Journal Name OPSI Journal Initial OPSI Journal Abbreviation OPSI Frequency 2 issues per year (June and December) DOI prefix 10.31315 ISSN 1693-2102 (print) 2686-2352 (online) Editor-in-chief Eko Nursubiyantoro Managing Editor Raden Achmad Chairdino Leuveano Publisher Universitas Pembangunan Nasional Veteran Yogyakarta Submissions Received 69 Articles/year Days to First Editorial Decision 107 Days Acceptance Rate 39% Opsi is an Industrial System Optimization Journal published by the Industrial Engineering Department of Universitas Pembangunan Nasional "Veteran" Yogyakarta to publish scientific works or technological engineering research related to Industrial Engineering, Industrial Systems, Industrial Management, and Information Technology. e-ISSN p-ISSN OPSI ISSN 2686-2352 (online) and 1693-2102 (printed) are published regularly every 6 months (in June and December). OPSI provides readers with open access to download and read the journal's contents. This journal fully supports the commitment to exchange information and knowledge with the public. All articles are open-access, yet readers are not permitted to modify the article's contents without the publisher's permission. OPSI Journal has been accredited SINTA 3 by The Ministry of Research, Technology, and Higher Education (RistekDikti), acknowledged on December 23rd, 2020. After two years, the quality improvement of the journal has brought the Opsi Journal to a new level of accreditation, that is SINTA 2, which starts in Volume 15 No. 1 of 2022 All submitted manuscripts will be initially reviewed by editors and then evaluated by at least two reviewers through the double-blind review process. This is to ensure the quality of the published manuscripts in the journal. Before Submission The author must ensure that the manuscript has been prepared using the template and following the author guidelines. The manuscript should also have been carefully proofread. Any manuscript that does not meet the template requirements will be rejected
Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta
Authors who publish articles in this journal agree to the following conditions: Copyright remains with the author and gives the Opsi journal the right as a priority to publish its articles with Creative Commons Attribution 4.0 International license. Which allows articles to be shared with acknowledgement of the author of the article and this journal as the place of publication. Authors can distribute their articles on a non-exclusive basis (e.g. in university repositories or books) with notification or acknowledgement of publication in Opsi journals. Authors are allowed to post their work online (e.g. on a personal website or in a university repository) before and after the submission process (see The Effect of Open Access) This work is Licensed Under a Creative Commons Attribution 4.0 International license.
Integrated Weibull-based maintenance optimization and root cause analysis for improving reliability of an electronic production systems
Unexpected equipment failures in electronics manufacturing can disrupt production continuity, increase maintenance costs, and reduce system reliability. Although reliability-centered maintenance approaches have been widely applied, most studies focus on maintenance interval optimization without systematically integrating failure prioritization and root-cause analysis for continuous reliability improvement. This study proposes an integrated framework combining Weibull reliability modeling, age-replacement cost optimization, Pareto analysis, and fishbone root-cause investigation to improve equipment reliability while minimizing maintenance costs. Historical failure data were analyzed to estimate Weibull parameters and determine the optimal preventive maintenance interval, while Pareto and fishbone analyses were used to identify dominant failure modes and their root causes for targeted corrective actions. The framework was implemented in an electronics manufacturing system and the results indicate a wear-out failure pattern with a Weibull shape parameter greater than one. Before improvement, the optimal preventive maintenance interval was approximately 510 operating hours. After implementing corrective actions, equipment reliability increased from 89.05% to 90.40%, the expected maintenance cost rate decreased by 6.14%, and the mean operating interval between failures increased by 1.07%. The proposed framework provides a practical decision-support tool for integrating reliability improvement with maintenance policy optimization, thereby enhancing equipment performance and production continuity in electronics manufacturing systems.
An evaluation of life cycle assessment and cost-benefit analysis of an ecoprint fabric micro, small, and medium enterprise in Yogyakarta
The rapid growth of the fashion industry has led to the emergence of fast fashion, which often overlooks its environmental impacts. In contrast, environmentally conscious practices are being adopted by some enterprises, including an MSME located in Yogyakarta, Indonesia, specializing in ecoprint fabric production. To evaluate its environmental and economic performance, this study conducts a Life Cycle Assessment (LCA) and Cost-Benefit Analysis (CBA) focusing on green production, green transportation, and green packaging. LCA results show that the use of LPG in the steaming process has notable environmental impacts, particularly in fossil depletion (0.00076), climate change–human health (0.000359), and human toxicity (0.0000956). Based on these findings, Solar PV was evaluated as an improvement condition to reduce dependence on LPG and mitigate environmental impacts across several categories. However, human toxicity increased from 9.56E-05 to 0.00164, indicating environmental trade-offs throughout the life cycle. The CBA results indicate that the existing production system is economically feasible, with NPV of IDR 58,781,312, IRR of 9%, BEP of 2,136.34 units (IDR 534,084,829.96), Payback Period of 5.52 years, and BCR of 1.40. This implies that the project is already economically feasible under current LPG use, while the substitution with Solar PV further enhances its sustainability and overall benefits.
From standards to practice: Applying ISO/IEC 27005:2022 for information security risk management in regional water company
Regional water companies have increasingly adopted information technology to support their operations. However, the absence of formalized information security risk management procedures can lead to substantial operational disruptions and financial losses. Therefore, this study aims to conduct a systematic risk assessment of a regional water company based on its IT assets, utilizing the ISO/IEC 27005:2022 standard. Data collection through semi-structured interviews and questionnaires with the company's IT department identified 31 assets, which were subsequently used for risk mapping and assessment. The assessment identified a total of 265 risk scenarios, categorized into 10 High (3.77%), 68 Medium (25.66%), and 187 Low (70.57%) level risks. Following the evaluation where all risks were deemed unacceptable, risk modification was recommended as treatment for all risk scenarios. Based on the results of the risk assessment, control recommendations were developed according to ISO/IEC 27001:2022 to assist the company in managing and mitigating risks. The implementation of the two ISO standards aligns to comprehensively map risks and provide a structured mitigation plan. These results are expected to assist the company in establishing formal risk management procedures and maintain business process continuity and effectiveness.
Forecast-guided simulation for optimizing cargo handling personnel requirements
The increase in the number of cargo handling at the Ahmad Yani Airport Domestic Cargo Terminal has reached 217.18% from 2009 to 2019, but decreased by 47% in 2020 due to the COVID-19 pandemic. It will affect the service in cargo handling, especially the number of personnel and facilities. This research was conducted to determine the optimal number of Cargo handling personnel at a logistics company in 2024. The forecasting methods used are Linear Moving Average, Double Exponential Smoothing Brown's, and Simple Linear Regression, where these methods will be compared to see which method has the smallest error value. Then a cargo handling simulation model will be created for this company in 2024 to find out the optimal number of Cargo handling personnel at the logistics company uses ARENA Simulation Software. The results show that in 2024 with the simple linear regression method (which has the smallest error) around 7,816,594.9 kg of Cargo is predicted as incoming Cargo, and around 7,847,581.01 kg of Cargo is predicted as outgoing Cargo in that year at the logistics company. And from the simulation model, it is found that to optimize the number of cargo handling personnel, the number of additional personnel required is 1 Aviation Security, Dispatcher, and Transporter.
Implementation of YOLO11 for accurate waste detection
Waste management, particularly the waste sorting process, remains a major challenge in urban areas. Manual sorting is often inefficient and prone to human error, highlighting the need for an accurate and automated waste classification system. This study investigates the implementation of the YOLO11 model for detecting and classifying six waste categories—plastic, paper, glass, metal, electronics, and organic—using a bounding box-based object detection approach. The lightweight YOLO11n variant developed by Ultralytics was employed in this study. The dataset was obtained from previous research and subsequently annotated, augmented, and divided into training, validation, and testing subsets. The model was trained for 100 epochs using the default configuration on an NVIDIA GeForce RTX 4060 Ti GPU (16 GB VRAM). During the final evaluation on the unseen test dataset, the model demonstrated reliable generalization and classification performance, achieving an overall macro-average precision of 0.75, an overall recall of 0.87, and a global F1-score of 0.79. The Paper and Plastic classes showed the highest detection performance, with Plastic achieving a flawless recall of 1.00, while the Organic class remained the most challenging due to higher visual variability. These results demonstrate that YOLO11n provides an effective approach for automated waste detection and has the potential to support more efficient and accurate waste management systems.
