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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

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.

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

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%.

Defect Reduction in The Manufacturing Industry: Systematic Literature Review Mukti Ali Sadikin
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.v5i2.7495

Defect reduction is an important aspect of quality improvement in the manufacturing industry, as it directly impacts product quality, customer satisfaction, and operational efficiency. This paper presents a systematic literature review on defect reduction in the manufacturing industry. The study systematically reviewed articles published in the period 2012-2022 in the Google Scholar, ScienceDirect, Emerald, and Springer Link databases. The review aims to provide a synthesis of research studies, methodologies, and best practices employed to minimize defects and enhance overall product quality. This review identifies key themes, challenges, and future directions in defect reduction by analyzing the existing literature, offering valuable insights for researchers and practitioners.

Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory Agada, Alexander Iwodi; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
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.v5i2.7740

Precise monitoring of vehicle emissions in green logistics, focusing on the contributions of vehicles from packing industries, is crucial for many issues. It helps to understand the total emissions and gain insights into the mechanism of vehicle-associated environmental concerns. Notwithstanding, a key issue when monitoring vehicle emissions is the effective discrimination problem for different patterns generated from the parameters. Data from the packing industry are available from distribution networks but its pattern cannot be discriminated. Given this background, this article presents a new method of the orthogonal array-based rough set to discern patterns of the parametric behaviors to monitor emissions from vehicle exhausts in the packing industry. The proposed method is based on an Indian logistics network and delivery system data, which was obtained from previous work in the literature. By setting controls on the parameters of the packing industry which includes revenue obtained, packing units sold, growth rate, carbon-dioxide equivalent, materials utilized, and quantity consumed, the method was able to discern the patterns of the parametric behavior. The orthogonal arrays, which are developed, form factors (parameters) and levels to ascertain a balanced and uniform analysis of the various groups of options. Indiscernibility and approximation concepts of fuzzy sets are then applied to arrive at the outcome. Unlike previous studies, this study eliminates the need for tracking data, assumptions, and external information to establish the set membership. However, it utilizes the available information within the data. The rough set analysis indicates that there are no discernable patterns or rules that distinguish between "Yes" and "No" decisions. The method of rough set illustrated in this work shows the feasibility of the approach in the Indian packing industry. The method is useful for the logistics manager and government agencies responsible for the control of vehicle-generated greenhouse emissions.

Application of Data Envelopment Analysis for Performance Efficiency Evaluation of Oil Palm Empty Bunch Fruit Composites in The Aerospace Industry Udoibe, Ndifreke John; Oke, Sunday Ayoola; Ayanladun, Chris Abiodun; Rajan, John; Jose, Swaminathan; Adeyemi, Olusola Michael; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
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.v5i2.7741

In this study, we propose the data envelopment analysis method as a scheme to determine the technical efficiency of a set of parametric inputs of the water absorption process when developing the oil palm particulate composite treated with an alkali solution. Although alkali-treated oil palm bunch composites have been analyzed previously for water absorption, a single parameter such as water absorption rate prevails in analyses. Unfortunately, multiple inputs and multiple outputs have been ignored and the efficiency evaluation of such composites has been missing in the literature. To address this gap, the present study exploits the linear programming theory and formulated models for each decision-making unit and solves that formulation for optimum value determination for inputs of the composites. This study investigates the technical efficiency of the water absorption in the oil palm empty fruit bunch composite development process. Overall, judging the performance of the parameters regarding the frequency of attaining 100% efficiency, analysis was performed on the average performance of all parameters in all sixteen scenarios. In this regard, the efficiency of particulate loading was 36.1%, for composite weight plus mold, it was 96.3% and for initial weight, the average efficiency score was 67.8%. It is suggestive that composite weight plus mold with an average efficiency of 96.3% is the best parameter while particulate loading with 36.1% is the worst parameter. Thus result is consistent with the result based on each scenario. From the perspective of DMUs, DMU11 with a score of 78.4% is the best ranking unit while DMU14 is the work ranking unit with an efficiency score of 60.9%. Besides, the average efficiency score for all the DMUs is 66.7%. The work is important to composite development engineers and for policy decision-making.

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

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.

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

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%.

