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Spektrum Industri
Published by Universitas Ahmad Dahlan
ISSN : 16936590     EISSN : 24422630     DOI : https://doi.org/10.12928/si.vxix.xxx
Core Subject : Science, Social, Engineering,
Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Spektrum Industri ISSN 1693-6590(print); ISSN 2442-2630(online) is a Journal that publish scientific articles in the science scope related to engineering and/or industrial management both research and theoretical. Literature review will be considered if it is written by an expert.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 73 Documents
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Design and Integration of a Robotic Welding Parameterized Procedure for Industrial Applications Puthussery, Sangeeth; Secco, Emanuele Lindo
Spektrum Industri Vol. 22 No. 1 (2024): Spektrum Industri - April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i1.179

Abstract

This paper explores the development of an effective motion planning strategy for robotics welding in tube to tubesheet joints, a critical process in heat exchanger manufacturing. The research methodology follows an experimental paradigm, investigating two distinct approaches to tackle the intricacies of this task. The initial approach, involving a welding torch affixed to the robotic arm's flange, proved ineffective due to the complexity of continuous 360° orbital welding. This led to the adoption of a custom end effector in the second approach, designed to enhance adaptability and precision. Key tools and materials employed in this research include the Robot Operating System (ROS), Rviz for 3D visualization, MoveIt for motion planning, SolidWorks for CAD modelling, and the xArm7 Robotic Arm. These tools facilitated the creation of a comprehensive planning environment. The motion planning process relies on three essential parameters: tube diameter, type of tube to tubesheet joint (flush or protruding), and the 3D coordinates of tube centers. A Python scripts control the robot's movements, with specific joint state and pose goals for precise positioning. Finally, this study contributes to present a program that orchestrates the robotic arm's motion, simulating the welding process for tube to tubesheet joints. This comprehensive research endeavor contributes to the optimization of motion planning strategies in the context of tube to tubesheet welding, with practical applications in the manufacturing industry.
Cost Optimization for Logistics Services: A Simulation Approach to Delivery Alternatives Sihotang, Farida
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.195

Abstract

An essential activity in the delivery of goods by logistics service companies is how to deliver goods to consumers according to the agreed time with minimal costs. A case study was conducted on one of the logistics service companies in Bandung, which has an exciting feature: promising goods to consumers within 24 hours. The interesting thing about this company is that it uses the rest of the luggage of travelers traveling to the destination city by plane. In existing conditions, problems often arise, namely, goods do not reach customers according to the agreed time. This causes losses to the company because it must pay a late penalty. Therefore, the author designed several alternatives to meet freight forwarding in less than 24 hours. This study aims to optimize the cost of shipping goods from various alternatives by considering the delivery time of less than 24 hours. This study uses an experimental method with a system model to conduct simulations. Parameters use primary data from the company and secondary data from websites. The author designed two alternatives to shipping goods if no match was found with the traveler. The first alternative is to use air cargo at Bandung Airport. The second alternative is that if it is predicted that the goods will not reach the customer within 24 hours through Bandung Airport, they will be sent to Soekarno Hatta Airport Jakarta using a truck. A match with the traveler at the airport will be sought. The second alternative is also considered if there is no match with the traveler, then the delivery of goods uses air cargo. The simulation results provide a total cost for alternatives 1 and 2 of IDR 69,779,084.40/month and IDR 107,025,296, respectively, for goods that do not meet the delivery of less than 24 hours for alternative 1, namely nine items/month or 1% of the total shipment and alternative 2, namely 19 goods or 2% of the total delivery. The simulation in this study resulted in choosing the first alternative as the best alternative with the lowest cost.
Enhancing Pharma Manufacturing Efficiency: Integrating Lean Six Sigma and Fuzzy FMEA for Waste Reduction Kusumawardani, Rindi; Widyatmoko, Adiyodha Ayudha
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.199