Barriers and drivers of sustainable hotel implementation: A systematic review
Sustainability is becoming progressively important in the hospitality industry, especially in the implementation of sustainable practices in hotels. This study is a systematic literature review (SLR) that aims to explore the barriers and drivers of sustainable hotel implementation across four key pillars: economic, social, environmental, and cultural. The paper synthesizes existing studies from 2020 to 2026 to identify factors that hinder and promote sustainability in hotels. Barriers include financial constraints, lack of awareness, and complex regulations, while drivers such as cost savings, improved guest experiences, and government incentives play significant roles. The analysis suggested potential strategies to help hotels navigate these barriers and utilize key drivers to reach sustainability. The mapping of potential strategies highlights the need for integrated policies, employee training, and technology investments. The study demonstrates that stakeholder engagement in facing challenges is key to the successful implementation of sustainability in hotels. The implications of this research are essential for guiding hotel management, policymakers, and society in building and supporting sustainable practices within the hospitality industry.
A proposed socio-technical demand–resource equilibrium model for burnout mitigation
Research on burnout mitigation is expanding rapidly. However, the evidence remains fragmented and is often confined to healthcare or education-specific contexts. To improve transferability across broader work systems, this study conceptualizes burnout mitigation as a socio-technical and ergonomic problem. A structured narrative review combined with exploratory bibliometric analysis was conducted using Scopus-indexed literature. Literature identification and selection adopted PRISMA-informed screening procedures. After screening and eligibility assessment, 13 studies were included in the final review corpus. Bibliometric mapping was performed using VOSviewer (v1.6.20) to explore thematic relationships and keyword co-occurrence patterns. The exploratory bibliometric mapping identified thematic concentrations around individual recovery and resilience, peer and community support, technology-mediated work redesign, and organizational or macroergonomic interventions. The findings indicate a gradual shift from prevalence-oriented burnout research toward mitigation-focused and prevention-oriented approaches. The study proposes the Socio-Technical Demand–Resource Equilibrium Model (SoTDREM) as a conceptual framework for burnout mitigation, advancing macroergonomic theory by positioning burnout mitigation as systemic design optimization rather than individual resilience enhancement. The framework offers a preliminary conceptual structure that can inform future ergonomic assessment and empirical validation of burnout mitigation strategies across sectors.
Proposed design of prosthetic arm with the integration of Kano model and TRIZ method
Individuals with upper-limb disabilities face substantial limitations in performing daily activities. Statistics Indonesia reports that 62.59% of persons with disabilities have physical impairments, while the Special Region of Yogyakarta ranks among the three provinces with the highest prevalence of finger and hand mobility disorders, at 0.44%. However, most available prosthetic devices remain primarily cosmetic and provide limited functional performance, leaving users’ needs and expectations unmet. This study aims to design a functional prosthetic hand that addresses user requirements and expectations by integrating the Kano model and the TRIZ (Teoriya Resheniya Izobretatelskikh Zadatch) method. The Kano model was applied to identify and classify user needs based on satisfaction levels, involving 15 individuals with upper-limb disabilities in Gunungkidul Regency. TRIZ was subsequently used to develop systematic and innovative design solutions. The proposed design emphasizes functionality, comfort, safety, ergonomics, ease of use, product quality, and aesthetic appearance. The design was validated through feedback from users and experts. Of the 13 respondents involved in the validation process, 11 agreed with the proposed design, while two recommended minor revisions to accommodate specific disability conditions. The final design consists of two prosthetic configurations: transhumeral and transradial prosthetic hands.
