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Journal : Jurnal IPTEK

ANALYSIS OF LOCATION AND DECISION-MAKING OF FLEET VEHICLE TYPE WITH CVRP MULTI TRIP AND GRAVITY LOCATION MODEL FOR OPERATIONAL COST EFFICIENCY (Case Study CV. XYZ, Wonoayu-Sidoarjo) Nofan Hadi Ahmad; Tri Novita Sari; Ari Pranata Primisa Purba
Jurnal IPTEK Vol 27, No 1 (2023)
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2023.v27i1.2344

Abstract

Transportation has an important role in the logistics of a company, both in services and products. Increased orders in 2020 for wooden speaker products at CV. XYZ (Wonoayu-Sidoarjo) makes this company try to minimize transportation costs at their operational level. This study focuses on determining the relationship between changes in the type of fleet vehicle and the depot location on the operational costs of product delivery and the time to return to the depot in terms of adding trips. The methodology used in this study is the CVRP Multi Trip with Heterogeneous fleet vehicle and the Gravity Location Model based on the heuristic method. Saving heuristic method and nearest neighbor are heuristic methods used in computational studies to determine the order of visits to the formed sub-routes. There are 4 scenarios that are modeled to further analyze the results of these computations, namely: (1) CVRP multi-trip of old location with wings box truck, (2) CVRP multi-trip of old location with Fuso truck, (3) CVRP multi-trip of the new location with wings box truck, and (4) CVRP multi-trip of the new location with fuso truck. The results of the study concluded that there is a relationship between: (1) changes in fleet vehicle type with total traveling distance, (2) changes in depot location with total traveling distance, (3) fuel consumption rate on vehicle operating costs, (4) average vehicle speed on the time back to the depot. Scenario 4 is the best scenario in terms of traveling distance, fuel costs and delivery time. However, moving the depot center is not easy, so the scenario 2 is the most applicable condition considering that the fuso truck is available and has a higher utility than the wings box truck
ANALYSIS OF LOCATION AND DECISION-MAKING OF FLEET VEHICLE TYPE WITH CVRP MULTI TRIP AND GRAVITY LOCATION MODEL FOR OPERATIONAL COST EFFICIENCY (Case Study CV. XYZ, Wonoayu-Sidoarjo) Ahmad, Nofan Hadi; Sari, Tri Novita; Purba, Ari Pranata Primisa
Jurnal IPTEK Vol 27, No 1 (2023): May
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2023.v27i1.2344

Abstract

Transportation has an important role in the logistics of a company, both in services and products. Increased orders in 2020 for wooden speaker products at CV. XYZ (Wonoayu-Sidoarjo) makes this company try to minimize transportation costs at their operational level. This study focuses on determining the relationship between changes in the type of fleet vehicle and the depot location on the operational costs of product delivery and the time to return to the depot in terms of adding trips. The methodology used in this study is the CVRP Multi Trip with Heterogeneous fleet vehicle and the Gravity Location Model based on the heuristic method. Saving heuristic method and nearest neighbor are heuristic methods used in computational studies to determine the order of visits to the formed sub-routes. There are 4 scenarios that are modeled to further analyze the results of these computations, namely: (1) CVRP multi-trip of old location with wings box truck, (2) CVRP multi-trip of old location with Fuso truck, (3) CVRP multi-trip of the new location with wings box truck, and (4) CVRP multi-trip of the new location with fuso truck. The results of the study concluded that there is a relationship between: (1) changes in fleet vehicle type with total traveling distance, (2) changes in depot location with total traveling distance, (3) fuel consumption rate on vehicle operating costs, (4) average vehicle speed on the time back to the depot. Scenario 4 is the best scenario in terms of traveling distance, fuel costs and delivery time. However, moving the depot center is not easy, so the scenario 2 is the most applicable condition considering that the fuso truck is available and has a higher utility than the wings box truck
Inventory Analysis of Spare Part Using Always, Better, Control (ABC) and Economic Order Quantity (EOQ) Method in PT. XYZ - Medan Ahmad, Nofan Hadi; Mufti, Wahyu Fitrianda; Sari, Tri Novita; Muti, Asri Amalia; Yulfadila, Yulfadila
Jurnal IPTEK Vol 29, No 2 (2025): December
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2025.v29i2.7557

Abstract

Inventory plays a pivotal role in a company's logistics, serving both to fulfill external customer demands and to enhance internal production efficiency. However, PT. XYZ in Medan did not address yet several cost factors that could significantly influence the overall procurement expenses of spare parts, particularly given that certain spare parts carry notably high purchase prices. While PT. XYZ has been placing orders for spare parts, these are typically initiated only when stock is depleted, based on the assumption that spare parts fall under the category of slow-moving goods. Consequently, it is imperative to conduct an inventory analysis to identify gap between the existing conditions and the outcomes derived from the proposed methodological approach. The methodology used in this study is Always, Better, Control (ABC) method to classify spare parts based on their cost percentage and Economic Order Quantity (EOQ) method to analyze the economic order size, order frequency and optimal ordering time. From the results of data processing that has been done, there are 7 types of spare parts that fall into category A and there is a decrease in Total Variable Cost (TVC) ranging from 13% to 40% from existing conditions. Ordering costs consist of telecommunications costs, labor costs, fuel costs and loading/unloading costs; while storage costs consist of electricity costs and maintenance costs. Scheduling the time of reordering or sending purchase order (PO) to the vendor, the number of spare part units to be ordered and the estimated arrival of spare parts are carried out based on the EOQ calculation that has been compared and adjusted to the previous existing conditions.