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All Journal Jurnal Teknik Industri USU Jurnal Sistem dan Manajemen Industri PRODUCTUM : Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Ilmiah Teknik Industri Jurnal Sistem Teknik Industri JURNAL PENGABDIAN AGRO AND MARINE INDUSTRY Jurnal Pengabdian Masyarakat Ilmu Kesehatan
Aulia Ishak
Departemen Teknik Industri, Fakultas Teknik, Universitas Sumatera Utara
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation

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Journal : Jurnal Sistem Teknik Industri

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Implementation of Lean Manufacturing Methodology and Its Application: A Literature Review Manurung, Martin; Anizar, Anizar; Ishak, Aulia
Jurnal Sistem Teknik Industri Vol. 26 No. 1 (2024): JSTI Volume 26 Number 1 January 2024
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v26i1.12158

Abstract

This study aims to investigate and analyze several previous works of relevant literature on the Lean Manufacturing technique in international journals. The methodology used to review the previous studies was carried out through a survey based on descriptive, qualitative, and bibliographical surveys in International Journal with restriction to the period of publication from 2017 – 2022 published on databases and electronic journals in English with the scope to examine and analyze in-depth the extent to which literature used to discuss results in the selected papers of applying the Lean Manufacturing technique in several case studies. After conducting a survey, only thirty-three articles were found with the theme of the application of Lean Manufacturing and its technique in manufacturing companies. Twenty-one techniques/tools of Lean Manufacturing were found problem-solving for waste time elimination, reducing process cycle times, and implementing process improvement. It is concluded that the most used methodology in waste reduction is Value Stream Mapping.
Literature Review of Concurrent Engineering in Kansei Engineering and Ergonomic Setiawan, Alvin; Ginting, Rosnani; Ishak, Aulia
Jurnal Sistem Teknik Industri Vol. 26 No. 2 (2024): JSTI Volume 26 Number 2 July 2024
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v26i2.14696

Abstract

This research aims to conduct a literature review on the application of the integration of Kansei engineering, ergonomics, and concurrent engineering methods in the context of product design. A systematic study of 8 scholarly journals related to the topic in the last decade indicates that combining these three methods has a positive impact on product performance and the efficiency of the development process. In conclusion, a multidisciplinary approach is highly recommended to produce innovative and highly competitive products through a faster and cost-effective process.
Integration of Value Engineering for Design for Assembly in Product Design: A Comprehensive of Literature Review Hartanto, Adrian; Ginting, Rosnani; Ishak, Aulia
Jurnal Sistem Teknik Industri Vol. 26 No. 2 (2024): JSTI Volume 26 Number 2 July 2024
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v26i2.15268

Abstract

This study explains the benefits obtained from the integration of Design for Assembly (DFA) and Value Engineering (VE) methods in the product design process. DFA is proven to provide benefits such as product simplification, reduced assembly costs, and improved quality by creating product structures that are simpler and easier to install. While VE adds value by taking into account the replacement of expensive or difficult-to-assemble components, speeding up overall assembly time. Although specific research on the integration of these two methods may be limited, studies show that the combination of DFA and VE produces design alternatives that consider various aspects of the product life cycle. The result is reduced costs, faster development times, and a reduced need for rework. The concepts and benefits of integrative DFA and VE approach can be an effective strategy for enhancing assembly efficiency and reducing production costs in product design.
Life Cycle Analysis Study of Plastic Flower Pot Products Ishak, Aulia; Siregar, Khawarita; Sarjana, SS
Jurnal Sistem Teknik Industri Vol. 26 No. 2 (2024): JSTI Volume 26 Number 2 July 2024
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v26i2.15349