Minimization of waiting time in coal loading and unloading processes to reduce demurrage using value stream mapping
Demurrage issues pose a significant challenge that affects operational efficiency in the coal transportation industry, particularly in the coal transhipment process using mother vessel and barges. This study aims to identify and reduce waiting times that cause demurrage. Waste identification leading to demurrage was conducted through a structured Value Stream Mapping (VSM) approach consisting of current-state mapping, waste identification and analysis, process activity mapping, and future-state mapping to develop improvement recommendations for coal loading and unloading operations. The results from the Port of Loading (POL) showed a significant improvement in operational efficiency after the proposed improvements were incorporated into the future-state process. Before the improvements, value-added activities contributed 28.20% of the total time and increased to 84.97%. The total loading time was reduced from 10.04 days to 3.17 days. At the Port of Discharge (POD), value-added activities increased from 47.27% to 77.24%, and the unloading time decreased from 14.58 days to 4.89 days. This improvement was achieved through better coordination, equipment maintenance, and optimization of the loading and unloading process, which significantly enhanced overall efficiency and reduced demurrage costs. This study highlights the importance of process optimization in the coal shipping industry, offering valuable insights to reduce delays and improve profitability.
Effect of bottom front roller eccentricity on yarn unevenness (U%), mass variation (CV%), and hairiness in PV 30 ring spinning
This study demonstrates that bottom front roller eccentricity in ring spinning negatively affects PV 30 yarn quality by increasing yarn unevenness (U%) and mass variation (CV%). Using a paired-sample experimental design and paired t-test analysis, the study evaluated yarn quality before and after corrective alignment of the bottom front roller under controlled mechanical and environmental conditions. Yarn unevenness decreased from 9.43 ± 0.20 to 8.55 ± 0.06, while yarn mass variation decreased from 11.87 ± 0.30 to 10.76 ± 0.10 after corrective alignment, indicating statistically significant improvements in drafting stability and yarn uniformity (p < 0.05) with a large practical effect size based on Cohen’s d analysis (Cohen’s d = 1.21). The bottom front roller was specifically investigated because it directly controls fiber movement within the drafting zone, where mechanical instability can generate irregular fiber tension and drafting waves. In contrast, no statistically significant effect on yarn hairiness was observed. From an industrial engineering perspective, the findings highlight the importance of preventive maintenance and precise roller alignment in reducing off-quality yarn production, minimizing material waste, and improving operational efficiency. Unlike previous studies that broadly examined drafting irregularities and machine vibration, this study specifically isolates the effect of bottom front roller eccentricity before and after corrective alignment under controlled operating conditions.
Proactive quality control in cotton yarn manufacturing using random forest defect forecasting and CTQ analysis
Quality control in cotton yarn manufacturing is affected by the daily variation in the occurrence of defects and the late detection of abnormal events at the packing stage. This study proposes a decision-support workflow that integrates Random Forest regression for daily defect forecasting with Critical-to-Quality (CTQ) analysis to enable proactive quality control in an industrial case. The model is trained and validated with time ordered evaluation using historical production volume and defect counts, and the performance is reported using MAE, RMSE and sMAPE. Results indicate that the model learns to capture routine up-down defect patterns during the training period, but prediction accuracy is degraded on test days with extreme defect spikes. However, despite this limitation, the forecast outputs provide an early warning signal to prioritize inspection and corrective actions on high risk days. The predicted risk levels are then further linked to CTQ mapping to identify dominant defect types and convert model outputs to actionable defect-specific control recommendations. The proposed integration of machine-learning forecasting with shop-floor quality planning enables more timely and targeted quality interventions in cotton yarn packaging operations.
Implementation of cleaner production in the refined sugar industry to reduce landfilling in waste management at sugar industry in Cilegon
Sugar Industry in this study is a company located in Cilegon City, Banten Province, operating in the refined sugar industry. The objective of this study is threefold: first, to identify the flow of materials, products, and non-products in the refined sugar production process; second, to identify potential cleaner production alternatives applicable to the industry; and third, to determine the priority scale of cleaner production opportunities in the refined sugar industry. The research methods employed encompass a comprehensive array of approaches, including a thorough literature review, observational studies, environmental assessments, and comparative analyses. According to the findings of the research study, the total amount of waste generated in 2023 was 19,025.36 tons. Of this, 5,575.52 tons (29.3%) were landfilled, and 13,449.84 tons (70.7%) were reused by other industries. In 2024, the total waste generated was 16,579.35 tons, of which 16,568.44 tons were utilized by other industries as alternative fuel or alternative raw materials, and a mere 10.91 tons were sent to landfill. According to the 2024 data, a mere 0.07% of the total waste was landfilled, while a staggering 99.7% was reused by other companies. The implementation of cleaner production and zero-landfill principles has the potential to repurpose the waste generated.
