Publication Search

Abstract. This research aims to analyze the effectiveness and reliability of production machines in the process of making public street lighting poles (PJU) at PT. XYZ The main problem faced by the company is high machine downtime so that production targets are not achieved. Therefore, a method is needed that is able to measure machine effectiveness as a whole and identify the main causes of production losses. The method applied includes Overall Equipment Effectiveness (OEE) to measure machine effectiveness based on three components, namely availability, performance and quality. The Total Productive Maintenance (TPM) approach is used to identify factors causing low effectiveness through Six Big Losses analysis. Apart from that, Mean Time To Repair (MTTR) and Mean Time Between Failure (MTBF) are calculated to determine the level of machine reliability. The data used includes machine working hours, downtime, operating time, production quantities, defective products, as well as machine damage and repair data. The analysis results are expected to show the level of machine effectiveness and identify the dominant factors causing downtime. Based on these results, improvement proposals are prepared to reduce downtime, increase machine reliability and improve production productivity Keywords: Overall Equipment Effectiveness (OEE), Total Productive Maintenance (TPM), Six Big Losses, Downtime, Efektivitas   Abstrak. Penelitian ini bertujuan untuk menganalisis efektivitas dan keandalan mesin produksi pada proses pembuatan tiang penerangan jalan umum (PJU) di PT. XYZ Permasalahan utama yang dihadapi perusahaan adalah downtime mesin yang tinggi sehingga target produksi tidak tercapai. Oleh karena itu, diperlukan metode yang mampu mengukur efektivitas mesin secara menyeluruh dan mengidentifikasi penyebab utama kerugian produksi. Metode yang diterapkan meliputi Overall Equipment Effectiveness (OEE) untuk mengukur efektivitas mesin berdasarkan tiga komponen, yaitu availability, performance, dan quality. Pendekatan Total Productive Maintenance (TPM) digunakan untuk mengidentifikasi faktor penyebab rendahnya efektivitas melalui analisis Six Big Losses. Selain itu, dilakukan perhitungan Mean Time To Repair (MTTR) dan Mean Time Between Failure (MTBF) untuk mengetahui tingkat keandalan mesin. Data yang digunakan mencakup jam kerja mesin, downtime, waktu operasi, jumlah produksi, produk cacat, serta data kerusakan dan perbaikan mesin. Hasil analisis diharapkan dapat menunjukkan tingkat efektivitas mesin dan mengidentifikasi faktor dominan penyebab downtime. Berdasarkan hasil tersebut, disusun usulan perbaikan untuk mengurangi downtime, meningkatkan keandalan mesin, dan memperbaiki produktivitas produksi Kata kunci: Overall Equipment Effectiveness (OEE), Total Productive Maintenance (TPM), Six Big Losses, Downtime Mesin, Efektivitas Mesin

This study aims to analyze the shoe production process from an operational management perspective at PT. XYZ. The focus of the research is directed at the stages of the production process and the management of raw materials in supporting the smooth running and efficiency of production activities. This research uses a descriptive qualitative approach carried out through an Internship Experience Practice (PPL) at PT. XYZ. Data was collected through direct observation of production activities, interviews with relevant parties in the production department, and supporting documentation. The data obtained was analyzed by describing the production process flow, raw material management system, and production process control, then linked to the concept of operational management. The results showed that the shoe production process at PT. XYZ consisted of several interrelated stages, starting from raw material management to the main production process. The company has implemented a fairly structured operational management system, characterized by the recording of raw materials, the separation of materials by type, and the application of the First in First Out (FIFO) method to maintain material quality and smooth production. However, several operational obstacles were still found, such as limited production time, suboptimal coordination between departments, and the potential for defective products in the production process. The implementation of operational management at PT. XYZ has supported the shoe production process quite effectively, particularly in raw material management and production control. Nevertheless, improved coordination and continuous evaluation of the production process are needed to enhance operational efficiency and product quality.

This study aims to analyze the quality control of white crystal sugar production at ABC Sugar Factory using the Statistical Quality Control (SQC) method. The research employed a descriptive quantitative approach with a case study design. The primary data consisted of production volume and defective product data during the 2024 production period, while supporting data were obtained through observation and interviews with the Quality Control department. The analytical tools applied included check sheets, histograms, Pareto diagrams, p control charts, and fishbone diagrams. The results show that from a total production of 190,745.89 tons, defective products amounted to 66.70 tons, representing 0.33 percent of total output. The identified defects consisted of wet sugar at 45 percent, brownish sugar color at 30 percent, and oversized sugar crystals at 25 percent. Defective products occurred only during the first to third production periods, while no defects were observed from the fourth to seventh periods. The p chart analysis indicates that the production process was statistically out of control in the early periods but became stable and controlled in the subsequent periods. From a managerial perspective, these findings provide practical guidance for improving manufacturing quality through enhanced process control, equipment maintenance, and workforce capability development.

