Defect Per Million Opportunities Research Articles

Defects analysis of frozen fish steak processing using six sigma: a case study

Six Sigma has been utilised to analyse defects of fish steak processing at PT X located in North Jakarta. The tools of the Six Sigma implemented in the study were Define, Measure, Analyse and Improve. The observation was conducted for two months in 2020 before the company was temporarily shut down due to Covid-19 pandemic. Four defects were detected during the study, ie under size fish, softened meat, off odor and green coloration of meat, totaling 2,446 kg out of 15,080 kg of fish. Further analysis showed that the Sigma level was 3.24 with a Defect per Million Opportunities (DPMO) of 40,739. Some improvements were recommended based on cause-effect diagram.

Six Sigma in Urban Logistics Management—A Case Study

A city as a system that constitutes one of the most important areas of human activities. The significant role to fulfill their expectations pay the goods transport and deliveries. These issues are the subject of urban logistics. In broad terms, urban logistics may be construed as a number of processes focused on freight flows, which are completed in cities, including deliveries, supply, goods transfer, services, etc. Due to the different urban logistics stakeholders’ expectations, these systems generate many challenges for managers, especially in the context of city users’ needs and their quality of life. Today, there is a lack of broadened approach and methodology to support them from the processes’ efficiency perspective. To fulfill this gap, the purpose of this paper is to apply the Six Sigma method as a support in last mile delivery management. Six Sigma method plays important role in production systems processes management. However, it could be useful in much wider perspective, including transport and logistics processes. The Authors emphasize that the Six Sigma method could be efficient approach in the last mile delivery processes’ analysis in the context of their efficiency. It helps positioning the customer satisfaction level and quantify the delivery processes defects, related to the undelivered goods. Following that it could improve significantly the last mile delivery processes efficiency. The concept is illustrated by a sample evaluation of one of the urban logistics processes: completion of deliveries. To this end, urban logistics processes were defined. In particular, the delivery completion process was mapped, and the process client was defined along with their expectations. The defects that occurred in the process were identified and analyzed. A DPMO (Defect per Million Opportunities) indicator was established for three randomly selected months. In addition, a root cause analysis of errors was performed. The sigma level for the studied process ranged from 2.61 to 2.89. The factor that had the greatest impact on the number of defects defined as failed deliveries was customer’s absence. The obtained results indicate that the delivery process should be examined in more detail.

ANALISIS KECACATAN PRODUKSI GALLON DENGAN METODE DMAIC SIX SIGMA SEBAGAI UPAYA PENGENDALIAN KECACATAN PRODUKSI Studi Kasus: PT PRIMADAYA PLASTISINDO

Defects are products that produced in the production process, the product is not in accordance with the applied quality standards, but economically the product can be repaired by spending certain cost. The cost that incurred must be lower than the selling value after the product is repaired. PT Primadaya Plastisindo is a company engaged in plastic packaging manufacture by using “Blow Moulding” and “Extrusion” with a set of foreign investment (PMA), namely Taiwan, Malaysia and Singapore. It is quite important in the company to analyze defects in gallon products as a result of disability control efforts with the six sigma method with DMAIC approach, those are define, measure, analizy, improve and control. The results showed that sigma level value is 2,625 or in 3 sigma with possible damage is 133,219 for a million production process or 13.3% defect per million opportunities (DPMO). The damage generated in production is categorized into 2 groups namely Process Reject and Non-process Reject respectively 57.1% and 42.9%. However, from the control chart obtained the fact that the number of defects is still within reasonable.Keywords: control, DMAIC, Six sigma.