Abstract

Some flower pots are made of plastic materials. Plastic waste is a global environmental issue with varying quantities and types in different countries. One source of plastic pollution is low-durability plastic pots, commonly used for seeding in agriculture, horticulture, and forestry. Waste from these plastic pots is difficult to decompose by soil microbes, thus posing an environmental contamination risk. Life Cycle Analysis (LCA), also known as life cycle assessment, is a method to measure the environmental impacts of products, such as biofuels. In LCA, researchers prepare an inventory of the resources used (e.g., fossil fuels and raw materials) and substances produced (e.g., greenhouse gases, solid waste, and other pollutants) throughout the full life cycle of production, transportation, and use of the product in question. From this inventory, researchers conduct impact assessments that estimate the final effects on human health, ecosystem function, and depletion of natural resources. This study aims to assess the life cycle analysis of plastic flower pot products from  their initial material stage to their disposal as waste, in order to gain insights into the potential  for minimizing their environmental impact. The results of research where the production of 600 ml plastic flower pot bottles required 28 grams of plastic resin per bottle, as well as energy for the production and transportation processes. Plastic packaging production produces defective products.
Analysis of Goods Delivery Routes Using Saving Matrix and Clarke & Wright Savings Methods Sari, Rahmi M; Christoffel P, junardi; Ishak, Aulia; Tambunan, Mangara M
Jurnal Sistem Teknik Industri Vol. 27 No. 1 (2025): JSTI Volume 27 Number 1 January 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i1.16017

Abstract

Distribution routes are distribution delivery routes that are created taking into account distance traveled, transport equipment capacity, and delivery capacity so that distribution costs are minimal. To date, there are 14 routes with 32 delivery points. Of the 14 existing routes, there are drop points through which several routes pass. So, companies need to evaluate the routes currently used. This problem arises as a result of the increase in shipping capacity over time. The general objective of this final research is to obtain alternative distribution routes in the process of distributing goods and analyze route improvements by comparing company routes and alternative routes obtained using the Saving Matrix and Clarke & Wright Savings methods. The research results showed that alternative distribution routes using the Saving Matrix method experienced an increase in costs of 5.4% from the original costs. Meanwhile, using the Clarke & Wright Savings method, distribution costs decreased by 3.6% per day. The improvement proposal given is an alternative distribution route using the Clarke & Wright Saving method, which has 11 routes and a savings of 3.6%.
Integration of Reverse Engineering and Additive Manufacturing Methods in the Design and Development of Prosthetic Products : A Literature Review Rumapea, Elsa S E; Ginting, Rosnani; Ishak, Aulia
Jurnal Sistem Teknik Industri Vol. 27 No. 1 (2025): JSTI Volume 27 Number 1 January 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i1.17188

Abstract

The integration of reverse engineering (RE) and additive manufacturing (AM) in the design and development of prosthetic devices has shown significant potential for improving the customization, efficiency, and overall quality of these essential medical aids. This paper reviews recent advancements in the use of RE and AM for prosthetics, highlighting key methodologies and findings from various studies. The results demonstrate that combining these technologies can enhance mechanical properties, dimensional accuracy, and user satisfaction while reducing production costs and time. However, challenges such as material biocompatibility and the need for standardized frameworks remain. Continued research and collaboration among researchers, clinicians, and industry stakeholders are essential to fully realize the potential of RE and AM in prosthetic development, ultimately improving the quality of life for individuals with limb loss.
The Design of a Demand Forecasting Model of Glass Bottled Tea Products With Machine Learning Approach Said Munal Akid; Ishak, Aulia; Sinulingga, Sukaria
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.17069

Abstract

An accurate sales forecasting is crucial to the profits earned because it affects the company's stock management. With computational support, machine learning and artificial intelligence can continuously and automatically recognize patterns in data, thereby reducing the risk of demand unpredictability. PT XYZ is one of the companies in industrial sector that produces various beverage products. The factory in Medan. One of the products is the tea glass bottle. At PT XYZ, there are frequent differences between forecasting data and sales data, causing high error rates in production planning accuracy. This study aims to analyze the most effective model for forecasting future sales by comparing the accuracy of a Machine Learning-based forecasting model with the existing forecasting method currently employed at PT XYZ. This research was conducted using the Recurrent Neural network (RNN) method as part of the Machine Learning approach. The data that was inputted to the programme was weekly demand data, calendar day off data, temperature data, and population data. The forecasted data is weekly demand. Based on the company's historical data, a demand graph is obtained which has a cyclical pattern. From the results of forecasting using Machine Learning, an accuracy value of 99.47% is obtained with an error rate of 0.53%, which is still below the tolerance limit set by the company. The error rate shows a decrease of 14.72% compared to the error value in the previous company model. This decrease is expected to help control inventory more effectively.  
Additive Manufacturing in Prosthetics Field: A Literature Review Ginting, Rosnani; Ishak, Aulia; Nasution, Fadylla Ramadhani Putri; Malik, Alfin Fauzi; Bangun, Putri Syahmina Atirah
Jurnal Sistem Teknik Industri Vol. 27 No. 3 (2025): JSTI Volume 27 Number 3 July 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i3.20416

Abstract

Prosthetic devices play a critical role in restoring mobility and enhancing the quality of life for individuals who have experienced limb loss due to trauma, disease, or congenital conditions. However, the high cost, discomfort, and limited accessibility of conventional prosthetics present ongoing challenges. In response, Additive Manufacturing (AM), particularly 3D printing, has emerged as a transformative solution in the field of prosthetics. This technology enables the creation of patient-specific prosthetic components with complex geometries, improved fit, and reduced weight, all while lowering production costs and minimizing the need for post-processing. Through a comprehensive review of recent studies, this paper explores the advancements and applications of AM in prosthetics, including the integration of machine learning, finite element method (FEM) simulations, and new materials such as PLA, ABS, ASA, and carbon fiber-reinforced composites. Research findings indicate that AM facilitates the development of durable, lightweight, and anatomically accurate devices, such as transfemoral sockets and prosthetic thumbs, which pass international fatigue and safety standards. The studies also highlight the advantages of AM in pediatric prosthetic design, where rapid anatomical changes necessitate frequent adjustments. By streamlining the production process and enabling customization, AM significantly improves comfort, usability, and accessibility for users. This review concludes that additive manufacturing holds immense potential to revolutionize prosthetic development by offering cost-effective, sustainable, and user-centered solutions. The continued advancement and integration of digital manufacturing technologies are poised to address existing limitations in prosthetic care and support the growing global demand for innovative, inclusive, and high-quality assistive devices.
Co-Authors A. Rahim Matondang Adrian Hartanto, Adrian Aguslina S, Fazidah Alvin Setiawan Amelia, Tia Anizar Anizar Asfriyanti, Asfriyanti Asfriyati ,MKes Bangun, Putri Syahmina Atirah Chenio, Alkent Christoffel P, junardi Dewi Sari Kencana Dudin, Sa Febi Ardani Halinda Sari Lubis Harmein Nasution Heryanto Handoko Humala L Napitupulu Khatami, Muhammad Khawarita Siregar M. Sari, Rahmi Malik, Alfin Fauzi Mangara M Mangara M Tambunan Manik, Donald Manurung, Martin Marta Elissa Sirait Matius J Situmorang Maya Fitria Mutia Hasanah Nababan, Poltak Nadia Kurnia Putri Napitupulu, Humala Lodewijk Nasution, Alfian Aziz Nasution, Fadylla Ramadhani Putri Nazaruddin M Nazaruddin Matondang Nova Tarihoran novalin, Susi Diriyanti Nursafwah Poltak Nababan Prawira, Yoga Putri Oktalisa Rahmi M Sari Rosnani Ginting Rumapea, Elsa S E Said Munal Akid Sarjana, SS SATRIA Situmorang, Syafrizal Helmi Sri Rahayu Sanusi Sugih Arto Pujangkoro Sukaria Sinulingga Sukaria Sinulingga Syah, Chairul Syahri, Isyatun Mardhiyah Tania Alda Tarigan, Indah Rizkya Ukurta Tarigan Wilianto Wilianto William Arfayo Yos Indra Mardatillah Yuman, Syafiq Alhadi