Analyzing operational risks of a recyclable waste-based payment public transit system in Surabaya, Indonesia

Suroboyo Bus, a municipal public transportation initiative managed by the Surabaya Department of Transportation (SubDOT) in Indonesia, was launched to promote the use of public transit by accepting recyclable plastic waste as transit fare payments. However, this transportation system presented challenges, as prior to 2019, Suroboyo Bus performed its operational activities without adequately incorporating operational risk, specifically considering Health, Safety, and Environment (HSE) factors. The analysis of risk profiles and a mitigation plan concerning the well-being of both their staff and passengers was uncomprehensive. To address these issues, this paper evaluates the operational risk based on ISO 31000:2018, the Failure Mode and Effect Analysis (FMEA), and the Benefit Cost-Analysis (BCA). The analysis identified 114 risks and 189 combinations of risks and impacts across 70 business processes associated with Suroboyo Bus operations, with varying degrees of risk severity. Risk prioritization analysis was performed using the Pareto 80:20 principle. Proposed risk response strategies include avoidance, mitigation, transfer, and tolerance. Evaluation of the feasibility of these strategies through benefits and cost analysis, supplemented by a sensitivity analysis, revealed Benefit-Cost Ratio (BCR) values ranging from 1.041 to 1.471, indicating that the proposed mitigation plan is feasible for all evaluated scenarios. These findings underscore the importance of implementing risk mitigation measures to improve the sustainability and effectiveness of the Suroboyo Bus service. Future research should explore the digital application developed for Suroboyo Bus passengers as part of the business process named “Golek Bis” (GOBIS) and other methods that can be used to enhance the quality and comprehensiveness of risk management

Layout improvement design to reduce material handling cost by using the systematic layout planning method in the MSME industry

This research discusses layout improvements in MSMEs that produce skin crackers distributed in the Jabotabek area. Currently, the quantity of skin crackers produced is experiencing problems. One of the causes of problems is that material handling is still manual, poor layout settings, limited costs, unpredictable weather and lack of labor availability. Poor material handling causes long production duration, workers are less safe and comfortable, and material handling costs are high. Therefore, this research improved the layout by improving the material handling process. The research aims to analyze the existing layout problems, improve the layout, and compare the existing layout with the proposed layout. The method used to improve the layout is systematic layout planning (SLP). The results of the study are that material handling costs reduced by IDR 256,754.99 or 67.8%, increasing capacity by 17.77 kg per week can solve stock shortages, and the duration of material handling is reduced by 28.95 minutes per day or 69.19%

Innovative canting: A triz approach to improve traditional batik production process in small and medium enterprise

This research aims to improve the efficiency of the canting tool used in the Batik-making process in Giriloyo Village. One of the main issues identified is the suboptimal size of the canting spout, which causes wax blockages due to dirt particles. This study employs TRIZ tools, including Function Analysis, to identify problems, develop innovative solutions to the issues, and develop solutions that address contradictions in the canting system. The analysis results indicate that several inventive principles, such as Merging, Beforehand Cushioning, Segmentation, and Feedback, can enhance the canting tool\u27s performance. Proposed solutions include adding a heater, filter, flow regulator, and interchangeable canting spouts to meet different needs. These solutions can accelerate the Batik-making process, reduce production costs, and enhance market competitiveness. However, further verification is required to validate the proposed design\u27s superiority over traditional canting tools. This research opens opportunities for further development in Batik tool innovations to enhance the sustainability of the Batik creative industry in Indonesia

Harnessing Lean and FMEA techniques to eliminate waste and enhance performance in poultry processing