Initiating a used cooking oil collection network: An SCP–TSP approach within the circular economy framework
Used cooking oil (UCO) management is a critical issue in advancing circular economy practices within the energy and environmental sectors. While UCO poses environmental risks, it also holds significant economic potential. The main challenge lies in the absence of an efficient and structured collection system. This study proposes a collection network model focusing on distance efficiency and coverage. The Set Covering Problem (SCP) was applied to identify optimal collection points, while the Traveling Salesman Problem (TSP) was used to design transportation routes to centralized facilities. Data were collected from 101 food service businesses in Bantul, with 28 units willing to serve as candidate sites. SCP results identified 12 optimal points capable of serving all sources within a 5 km radius. TSP application with two alternative centres produced efficient routes: BUMDes Panggung Lestari (95.7 km; IDR 76,560) and DLH Bantul (95.4 km; IDR 76,320). These findings demonstrate the effectiveness of SCP and TSP in reducing operational costs and expanding service coverage. The study contributes practical insights for sustainable UCO collection planning and strengthens circular economy strategies through resource reutilization.
Analysis of subsidised fertiliser distribution efficiency using the lean thinking approach following the implementation of the zero ODOL policy: A case study of deliveries to Bojonegoro Regency
The Zero Over Dimension Overload (Zero ODOL) policy, regulated by Minister of Transportation Regulation No. 60 of 2019, significantly impacted fertiliser distribution, decreasing truck transport capacity by 47%. This raised costs from Line I to Line III Bojonegoro Warehouse to Rp 26.2 billion annually. This study identifies inefficiencies and improvements using Lean Thinking with tools like Pareto Analysis, Ishikawa Diagram, and 5w+2 h. Manual loading and unloading caused waste through waiting, unproductive movements, defects, and repetition. The solution adopts pallets and forklifts to cut reliance on labour. Validated through a one-month operational pilot project managing 2,370 tonnes of fertiliser, Lean implementation structurally improved efficiency: logistics costs dropped to Rp 21 billion (20% savings), loading/unloading speed tripled from 250 to 750 tonnes/day, fertiliser damage reduced to 0.002%, and quantitative stakeholder satisfaction increased significantly. Lean delivers cost savings and enhances quality, safety, and sustainability amidst Zero ODOL challenges.
Integrating cultural dimensions into a cognitive affective model for LMS user satisfaction in Indonesia’s higher education institution
This study investigates how cultural dimensions are integrated into a cognitive-affective model to explain user satisfaction with Learning Management System (LMS) interfaces in Indonesian higher education. Using PLS-SEM with data from 348 university students across Indonesia, the study examined the effects of cognitive factors, affective factors, and cultural dimensions on satisfaction. The results show that Classical Aesthetic significantly influences Efficiency (β = 0.755, t = 29.767, p < 0.05), Expressive Aesthetic (β = 0.752, t = 32.485, p < 0.05), and Satisfaction (β = 0.185, t = 2.559, p = 0.011). Efficiency positively affects Effectiveness (β = 0.744, t = 25.889, p < 0.05) and Satisfaction (β = 0.298, t = 4.667, p < 0.05), while Effectiveness also contributes to Satisfaction (β = 0.273, t = 4.684, p < 0.05). Expressive Aesthetic strongly predicts Playfulness (β = 0.804, t = 37.624, p < 0.05), but Playfulness does not meaningfully affect Satisfaction (β = 0.066, t = 1.364, p = 0.172). Power Distance has a significant positive effect on Satisfaction (β = 0.183, t = 3.306, p = 0.001), whereas Collectivism shows no substantial influence (β = –0.068, t = 1.694, p = 0.09). Overall, the findings suggest that LMS interfaces in Indonesia should prioritize efficient navigation, structured aesthetics, and clear hierarchical organization aligned with high power distance culture, providing practical insights for culturally responsive LMS design.
