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Enny Aryanny
Program Studi Teknik Industri, Universitas Pembangunan Nasional “Veteran” Jawa Timur
Medicine & Pharmacology Public Health

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Route Optimization Using Ant Colony for Three-Wheel Vehicle Delivery: Optimasi Rute Menggunakan Koloni Semut untuk Pengiriman Kendaraan Roda Tiga Fitria Novitasari; Enny Aryanny
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.11192

Abstract

General Background: Efficient distribution systems are essential in logistics, especially in geographically complex regions like Indonesia. Specific Background: PT. Sinar Genta Logistik distributes three-wheeled Viar motorcycles using double-deck trucks but has not yet optimized its delivery routes. Knowledge Gap: Although the Ant Colony Optimization (ACO) method has been widely applied in solving distribution problems, its application in routing three-wheeled vehicle shipments with fleet capacity constraints using real industry data is limited. Aims: This study aims to optimize delivery routes to reduce travel distance and improve route allocation by applying the ACO algorithm. Results: Using Python programming on Google Colab, the ACO method reduced the total travel distance from 1,849.8 km to 1,556.5 km—a reduction of 293.3 km or 15.86%. The new routing model reorganized deliveries into six vehicle routes adjusted to truck capacity. Novelty: The research applies ACO specifically for the distribution of Viar three-wheeled vehicles with real-world data, integrating Google Maps-based routing and considering capacity constraints. Implications: The findings offer a practical solution for logistics firms to decrease operational distance and adopt algorithm-based distribution strategies for cost efficiency and timely deliveries. Highlights: ACO reduced total delivery distance by 15.86%. Delivery restructured into six efficient routes. Uses real company data and Python-based ACO. Keywords: Ant Colony Optimization, Vehicle Routing Problem, Logistics, Fleet Capacity, Viar
Optimizing Spare Part Delivery Routes Using Ant Colony Optimization: Optimasi Rute Pengiriman Suku Cadang Menggunakan Algoritma Koloni Semut Septia Anggraini; Enny Aryanny
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.11477

Abstract

General Background: Efficient route planning is a fundamental aspect of logistics, directly impacting operational costs, fuel consumption, and customer satisfaction. Specific Background: A logistics company based in Batam has been facing inefficiencies in spare part delivery operations due to suboptimal routing strategies. Knowledge Gap: While various routing solutions exist, few are tailored to accommodate dynamic, real-world constraints such as vehicle capacity and varying delivery points in mid-scale logistics operations. Aim: This study aims to optimize delivery routes using the Ant Colony Optimization (ACO) algorithm by modeling the problem as a Vehicle Routing Problem (VRP) with specific operational constraints. Results: The implementation of ACO significantly reduced total travel distance compared to the company’s existing manual routing approach. As a result, fuel consumption was lowered, delivery times improved, and customer service enhanced. Novelty: Unlike generic routing systems, the proposed ACO-based model dynamically adapts to real operational variables through pheromone-based local and global updates, improving the solution iteratively with each cycle. Implications: This research provides a practical and intelligent decision-support framework for logistics planning, demonstrating that metaheuristic algorithms such as ACO can robustly handle complex delivery challenges and be scaled to broader logistics applications Highlights: Improves route efficiency using ACO in real delivery operations. Reduces distance, fuel usage, and delivery time significantly. Provides a scalable model for intelligent logistics planning. Keywords: Ant Colony Optimization, Vehicle Routing Problem, Logistics Efficiency, Route Optimization, Metaheuristic Algorithm
Controlling Raw Material Inventory for Methanol Production Using the Silver Meal Method: Pengendalian Persediaan Bahan Baku Penunjang Methanol Menggunakan Metode Silver Meal Hafidz Raif Harashta; Enny Aryanny
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.11651

Abstract

General background: Effective inventory control is essential for manufacturing firms to ensure operational continuity and cost efficiency. Specific background: Methanol production facilities often experience persistent overstock of supporting chemicals such as Caustic Soda Flake (NaOH) and Sulphuric Acid (H₂SO₄), resulting in increased storage costs and heightened safety risks. Knowledge gap: Prior studies predominantly apply the Silver Meal heuristic to primary raw materials, with limited evidence of its effectiveness for fluctuating supporting materials in high-risk chemical industries. Aims: This study aims to optimize supporting-material inventory using the Silver Meal method to reduce total inventory costs and improve ordering policies. Results: The method produced lower total costs—Rp 4.144.915.411 for Caustic Soda and Rp 1.096.242.822 for Sulphuric Acid—representing reductions of 4.6% and 8.5% compared to the existing approach commonly used in industry. Novelty: The study introduces the application of a heuristic lot-sizing method to hazardous supporting materials using actual operational data, demonstrating its feasibility in chemically sensitive environments. Implications: Findings provide a practical decision-support model for companies to minimize overstock, enhance operational efficiency, and mitigate safety hazards associated with chemical accumulation. Highlights: Highlights the efficiency of the Silver Meal method in reducing total inventory costs. Addresses overstock issues of hazardous supporting materials in methanol production. Provides a practical model for safer and more economical inventory management. Keywords: Inventory Control, Silver Meal, Methanol Production, Supporting Materials, Cost Optimization
Integrated Lean Warehousing Framework Reduces Lead Time in Raw Material Warehouse: Kerangka Kerja Lean Warehousing Terintegrasi untuk Mengurangi Lead Time pada Gudang Bahan Baku M. Husin As Ari; Enny Aryanny
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13443