Defect Reduction in The Manufacturing Industry: Systematic Literature Review Mukti Ali Sadikin
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.v5i2.7495

Defect reduction is an important aspect of quality improvement in the manufacturing industry, as it directly impacts product quality, customer satisfaction, and operational efficiency. This paper presents a systematic literature review on defect reduction in the manufacturing industry. The study systematically reviewed articles published in the period 2012-2022 in the Google Scholar, ScienceDirect, Emerald, and Springer Link databases. The review aims to provide a synthesis of research studies, methodologies, and best practices employed to minimize defects and enhance overall product quality. This review identifies key themes, challenges, and future directions in defect reduction by analyzing the existing literature, offering valuable insights for researchers and practitioners.

Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory Agada, Alexander Iwodi; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
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.v5i2.7740

Precise monitoring of vehicle emissions in green logistics, focusing on the contributions of vehicles from packing industries, is crucial for many issues. It helps to understand the total emissions and gain insights into the mechanism of vehicle-associated environmental concerns. Notwithstanding, a key issue when monitoring vehicle emissions is the effective discrimination problem for different patterns generated from the parameters. Data from the packing industry are available from distribution networks but its pattern cannot be discriminated. Given this background, this article presents a new method of the orthogonal array-based rough set to discern patterns of the parametric behaviors to monitor emissions from vehicle exhausts in the packing industry. The proposed method is based on an Indian logistics network and delivery system data, which was obtained from previous work in the literature. By setting controls on the parameters of the packing industry which includes revenue obtained, packing units sold, growth rate, carbon-dioxide equivalent, materials utilized, and quantity consumed, the method was able to discern the patterns of the parametric behavior. The orthogonal arrays, which are developed, form factors (parameters) and levels to ascertain a balanced and uniform analysis of the various groups of options. Indiscernibility and approximation concepts of fuzzy sets are then applied to arrive at the outcome. Unlike previous studies, this study eliminates the need for tracking data, assumptions, and external information to establish the set membership. However, it utilizes the available information within the data. The rough set analysis indicates that there are no discernable patterns or rules that distinguish between "Yes" and "No" decisions. The method of rough set illustrated in this work shows the feasibility of the approach in the Indian packing industry. The method is useful for the logistics manager and government agencies responsible for the control of vehicle-generated greenhouse emissions.

Application of Data Envelopment Analysis for Performance Efficiency Evaluation of Oil Palm Empty Bunch Fruit Composites in The Aerospace Industry Udoibe, Ndifreke John; Oke, Sunday Ayoola; Ayanladun, Chris Abiodun; Rajan, John; Jose, Swaminathan; Adeyemi, Olusola Michael; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
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.v5i2.7741

In this study, we propose the data envelopment analysis method as a scheme to determine the technical efficiency of a set of parametric inputs of the water absorption process when developing the oil palm particulate composite treated with an alkali solution. Although alkali-treated oil palm bunch composites have been analyzed previously for water absorption, a single parameter such as water absorption rate prevails in analyses. Unfortunately, multiple inputs and multiple outputs have been ignored and the efficiency evaluation of such composites has been missing in the literature. To address this gap, the present study exploits the linear programming theory and formulated models for each decision-making unit and solves that formulation for optimum value determination for inputs of the composites. This study investigates the technical efficiency of the water absorption in the oil palm empty fruit bunch composite development process. Overall, judging the performance of the parameters regarding the frequency of attaining 100% efficiency, analysis was performed on the average performance of all parameters in all sixteen scenarios. In this regard, the efficiency of particulate loading was 36.1%, for composite weight plus mold, it was 96.3% and for initial weight, the average efficiency score was 67.8%. It is suggestive that composite weight plus mold with an average efficiency of 96.3% is the best parameter while particulate loading with 36.1% is the worst parameter. Thus result is consistent with the result based on each scenario. From the perspective of DMUs, DMU11 with a score of 78.4% is the best ranking unit while DMU14 is the work ranking unit with an efficiency score of 60.9%. Besides, the average efficiency score for all the DMUs is 66.7%. The work is important to composite development engineers and for policy decision-making.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name -

Contact Email ijieem@uajy.ac.id

Phone -

Journal Mail Official ijieem@uajy.ac.id

Editorial Address Jl. Babarsari no. 43 Yogyakarta

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
-

Contact Email
ijieem@uajy.ac.id

Phone
-

Journal Mail Official
ijieem@uajy.ac.id

Editorial Address
Jl. Babarsari no. 43 Yogyakarta

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA