Greeners: Journal of Green Engineering for Sustainability

Integrating Quality Function Deployment and 3D CAD for Composter Machine Design

2026-08-28T09:19:53+00:00

Organic waste management in urban residential areas remains a serious challenge, including at the temporary waste collection site (TPS) of The Vitka City Complex, Batam, where about 7.3 tons of organic waste per week is largely unprocessed, causing odor, maggot infestation, leachate accumulation, and potential soil and water pollution. This study aims to identify user requirements for a composter machine using the Quality Function Deployment (QFD) method and to develop a 3D Computer-Aided Design (CAD) based design that improves organic waste processing at the site. A descriptive quantitative approach was applied through field observation, structured interviews, and a five-point Likert questionnaire administered to 16 site managers and officers. All 15 user-need items (Voice of Customer) were valid, with item-total correlations of 0.70 to 0.88, and reliable, with a Cronbach's alpha of 0.89. QFD analysis produced seven technical characteristics, with large capacity and strong construction obtaining the highest relative weight (25%), followed by an optimal shredding system (19%) and a simple control system (19%). The design was developed in SolidWorks 2021 as a 1,000 kg capacity machine with steel shredding blades, a simple control panel, an aeration system, and an emergency stop. Static simulation using AISI 4340 steel showed that the dominant working stress remained below the material yield strength, indicating a structurally safe design. Integrating QFD and 3D CAD thus produces a composter design that matches actual user needs and can serve as a model for sustainable organic waste management in other residential areas.

The Comparative Perfomance and Kinetics of Phytoremediation and Bioremediation Systems for Tofu Wastewater

2026-09-28T07:21:01+00:00

Tofu industrial wastewater contains high levels of organic matter and suspended solids and is acidic, posing a significant water pollution risk if discharged untreated. This study aims to compare the effectiveness of phytoremediation using water hyacinth (Eichhornia crassipes) and eco-enzyme in reducing chemical oxygen demand (COD), total suspended solids (TSS), and pH of home-scale tofu wastewater. An experimental study was conducted over six days with three treatments: five water hyacinth plants (P1), a combination of water hyacinth and 10% eco-enzyme (P2), and 10% eco-enzyme alone (P3), with testing performed on days 0, 3, and 6. The initial wastewater characteristics showed a COD of 163.75 mg/L, TSS of 440 mg/L, and pH of 4.55. Treatment P1 yielded a COD reduction of approximately 41% and a TSS reduction of about 45% by day 6, along with an increase in pH to 4.82. Treatment P2 reduced COD by about 20.6% and TSS by about 36.3%, whereas P3 reduced COD by approximately 27.7% and TSS by 25%; both treatments decreased the pH to 3.82–4.34. One-way ANOVA tests revealed that exposure duration (3 and 6 days) had no significant effect on COD (p = 0,091), TSS (p = 0,628), or pH (p = 0,669). These findings indicate that water hyacinth without eco-enzyme supplementation is more effective and simpler to apply under the conditions of this study.

Design of Python-Based Expert System for Healthy Diet Recommendations Using Forward Chaining

2026-09-29T07:17:36+00:00

A healthy diet is an important factor in maintaining overall health. However, many people still have difficulties determining their weight status, daily calorie requirements, and appropriate dietary patterns based on their individual conditions. In addition, the variety of diet information available on the internet may make it difficult for users to select appropriate recommendations. This study aims to design an expert system that calculates Body Mass Indes (BMI), determines calorie requirements, and provides dietary recommendations and health advice based on user conditions. The inference method used is Forward Chaining, supported by a knowledge base consisting of user facts and IF-THEN rules based on nutritional expertise. Specifically, the IF-THEN rules map user inputs (such as age, height, weight, target weight, and meal frequency) to evaluate BMI classification thresholds (e.g., if 25 ≤ BMI ≤ 30, the system triggers an Overweight status and assigns an 1800 kcal target) along with supplementary goal-adjustment rules. The validation of these rules and the system's mathematical accuracy were verified through clinical test scenarios. The results show that the system can automatically calculate BMI, determine BMI status, provide calorie requirement information, and generate meal recommendations and health advice based on predefined rules. However, the system's scope is strictly limited to general BMI-based nutritional estimation and does not account for biological sex, physical activity levels, or pre-existing medical conditions; therefore, its automated outputs serve solely as a practical supporting tool and do not replace professional medical or nutritional consultation.

Hazardous Waste Risk Analysis in Heavy Equipment Maintenance

2026-09-25T08:41:26+00:00

The increasing frequency of heavy equipment maintenance activities has led to a significant rise in hazardous waste generation, which may pose operational, environmental, and occupational health and safety (OHS) risks if not properly managed. This study aims to identify failure modes, prioritize risks using Failure Mode, Effects, and Criticality Analysis (FMECA), determine root causes through Root Cause Analysis (RCA), and develop improvement recommendations for hazardous waste management in heavy equipment maintenance activities at PT XYZ. A case study approach was employed, with data collected through field observations, interviews, documentation, and expert judgment involving four experts. Risk assessment was conducted using Severity (S), Occurrence (O), and Detection (D) scores to calculate the Risk Priority Number (RPN). Normalized RPN (NRPN) values were classified as high risk (NRPN > 75%), moderate risk (50% < NRPN ≤ 75%), and low risk (NRPN ≤ 50%). The results identified 15 failure modes, comprising four high-risk, nine moderate-risk, and two low-risk failure modes. FM-08, involving contamination of the drainage system by used oil and dirt, had the highest RPN of 324 (NRPN = 100%). The four high-risk failure modes were further analyzed using RCA, which identified human factors, work methods, and facilities as the predominant root cause categories, with material and environmental factors also contributing to several failure modes. Improvement recommendations were subsequently developed using the 5W+1H approach. The integration of FMECA and RCA provides a systematic framework for prioritizing risks, identifying root causes, and formulating targeted improvements in hazardous waste management during heavy equipment maintenance activities.

Turbine Ventilator Layout Design for a Food Product Logistics Warehouse

2026-10-05T08:59:27+00:00

This study aims to determine the required number of turbine ventilators and design an optimal layout for a food logistics warehouse, taking into account air circulation, temperature, relative humidity, airflow distribution, and heat reduction. The research employs an experimental method combined with quantitative analysis. Measurements were taken at 17 points using a multi-sampling approach over a three-day period. The recommended air exchange rate for the warehouse is 2–4 air changes per hour (ACH), in accordance with the Axair Industrial Ventilation Guide and HVAC standards. Several ventilator layout alternatives were developed and evaluated using a Performance-Based Design (PBD) approach, considering ACH values, temperature, relative humidity, airflow distribution, and the effectiveness of heat reduction. The results indicate that the current ventilation system produces an airflow rate of 3,691.01 m³/hour, equivalent to an ACH of 0.37 per hour. The average air velocity was recorded at 0.089 m/s, with an average temperature of 30.13°C and an average relative humidity of 77%; these conditions reflect inadequate air circulation and an environment that exceeds recommended limits. Based on the ACH calculations, 12 turbine ventilators are required to achieve 2 ACH, 19 units for 3 ACH, and 25 units for 4 ACH. The PBD evaluation identifies the 19-unit configuration as the optimal design, as it effectively balances improved air circulation, airflow distribution, temperature and humidity control, and implementation efficiency. This configuration is expected to enhance ventilation performance and support more suitable storage conditions for packaged food products within the warehouse.