Analysis on Product Quality of Semi Refined Carrageenan using Six Sigma and Cost of Poor Quality

The study aimed to minimize defective products to improve the production process quality of PT BI by identifying the most types of defects, calculating Defect per Million Opportunities (DPMO) value, suggesting the quality improvement of the Semi Refined Carrageenan (SRC) production process, and calculating Cost of Poor Quality (COPQ) value. The methods used in this research were Six Sigma and the COPQ. The priority improvement based on the Pareto chart was moisture defects with the percentage of damage of 36.9%. The Sigma level of the production process of PT BI was 3.42 with a defect rate of 27,429 DPMO. The analysis on the cause and effect diagram showed that factors affected the occurrence of defective products were error in reading on moisture content, diverse raw material, the wrong method of mixing raw materials prior to production process, and the lack of inspectors of production process. The most influential-dominant factor was the obsolete machine which causes error in reading on moisture content. The company can take preventive and corrective actions to suppress defective products and improve product quality. Based on the calculation of the COPQ, the costs that must be incurred by the company due to defective products was IDR 1,007,690,694.

Pengendalian Kualitas Pengelasan Pada Proyek Pipeline Sabar#2

PT. ICG is a company that handles the pipeline welding process at PetroChina Jabung Ltd. The welding process carried out is cutting, rolling, pressing and painting. The problem that occurs is that 243 defects are found from the output of 457 welding points. The types of defects after the welding process included 106 points of Root Cancellation defects, 99 points of Incomplete fusion, 29 points of Porosity, 8 points of Slug Inclusion, and 1 point of Tungsten Inclusion. This study aims to control quality by looking at the sigma value of the pipeline production process and analyzing the improvements that should be made to reduce the defects that occur. The results of the calculation of Defect Per Million Opportunities (DPMO) show that the number of welding defects that arise every one million opportunities is 174,10. The quality of the welding process in the pipeline Sabar # 2 project is at a sigma value of 2,43 with a DPMO value of 174,10. From the results of the sigma value obtained, this value is still far from the expectations of Petrochina's management to achieve a minimum sigma value of 4,0. The potential causes of weld defects include welding machines, work errors, work methods and work environment.

Analisis Peningkatan Kualitas Layanan Penyelesaian Gangguan Pstn Dengan Metode Six Sigma

In the era of industrialization increasingly competitive currently, every business actors that wants to winthe competition in the industry will give full attention to the quality. Six Sigma provides a perfect solution aboutbreakthroughs or steps that should be done to produce a dramatic improvement to the level of failures = 0 (zerodefect). PT. X is a company engaged in the business of telecommunications services with one of its products is thePSTN (Public Switch Telephone Network). The author will examine the improvement of service quality controlproblems using the five phases of Six Sigma, namely: 1) Define, The completion of repair that have been madeduring the year 2010 as many as 26 421 with the failure of 23, 2) Measure, cause of the failure that occurred atthe IKR 39.13%, DP 34.78%, 21.73% MDF and RK 4.34%, 3) Analyze, the overall repair process disruption incontrol limits, indicated by the absence of data that passes through the UCL and LCL.The process capability hasbeen which achieved is 5:01 sigma, and the dominant cause of any failure lies in the material factors 43.54%, 4)improve, target to be achieved is 3.4 failures per million opportunities DPMO (Defect per million opportunities)with the proposed improvements on Human Factors, Methods, Machinery/equipment, material and theenvironment, 5) Control, not discussed in this paper because the analysis is only a proposal to the Company.

Six Sigma Implementation in Quality Evaluation of Raw Material: A Case Study

The study aims to evaluate the quality level of raw material in order to improve its quality. This study is constructed based on the implementation of six sigma methodology. Six Sigma is one powerful tool that used in this study to identify the problem, determine the quality level, and to develop the improvement comprehensively. Five phases of the model has been structured by stages respectively. Six sigma had been implemented in many kinds of industry, particularly in production process phase. However, there is a challenge to implement the methodology in other phase in supply chain in the context of developing country. The implementation was conducted on receiving raw material process part in the industry. The result showed some defects identified dominantly; damage seed, broken seed, insects, and moldy seed. There are 6734.13 possibilities of raw material in experiencing defect per million opportunities (DPMO). Lack of knowledge of the workers about the raw material and lack of supporting equipment are the two main causes of poor quality of receiving raw material process.

Analisa kinerja bongkar muat dengan lean six sigma untuk mengurangi demurrage di pelabuhan PT. Petrokimia Gresik

PT. Petrochemical Gresik is one of the firms that has a terminal to be operated by own company (Terminal for Self-interest / TUKS) which supports the activity of unloading raw materials for production and loading activities to load production results. However, in carrying out its operational activities, it still causes demurrage which is a penalty that must be paid by the shipper to shipowner because it exceeds the time limit agreed in the contract of the ship. In this study, an analysis will be carried out on how to identify waste, analyze the causes of waste in the loading and unloading performance of the ship, and analyze how to minimize the factors causing demurrage in TUKS PT. Petrochemical Gresik. The research method used is lean six sigma by integrating the concept of lean process (7 waste) to the six sigma tools namely DMAIC (Define, Measure, Analyze, Improve, and Control). The results of the research at the define phase can be identified into twenty-one CTQ (Critical to Quality) with the highest waste value, namely the internal equipment breakdown category which will only be analyzed further. Subsequently, the measurement phase is identified by the value of DPMO (Defect per Million Opportunities) and six sigma capabilities. Furthermore, the analyze phase is done by finding the root of the problem using fishbone diagrams and FMEA (Failure Mode and Effect Analysis) to attain the value of RPN (Risk Priority Number) and the highest five RPN values. One out of the five causes that are recommended to be prioritized in the handling is operators do not work according to SOP. Finally, in the improvement phase, the new SOP from the results of discussions / interviews was made with the expert judgment related to the operation of the unloading equipment at TUKS PT. Petrochemical Gresik. By this study, lean six sigma can be applied to minimize the occurrence of demurrage by PT. Petrochemical Gresik and other industrial ports.

Quality Improvement for Product Body 2-1 at PT. X

Customer satisfaction is an important indicator for companies to improve the quality of products or services. And if the customer feels satisfied it will automatically increase sales so that it also impacts on the company profits.PT Y is one of the customers who are not satisfied with the product produced PT X, because based on data from January to December 2018, the average monthly defect is 2.34 % whereas the company target is 0.2 %.Therefore in this research it is necessary to minimize the level of defects with the Six Sigma. With five stage, Define, Measure, Analyse, Improve and Control. The proposed improvement provided are installing pins on the stopper, making checklist form of dies check, updating the SOP on the bending process, the results Defect per Million Opportunities (DPMO) before implementing is 19.268 after implementing is 18.229 or decrease (5.3 %) and Sigma level before implementing is 3.57, after implementing is 3.59 increase (0.5 %)

Reducing waste on wheat flour packaging: an analysis of Lean Six Sigma

Reducing defects in the process of packaging wheat flour is important to be done continuously. This study aims to identify and measure the activity of waste that occurred, performance sigma value, and obtain solutions which do by the researcher in Consumer Packing Division PT Z. Waste is measured and assessed using the methods of Lean Six Sigma and Failure Mode and Effect Analysis (FMEA). Based on research, activity categorized waste activities include Defect, Waiting, Non-Utilizing People’s Talent, Transportation, and Motion. Measurement focused on the largest waste Defect is Broken Pack. The result showed the defect per million opportunities (DPMO) value 4089.2475 with level sigma 4.14 and capability process (Cp) 1.31. FMEA showed eight causes factors of the failure broken pack. Four failure mode of which exceeds the critical value that is less of a response operator (Risk Priority Number or RPN=150), lack of control of packaging (RPN=126), less-skilled workers (RPN = 120) and the inaccuracy of allocating the number of workers (RPN=105). Therefore, on the job training, proper allocation of workers during breaks, the packaging audit of the suppliers, and increase the number of workers needed to support the packaging efficiency of wheat flour.

Analysis of product quality control using six sigma method

Quality control is the activity of management to measure the quality characteristics of the product, compare it with specifications or requirements, and take appropriate action if there is a difference between the actual appearance of the standard. Every company needs an operational system that can indicate and overcome defective or damaged products, the company must control quality in each of its production processes. This study aims to determine the quality control of production and actions that should be done by the company to reduce product failure. The research subject used is a case study at the company, this manufacturing company produces bottled water products. The data used in the study include primary and secondary data, and data collection methods used are interviews, observation and documentation. Analysis of the data used in this study is the Six Sigma method which includes five stages of DMAIC analysis namely define, measure, analyze, improve and control. This study revealed that there are five types of defects namely lid defects, cup defects, sliding machine, volume defects, and dirty water. Based on the calculation of sigma value, the average sigma value of company is 4.39 with 2,047.96 Defect per Million Opportunities (DPMO). Fishbone diagrams are carried out to analyze the causal factors of defective products, namely machinery, humans, methods, and materials.

Analisis Pengendalian Kualitas Air Minum dalam Kemasan Menggunakan Metode Six Sigma

Bottled drinking water is market with a variety of packaging, one of which is gallon packaging. Some of the problems that occur in the quality of the gallon are leaky gallons, broken gallons, dirty water, dirty bodies, and mossy gallons. This study aims to determine the company's baseline performance as seen from the value of Defect Per Million Opportunities (DPMO) and sigma level, identifying the causes of product defects. Discussions were carried out following DMAIC's steps on six sigma. Based on the results of data processing, it can see that the DPMO value is 662.46, and the sigma level is 4.84. This result can be the basis for the company to improve the performance of the quality of the products produced.

PENINGKATAN KUALITAS PRODUKSI PELAT DINDING DAN ATAP INSULATED PANEL SYSTEM PENERAPAN METODE SIX SIGMA DENGAN KONSEP DMAIC

This research aims to identify, measure, and analyze process production of EPS (Expanded Polystyrene) Sandwich Panel produced by PT. BI. It also gave recommendation to improve the process production for increasing product quality. This products produced by PT. BI is still have high defects so that it need improvement to decrease defect product. The approach used to solve this problem is Six Sigma method based on the stages of DMAIC (Define, Measure, Analyze, Improve and Control). Identification for defect product consists of defects occurred in the process bending plate, gluing, press roll pressing and cutting. The results of previous research obtained DPMO (Defect Per Million Opportunities ) value is 6500 and sigma level is 3.98. It has not reached the expected target of 6 sigma. Analysis using fishbone diagram and FMEA (Failure Mode and Effect Analysis) show that there is need for corrective action to improve company's performance. Proposed quality improvement is conducted by installing plastic roll (laminating coating) and replacing broken roll press. The result of proposed improvement shows DPMO value is 3227 and the sigma level is 4.22.

A six sigma based approach to evaluate the on time performance of Indian railways

PurposeThe purpose of this paper is to propose an approach to evaluate “on time” performance for a class of Indian railways (IR). This approach is build-up on the theme of six sigma level computation for continues data. The arrival data obtained from a class of IR called “Rajdhani Express” exhibited a unique characteristic: neither did the data followed a distribution nor could it be transformed to fit into a distribution. In this work, the authors present an approach to evaluate on time performance of IR, given such “unruly” data.Design/methodology/approachAn attempt is made to develop a lucid approach, given an unruly data. Initially, the authors plot a histogram using Scott’s method. Later, the authors use Taguchi’s quality loss function to assign weights to each of the bins in histogram. Weights to each of the bins are assigned based on the predefined rules. Finally, sigma level is computed by using weighted defect per million opportunities (DPMO) approach. In this paper, the authors discuss the proposed algorithm, an illustrative example with an emphasis on a class of IR.FindingsGiven the unique characteristic (unruly data) of arrival data of IR, the proposed methodology helps in quantifying it is on time performance. This method extends the conventional DPMO approach of computing the sigma level. The proposed method is validated using various data sets of different distributions. Further, this approach can be generalized and applied to data set of any distribution. Since distribution of the data is not the pre-requisite, the proposed approach can be applied to compare (and benchmark) data sets of different distributions. This methodology, thus, paves path to develop newer approaches in quantifying and benchmarking the sigma levels.Research limitations/implicationsIn this manuscript, the authors present a case of Rajdhani Express trains, a class of IR. A practicing manager can use this approach to compare the performance of various classes of railways and benchmark their performance. Such an approach, with suitable modifications (if any) can be applied to evaluate performance in various service industries.Originality/valueUsually, if the data are unruly, the sigma level is computed by using ad-hoc methods that may provide compromising solutions and/or inaccurate results. The developed methodology proposes a unique approach to quantify sigma level, given such an unruly nature of the data. This approach thus fills the long needed gap in addressing such situations. This approach can be applied in various similar situations. A case of IR is presented.

