Academic Journal of Industrial Technology Innovation

A Comparison of Moving Average and Simple Exponential Smoothing Methods for Predicting Engine Oil Change Demand in Trucks: A Case Study in Songkhla Province

2024-08-02T19:32:46+07:00

The objective of this research is to predict the demand for engine oil changes in large trucks using monthly data from a case study service center between 2019 and 2021. This study focuses on comparing the performance of various prediction methods to determine the most suitable approach for forecasting future service demands. The prediction methods employed in this research comprise two main approaches: Moving Average (MA) with 3 and 5-month periods, and Exponential Smoothing with alpha (α) values of 0.1 and 0.5. Each method was applied to the same dataset to generate predictions, followed by a performance evaluation. To assess prediction accuracy, three criteria were utilized: Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Mean Squared Error (MSE). The results demonstrate that the Exponential Smoothing method with an alpha value of 0.5 yields the most accurate predictions based on MAE, MSE, and MAPE, indicating its superior ability to predict values closely aligned with actual figures. This method is recommended for planning engine oil demand in large trucks at the case study company.

Location Selection Using the Analytic Hierarchy Process: A case study of private vehicle inspection centers, Mueang, Songkhla

2024-08-02T15:39:14+07:00

This study employed the Analytic Hierarchy Process (AHP) to examine the location selection process for private vehicle inspection centers (PVICs). The research aims to (1) identify factors influencing location selection, (2) assess the relative importance of these factors, and (3) evaluate decision consistency. Data were collected through interviews with executives or decision-makers from seven PVICs in Mueang District, Songkhla Province, Thailand. An interview instrument was developed based on a comprehensive literature review of location selection research. The findings reveal four primary factors affecting the PVIC location selection, ranked in descending order of importance: facilities, customer base, raw material sources, and business premises details. Within these categories, land price, reduction of raw material transportation costs, product sales, and transportation convenience emerged as the most critical sub-factors, respectively. The analysis confirms decision consistency across all factors, with the Consistency Ratio (CR) below 0.10.

A Stepwise Multiple Regression Analysis of Factors Influencing the Decision to Choose Freight Companies' Services

2024-08-02T19:14:13+07:00

A stepwise multiple regression analysis was conducted to examine the factors influencing consumers' decisions in choosing freight forwarding companies. The objectives were to investigate the relationships between marketing strategy factors and consumers' decisions in choosing freight forwarding companies in Songkhla province, Thailand; and to develop a predictive equation using stepwise multiple regression analysis. Data were collected from 404 consumers who used freight forwarding services in Songkhla province. Pearson's correlation coefficient was used to determine the relationship between marketing strategies and other factors influencing the decision to use freight forwarding services. Stepwise multiple regression analysis was employed to create a predictive equation. The study found that the overall level of marketing strategy in influencing the decision to use freight forwarding services was moderate ( = 3.345). The correlation coefficient analysis revealed a statistically significant positive relationship at the .01 level between marketing strategies and other factors influencing the decision to use freight forwarding companies. The location factor and the product service factor were identified as significant predictors of marketing strategy in the decision to use freight forwarding services.

Activated Carbon from Cassava Rhizomes to Design Odor Absorbing Products

2024-08-07T10:17:55+07:00

Objective of this research is to: 1) utilize agricultural waste, specifically cassava rhizome types in the eastern region, 2) study the production process of activated carbon with suitable material properties, and 3) create value-added odor-absorbing products through three different design processes. The research methodology is qualitative, involving laboratory research and development, data analysis, summarization, product prototype testing, and production. The research findings are as follows: 1) Cassava rhizome types, a form of agricultural waste, have potential for value-added applications. 2) The activated carbon production process consists of two steps: charcoal preparation and subsequent stimulation to create micropores. Chemical stimulation is the most effective method, resulting in activated carbon with high porosity and strong odor-absorption capabilities. 3) Odor-absorbing products were developed: car air fresheners containing 60 % activated carbon powder and 40 % plaster, molded into a cactus shape (50x50x80 mm); kitchen deodorizers containing 70 % activated carbon powder and 30 % plaster, molded into a hexagonal shape (150x125x40 mm); and deodorizing soap containing 20 % activated carbon powder and 80 % glycerin soap base, molded into a square shape (50x50x20 mm).

A Study of Corrosion-Erosion Behavior of Low and High Carbon Steels in Acid and Sand Environments Using Taguchi's Experimental Design

2024-08-07T11:01:30+07:00

This research aims to investigate and compare the corrosion-erosion behavior of low carbon steel (AISI 1018) and high carbon steel (AISI 1060) under different environmental conditions. A Taguchi experimental design was employed to efficiently evaluate the effects of rotational speed (1,800, 3,600, and 5,400 RPM) and three environmental conditions: distilled water with sand, sulfuric acid solution at pH 4, and sulfuric acid solution at pH 4 with sand on weight loss. An L9 orthogonal array and a rotating cylinder electrode (RCE) setup were utilized for the experiments. Both steel types exhibited good corrosion-erosion resistance, particularly in the sulfuric acid solution at pH 4 without sand. Signal-to-noise ratio (S/N) analysis indicated slightly better performance for high carbon steel (S/N = 53.9) compared to low carbon steel (S/N = 52.4). These findings can be applied to select suitable materials for applications demanding resistance to diverse environments, especially those with high acidity. The application of Taguchi methodology facilitated efficient experimental planning and analysis, enabling informed material selection.