Abstract

In pharmaceutical manufacturing, inefficiencies such as waiting times, excessive material usage, and packaging defects can significantly impact productivity and quality. This study adopts a Lean Six Sigma approach, integrating lean manufacturing and six sigma methodologies, to systematically address these challenges. Through Process Activity Mapping (PAM), it was determined that value-added (VA) activities account for approximately 63% of total production activities, while non-value-added (NVA) and essential non-value-added (ENVA) activities contribute about 34% and 4%, respectively. Critical waste was identified using the genba shikumi method, followed by Failure Modes and Effects Analysis (FMEA) to determine Risk Priority Numbers (RPNs). Fuzzy logic was applied to prioritize the suggested improvements for more accurate risk assessments. Key recommendations based on Fuzzy RPN rank include, enhancing bulk product quality before printing, implementing rigorous inspections of the printing process, optimizing machine utilization, and adjusting production schedules using the Shortest Processing Time (SPT) method.
Successful phytoremediation of simulated steel rolling industry heavy metals-contaminated soils using a Sorghum bicolor cultivar from Riko, Katsina, Nigeria Yunusa, Yahaya Riko; Umar, Zubairu Darma; Kabir, Kamaluddeen
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.202

Abstract

The release of hazardous heavy metals (HMs) from industries and other sources threatens ecosystems in Katsina, Nigeria and beyond. Bioengineering through microbially-assisted phytoremediation (MAP) is the best innovative alternative to these industries for remediating HMs contaminated environments. Sorghum bicolor (L. Moench) had been reported to be efficient in heavy metals phytoremediation. This study evaluated the ability of a fast-growing local cultivar of S. bicolor (rirrik’a/rirritsa/mota in Hausa) from Riko village, Jibiya L.G.A., Katsina State, Nigeria to remediate mesocosms simulating mixed HMs contamination obtainable at the soils of the defunct DANA Steel Rolling Mills, Katsina industrial site, to residual concentrations matching USEPA/EU limits. A chronosequential, nutrient-poor phytoremediation approach was employed to study the restoration of the contaminated soils in greenhouse experiments. The bioremoval of HMs in individual (0.05-10 g/L Cr, 0.04-1 g/L Cu, 0.08-1 g/L Pb and 0.02-1 g/L Zn) and mixed mesocosms was studied over 8 weeks, in multiple replicates, with positive and negative controls. ANOVA, Mann-Whitney and Kruskal-Wallis (with Dunn’s post-hoc) tests were used to statistically analyse the obtained data. The results confirmed an overall bioremoval of 66.67% of the HMs. Bioremoval rates were statistically similar across all HMs (one-way ANOVA: p = 0.64); with 69.48% of Zn, 67.46% of Cu, 63.34% of Cr and 58.33% of Pb bioremoved. The final residual HMs were within limits set by EPA/EU (Mann Whitney U test: p = 0.23). Study verified the status of the local cultivar of S. bicolor as a suitable agent for safe, effective phytoremediation of industrial heavy metal contaminated sites. Thus, its use is recommended for on-the-field phytoremediation of hotspots of HM contamination within the study area and beyond. The study also contributes towards sustainable and eco-friendly practices by using phytoremediation to manage environmental wastes from industrial pollution.
Fuzzy-FMECA: Right Solution for Jet Dyeing Machine Damage Prevention Ihsan, Tiaradia; Rochman, Didit Damur; Ferdian, Rendiyatna
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.204