This study aims to analyze the bread production system of UMKM Roti D’One using the Input–Process–Output (IPO) approach and to identify product defects through the application of the Seven Tools of quality control. Data were obtained through interviews, field observations, and production recording. The IPO analysis shows that the production process is carried out manually and relies heavily on worker skills and household-scale equipment. Based on the checksheet, two dominant types of defects were identified—non-soft texture and uneven color—resulting in 30 defective products out of 1,400 breads produced in one week. The Pareto analysis indicates that texture defects contribute the largest portion (56.7%) of total defects. Meanwhile, the fishbone diagram reveals that the main causes originate from raw material inconsistency, equipment limitations, variations in worker skills, and manual production methods. This study suggests improvements related to raw material standards, production consistency, and worker training to reduce defects and enhance the overall quality of Roti D’One products.

The purpose of this research is to use the six sigma approach to assess the quality of cracker manufacturing at UD. Palapa in Nganjuk Regency. This technology was chosen because it allows for quantitative measurement and analysis of product defect levels, as well as the identification of defect-causing variables. The study was carried out using the DMAIC (Define, Measure, Analyze, Improve, Control) steps and statistical methods such as Pareto diagrams, fishbone diagrams, and C-chart control charts. According to the research, the cracker manufacturing process at UD. Palapa has an average sigma value of 2.74, which is still below the six sigma (6σ) threshold.  This figure implies that the product fault rate remains fairly high.  The most common forms of faults are irregular shape and uneven thickness, which are mostly produced by machine, human, process, and raw material problems. C-chart analysis reveals that most processes are still under control, while there are a few spots beyond the control boundaries that indicate unique variances. Based on these data, it is possible to infer that UD. Palapa's quality control system is still reactive and has to be improved in order to be more proactive. Routine equipment maintenance, operator training, the introduction of standard operating procedures (SOP), and more stringent raw material selection are all possible efforts. Six Sigma deployment has been shown to provide a full view of production quality conditions, as well as a foundation for future continuous improvement programs.

PT. Lotus Indah Textile Industries, a manufacturing company in the open-end yarn spinning sector, faces significant issues related to defective products in its production process. This study aims to identify the level of human error among open-end machine operators and analyze the root causes of these errors. The methods employed include the Human Error Assessment and Reduction Technique (HEART) to calculate the Human Error Probability (HEP), as well as Root Cause Analysis (RCA) with the 5 Whys approach to identify the root problems. Data were collected through observation, interviews, and questionnaires during the period of May to June 2025. The results indicate that the activity of "pushing the full yarn so that it detaches from the holder and moves to the conveyor with the right hand" had the highest HEP value of 0.281996. The main root causes of human error include a lack of focus and accuracy among operators, rushing while working, limited experience, and insufficient training and periodic evaluations of employee effectiveness by the company. The impact of these errors results in defective products such as dirty yarn and rolls that do not meet standards. As an improvement recommendation, the company is advised to conduct periodic evaluations of operator effectiveness after training to enhance productivity and provide feedback, as well as to establish clear procedures for the doffing process of yarn on open-end machines to reduce errors. This study is expected to assist the company in improving operator performance, reducing human error rates, and minimizing defective products.

Osha Snack UMKM faces issues related to product defects, which are suspected to arise due to a lack of quality control in the production process. This study aims to identify the causes of product defects, provide improvement suggestions, and determine effective ways to control product quality. Data were collected through interviews with relevant parties and field surveys to gather information on production volume, product defects, and production activities. The data were processed by organizing it into check sheets, performing regression calculations, and analyzing it using scatter diagrams and fishbone analysis. The Statistical Process Control (SPC) method was applied to analyze, control, and improve the production process. The results show a significant relationship between production volume and the number of defective products, with the regression equation Y = 0.0764X and a coefficient of determination R² = 0.9625. The most common type of defect is broken snacks before packaging. In addition, waste products also come from product returns by buyers, which leads to raw material waste and hinders the achievement of production targets. The analysis results suggest that the UMKM should implement quality control measures in the form of process improvements, enhancement of work skills, proper machine maintenance, implementation of SOPs, and improvement of working conditions.