This study integrates lean manufacturing and failure mode and effects analysis (FMEA) to identify and mitigate production waste and risk in a poultry processing facility. The study identifies dominant waste types, waiting, motion, and over-processing by applying value stream mapping (VSM), fishbone diagram, and FMEA. The highest risk priority number (RPN) of 210 was found in the chilling process, indicating a critical need for corrective action. Implementing proposed improvements such as layout redesign and chiller capacity expansion resulted in measurable gains: a 5.8% reduction in labor costs, a 2.3% drop in operational expenses, and a 1.2% decrease in raw material waste. Compared to prior studies that applied Lean or FMEA separately, this research offers a structured Lean–FMEA framework tailored for the poultry industry. This model enhances efficiency while ensuring food safety and serves as a replicable method for similar industries

A comparison allocation of labor qualification on real, plan, and regulation calculation using resource-leveling method

Labor is a crucial resource in industrial construction projects. A common issue is the uneven number of laborers who are overallocated. This study uses the resource-leveling method to compare and determine the optimal number of labor and project duration based on plan, real, and regulation conditions. In this study, the data required in real conditions is obtained from daily report data. In planned conditions, data is obtained from the scheduled manpower made by the contractor, while in conditions based on regulations, the calculation of the number of laborers uses the coefficient values listed in the Regulation of the Minister of Public Works and Public Housing No. 1 of 2022. This research is measured through disparity values, which show an imbalance in the allocation of labor caused by the uneven allocation of labor based on its workload. The results showed a significant difference in the number and distribution of labor. Regulation conditions resulted in higher labor numbers due to detailed calculations on each type of work and labor qualifications. The highest disparity occurs in workers, with a value of 0.93 in the plan condition and -0.51 in the regulation condition. The resource leveling helped balance labor allocation but increased project duration from 98 to 112 working days. These findings provide practical insights for project managers to optimize worker planning and distribution, improve efficiency, and reduce overallocated risks

Optimizing business location for small and medium enterprises considering travel time uncertainty, natural disasters, and density population: a study case in Jakarta

This study addresses the critical problem of identifying optimal business locations for small and medium enterprises (SMEs), a decision-making process by factors such as travel time uncertainty, natural disasters, and population density. Existing research in this area has not adequately addressed these complexities, leaving a knowledge gap that this study aims to fill. Our research employs two optimization methods, differential evolu­tion (DE) and mixed integer programming (MIP), to maximize customer coverage. We present a comprehensive model that not only determines optimum and near-optimum business locations but also investigates the scalability of the algorithms with increasing facilities and their adaptability to different traffic scenarios. Key findings indicate that the DE algorithm, in particular, demonstrates superior coverage performance. This study contributes to the field by providing a robust and adaptable model for facility location problem-solving. The insights gained have practical applications for both academia and industry, aiding SMEs in making informed, strategic decisions about business location placement

Analysis of production area layout design based on lean and green thinking in the micro, small and medium enterprises (MSME) industry

This research aims to analyze and design the layout of production areas based on Lean-Green (L&G) Thinking in Micro, Small and Medium Enterprises (MSMEs) Scale Companies. By focusing on operational efficiency and sustainable production processes, this research can help MSMEs increase their competitiveness in an increasingly competitive market. To support this goal, researchers used the Systematic Layout Planning (SLP) method combined with the Promodel 6.0 simulation tool. The SLP method helps in evaluating the current MSME layout system and identifying areas that can be made more efficient by considering the criteria of distance, time and electrical energy consumption. Meanwhile, simulation techniques are used to help formulate appropriate lean-green strategies to increase process efficiency and minimize environmental impacts. Evaluation of the company\u27s current layout resulted in an increase in operational efficiency of 1.55%, a reduction in inventory of 83%, and a reduction in electricity consumption of 26%. This research recommendation includes concrete steps to improve the layout of production areas that support MSMEs to become agents of change that combine operational efficiency with environmental responsibility

A compromise-based MADM approach for prioritizing failures: Integrating the RADAR method within the FMEA framework

