Application of the Single Moving Average, Weighted Moving Average and Exponential Smoothing Methods For Forecasting Demand At Boy Delivery

Alex, Muhammad Asyrof Hidayatullah; Rahmawati, Nur

doi:10.36456/tibuana.6.1.6442.32-37

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…The selection of forecasting models involved a comprehensive consideration of different approaches. Classical time series models, including Moving Average (MA), Weighted Moving Average (WMA), and Exponential Smoothing, were among the initial methodologies applied [9]. These traditional models provided a baseline for comparison against more sophisticated techniques [10].…”

Section: Model Selection and Implementationmentioning

confidence: 99%

Innovative Framework for Effective Service Parts Management in the Automotive Industry

Balasubramanian,

Chebiyyam

et al. 2023

Preprint

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The Thailand automotive industry grapples with complex challenges in service parts management, demanding a strategic approach for post-sales operations. This research unveils a tailored methodology, leveraging historical sales data, refined part classifications, and strategic decision rules. A high-level overview of the automotive supply chain emphasizes interconnected stakeholders. The systematic methodology delves into part categorization, decision rules, and data analysis. Decision rule outcomes, exceptions, and contingency solutions showcase efficacy. A cost impact assessment highlights substantial savings. Visualization tools offer nuanced perspectives. Optimized service parts classification, robust stocking decision rules, and cost-effective strategies emerge. Support Vector Regression excels in forecasting, with recommendations for dynamic stocking. Implications extend to the broader industry, offering efficiency and service quality blueprints. Acknowledging limitations and suggesting future research, this study contributes a valuable framework for Thai automotive service parts management.

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Section: Model Selection and Implementationmentioning

confidence: 99%

Innovative Framework for Effective Service Parts Management in the Automotive Industry

Balasubramanian,

Chebiyyam

et al. 2023

Preprint

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Innovative framework for effective service parts management in the automotive industry

Nathan,

Siva Reddy,

Sastry

et al. 2024

Front. Mech. Eng.

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Effective service parts management and demand forecasting are crucial for optimizing operations in the automotive industry. However, existing literature lacks a comprehensive framework tailored to the specific context of the Thai automotive sector. This study addresses this gap by proposing a strategic approach to service parts management and demand forecasting in the Thai automotive industry. Drawing on a diverse set of methodologies, including classical time series models and advanced machine learning techniques, various forecasting models were assessed to identify the most effective approach for predicting service parts demand. Categorization of service parts based on demand criteria was conducted, and decision rules were developed to guide stocking strategies, balancing the need to minimize service disruptions with cost optimization. This analysis reveals substantial cost savings potential through strategic stocking guided by the developed decision rules. Furthermore, evaluation of the performance of different forecasting models recommends the adoption of Support Vector Regressor (SVR) as the most accurate model for forecasting service parts demand in this context. This research contributes to the automotive service industry by providing a nuanced framework for service parts management and demand forecasting, leading to cost-effective operations and enhanced service quality. The findings offer valuable insights for practitioners and policymakers seeking to improve efficiency and sustainability in the Thai automotive sector.

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Application of the Single Moving Average, Weighted Moving Average and Exponential Smoothing Methods For Forecasting Demand At Boy Delivery

Cited by 2 publications

References 10 publications

Innovative Framework for Effective Service Parts Management in the Automotive Industry

Innovative Framework for Effective Service Parts Management in the Automotive Industry

Innovative framework for effective service parts management in the automotive industry

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