PROZIMA (Productivity, Optimization and Manufacturing System Engineering)

Clustering-Allocation Model Under Risk, and Emissions Factors: Evidence from an Indonesian Region

Pipit Sari Puspitorini — 2024-12-31

This study contributes to risk-based location-allocation problems by constraining time and emergency medical services (EMS) carbon emissions. During the COVID-19 pandemic, this study develops a location set covering the problem of implementing ambulance allocation to optimize opening new facilities and the cluster with the highest emission value in heritage cities. This study also presents an integer linear program considering risk, time, and carbon emissions at three facilities with demand locations. The model was also validated using two cluster methods, K-means clustering and Agglomerative Hierarchical Clustering, with Python software and Google Collaboratory machine learning (GCC). The findings revealed the opening of three facilities and clusters with potential points, with the highest emission values at M₃ (0.575% (kg). M_2. potential point, with a value of 5832 represents the highest risk. Furthermore, the validation results indicate that the distance significantly total energy consumption (BTU) and carbon emissions (kg). This study ignores the vehicle category. It can be used as a reference by decision-makers by considering these parameters and making a clear contract with a third party in ambulance procurement for humanitarian logistics. The model will help provide insight into another region's relevant emergency medical center. Furthermore, research can anticipate strategies to deal with pandemic outbreaks.

Design and Build of Broom Handle Cutter and Shaper to Improve Production Efficiency and Working Time

Davin Herdiansyah Putra — 2024-12-31

This study designs a cutting and shaping tool for broom handles to improve production efficiency and reduce operator workload at Victory 2 Singa. The main issues include slow manual production processes, high costs due to the use of nails, and non-ergonomic tool designs. The proposed solution involves designing a new tool using Quality Function Deployment (QFD). Through QFD, customer requirements such as comfort, safety, durability, affordability, and ease of use are analyzed and translated into technical attributes for the tool. The results of the research show that the designed tool can meet the primary priorities, namely providing precise cutting results, ergonomic handle shapes, and an efficient working process.

Lean Six Sigma Project Selection to Improve College Business Processes

Ig. Jaka Mulyana — 2024-12-31

Higher education institutions are required to continuously improve the quality of their services to ensure institutional sustainability. Lean Six Sigma (LSS) offers a framework that integrates efficiency and quality improvement. This study aims to determine the priorities of LSS projects in higher education, considering the limited resources and the risk of project failure. The Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods were used to determine priorities. The results showed that improving human resources (HR) and financial information systems is a strategic step. An integrated HR system supports the effective management of lecturers and education personnel, while an accountable financial system increases the transparency and efficiency of financial management. Both systems contribute to improving the quality of services to students. This research provides a basis for developing a digital transformation roadmap for higher education institutions.

Proposed Crane Machine Maintenance Schedule with Reliability Centered Maintenance Method

Dimas Maulana Agta Pratama — 2024-12-31

PT XYZ is a steel smelting company located in Sidoarjo. The company is assisted in the production process by a total of 15 cranes to lift loads that cannot be lifted by bare human hands. Currently the crane machine has the highest downtime of 157 hours compared to other machines. The components that are often damaged are the hover control, braking system, and trolley cable. The purpose of this research is to find out what causes high downtime, know the maintenance schedule, and can improve the reliability of critical components. This research will discuss the maintenance scheduling of crane machine No. 5 using the Reliabilty Centered Maintenance method. The results showed that the cause of high downtime is 3 critical components, namely hover control, braking system, and trolley cable. The proposed maintenance schedule for the 3 critical components has a maintenance time interval of hover control every 250 hours, braking system every 397 hours, trolley cable every 1460 hours, and the machine reliability obtained is 60%. The costs incurred for preventive maintenance amounted to Rp. 382,104,000, this figure increased by Rp. 185,840,000 from the cost of corrective maintenance which initially amounted to Rp. 196,264,000.

Bibliometric Analysis and Data Visualization: Business Intelligence in Digitalization of Supply Chain Management in Healthcare Sector

Fadhil Adita Ramadhan — 2024-12-31

Digital transformation in healthcare supply chain management is increasingly important in addressing operational and distribution efficiency barriers. However, many healthcare institutions have yet to adopt Business Intelligence (BI), causing delays in decision-making, inefficiencies in drug stock management, and waste of resources due to suboptimal distribution. The method used is a bibliometric analysis based on literature observations from major academic databases, with a quantitative approach using VOSviewer to map topic relationships, research trends, and collaboration patterns between researchers. The results of the study confirm that the application of Business Intelligence (BI) in healthcare supply chain management is more dedicated to existing technology-based solutions, such as Artificial Intelligence (AI), Internet of Things (IoT), blockchain, and Big Data, compared to new development methodologies. This study found that although BI can increase efficiency in inventory management by up to 50%, accelerate data-based decision-making by up to 40%, and reduce resource waste by 25%, there are still similarities in policy aspects and obstacles that hinder optimal implementation. In conclusion, the application of BI in the healthcare supply chain must be supported by a structured strategy, including investment in digital infrastructure and workforce training. Further research is recommended to explore policies that can accelerate the implementation of BI in the health sector.