Eye-tracking study of generation z’s visual attention to traffic signs
The number of accidents in Indonesia reached 116 thousand cases in 2023, including in University areas. Most of the traffic victims are Generation Z. The impact of road accidents includes minor injuries, serious injuries, deaths, and material losses. In order to achieve the golden generation in 2045, Generation Z can achieve driving safety on the highway by ensuring a level of understanding of the meaning of traffic signs to drive safely. The purpose of this study is to investigate the visual search pattern of Generation Z on traffic sign design using an ergonomic approach. This study uses an experiment with three conditions, namely displaying warning signs, prohibitions. The results showed that the values of blink duration, dwell time, and total fixation duration did not have significantly different values for each sign condition, but the blink frequency values for the three sign conditions had significantly different values. As many as 91% of the gaze map direction moves from the top left to the center of the traffic sign. Counseling through interactive visual media will be more effective and appropriate for Generation Z. This results could help government and the National Police of Indonesia to minimize the risk of accidents.
Sustainable strategy development for organic waste management supply chain in Bekasi Regency
The rapid population growth and urbanization in Bekasi Regency have led to a significant increase in organic waste, creating a serious challenge in waste management. This study aims to identify and prioritize strategies to improve the performance of the organic waste management supply chain by applying Interpretive Structural Modeling (ISM) and Analytical Hierarchy Process (AHP). Data were collected from six experts in waste management, government institutions, and academia. ISM results revealed that the most fundamental elements driving system performance are land availability, infrastructure readiness, and institutional support. Meanwhile, AHP analysis indicated that the top strategic priority is provision of land and supporting infrastructure (48.6%), followed by technological enhancement (32.3%), and human resource capacity building (19.1%). The findings highlight that limited land availability is the most critical issue in Bekasi, while technology and human resources serve as supporting enablers. This study provides managerial insights for local governments and stakeholders in designing sustainable and context-specific strategies for organic waste management.
Enhancing product quality in precast concrete spun pile through the Six Sigma DMAIC
Defects in precast concrete spun pile production pose risks to structural reliability, operational efficiency, and project costs. The Company has experienced recurring defects that increase the cost of poor quality and reduce customer satisfaction, highlighting the need for a systematic improvement approach. This study applies the Six Sigma DMAIC methodology to analyze and reduce defects using production data from 25,206 units manufactured between 2020 and 2022. Statistical analysis using P-chart control limits, DPMO calculations, and sigma-level evaluation revealed an overall defect rate of 0.63%, dominated by Broken PC Bars, Cracks in the Stock Area, and Dry Concrete, which together contributed 62.5% of total defects. The initial process performance averaged 3.4 sigma (approximately 2,150 DPMO), which improved to 4.67 sigma following the proposed corrective actions. Root cause analysis identified human factors, unstable machine calibration, procedural inconsistencies, and material variability as the primary contributors. Improvement recommendations include operator training, biweekly machine maintenance, digital standardization of work procedures, and stricter material control. The findings demonstrate the effectiveness of a data-driven DMAIC approach for enhancing product quality in precast manufacturing. Future improvements may incorporate IoT-based monitoring and stronger supplier collaboration to support long-term process stability and operational excellence.
A system dynamics model for energy transition: Substituting fossil fuels with renewable energy
This study develops a system dynamics model to analyse the gradual transition from conventional to renewable energy in Indonesia. The model was built in Powersim Studio 10 and aims to capture the interplay among economic conditions, regulatory signals, and investor behaviour over time. The model represents two major components of the system: conventional energy demand and renewable energy development, connected by a substitution flow to illustrate the gradual transition. The model parameter remained hypothetical but was relevant to the literature on Indonesia's energy transition. The result indicates that the transition does not follow a linear path, but evolves through three phases: an initial acceleration, a stabilisation period, and a dynamic equilibrium phase. Sensitivity analysis shows that substitution elasticity alone does not directly determine the speed of transition. Instead, a transition dynamic emerged from the interaction between substitution elasticity and the relative willingness to invest between renewable and conventional energy technologies. The model indicates that a rapid transition occurs only when renewable energy is more economically attractive than fossil energy, whereas a high substitution elasticity is insufficient to accelerate the transition when conventional energy remains economically dominant. Rather than being used to obtain a precise forecast, the model provides a conceptual system-level framework for understanding how the energy system behaves with respect to interactions among different factors. The model’s structure can be used to identify which conditions matter among the combined effects of economics, regulation, and investment behavior in designing strategies for renewable energy transition.