Abstract

Jet dyeing machines, essential for producing high-quality and environmentally friendly textiles, face persistent issues with defects that lead to production stoppages, compromised cloth quality, and significant financial losses for companies. These challenges hinder operational efficiency and undermine the competitive edge of textile manufacturers in a rapidly evolving market. Jet Dyeing machines continue to innovate to produce high quality and environmentally friendly textiles, with the discovery of defects causing cloth production to stop, cloth quality to decline, and company losses. The Fuzzy-FMECA approach enhances accuracy and adaptability in identifying failure risks, improving maintenance for complex jet dyeing systems. This study aims to identify the root causes of jet dyeing machine damage for preventive maintenance design. Studies using robust fuzzy-FMECA can identify critical components of jet dyeing machines with a high degree of accuracy. This can improve machine reliability and reduce fabric quality failures. The dominant machine failures identified in jet dyeing components are leakage, short circuits, and installation errors. The Pareto analysis shows that leaks, tears, and short circuits are responsible for over 70% of total failures. The most critical components include the main pump and electric socket, both with an RPN score of 7.42, representing a significant 30% of overall risk. Other high-risk components such as the steam pipe packing and heat exchanger steam pipe also have an RPN of 7.25. These findings indicate that over 60% of the failures arise from just a few key components. These findings have succeeded in identifying the critical components of the jet dyeing machine (main pump and socket) which have the highest potential risk of failure. The proposed preventive maintenance design can reduce these risks, but needs to be refined with consistent, competent and monitored inspections. The preventive maintenance design significantly mitigates risks, requiring ongoing refinement through regular, skilled, and supervised inspections to ensure optimal effectiveness.
Systematic Risk Analysis of Railway Component Quality: Integration of Failure Mode & Effect Analysis (FMEA) and Fault Tree Analysis (FTA) Andy Prastyabudi, Wahyu; Faharga, Rafidsyah Aldin; Chandra, Huki
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.223

Abstract

Quality assurance is a critical aspect in the production systems, affecting product quality and safety. Defects and failures of manufactured components will diminish overall product quality, which could vulnerably risk consumer safety. This study focuses on quality assurance analysis of train component manufacturing systems. According to the quality control data, the number of defects recorded was about 10-12, on average, for each wagon produced. The defect mainly occurred while making the underframes, car body, and even the small components. This led to the tardiness of product delivery for 1-2 months. This study aims to analyze non-conformance report data and identify the potential failure modes, potential effects, and root causes. To do so, we integrated systematically FMEA (Failure Mode and Effect Analysis) and FTA (Fault Tree Analysis). First, RPN (Risk Priority Number) score was calculated to determine risk priority. Second, Pareto analysis was performed to select defects that most contributing to overall failures, which were then analyzed using FTA to obtain root causes. The results show that 8 defects exceed the critical RPN score of 209. Materials and personnel are identified as two major contributor failure events from three selected defects. The recommendation for further improvements is provided based on various defect categories to prevent similar defects. The findings demonstrate that the combined use of FMEA and FTA is effective in identifying failures and root causes within complex and long production cycle systems.
Efficiency Evaluation in Indonesia's Quarrying Industry Using Variable Combinations DEA Puspanantasari Putri, Erni; Parinov, Ivan A.; Wongloucha, Chuleeporn
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.227

Abstract

Data Envelopment Analysis (DEA) is a method considered to evaluate a company's performance. DEA applies multiplies the input and output variables for analyzing the efficiency but does not provide guidance in selecting those variables. As a rule, researchers use several methods. If the number of variables used is too many, it will affect the efficiency value. This will reduce the strength of the efficiency value, which can cause all DMU values to be efficient.   DEA and variable selection are important in performance evaluation because DEA aids in determining relative efficiency, whereas variable selection guarantees that the evaluation is based on the most relevant and significant aspects. The purpose of this study is to suggest the variable combination method for subtracting the number of variables that will be utilized in implementing the DEA. The method used in this study is the Average Input Variable Combinations (VCs)-Variable Returns-to-Scale (VRS) DEA.  The data were classified, defined, and processed with a view to computing efficiency scores and DMU classifications. The research result indicated that the proposed method (VCs-DEA) treats the variable reduction factor and the average calculation factor to obtain the final result of the efficiency score.  These two factors contribute to the accuracy of the efficiency value. Some real-world implications of these findings, such as making better use of resources, streamlining operations, and coming up with new plans, Furthermore, the evidence may be used to benchmark performance as well as help decision-makers in creating more effective policy. This study finds that only 1 out of 12 DMUs is efficient (8%), while the remaining 11 are inefficient (92%). Indonesia quarrying establishment can be classified into 3 categories such as Optimal Category (S-Sand); Middle Category (LS-Lime-Stone; F-Feldspars; Gr-Granite; SA-Stone and Andesite; K-Kaolin; Q-Quartz; and G-Gravel); and Less Category (So-Soil; C-Clay; M-Marble; and O-Others).
Economic Production Quantity Model under Back Order, Rework, Imperfect Quality, Electricity Tariff, and Emission Tax Marsetiya Utama, Dana; Dwi Asmara Putri, Yolanda; Kusuma Dewi, Shanty
Spektrum Industri Vol. 23 No. 1 (2025): Spektrum Industri - April 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v23i1.233

Abstract

This study aims to develop a novel Economic Production Quantity (EPQ) model that integrates important sustainability and operational factors reorders, rework, imperfect quality, emission taxes, and variable electricity tariffs- by minimizing the total inventory cost while considering environmental and energy-related constraints. The model is formulated as an Integer Non-Linear Programming (INLP) problem, with two main decision variables: the total number of products produced in a cycle (y) and the maximum allowable reorder level (w). To solve this complex optimization problem, the Genetic Algorithm (GA) is used for its efficiency in handling non-linear and combinatorial problems. In addition, a sensitivity analysis is performed to assess the impact of various parameters on the total cost. Numerical experiments show that increasing emission taxes, electricity tariffs, and installation costs significantly increase the total inventory and production costs. In particular, higher emission taxes and electricity tariffs amplify the financial burden on manufacturers, underscoring the economic implications of environmental regulations and energy use. These findings emphasize integrating operational and ecological considerations into production planning. This study contributes to the field by offering a comprehensive framework that supports sustainable manufacturing practices through cost-effective inventory management. The proposed EPQ model enables manufacturers to balance economic performance and ecological responsibility, aligning operational strategies with sustainability goals and regulatory compliance.
Tabu Search Algorithm for Solving a Location-Routing-Inventory Problem Saragih, Nova Indah; Turnip, Peri
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.234

Abstract

Location decisions, inventory control, and vehicle routing are interrelated decisions. Inventory control decisions, such as order lot size and order frequency, affect both inventory and transportation costs. Failure to take inventory and transportation costs into consideration when determining location decisions can lead to suboptimality since they have a large impact on inventory and transportation costs. Therefore, how to decide locations, determine vehicle routing, and control inventory optimally, or location-routing-inventory problem (LRIP), becomes an important issue to design logistics systems. The objective of this paper is to develop a heuristic method base on Tabu Search (TS) to solve a LRIP. The contribution of this paper which is the heuristic method based on TS to solve a LRIP has never been developed before. TS is a type of metaheuristic. The success of TS is due to its ability to direct the search process so as not to get trapped in the local optimum, in large part, like many other metaheuristics. TS has been widely used to solve complex combinatorial optimization problems. The result of the computational comparison show that the heuristic method can provide a relatively small average gap of 3.20% compared to the optimal method. Application of the proposed heuristic is done in DKI Jakarta.
Corn Agroindustry Supply Chain Management in Indonesia: Increasing Added Value and Competitiveness through the Hayami Method Nur Arifani, Erlina; Mahfudz, Muhammad Syarqim
Spektrum Industri Vol. 22 No. 2 (2024): Spektrum Industri - October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v22i2.241

Abstract

The agro-industry serves as a crucial intermediary for transforming agricultural societies into industrial ones, contributing to a balanced economic structure. This sector processes agricultural products through various methods, adding value and yielding higher profits than raw commodities. Corn, a staple in Indonesian agriculture, is predominantly cultivated with limited post-harvest activities, impeding rural economic growth. This study examines the supply chain management of the corn agro-industry to enhance value addition and competitiveness. Utilizing the Hayami method, the research identifies stages in the corn processing chain, including cleaning, grinding, filtering, and drying, and evaluates the value added at each stage. The analysis reveals that the supply chain involves multiple stakeholders, from farmers to retailers, and highlights the disparity in value addition among different actors. The study concludes that effective supply chain management, risk mitigation, and strategic interventions are vital for sustaining the corn agro-industry. Recommendations include extended mentorship for farmers and the implementation of efficient production practices to ensure long-term sustainability and economic growth.

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