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Journal Of Engineering Sciences (Improsci)
Published by Ann Publisher
ISSN : 30323452     EISSN : 30317088     DOI : https://10.62885/improsci.v1i1
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering
Journal Of Engineering Sciences (Improsci) merupakan peer-reviewed jurnal yang mempublikasikan artikel-artikel ilmiah dalam bidang industri. Artikel-artikel yang dipublikasikan di Jurnal Improsci meliputi hasil penelitian ilmiah asli (prioritas utama), artikel ulasan ilmiah yang bersifat baru (tidak prioritas), serta hasil kajian dalam bidang industri.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 82 Documents
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Production Scheduling Optimization Using The Campbell Dudek Smith (CDS) Method to Minimize Makespan in A Flow Shop Manufacturing System Mario, Venantius Almas; Alfian, Achmad; Setiawan, Heri
Jurnal Improsci Vol 3 No 5 (2026): Vol 3 No 5 April 2026
Publisher : Ann Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/improsci.v3i5.1130

Abstract

Background: Production scheduling plays a crucial role in improving manufacturing system efficiency, particularly in flow shop environments where jobs must follow the same processing sequence across multiple machines. At CV. Sinar Surya, the production scheduling for lathe machines is still conducted manually based on operator experience, resulting in high machine idle time, low machine utilization, and prolonged makespan. This condition causes inefficiencies in production processes and delays in order completion. Therefore, an effective scheduling method is required to optimize the production sequence and improve operational efficiency. Aim: This study aims to optimize production scheduling in a flow shop manufacturing system by applying the Campbell-Dudek-Smith (CDS) method to minimize makespan and reduce lathe machine idle time. Methods: The research was conducted at CV. Sinar Surya Palembang uses a quantitative approach. Data were collected through direct observation, interviews with production staff, and company documentation. The collected data include processing time for each job, production sequences, machine working hours, and existing production schedules. The CDS heuristic method was applied by transforming the multi-machine flow shop problem into several two-machine subproblems, which were then solved using Johnson’s rule to determine the optimal job sequence. Results: The existing production schedule yielded a makespan of 163 minutes and a total machine idle time of 140 minutes. After applying the CDS method, the optimal job sequence obtained was J4 - J5 - J3 - J1 - J2, which reduced the makespan to 147 minutes and decreased total idle time to 95 minutes. This represents a 16-minute reduction in makespan (approximately 9.8%), indicating improved production efficiency. Conclusion: The implementation of the CDS method improves production scheduling efficiency in a flow shop manufacturing system by generating a more optimal job sequence, reducing makespan, and machine idle time. Implication: The findings suggest that the CDS method can be an effective scheduling approach for manufacturing companies using flow shop systems, particularly for improving machine utilization, reducing production delays, and supporting better production planning and decision-making.
Designing a Cost-Efficient Inventory System Using The Economic Order Quantity Model for Construction Materials Distributors Devi Sipayung, Indah Sry; Setiawan, Heri
Jurnal Improsci Vol 3 No 5 (2026): Vol 3 No 5 April 2026
Publisher : Ann Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/improsci.v3i5.1131

Abstract

Background: The construction materials distribution sector faces significant challenges in managing inventory due to fluctuating demand and the absence of systematic planning. Distributor Bintang Kerahiman, operating in Palembang and South Sumatra, currently relies on estimation-based inventory decisions, leading to frequent stockouts and overstocking. These inefficiencies lead to increased operational costs and lost sales opportunities, underscoring the need for a more structured, quantitative inventory control approach based on the Economic Order Quantity model. Aim: This study aims to design a cost-efficient inventory system by applying the Economic Order Quantity model and to compare its performance with the company's existing inventory method. Methods: A quantitative approach was employed using historical sales data from March to August 2025 across 30 selected products. Demand forecasting was conducted using the moving average method. Inventory parameters, including ordering cost, holding cost, safety stock, and reorder point (ROP), were calculated. The optimal order quantity was determined using the Economic Order Quantity formula, and total inventory costs were compared between the current method and the proposed model. Results: The implementation of the Economic Order Quantity model successfully reduces total inventory costs by optimizing order quantities and balancing ordering and holding costs. Across 30 products, the model demonstrated consistent cost savings and reduced inefficiencies. Additionally, profit improvements were observed due to decreased lost sales. For instance, profit for Afur BCP PVC Basket increased from IDR 990,000 to IDR 996,000, while Mold Cleaning Liquid increased from IDR 305,000 to IDR 330,000. Conclusions: The Economic Order Quantity model is more effective than the existing method in minimizing inventory costs, reducing stock imbalances, and improving service levels. The integration of safety stock and reorder point further enhances the system’s ability to handle demand variability. Implication. This study provides practical implications for construction material distributors by offering a data-driven inventory control framework. The findings support improved decision-making, cost efficiency, and customer satisfaction. Furthermore, the proposed system can be extended by integrating digital inventory applications and hybrid models for future research.

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