Abstract

General Background: Warehousing process flow efficiency plays a crucial role in supporting manufacturing operational performance, yet warehouse activities are often dominated by non-value-added tasks. Specific Background: This condition was identified in the raw material warehouse of PT XYZ, a paint manufacturing company, where delays in material flow, repetitive administrative processes, and unstandardized verification procedures contributed to inefficiencies. Knowledge Gap: Although Lean Warehousing is widely recommended, studies integrating Value Stream Mapping (VSM), Process Activity Mapping (PAM), VALSAT, and Fishbone analysis in raw material warehouses remain limited. Aims: This study aims to identify dominant waste and formulate structured improvement proposals to improve warehouse flow efficiency. Results: Initial mapping identified 29 activities with a total lead time of 12,580.2 seconds and a Process Cycle Efficiency (PCE) of 11.70%, dominated by Necessary Non-Value-Added activities (9,811.6 seconds). After implementing the integrated Lean Warehousing framework supported by 5S principles, total lead time decreased to 10,944.8 seconds and PCE increased to 13.45%, representing a 1.75% improvement. Novelty: This research proposes a multi-tools integrated Lean Warehousing framework (VSM–PAM–VALSAT–Fishbone) specifically applied to a raw material warehouse in the paint industry. Implications: The findings demonstrate that structured waste identification and process simplification can systematically improve warehouse performance and provide a replicable model for manufacturing warehouse optimization. Highlights: Initial mapping revealed 29 activities dominated by Necessary Non-Value-Added time of 9,811.6 seconds. Process simplification reduced total flow duration from 12,580.2 to 10,944.8 seconds. Process Cycle Efficiency increased from 11.70% to 13.45% after structured improvement implementation. Keywords: Lean Warehousing, Process Activity Mapping, VALSAT, Value Stream Mapping, Fishbone Diagram
Integrated SQC and FMEA Framework for Woven Bag Defect Reduction In Manufacturing Industry: Kerangka Terpadu SQC dan FMEA untuk Pengurangan Cacat Woven Bag Di Industri Manufaktur Asmaul Husna; Enny Aryanny
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13453

Abstract

General Background: In highly competitive manufacturing industries, systematic quality control is required to maintain product conformity and reduce defect rates. Specific Background: PT XYZ, a plastic packaging manufacturer, recorded woven bag production of 41,749,730 sheets in 2025 with a defect rate of 3.14%, exceeding the company target of below 2%, resulting in rework and recycled products. Knowledge Gap: Previous studies combining Statistical Quality Control (SQC) and Failure Mode and Effect Analysis (FMEA) applied SQC tools to aggregated defect data without differentiating defect types, limiting analytical precision. Aims: This study aims to analyze woven bag quality using an integrated SQC and FMEA framework and to determine prioritized corrective actions based on Risk Priority Number (RPN). Results: Four dominant defects were identified: knit-through (354,623 sheets; 27.1%), improper stitching (25.6%), uneven cutting (24.3%), and printing mismatch (23%). Scatter diagrams indicated a positive relationship between production volume and defect quantity, while p control charts revealed multiple points outside control limits. FMEA results showed the highest RPN (336) for knit-through caused by suboptimal yarn tension on the circular loom machine. Novelty: This research applies SQC tools separately to each defect category, generating more detailed diagnostic insights prior to FMEA prioritization. Implications: The findings provide data-driven recommendations, including sensor upgrades on circular loom machines, routine cleaning of cutting tools, scheduled cliché replacement, and standardized machine settings to reduce woven bag defects and strengthen manufacturing quality control. Highlights: Knit-through recorded the largest proportion of nonconformities at 27.1% of total rejected output. Control chart evaluation showed several monthly proportions exceeding statistical limits. The highest priority corrective action targeted yarn tension deviation on the circular loom with an RPN of 336. Keywords: Statistical Quality Control, Failure Mode and Effect Analysis, Risk Priority Number, Woven Bag Defects, Manufacturing Quality Control
Co-Authors Asmaul Husna Fitria Novitasari Hafidz Raif Harashta M. Husin As Ari Septia Anggraini