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Indar Sugiarto
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Institute of Research and Community Outreach Petra Christian University Siwalankerto 121-131, Surabaya - Indonesia
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International Journal of Industrial Research and Applied Engineering
Published by Universitas Kristen Petra Surabaya
ISSN : -     EISSN : 24077259     DOI : 10.9744/jirae
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering
JIRAE is a peer-reviewed international journal providing a medium for the academic and industrial community to share cutting-edge research and development in various aspects of industrial technology and applied engineering. The objectives are: to encourage research work in the field of industrial technology and applied engineering among scientists, researchers, engineering practitioners, and industrial experts to improve efficiency, reduce costs, and generate high-quality products / services; to promote the adoption and development of comprehensive and state-of-the-art technologies for enterprises and industries; and, to bridge the theoretical and practical gap between academia and industry, and advocate collaboration to address enterprise and industry challenges.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 6 Documents
 1 
Search results for , issue "Vol 1, No 1 (2016)" : 6 Documents clear
From Adaptive Reasoning to Cognitive Factory: Bringing Cognitive Intelligence to Manufacturing Technology Indar Sugiarto; Cristian Axenie; Jörg Conradt
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1186.697 KB) | DOI: 10.9744/JIRAE.1.1.1-10

Abstract

There are two important aspects that will play important roles in future manufacturing systems: changeability and human-machine collaboration. The first aspect, changeability, concerns with the ability of production tools to reconfigure themselves to the new manufacturing settings, possibly with unknown prior information, while maintaining their reliability at lowest cost. The second aspect, human-machine collaboration, emphasizes the ability of production tools to put themselves on the position as humans’ co-workers. The interplay between these two aspects will not only determine the economical accomplishment of a manufacturing process, but it will also shape the future of the technology itself. To address this future challenge of manufacturing systems, the concept of Cognitive Factory was proposed. Along this line, machines and processes are equipped with cognitive capabilities in order to allow them to assess and increase their scope of operation autonomously. However, the technical implementation of such a concept is still widely open for research, since there are several stumbling blocks that limit practicality of the proposed methods. In this paper, we introduce our method to achieve the goal of the Cognitive Factory. Our method is inspired by the working mechanisms of a human’s brain; it works by harnessing the reasoning capabilities of cognitive architecture. By utilizing such an adaptive reasoning mechanism, we envision the future manufacturing systems with cognitive intelligence. We provide illustrative examples from our current research work to demonstrate that our proposed method is notable to address the primary issues of the Cognitive Factory: changeability and human-machine collaboration.
Application of Genetic Algorithm on Spare Part Automotive Body Scheduling Rendy -; Anastasia Lidya Maukar; Arthur Silitonga
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (511.469 KB) | DOI: 10.9744/JIRAE.1.1.25-32

Abstract

Job shop scheduling is one of the complex problems in the manufacturing industry, such as an automotive body manufacturer. This manufacturing company, located in Cikarang, Indonesia, deals with huge customer demand that leads to difficulties in production scheduling. This will cause a delay in some jobs and product deliveries. The current system is using the semi-active scheduling approach and requires 637 minutes for performing 6 jobs with 5 machines. The genetic algorithm (GA) model is proposed as an alternative solution to solve this problem. The GA parameter is set as follow: The population size expected is 30 with maximum generation can be produced in amount of 50. The crossover rate, mutation, and preservation are set to 0.3, 0.1, and 0.1, respectively. After 50 generations are obtained, the optimum solution is shown in generation 6 with a makespan of 597 minutes. Thus, the genetic algorithm model is effectively reducing the makespan of the job-shop scheduling problem by 10% compared to the current method applied at the company.
Optimization of Units Movement in Turn-Based Strategy Game Kristo Radion Purba; Liliana Liliana; Johan Pranata
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.118 KB) | DOI: 10.9744/JIRAE.1.1.33-37

