Article in Press
1. Improving Incubator Manufacturing Performance Through RPW-Based Line Balancing and Constraint Management
Fredy Sumasto, Febriza Imansuri, Indra Rizki Pratama, Abdul Wahid Arohman, Sanurya Putri Purbaningrum
In the regulated field of medical device manufacturing, optimizing production efficiency without compromising compliance is critical particularly for small and medium-sized enterprises (SMEs) operating in resource-constrained environments. This study addresses production inefficiencies in the assembly of the TSN 89 TR neonatal incubator at PT Tesena Inovindo, an Indonesian manufacturer, by implementing an integrated improvement framework. The approach combines Lean Manufacturing for process stabilization, the Ranked Positional Weight (RPW) method for line balancing, and the Theory of Constraints (TOC) for bottleneck resolution. Time study data were collected across 30 cycles per task to ensure reliable estimates of average cycle times, based on the Central Limit Theorem. The initial production system exhibited unbalanced workloads, high idle time, and frequent work-in-process (WIP) accumulation. After reconfiguration, the number of workstations was reduced from ten to eight, cycle time decreased by 23.8%, and daily output increased from four to six units. Line efficiency improved from 67.2% to 89.5%, with idle time dropping from 32.8% to 10.5%. These gains were achieved without automation or additional labor, relying solely on empirical task analysis and workflow redesign. The study offers a replicable, low-cost framework for optimizing semi-manual assembly lines in regulatory environments. It demonstrates that substantial performance improvements can be achieved through structured, data-driven interventions, making it particularly valuable for SMEs in emerging markets seeking ISO 13485 compliance and operational excellence
[Accepted Date: 2026-03-03]
2. Integrating SWOT and Business Model Canvas for MSMEs Development
Bayu Wahyudi, Nidya Wisudawati, Adellia Gustianda
MSMEs Pempek Koyek is a business engaged in the production of traditional Palembang food facing several challenges, including a decline in sales due to the COVID-19 pandemic, limited promotional activities, lack of an online store, and a less strategic location. This study aims to identify and analyze the internal and external factors affecting the business and formulate effective strategies for growth. A mixed-methods approach was adopted, using SWOT analysis and the Business Model Canvas (BMC) framework. Data collection included observations, interviews with owners, customers, and stakeholders, and surveys distributed to 122 respondents identified using Slovin's formula. The SWOT analysis revealed that the company is positioned in Quadrant I, suggesting the adoption of an aggressive Strength-Opportunity (S-O) strategy. Key strategies include using social media and e-marketplaces to promote high-quality products, forming strategic partnerships with the hospitality industry, diversifying product offerings, enhancing social media engagement, and optimizing customer service with faster delivery. The BMC approach focused on improving key activities such as raw material sourcing, product innovation, and digital marketing. The results of this study provide valuable insights into the strategic development of MSMEs, particularly in the food sector, by combining internal strengths with external opportunities. The findings contribute to the growing body of knowledge on MSME development and offer practical strategies for business sustainability in a competitive market environment.
[Accepted Date: 2026-03-05]
3. Printing Parameter Optimization of Flexible Strain Sensor for Maximum Strain Level Analysis
Faiq Ramadhani, Wangi P. Sari
This study explores the optimization of printing parameters for Flexible Strain Sensors (FSS) produced using fused deposition modeling. The experimental design employs a Taguchi L18 orthogonal array to evaluate the effects of five parameters—substrate material, sensor thickness, printing temperature, printing speed, and layer height—on the maximum tensile strain (elongation at break) of the printed sensors. The findings indicate that thermoplastic polyurethane (TPU) significantly enhances strain capability compared to polylactic acid (PLA). The optimal parameter combination includes a sensor thickness of 0.3 mm, a printing temperature of 210 °C, and a printing speed of 40 mm/s, while variations in layer height show minimal influence. Validation testing confirmed the optimization results, achieving a maximum tensile strain of 26.3% with strong agreement between predicted and experimental responses.