The mediating role of motorcycle riding behavior in the relationship between risky riding intention and safety incidents among housewife motorcyclists in Jabodetabek
Motorcycles accounted for 73% of all accidents in 2024, with human mistake causing 95% of these crashes. While the experiences of female riders, particularly suburban housewife motorcyclists, who face severe multitasking demands and time constraints remain largely unexplored, little is known about how dangerous driving intentions convert into driving habits that could lead to safety problems. In order to assess how psychological variables are reflected in driving behavior and how this behavior affects safety incidents, this study utilizes the MRBQ (Motorcycle Rider Behavior Questionnaire) and PLS-SEM (Partial Least Squares Structural Equation Modeling). The findings indicate that all aspects of the MRBQ (speeding, traffic infractions, control errors, and stunts) are directly affected by risky riding intentions. It was discovered that only speed violations had a substantial indirect impact of risky riding intention on safety incidents. Speed violations is a mediator between risky riding intention and safety incidents, even though risk-taking driving intentions affect a variety of driving behaviors. Practical insights into the creation of speed management measures and psychologically grounded road safety interventions that aim to reduce safety-related events among female motorcyclists in Indonesia's urban areas are provided by the findings.
Current performance standard of circular product design: A systematic literature review
The rising number of green customers has encouraged industries to assess product consequences. As a result, there has been an alignment of product development focus with regards to circular economy concepts. Consequently, several methods and tools have been developed, and thus new performance standards were introduced for product development. Nevertheless, there still exist deficiencies in industry-wide acceptance and adoption within these standards. The objective of the study aims at examining and optimizing existing standards on Circular Product Design. A systematic literature review method will be adopted with three phases: identifying research on Circular Product Design using Preferred Reporting Items for Systematic Reviews and Meta-Analyses, developing approaches on designs, and examining standards on design performance. The result shows that there are seven prevailing approaches on designs for Circular Product Design. Moreover, this study contributes an a structured classification of CPD approaches and performance standards, thus dealing with the problem of fragmented knowledge and and serves as a basis for further frameworks and research on circular product performance.
Optimization of steam utilization in palm oil refinery processes using Kaizen and design of experiment
This research investigates the optimization of steam consumption in the refinery process of palm oil production. Excessive steam usage during the drying stage of Spent Bleaching Earth (SBE) has resulted in higher production costs and oil content levels that do not meet company targets. To address this issue, Kaizen's continuous improvement cycle and the Design of Experiment (DOE) method were applied. Data collection involved field observation, operator interviews, and documentation, which were analyzed using Pareto diagrams and checksheets. The improvement focused on adjusting the SBE drying time as a key parameter influencing both steam usage and oil content. Prior to improvement, the drying process required 850 seconds per cycle, consuming 6,824 kg of steam per day, while producing an average oil content of 18.91%. After implementing DOE-based adjustments, the drying time was reduced to 700 seconds, decreasing steam consumption to 5,600 kg per day, a reduction of 1,224 kg/day (17.9%), and achieving an oil content of 21.03% within the company's target range of 20–22%. The study demonstrates that combining Kaizen and DOE provides an effective strategy for reducing energy usage while maintaining product quality.
Design of a liquid organic fertilizer composter device utilizing pineapple waste based on voice of customer and technical responses
Pineapple peel waste in Kutai Kartanegara Regency poses a significant environmental burden with a food waste accounting for 73.92%. One method which can be employed to reduce this pineapple peel waste is by producing liquid organic fertilizer (LOF). This research aims to design a LOF composter device utilising pineapple peel waste which tailored to the needs and preferences of local farmers. Quality function deployment (QFD) was used by collecting voice of customer (VOC) and translating it into technical response (TR) as the basis of the design. The resulting LOF composter device’s design, incorporate mobility features using wheels and brake plates, equipped with fermentation temperature monitoring via a digital monitor or sensor, and a transparent container for visual monitoring. Stainless steel was selected for its corrosion resistance. Furthermore, the device is designed to be equipped with semi-automatic or automatic shredder blade for optimal texture and a mixer blade designed for even distribution throughout the container. This device is expected to provide an effective solution for managing pineapple peel waste while producing high-quality LOF.