Abstract

Each game has an artificial intelligence that is used to fight the player, which will provide more challenge. But in some strategy games, unit movements are usually done using simple considerations. For example the rest of unit lives, unit strength, and so forth. In this study, a turn based strategy game is designed using genetic algorithm to control the movement of the enemy armies.In each turn, the enemy will move based on the potential level of produced damage to and from the opponent, the distance between the units, and the distance to the opponent’s building. The genetic algorithm’s chromosome for each unit contains the following information: the position where the unit will move, who is the target, and the distance to the armies’ centroid. Distance to centroid (midpoint) is used to force the units to remain in the set. The genetic algorithm process is used to control when and where the units will move or attack. From the test results, the genetic algorithm can create a more powerful enemy than the randomly moving enemy because it creates a higher winning chance of enemy units and acts more efficiently, in terms of the usage of money, the damage produced to the opponent, and the received damage.
Investigation on Biomass Briquette as Energy Source from Waste Leaf Cerbera Manghas Willyanto Anggono; Fandi D. Suprianto; Sutrisno Sutrisno; Andreas W. Kasrun
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.448 KB) | DOI: 10.9744/JIRAE.1.1.11-14

Abstract

Indonesia is a tropical country and has abundant varieties of plants but has not been utilized to the fullest. One of the plants that are often encountered in the community is Cerbera manghas. Cerbera manghas is known as one of the trees that have solid roots; thus, it is widely used for adding greenery both on the roadside and the residential areas of Surabaya. Although beneficial for shade and the reduction of air pollution in urban areas, waste from the leaves of this plant become a serious issue for the cleanliness of the city. Organic solid waste that comes from the falling leaves have the potential to be used as a solid fuel alternative in the form of briquettes when processed appropriately. This study aims to investigate the potential of Cerbera manghas leaves waste to be used as raw material of biomass briquettes with tapioca as a binder, to evaluate the property of the resulted briquettes using ultimate analysis, proximate analysis, and also to find the effect of the composition of tapioca to the heating value of the biomass briquettes. Heating values ​​of five mixtures with various tapioca compositions of 10%, 20%, 30%, 40%, and 50% were evaluated using an oxygen bomb calorimeter. The experimental results showed that the biomass briquettes made of Cerbera manghas leaves waste can be made using tapioca as a binder. The greater the percentage of the mass of tapioca in the briquettes, the lower heating value generated. Biomass briquettes made of Cerbera manghas leaves waste can be made into a source of sustainable energy with the optimal composition of 90% waste leaves and 10% tapioca.
Desigining an Integrated Product and Process Layout Using a Simulation: The Case of Plastic Bag Company Naomi Melina Tanutomo; Tanti Octavia
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (533.966 KB) | DOI: 10.9744/JIRAE.1.1.15-24

Abstract

This paper proposed an integrated product and process layout for optimizing process plant layout using a simulation approach. The proposed layout was compared to the existing layout in terms of the average work-in-process and the average waiting time of work-in-process. Currently, the plastic bag company uses process layout for its production facility layout and the activity of material movement is conducted in a batch fashion. In the proposed layout, product layout was utilized for two of six processes and process layout was utilized for the rest. Product layout changed material movement from batch into one piece flow with material handling conveyor. Software ProModel 7.0 was run in 1 year run-time with 10 replications. The simulation results show that the proposed layout reduces the average work-in-process and work-in-process waiting time in warehouse inspection by 97.92% and 96.82%, respectively. The proposed layout eliminates 47.42 minutes of the average waiting time in welding cutting temporary storage area.
Building APMv3 Map Visualization Using Nagios Host Data Hans Sebastian Tiono; Jelle Oosterkamp; Tom Peperkamp
International Journal of Industrial Research and Applied Engineering Vol 1, No 1 (2016)
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.237 KB) | DOI: 10.9744/JIRAE.1.1.38-45

Abstract

Nowadays, having a network monitoring is becoming an important thing for a growing or big company which should also have a network infrastructure inside it. Network monitoring is the use of a system that constantly monitors a computer network for slow or failing components and that notifies the network administrator in case of outages. Acknowledge Proactive Monitoring (APM), one of the sub-departments in Acknowledge, focuses on developing a network monitoring system using the Nagios tool. However, one of its main features called Map Visualization is not really efficient in terms of its map management. The current stable version of the system is called APMv2 and the team is developing a new version called APMv3 which needs a better Map Visualization. The application made in this project was a proof of concept that will later be used on APMv3. It is a web-based application which has a separate frontend written in HTML and JavaScript, has a separate RESTful backend written in PHP, and uses some frameworks such as jQuery UI, jCanvas, Twitter Typeahead, and Bootstrap 3. All necessary data within this application are exchanged asynchronously using AJAX. 

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