning company. Almost 65% of the company's assets are allocated for the procurement of raw leather, which consists of goat and sheepskin. In addition to being expensive, the availability of raw leather is also very limited. The company faces a trade-off where, on one hand, the raw material is easily decayed, but on the other hand, its availability is extremely limited, and if there is not enough inventory, the production process will be disrupted. In this research, a multi-objective optimization model is developed for controlling the inventory of raw leather using the Fuzzy Goal Programming approach. The objectives to be achieved are to minimize the total inventory cost, maximize the total quantity of raw leather that meets standards, and minimize the total cost of losses due to decayed raw leather. Based on the calculations, the fuzzy goal programming membership function value is obtained at 0.9155, with a total inventory cost over the planning horizon of IDR 10,341,630,000, a total of 1,279,542 sq ft of raw leather meeting standards, and a total loss cost due to decayed raw leather of IDR 142,911,691.

PERENCANAAN PRODUKSI MENGGUNAKAN GOAL PROGRAMMING (Studi Kasus di Bakpia Pathuk 75 Yogyakarta) Laila Nafisah; Sutrisno Sutrisno; Yan Ellia H. Hutagaol
Spektrum Industri Vol. 14 No. 2: Oktober 2016
Publisher : Universitas Ahmad Dahlan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v14i2.4913

Semakin berkembangnya jumlah UKM yang memproduksi bakpia di Yogyakarta maka membuatpersaingan semakin meningkat. Sehingga setiap owner selain harus memiliki inovasi dalam produksi danpemasaran, mereka juga harus memiliki perencanaan produksi yang baik untuk mempertahankanstabilitas keuangan perusahaan. Bakpia Patuk 75 adalah perusahaan yang memproduksi bakpia denganberbagai macam varian rasa.Setiap jenis varian yang dijual memiliki harga pokok produksi dan tingkatpermintaan yang berbeda. Namun demikian perencanaan produksi yang dijalankan perusahaankadangkala tidak dapat memenuhi permintaan pembeli yang berfluktuasi. Akibatnya seringkali terjadikelebihan dan kekurangan produk. Perusahaan berkeinginan meminimalkan biaya produksi dansekaligus memaksimalkan sumberdaya yang dimilikinya.dimana kedua tujuan tersebut memiliki sifat yangsaling bertentangan satu sama lain dalam upaya pencapainnya. Untuk membantu memecahkanpermasalahan multi objektif tersebut digunakan pendekatan goal programming. Hasil perencanaanproduksi dengan menggunakan metode Goal Programming ini mampu menghasilkan kombinasi produkyang dapat dijadikan dasar untuk menentukan jumlah produk yang akan diproduksi berdasarkansasaran-sasaran yang diinginkan perusahaan.Kata kunci : Perencanaan Produksi, Multiple Criteria Decision Making,Goal Programming.

Optimizing multi-item EPQ under defect and rework: A case in the plastic molding industry Nafisah, Laila; Sinaga, Rika Apriyanti Magdalena; Soepardi, Apriani; Salma, Melati; Irianto , Irianto
OPSI Vol 18 No 1 (2025): OPSI - June 2025
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v18i1.14740

Product availability is a key indicator of service performance and is closely linked to production planning. Inaccurate decisions in lot sizing may lead to either overstock or stockout, resulting in substantial financial losses. Classical Economic Production Quantity (EPQ) models generally assume perfect quality and ignore real-world factor such as defects, rework, and backorders. This study proposes an extended EPQ model for multi-item production systems that integrates random defect rates, rework, and backordering within a single framework. Unlike previous studies that focus on single-item scenarios or deterministic defect rates, this model reflects a more realistic setting faced by companies by accounting for stochastic defects, the cost of crushing and rework, and customer backorder fulfillment. The model aims to determine the optimal lot size and production cycle that minimize the total inventory-related costs. The proposed model is validated using real case data from a plastic molding company. Results show that the model yields cost savings of 0.19% compared to the current company policy. Although modest, these savings are significant when scaled across production periods. More importantly, the model demonstrates strong adaptability to operational constraints and provides a practical decision-support tool for industries managing multiple products, quality variation, and uncertain demand.

Multi objective optimization approach for multi-item inventory control: A case study in leather industry Nafisah, Laila; Prasetyo, Gigih Jono; Nursubiyantoro, Eko; Chaeron, Mochammad; Soepardi, Apriani; Suharsih, Sri
OPSI Vol 17 No 1 (2024): ISSN 1693-2102
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v17i1.11106

PT ASA is a leather tanning company. Almost 65% of the company's assets are allocated for the procurement of raw leather, which consists of goat and sheepskin. In addition to being expensive, the availability of raw leather is also very limited. The company faces a trade-off where, on one hand, the raw material is easily decayed, but on the other hand, its availability is extremely limited, and if there is not enough inventory, the production process will be disrupted. In this research, a multi-objective optimization model is developed for controlling the inventory of raw leather using the Fuzzy Goal Programming approach. The objectives to be achieved are to minimize the total inventory cost, maximize the total quantity of raw leather that meets standards, and minimize the total cost of losses due to decayed raw leather. Based on the calculations, the fuzzy goal programming membership function value is obtained at 0.9155, with a total inventory cost over the planning horizon of IDR 10,341,630,000, a total of 1,279,542 sq ft of raw leather meeting standards, and a total loss cost due to decayed raw leather of IDR 142,911,691.

Improving the job shop scheduling algorithm to minimize total penalty costs considering maintenance activity Puryani, Puryani; Chalida, Nurmalia; Soepardi, Apriani; Chaeron, Mochammad; Nafisah, Laila
OPSI Vol 17 No 2 (2024): ISSN 1693-2102
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v17i2.12291

Production scheduling is generally based on the assumption that resources are always available. In reality, these resources, machines, and supporting facilities experience limited availability due to interruptions during the production process. Therefore, to improve these conditions, the maintenance process conducted to reduce the disruption level of the machine needs to be scheduled as part of the available for job processing leading to penalty costs, such as tardiness and earliness. This research aims to develop a new algorithm to solve job shop scheduling problems to minimize the total penalty cost by considering machine unavailability due to scheduled maintenance activities. The proposed model modifies the existing model using a combination of priority rules and a heuristic approach algorithm known as priority dispatching. The result showed that the proposed model produces a greater total cost with a larger flow time than the previous model. Although the flow time is larger, it is more realistic according to real conditions because the proposed model considers machine maintenance activities. Furthermore, the combination of priority rules used also affected the flow time and the total penalty costs incurred, which can be minimized through several alternatives.

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