This study was conducted to evaluate the quality of banana chips products at My Kripis by using the Check Sheet and Fishbone Diagram methods. The main problem found was the high rate of defective products, which reached 3.79% of the total monthly production. The largest type of defect was recorded as inappropriate banana ripeness during the frying process, which amounted to 18 kg out of a total of 37.2 kg of defective products. Data was collected through direct observation and interviews, then analyzed using an inspection sheet to identify the type and frequency of defects. Results showed that the dominant cause of defective products came from raw material factors, such as non-uniform banana ripeness and inconsistent slice thickness. A Fishbone Diagram was used to identify root causes from various aspects, including man, methods, machines, and materials. These findings served as the basis for recommendations to improve the production process, such as standardizing cutting procedures, training operators, and monitoring the quality of raw materials. This research confirms the importance of simple yet systematic quality control for MSMEs to sustainably improve product quality.

Product quality is described as the characteristics of a product that supports its ability to meet customer needs standards or manufacturer feasibility standards. This research was conducted on potato chip products at Osha Snack by analyzing the types of defects in potato chips and their causative factors. In this study, the method used is the seven tools method, namely fishbone diagram, pareto diagram, and flowchart diagram. In one month, 57 units of defective potato chips were obtained. The purpose of this study using the seven tools method is to find out the types of defects in potato chips and the factors that cause defects in the product to minimize the level of defects in the production period in the next period. Based on the data obtained, there are two types of defects in potato chips, including 35 units of product returns and 22 units of burnt chips and inappropriate potato cutting. On the application of quality chips.    

Consumer protection is a crucial aspect in the face of rapid economic development and increased industrial competition, including in the bottled water sector. The Aqua product packaging defect case in Semarang in July 2017 is a clear example of weak quality control and the importance of producer accountability. Defects such as bottle caps that can be pried off without breaking the seal create uncertainty over product safety and reduce consumer confidence. Law No. 8/1999 on Consumer Protection provides a strong legal basis for consumers to obtain safe products and claim compensation for losses due to defective products. Manufacturers have an absolute responsibility to ensure product safety through the implementation of strict quality control systems, early detection of physical defects, and digital tracking for product recalls if necessary. In addition, consumer education and optimization of public complaint media are important parts of the consumer protection system. With a comprehensive preventive and corrective approach, risks due to defective products can be minimized, and public trust in the industry can be maintained.

Batik Banten Mukarnas is a company that produces stamped batik designs with various patterns and varieties of batik. Problems frequently arise in the company due to increased stamped batik production capacity to meet the demand for stamped batik design products, which continues to rise from stamped batik suppliers. Another impact of growing demand capacity is the high number of defects in stamped batik cloth products, because overall, the company's management, including human resources, tools, and methods, is not prepared for the increase in production capacity to meet the surge in consumer demand, resulting in an impact on the quality of the products produced—consequently, the organization endeavors to regulate the quality of stamped batik cloth at PT. Batik Banten Mukarnas establishes objectives that employ Six Sigma with the DMAIC method (Define, Measure, Analyze, Improve, and Control) in the production of batik stamp designs to meet production objectives. The results of the data processing that has been done obtained a sigma value before improvement for 3 CTQ of 3.54. After improvement, the sigma value increased to 3.86. While for the sigma value before improvement for 1 CTQ of 3.04, the sigma value increased to 3.42 after improvement. The factors contributing to defective products, as illustrated by the fishbone diagram, include methods, personnel, materials, machinery, and environmental conditions. The division leader consistently oversees and regulates operations, enhances the number of brushes, and trains operators to ensure proficient adherence to standard operating procedures (SOP).

PT Primayudha Mandirijaya merupakan suatu perusahaan yang bergerak dibidang pemintalan benang yang terletak di Desa Ngadirojo, Kecamatan Ampel, Kabupaten Boyolali, Provinsi Jawa Tengah. Pada data produksi benang cotton pada bulan Februari 2024 cacat yang paling sering terjadi yaitu cacat kotor sebanyak 21 unit, cacat stitching sebanyak 15 unit dan cacat non standar sebanyak 8 unit. Studi ini menggunakan metodologi Six Sigma yang bertujuan untuk mengurangi tingkat cacat dengan mendorong pemahaman, pengukuran dan perbaikan proses. Lima fase Six Sigma adalah Define, Measure, Analize, Improve dan Control. Upaya yang dilakukan untuk menurunkan ambang batas kecacatan pada PT Primayudha Mandirijaya, memberikan pemahaman mengenai penggunaan mesin dan perawatan mesin, melakukan pengecekan dan lebih meningkatkan kebersihan mesin, SOP di share ke operator dan di tempel di mesin, dan memberikan pemahaman bagaimana menciptakan kenyamanan lingkungan saat bekerja.

