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International Journal of Industrial Engineering and Engineering Management
Published by Universitas Atma Jaya Yogyakarta
ISSN : -     EISSN : 26854090     DOI : https://doi.org/10.24002/ijieem
Core Subject : Engineering,
Industrial & Manufacturing Engineering
International Journal of Industrial Engineering and Engineering Management (IJIEEM) is an open access scientific journal that publishes theoretical and empirical peer-reviewed articles, which contribute to advance the understanding of phenomena related with all aspects of Industrial Engineering and Engineering Management
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 161 Documents
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Optimization of Process Parameter of Tungsten Inert Gas Welding for Austenitic Stainless Steel using Grey Wolf Optimization Adekola, Anthony Ozimu; Oke, Sunday Ayoola; Nwankiti, Ugochukwu Sixtus
International Journal of Industrial Engineering and Engineering Management Vol. 4 No. 2 (2022)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v4i2.5748

Abstract

Optimization of welding parameters is essential on austenitic stainless steel for industrial applications since they declare the best parameters compared with prioritized constraints. However, available optimization methods, such as the Taguchi method, widely used in this research domain, are weak. Their results are merely comparative and fail to particularly show the specific factor that displays the highest performance in the process. In this paper, the aim is specifically to position the parameters in order of importance and present them in a grey wolf optimization framework. The ultimate tensile strength and yield strength were optimized, and the optimization was conducted using the C++ programming code. Literature data were analyzed for austenitic stainless steel under un-notched/smooth and notched specimen conditions. Empirical models were developed for the ultimate tensile strength and yield strength, among other principal criteria of the material. For the ultimate tensile strength, the best value was obtained at the 100th iteration as 640.75. For the yield strength, the best value of 394.98 was obtained after 100 iterations. A value of 31.07 for the PE was obtained. These results are for the unnotched specimens. However, the PE, NTS, and yield strength values for the notched specimens are 16.32, 780.12, and 494.46, respectively. Based on the findings of this study and compared with other optimization methods, the optimal parameters and outputs predicted using the grey wolf optimization approach were found to produce reliable results. This shows that the grey wolf optimization approach is a good option for predicting the optimal parameters of the tungsten arc welding process by utilizing austenitic stainless steel. The usefulness of this research effort is to help process engineers to implement robust and effective cost decisions in the production of materials based on austenitic stainless steel.
An Application of Data Envelopment Analysis in the Selection of the Best Response for the Drilling of Carbon Fiber-reinforced Plastic Composites Adedeji, Wasiu Oyediran; Odusoro, Salome Ifeoluwa; Adedeji, Kasali Aderinmoye; Rajan, John; Oke, Sunday Ayoola; Oyetunji, Elkanah Olaosebikan; Nwankiti, Ugochukwu Sixtus
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.5792

Abstract

In the drilling operation, defects such as delamination at exit and entry are very disturbing responses that impact the efficiency of the drilling process. Without control, an exponential growth in the amount of drilled components with defect quantities may result. Thus, the process engineer has input in attaining the desired production levels for components in the drilling process. Consequently, this article deploys a novel method of data envelopment analysis to evaluate the relative efficiency of the drilling process in reducing the defects possible in the producing components from the CFRP composites. The high-speed steel drill bits were utilized to process the CFPs, while the responses considered are the entry and exit determination, thrust force, and torque, among others. Literature experimental data in twenty-seven experimental counts were summarized into fewer groups and processed through the data envelopment analysis method. The results show that capturing the CFRP composite responses is feasible, providing an opportunity for enhanced efficiency and a situation where undesirable defects in the CFRP composite production process may be eradicated. The article’s uniqueness and primary value are in being the foremost article in offering an updated vast representation of the comparative efficiency of CFRP composite parameters within the literature for the composite area. The work adds value to the CFRP composite literature by envisaging and understanding the comparative efficiency for the parameters, identifying and separating the best from the worst decision-making unit. It also reveals how the parameters are linked by their relative placements. The article's novelty is that using data envelopment to compare the efficiency in reducing drilling defects such as entry and exit determination, among others. The method’s utility is to provide information for cost-effective drilling operations during the planning and control phases of the operation.
Optimizing The Machining Process of IS 2062 E250 Steel Plates with The Boring Operation Using a Hybrid Taguchi-Pareto Box Behnken-teaching Learning-based Algorithm Abdullahi, Yakubu Umar; Oke, Sunday Ayoola
International Journal of Industrial Engineering and Engineering Management Vol. 4 No. 2 (2022)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v4i2.5820

Abstract

In this article, a new method termed the Taguchi-Pareto-Box Behnken design teaching learning-based optimization (TPBBD–TLBO) was developed to optimize the boring process, which promotes surface roughness as the output. At the same time, the speed, feed, and depth of cut are taken as the inputs. The case examines experimental data from the literature on the boring of IS 2062 E250 steel plates. The proposed method draws from a recent idea on the Taguchi-Pareto-Box Behnken design method that argues for a possible relationship between the Taguchi-Pareto method and the Box Behnken design method. This idea was used as a basis for the further argument that teaching learning-based optimization has a role in the further optimization of the established TPBBD method. The optimal solutions were investigated when the objective function was generated using the Box Behnken design in a case. It was replaced with the regression method in the other case, and the python programming codes were used to execute the computations. Then the optimal solutions concerning the parameters of speed, feed rate, depth of cut, and nose radius were evaluated. With the Box Behnken as the objective function for the TLBO method, convergence was reached at 50 iterations with a class population of 5. The optimal parametric solutions are 800 rpm of speed, 0.06 min/min of feed rate, 1 min for depth of cut, and 0 min for nose radius. On the use of the regression method for the objective function, while the TLBO method was deployed, convergence was experienced after 50 iterations with a class population of 200 students. The optimal parametric solution is 1135rpm of speed, 0.06 min/min of feed rate, 1024 min of the depth of cut, and 0.61 min of nose radius. The speed, depth of cut, and nose radius showed higher values, indicating the use of more energy resources to accomplish the optimal goals using the regression method-based objective function. Therefore, the proposed method constitutes a promising route to optimize further the results of the Taguchi-Pareto-Box Behnken design for boring operation improvement.
Analysis of Work Posture and Manual Handling on the Material Transport Activities of Indonesian Traditional Market Worker Kurnianingtyas, Chandra Dewi; Sukma, Heydar Pradika
International Journal of Industrial Engineering and Engineering Management Vol. 4 No. 2 (2022)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v4i2.5921

Abstract

This research is about the observation of workers transporting sacks in a traditional market. The worker complained about pain in many body parts like the shoulders, waist, and arms, which are presented in the results of the Nordic Body Map questionnaire. This problem can be solved by massaging the body section to reduce musculoskeletal disorders. Because it is often get massaged, it makes the completion time of sack transport become longer. Work posture must be improved because too much pain piles up over long periods and can impact condition health and decrease productivity. The purpose of this research is to evaluate the working posture while doing manual handling. Evaluate work posture using Rapid Entire Body Assessment (REBA) and Manual Handling Assessment Chart (MAC Tool). As a result, work posture and manual handling have a higher level of risk of injury, so we need to investigate and implement change. The level of risk must be reduced to at least medium risk. Using auxiliaries can improve work posture, reduce health risks, reduce load sacks, and increase work productivity. The recommended outcome is adding a skid box to improve the value of REBA and manual material handling by providing a hand trolley cart.
Forecasting Non-Oil and Gas Exports in Indonesia Using Double and Triple Exponential Smoothing Methods Bustami; Yolanda, Anne Mudya; Thahira, Nisha
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.6211

Abstract

Non-oil and gas exports could be forecasted using exponential smoothing for future periods. This study examines non-oil and gas export data in Indonesia from January 2015 to May 2021, indicating trends and seasonality. Based on the data characteristics, the obtained data were analyzed using Holt's double exponential smoothing method and triple exponential smoothing with multiplicative and additives Holt-Winters. The MAPE for all three models is less than 10%, indicating that the method is very good and could be used to forecast the next period. Using MAPE as a comparison, the best model for non-oil and gas exports is the additive Holt-Winters method triple exponential smoothing, which has the lowest MAPE of any model. The best method was employed to forecast data, making it possible for us to anticipate the pattern of non-oil and gas exports. This forecast data could be used as the basis for policymakers' decision-making. The forecast results using this method indicate that the value of non-oil exports will increase for the next period.
Simulation-based Reliability Evaluation of Maintenance the Efficiency of A Repairable System Krit, Makram
International Journal of Industrial Engineering and Engineering Management Vol. 4 No. 2 (2022)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v4i2.6233

Abstract

  The aim of this paper is to study the asymptotic behavior of the Arithmetic Reduction of Intensity (ARI) and Arithmetic Reduction of Age (ARA) models as two imperfect maintenance models. These models have been proposed by Doyen & Gaudoin (2011), the failure process with bathtub failure intensity. The maintenance effect is characterized by the change induced by the failure intensity before and after a failure during the degradation period. To simplify the study, the asymptotic properties of the failure process are derived. Then, the asymptotic normality of several maintenance efficiency estimators can be proved in the case where the failure process without maintenance is known. Practically, the coverage rate of the asymptotic confidence intervals issued from those estimators is studied.
Analysis of Product Defect to Reduce Return Product in Flexographic Printing Apriyanti, Yunita; Zulkarnain
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 2 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i2.6244

Abstract

Product return in 2021 at PT XY increased, but the quality control implemented has not been running effectively. This study aims to analyze the failure risk that causes defects, gets the greatest failure risk in the Risk Priority Number (RPN),and gives suggestions for improvement for the next production. The focus of this study is on production defects that are returned by customers. This study used Failure Mode Effect Analysis (FMEA) methods and Problem Identification Corrective Action (PICA) table. From the gathered data, it is identified that there is one type of dominant defect that is outside the control limits. The results of data processing by multiplying the SOD value to get the RPN value found that the three largest ranking modes of failure were the engine settings did not match the RPN value of 484, negligent in the production control process with the RPN value is 230, and the compressor is not optimal with the RPN value is 210. Then an analysis was carried out using the PICA table to get suggestions for improvements, conducting periodic IK retraining, checking machine condition regularly, conducting periodic inspections during the production process, evaluating performance results, and running check sheets while carrying out the production process.
Application of Fuzzy Analytic Hierarchy Process (FAHP) to Improve Precision and Certainty on Safety Conformity Evaluation in a Bottling Plant Sawyerr, Babatunde Alade; Fasina, Ebun; Adedeji, Wasiu Oyediran; Martins, Shedrach Aliakwe; Rajan, John; Oke, Sunday Ayoola
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.6498

Abstract

With the bottling plant facing safety impacts, the commitment toward zero levels of accidents needs to be evaluated. However, the perception and measurement of safety conformity by the safety manager that is subjected to imprecision and uncertainty are hardly evaluated correctly with the present dominant approach of using crisp numeric values. This article presents a fuzzy analytic hierarchy process (FAHP) approach to reduce the imprecision and uncertainty in the safety conformity multicriteria decision-making results. The method establishes and selects the best safety conformity factors in alignment with different criteria within the segments of a Nigerian bottling plant. The fuzzy synthetic extent concerning each alternative, the degree of possibility, prioritizing weights, and the choice of the best criterion were judged based on the maximum weight in the FAHP evaluation process. The average weight criterion was used to distinguish the best from the worst units within each segment. The results reveal the criteria weights as 0.4937 for haulage drillers (warehouse), 0.3038 for palletizers (manufacturing corridor), 0.3333 for syrup mixers/lab technicians for quality assurance, and no choice of the best parameter for the fleet workshop. However, the highest weight for the contractors is 0.3201, which is for contractor 1. To compare the best and worst criteria in the present study and a literature source, the optimal criteria choices of safety conformity conflicted in all the segments. The principal difference between the present method and the analytic hierarchy process approach is integrating fuzzy application to the analytical hierarchy process to provide a more accurate safety conformity assessment, yielding reliable and informative results representing the vagueness of the bottling process decision-making process. This unique approach provides an opportunity for the production workers to work more collaboratively towards attaining new solutions to the uncertainty and imprecision problem in safety conformity for the bottling plant.
Supply Chain Performance Measurement at PT. Perkebunan Nusantara XIV Camming Sugar Factory in Bone District Saleh, Anis; Ahmad, Arfandi; Herdianzah, Yan; Lantara, Dirgahayu; Saputra, Nur Ihwan; Dahlan, Muhammad
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 2 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i2.6861

Abstract

PTPN XIV (PERSERO) of Camming Sugar Factory in Bone Regency Measuring work results in the company is one of the company's performance evaluation tasks, namely to find out if the results achieved are good enough or still need improvement. The characteristic of a weak result is the fact that the company's goal is not achieved in the desired way. The objective of this study is to identify the KPIs and measure the performance indicators at the Bone Regency of PTPN Camming Sugar Factory. Key Performance Indicator (KPI), Lean Supply Chain Management (LSCM), and Analytic Hierarchy Process (AHP) methods are used in this study. The results of this study provide 11 Lean metrics that align with business conditions. Once the indicators are obtained, the KPI weighting is carried out using the Analytical Hierarchy Process (AHP), prioritizing the performance criteria of the production and supply departments. KPIs that have a significant impact on a company's supply chain performance. This is reflected in the highest order of weight in three KPIs, namely production department performance criteria, employee productivity attributes (0.573) and delivery department criteria, on-time loading (0. 85), and delivery (0.372) attributes. with a weight percentage of 19.1, 16.20% and 12. 2%. The KPIs in the lowest weight category are collection (0.120) and delivery (0.116) with a weight percentage of .01% and 3.87%.
Emotion Detection Research: A Systematic Review Focuses on Data Type, Classifier Algorithm, and Experimental Methods Destyanto, Twin Yoshua R.
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.7077

Abstract

There is a lot of research being done on detecting human emotions. Emotion detection models are developed based on physiological data. With the development of low-cost wearable devices that measure human physiological data such as brain activity, heart rate, and skin conductivity, this research can be conducted in developing countries like Southeast Asia. However, as far as the author's research is concerned, a literature review has yet to be found on how this research on emotion detection was carried out in Southeast Asia. Therefore, this study aimed to conduct a systematic review of emotion detection research in Southeast Asia, focusing on the selection of physiological data, classification methods, and how the experiment was conducted according to the number of participants and duration. Using PRISMA guidelines, 22 SCOPUS-indexed journal articles and proceedings were reviewed. The review found that physiological data were dominated by brain activity data with the Muse Headband, followed by heart rate and skin conductivity collected with various wristbands, from around 5-31 participants, for 8 minutes to 7 weeks. Classification analysis applies machine learning, deep learning, and traditional statistics. The experiments were conducted primarily in sitting and standing positions, conditioned environments (for developing research), and unconditioned environments (applied research). This review concluded that future research opportunities exist regarding other data types, data labeling methods, and broader applications. These reviews will contribute to the enrichment of ideas and the development of emotion recognition research in Southeast Asian countries in the future.

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