[Accepted Date: 2026-05-04]
4. Development of Tourist Area Using SWOT Method in Buntu Kandora Tana Toraja District
Andi Pawennari, Arfandi Ahmad, Muhammad Dahlan, Ihwan Safutra
Buntu Kandora is one of the tourist areas listed in the South Sulawesi Provincial Tourism Development Master Plan (2015–2030) and the Tana Toraja Regency Spatial Plan (2011–2031). This area has great potential to be developed into a leading tourist destination because of its natural beauty, cultural richness, and man-made attractions. This study aims to identify the potential, characteristics, and obstacles to the development of the Buntu Kandora tourism area, as well as to formulate appropriate development strategies. The method used is qualitative through direct observation and distribution of questionnaires to stakeholders, with data analysis using the SWOT method. The results of the study indicate that the most appropriate strategy is the S-O (Strengths–Opportunities) strategy, which is utilizing internal strengths to capture external opportunities. The proposed strategies include developing tourist attractions, improving accessibility and infrastructure, and involving local communities in tourism development.
[Accepted Date: 2026-05-07]
5. Combined Application of CRITIC and Back Propagation Neural Network Prediction Method for Vehicle Emission Parametric Evaluation in Logistic Networks and Distribution System
Sunday Ayoola Oke, Alexander Iwodi Agada, Bayo Yemisi Ogunmola, Henry Ogbemudia Omoregbee, Modupe Adeoye Onitiri, Nehemiah Sabinus Alozie, John Rajan, Swaminathan Jose, Pandiaraj Benrajesh
Logistic network and distribution services in the packing industry generate vast amounts of vehicle emissions, which are difficult to control due to the lack of scientific guidance. This paper predicts the emission from vehicles engaged in logistic networks. The CRITIC (Criteria Importance Through Inter-criteria Correlation) method is integrated with the backpropagation neural network (BPNN) to analyze the input parameters of the emissions process from vehicles plying roads in the packing industry. The packing industry transports goods in packages and delivers them to customers in a road network. The application of the integrated CRITIC-BPNN method is demonstrated by using the dataset of a packing industry in India, obtained from the literature. The results revealed how the packing industry can translate its environmental control strategy into a parametric framework, yielding diverse outputs to assist in selecting optimal decisions. The proposed method exhibits unique characteristics. (1) It emerges as the first decision-making tool for objective criteria-based vehicle emission process control and could serve as a tool for logistics planning. (2) It employs integrated ideas of multi-criteria analysis and neural networks. (3) Objective and optimal emission analysis decisions are advanced through an analysis of multi-criteria tools. By employing the CRITIC method, the conflicting objectives of the emission process are successfully tackled and synchronized objectively to arrive at robust weights used in the back propagation neural network method for the final prediction. Moreover, the neural network method uses intelligence to gather data and translate it usable forms to predict vehicle emissions.
[Accepted Date: 2026-05-07]
6. Applying System Dynamics to Evaluate Lean Manufacturing Interventions in a Traditional Bakery: A Case-Based Conceptual Approach
Fredy Sumasto, Najla Aulia, Arif Setiadi, Fahriza Putra Zaman, Muhammad Raihan Adil, Febriza Imansuri, Indra Rizki Pratama, Dianasanti Salati, B. Handoko Purwojatmiko
Small and medium-sized enterprises (SMEs) in the traditional food sector often face operational inefficiencies caused by disorganized workspaces, inefficient layouts, and limited adoption of structured improvement practices. These challenges are particularly evident in small bakeries where manual production processes and spatial constraints disrupt workflow continuity. This study aims to analyze the relationships between operational inefficiencies and Lean Manufacturing interventions using a System Dynamics approach. A qualitative case study was conducted at Toko Roti Gelora, a traditional bakery in Jakarta, Indonesia. Data were collected through direct observation, informal interviews, and document analysis over a ten-week field study. Lean diagnostic tools, including Value Stream Mapping and Fishbone Diagram analysis, were employed to identify sources of operational waste. The findings were synthesized into a Causal Loop Diagram (CLD) to represent feedback structures influencing production efficiency. The results identify four key feedback loops shaping the bakery’s operations: two reinforcing loops representing the escalation of inefficiencies and the development of Lean culture, and two balancing loops representing system stabilization through 5S implementation and layout improvements. These interactions suggest how Lean interventions may contribute to reducing search time, motion waste, waiting time, and excess inventory while supporting the development of workplace discipline over time. The study contributes by integrating Lean Manufacturing and System Dynamics to propose a systemic framework for analyzing operational efficiency in SME production systems.
[Accepted Date: 2026-05-08]