PT Primayudha Mandirijaya merupakan suatu perusahaan yang bergerak dibidang pemintalan benang yang terletak di Desa Ngadirojo, Kecamatan Ampel, Kabupaten Boyolali, Provinsi Jawa Tengah. Pada data produksi benang cotton pada bulan Februari 2024 cacat yang paling sering terjadi yaitu cacat kotor sebanyak 21 unit, cacat stitching sebanyak 15 unit dan cacat non standar sebanyak 8 unit. Studi ini menggunakan metodologi Six Sigma yang bertujuan untuk mengurangi tingkat cacat dengan mendorong pemahaman, pengukuran dan perbaikan proses. Lima fase Six Sigma adalah Define, Measure, Analize, Improve dan Control. Upaya yang dilakukan untuk menurunkan ambang batas kecacatan pada PT Primayudha Mandirijaya, memberikan pemahaman mengenai penggunaan mesin dan perawatan mesin, melakukan pengecekan dan lebih meningkatkan kebersihan mesin, SOP di share ke operator dan di tempel di mesin, dan memberikan pemahaman bagaimana menciptakan kenyamanan lingkungan saat bekerja.

XYZ is a manufacturing company that produces Yamaha brand motorbike parts such as electrical switches, electrical sockets, lever assembly and horns. Many of the products sent were returned by customers because they did not meet quality standards, for example in March 2024 there were 1,420 pcs out of a total of 19,900 pcs that were returned. This means that companies have to increase production time and costs to replace defective products that are returned because they do not have safety stock. Forecasting is needed to control the production system so that it does not experience over stock and safety stock shortages. This research aims to provide recommendations for forecasting methods that companies can use to minimize the occurrence of production excesses and shortages in the company. Forecasting is done based on historical company sales data for 12 months. The method used is the exponential smoothing method which is then tested whether this method can be used in the future. This calculation uses the help of POM-QM (Production Operation Management – Quantitative Method) software. Calculations are carried out by testing the MAD, MSE, and MAPE values to obtain calculation error values. The results obtained by forecasting the main sw srtg lock assembly product using the exponential smoothing method were 15,708 for demand for the next period, MAD 3.38, MSE 22.84 and MAPE value 26%. Based on these results, the exponential smoothing method can be a recommendation for companies to forecast future demand. This is because the value of forecasting accuracy or MAPE is reasonable. The smallest percentage of MAPE values has a fairly minimal possibility of error in forecasting results.

The problem faced by the Bmrsign Wallgallery company is that products are found that do not match the specifications set by the company. The types of product damage are wrong size frames, broken frames, and uneven corners. To solve this problem, the SQC method is used to reduce the causes of defects in the product. The purpose of this method is to reduce the risk of damage to the product. The object studied was Bmrsign Wallgallery with a sample of 29 days. The use of the SQC method is accompanied by analysis tools in the form of control charts (p-charts), Pareto diagrams, cause and effect diagrams (fishbone). Based on the results of data analysis implementing the Statistical Quality Control (SQC) method using the P-Chart control map, the largest value of the Upper Control Limit (UCL) can be shown as 0.272, while the Lower Control Limit (LCL) is -0.013. The results show that the number of defective products during the frame making process is still within normal control limits. The analysis using the Pareto diagram shows that the types of frame defects are dominated by broken with a percentage of 35% or a total of 66 pcs, inappropriate size shapes as much as 33% or a total of 62 pcs, and uneven corners as much as 32% or a total of 60 pcs. Based on the results of the fishbone diagram analysis, defective products are caused by workers who are not focused, work standards are not adhered to, machine maintenance is not given attention, and there is a decrease in the quality of raw materials.

UD Sadewo Jagat is a company engaged in furniture production, this company provides sales of finished, semi-finished products and maintenance for various types of teak wood furniture. Finished products include tables, chairs, shelves and various other types of displays. However, in this study, we only analyzed defective products for wooden box table products because the production process of wooden box table products because the production process of wooden box tables experienced problems, namely the number of defects exceending 5% of the company’s standard provisions. The aim of this research is to analyze product quality control techniques using the Statistical Process Control method in reducing defective products, and to find out what factors cause defects in products produced by UD Sadewo Jagat. This research uses the Statistical Process Control (SPC) method, which is one of the analytical methods used to analyze the causes of defects that occur, both in terms of product quality and in terms of the quality of the production process. Quality control analysis is carried out using. The results of the check sheet analysis show an average of 9,6% product defects per month. From the results of the Pareto diagram, it can be seen that the highest level of defects is crack defects, with a total of 80 units or 44,94% of total product defects in 2023. Meanwhile, the results of the control chart that has been made can be seen that quality control is uncontrolled and not according to standards. From the results of the fishbone diagram, it is concluced that the factors causing product defects are human factors, materials, environment, and methods.