Multi-Attribute Decision-Making (MADM) methods are essential in decision-making processes, particularly in solving problems related to ranking and classifying alternatives. Among the MADM methods frequently utilized in the literature for ranking alternatives are distance-based or compromise-based methods. These methods have been widely applied for decades, with ongoing development leading to new approaches. One such approach is RAnking, based on the Distances And Range (RADAR) method. This novel distance-based method evaluates alternatives by considering their distance relative to the best and worst alternative values for a given criterion and the range between them. This paper applies the RADAR method to rank failure modes identified through a standard Failure Modes and Effects Analysis (FMEA) in an automotive industry company that produces rubber and plastic products. The results obtained from the RADAR method are compared with those derived from the traditional Risk Priority Number (RPN) approach. The comparison demonstrates that the RADAR method provides more distinct rankings, reducing the occurrence of ties between alternatives and thus offering a more nuanced and reliable decision-making tool in the context of failure mode prioritization

Intelligent optimisation for multi-objectives flexible manufacturing cells formation

The primary objective of conventional manufacturing cell formation typically uses grouping efficiency and efficacy measurement to reduce voids and exceptional parts. This objective frequently leads to extreme solutions, such as the persistently significant workload disparity among the manu­facturing cells. It will have a detrimental psychological impact on operators who work in each formed manufacturing cell. The complexity of the problem increases when there is a requirement to finish all parts before the midday break, at which point the formed manufacturing cells can proceed with the following production batch after the break. This research examines the formation of manufacturing cells using two widely recognized intelligent optimization techniques: genetic algorithm (G.A.) and particle swarm optimisation (PSO). The discussed manufacturing system has flexible machines, allowing each part to have multiple production routing options. The optimisation process involved addressing four simultaneous objectives: enhancing the efficiency and efficacy of the manufacturing cells, minimizing the deviation of manufacturing cells working time with the allocated working hours, which is prior to the midday break, and ensuring a balanced workload for the formed manufacturing cells. The optimisation results demonstrate that the G.A. outperforms the PSO method and is capable of providing manufacturing cell formation solutions with an efficiency level of 0.86, efficacy level as high as 0.64, achieving a minimum lateness of only 24 minutes from the completion target before midday break and a maximum difference in workload as low as 49 minutes

Performance evaluation using data envelopment analysis - stepwise modeling approach: A case study of construction industries in Indonesia

The construction industries are inextricably linked to employment, investment, the quantity of infrastructure building projects, and other economic sectors in Indonesia. They serve as catalysts for the expansion of goods and service production. Apart from having a strategic role in the national economic, construction companies also experience various obstacles to developing their businesses. These obstacles include weakening the IDR exchange rate against the US dollar, regulatory and legal frameworks, labor and skills shortages, economic and financial instability, and environmental and sustainability concerns. In order for the construction industry to survive, develop, and remain competitive in the face of international competition, it is crucial to evaluate its performance constantly. This research aims to evaluate the construction industry\u27s performance in Indonesia. There are 151,183 construction companies included in this study. Hence, these companies will continue to survive, grow, and compete in the face of global competition. The methods applied in this research are an input-oriented DEA envelopment model and a stepwise modeling approach. The research results indicated that 3% of the Indonesian construction industry is made up of efficient DMUs, and the remaining 97% are inefficient DMUs. DMUs are classified according to the distribution of efficiency scores. It is considered that for the classification of inefficient DMU, there exist four ranges, Rs: R1 (ES = 0.16-0.99), R2 (ES = 0.050-0.15), R3 (ES = 0.015-0.049), and R4 (ES = 0.000-0.014). The criteria for each classification, in terms of the level of effectiveness, are as follows: i) R0 Range (ES = 1]): Effective; ii) R1 Range (ES = 0.16-0.99): Relatively Low Ineffectiveness; iii) R2 Range (ES = 0.050-0.15): Moderate Ineffectiveness; iv) R3 Range (ES = 0.015-0.049): Significant Ineffectiveness; and v) R4 Range (ES = 0.000-0.014): Very High Ineffectiveness. The percentage of each classification is as follows: inefficient DMU-R1 0%, inefficient DMU-R2 30%, inefficient DMU-R3 37%, inefficient DMU-R4 30%.