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PENJADWALAN KEGIATAN PEMELIHARAAN UNTUK MEMAKSIMALKAN AVAILABILITAS MESIN Nur Kumala Sari; Puryani Puryani; Apriani Soepardi
OPSI Vol 11, No 2 (2018): ISSN 1693-2102
Publisher : Jurusan Teknik Industri Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Fuzzy Production Inventory Model considering Imperfect Quality and Shortage: A Case Study in a Goat Milk SMEs Puryani Puryani; Laila Nafisah; Nuansa Indriya Pramasthi; Apriani Soepardi; Mohammad Chaeron
OPSI Vol 15, No 2 (2022): 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.v15i2.7574

Goat milk powder is one of the perishable processed products. The decreasing quality of goat milk powder can cause financial losses to the company if not regulated properly. So far, the company is also faced with the problem of consumer demand uncertainty. When demand for powdered goat's milk is high, the company experiences stockout but can be overcome by backorder. When demand is low, there will be overstock. Overstock conditions, in addition to causing high holding costs, are also at risk of product quality degradation or expiration. In this study, an inventory model of goat milk powder was developed that considers the uncertainty of demand, product quality, and backorder to determine the optimal production quantity so that the total inventory cost incurred is minimum. The basic model used is economic production quantity. Uncertainty in demand and the percentage of products declining in quality is approached using a triangular fuzzy. While the defuzzification technique used is signed distance.

Redesign of the sizing process optimization to produce warp yarn with strong weaving ability Kartika, Wahyu; Soepardi, Apriani
OPSI Vol 16, No 2 (2023): 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.v16i2.11355

The research focuses on optimization of the sizing process parameters for cotton warp yarn material. The sizing process is a crucial step where warp yarn is coated with a starch solution before weaving. The aim is to produce warp yarn with strong weaving ability, thereby facilitating the entire process. To achieve this, several factors are considered, namely the steam bar, and squeeze roll pressure, including machine speed. The techniques used to address this issue include Taguchi in collaboration with Grey Relational Analysis (GRA) to effectively address multi-responses. In this analysis, the larger the better characteristic was applied to S/N Ratio, indicating that the higher the GRG value, the closer it is to the desired optimum condition. Based on the calculations from S/N Ratio response table for the GRG, it can be determined that factor steam bar pressure was selected at 4 Bar, with an average S/N Ratio value of -2.935. factor squeeze roll should be set to level 10 Km/m3, as it yields an average S/N Ratio value of -2.912. Factors squeeze roll) and C (Machine Speed) were selected at levels 2 (10 Km/m3) and 1 (45 M/Min) with average values of -2.912, and -4.771, respectively.

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.

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.

Redesign of the sizing process optimization to produce warp yarn with strong weaving ability Kartika, Wahyu; Soepardi, Apriani
OPSI Vol 16 No 2 (2023): 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.v16i2.11355

The research focuses on optimization of the sizing process parameters for cotton warp yarn material. The sizing process is a crucial step where warp yarn is coated with a starch solution before weaving. The aim is to produce warp yarn with strong weaving ability, thereby facilitating the entire process. To achieve this, several factors are considered, namely the steam bar, and squeeze roll pressure, including machine speed. The techniques used to address this issue include Taguchi in collaboration with Grey Relational Analysis (GRA) to effectively address multi-responses. In this analysis, the larger the better characteristic was applied to S/N Ratio, indicating that the higher the GRG value, the closer it is to the desired optimum condition. Based on the calculations from S/N Ratio response table for the GRG, it can be determined that factor steam bar pressure was selected at 4 Bar, with an average S/N Ratio value of -2.935. factor squeeze roll should be set to level 10 Km/m3, as it yields an average S/N Ratio value of -2.912. Factors squeeze roll) and C (Machine Speed) were selected at levels 2 (10 Km/m3) and 1 (45 M/Min) with average values of -2.912, and -4.771, respectively.

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.

Large neighborhood search for route and fleet optimization in frozen food distribution Simbolon, Jonathan Andrepa; Trismi Ristyowati; Soepardi, Apriani; Irwan Soejanto; Yuli dwi Astanti; Puryani; Chaeron, Mochammad
OPSI Vol 18 No 2 (2025): OPSI - December 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.v18i2.15743

This study develops an optimization model to enhance the distribution efficiency of a frozen food distributor. The company faces operational inefficiencies due to excessive fleet capacity and conventional route assignment methods, which increase travel distances and overall distribution costs. To address these challenges, an extended Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) model is proposed, which integrates heterogeneous fleet characteristics and prioritizes customer service constraints. The model is solved using the Large Neighborhood Search (LNS) metaheuristic to determine optimal routing and fleet allocation strategies. The optimized model achieves a 15.95% reduction in total travel distance and a 21.84% decrease in total distribution costs compared with the company’s current operations. The findings confirm the effectiveness of the LNS-based CVRPTW approach in improving logistics performance and provide practical insights for companies seeking to minimize distribution costs through strategic route planning and fleet management.

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