Pan Brothers Tbk is one of the garment companies that adopted garment production in the form of 3D VR (Virtual Reality) as a garment prototype in Indonesia. In the process of making 3D VR products, many defective products must be revised. The study aims to implement the Six Sigma method and suggest improvements to reduce defects in 3D VR garment products using the Six Sigma method with the stages of defining, measuring, analyzing, improving, and controlling. In the define stage, the identification of the production process using the SIPOC diagram and identifying the type of defect. In the measure stage, the DPMO and sigma value calculations are carried out. The most defects are fitting not balanced and properly with a DPMO value of 269619.2 and a sigma value of 2.11. In the analysis stage with a fishbone diagram shows the factors that cause defects, namely man, machine, material, method, and environment. In the improvement stage, suggestions for improvements are given to reduce defects in 3D VR garment products. In the control stage, quality control is carried out by conducting internal training, upskilling, creating inspection report forms, adding teams to the QC division, and adding SOPs for the 3D VR producing process.

The Pukun Kuala Tanjung rice factory is a rice factory located in Pematang Tobat village, Sei Suka subdistrict, Batubara district. The Pukun Kuala Tanjung rice factory has been operating for fifteen years in milling rice into rice. In operating the Pukun Kuala Tanjung rice factory, it can produce 25 tons of rice/week. In carrying out the rice production process at the Pukun Kuala Tanjung rice mill, we often find that the rice produced does not match the quality of production, including the color of the rice being less than good (yellow), rice that is not peeled and crushed, which can lead to a decrease in the quality for sale and even unsalability. rice on the market so that the Pukun Kuala Tanjung rice factory experiences losses in producing rice. The aim of this research is as follows: to know how to control the quality of rice using the SQC (Statistical Quality Control) method, to find out the quality of rice produced by the Pukun Kuala Tanjung rice factory is still in good condition. controlled or not. This research uses descriptive quantitative research both when collecting and processing data where the data collected is data on defective rice products and data processing will be carried out using the SQC (Statistica Quality Control) method. From the data processing that has been carried out in this research, the author draws the following conclusions: Rice quality control using the SQC (Statistical Quality Control) method can be seen as follows: Based on the control chart, it is known that defective products are not within the upper control limits (Upper Control Limit) and Lower Control Limit which can mean that a defective product requires repairs to be made to the defective product.

Azhari Bakar Bread Factory is an MSME domiciled in Rejowinangun, Kotagede, Yogyakarta. In the production process, this factory can produce 7807 pieces of bread in a month, of the total production that month 57 pieces of bread are defective. To reduce defects, quality control is needed. Quality control aims to produce products in the form of goods or services that comply with the desired and planned standards, as well as improve the quality of products that do not comply with predetermined standards and possibly maintain appropriate quality. This research uses the Six Sigma and Kaizen methods by showing factual data and comparing it with existing theories to find things that need to be added, improved, or maintained. This research found that the sigma process capability calculated for 1 month was 2.97 with a possible damage of 3661.21 for one million production. From these results, it can be said that the company has not implemented quality control completely properly and correctly because it is still far from the target level of 6 sigma, therefore the company needs to carry out quality control on defective products. The factor that causes production defects is the human factor. machines, methods, materials, and environment.

Azhari Bakar Bread Factory is an MSME domiciled in Rejowinangun, Kotagede, Yogyakarta. In the production process, this factory can produce 7807 pieces of bread in a month, of the total production that month 57 pieces of bread are defective. To reduce defects, quality control is needed. Quality control aims to produce products in the form of goods or services that comply with the desired and planned standards, as well as improve the quality of products that do not comply with predetermined standards and possibly maintain appropriate quality. This research uses the Six Sigma and Kaizen methods by showing factual data and comparing it with existing theories to find things that need to be added, improved, or maintained. This research found that the sigma process capability calculated for 1 month was 2.97 with a possible damage of 3661.21 for one million production. From these results, it can be said that the company has not implemented quality control completely properly and correctly because it is still far from the target level of 6 sigma, therefore the company needs to carry out quality control on defective products. The factor that causes production defects is the human factor. machines, methods, materials, and environment.