Quality Control of the Steel Wire Rod Product by Integration Lean Six Sigma and Taguchi Method

RMW Inc. is the global company in Indonesia. One of its product is the steel wire rod. This research aims to control the production process and improve the product quality. This research is using the integration between lean six sigma and taguchi method. The first step is to reduce the waste using lean six sigma method while the second step is to reduce the defect using taguchi method. Based on the identification of seven waste, the most dominant waste is the defect that is caused by there is no setting of the roll entry guide. The product has 11 CTQ (critical to quality) with the focus on laps defect, underfill defect, and overfill defect. Then, the cause of failure is identified using FMEA (failure mode effect analysis). The level of sigma capability is achieved at 4.54 with DPMO (defect per million opportunities) is 4006.55. The first improvement can reduce the time until 8.9 minutes. The second improvement sets the roll entry guide. The optimum factors for setting of the roll entry guide is A factor with 150 tonnages of wear level, C factor by 5 bar of cooling and D factor by 6 ml of lubrication.

Usulan Penurunan Tingkat Kecacatan Produk Pelat Baja dengan Metode Six Sigma

This study aims to maximize the decline in the level of product defects to lead to zero defects. Researchers use the six sigma method through 5 stages of completion, namely, define, measure, analyze, improve, and control. Based on the results of the study it can be concluded that the sigma level and the value of DPMO (Defect per Million Opportunities) of the company amounted to 3.47 with possible damage of 24,239 sheets for one million productions. After further analysis using the Pareto diagram, it found that the cutting fault transfer defect was the most common with a percentage of damage of 43%. And based on the results of the analysis of fishbone diagrams, it can be seen that the main factors causing contamination in the production process come from the worker factor (human), followed by machine factors, material, and work methods. The proposed improvements that can be made by the company include updating existing methods and SOPs (standard operating procedures) and monitoring the operator's performance and developing knowledge and planning proper maintenance scheduling.

Minimization of Defective Products in The Department of Press Bridge & Rib Through Six Sigma DMAIC Phases

This study proposes the DMAIC Six Sigma approach of Define, Measure, Analyze, Improve/Implement and Control (DMAIC) to minimizing the number of defective products in the bridge & rib department. There are 5 types of defects were the most dominant are broken rib, broken sound board, strained rib, rib sliding and sound board minori. The imperative objective is to improve the quality through the DMAIC phases. In the define phase, the critical to quality (CTQ) parameters was identified minimization of product defects through the pareto chart and FMEA. In this phase, to identify waste based on the current value stream mapping. In the measure phase, the specified control limits product used to maintain the variations of the product, the calculation of the value of DPMO (Defect Per Million Opportunities) and the calculation of the value of sigma level. In analyze phase, determine the type of defect of the most dominant and identify the causes of defective products. In the improve phase, the existing design was modified through various alternative solutions by conducting brainstorming sessions. In this phase, the solution was identified based on the results of FMEA. Improvements were made to the seven priority causes of disability based on the highest RPN value. In the control phase, focusing on improvements to be made. Proposed improvements include making and define standard operating procedures, improving the quality and eliminate waste defective products.

Electrophoretic deposition of PEEK/bioactive glass composite coatings for orthopedic implants: A design of experiments (DoE) study

This paper presents a study on the Design of Experiments (DoE) approach to optimize the electrophoretic deposition (EPD) process parameters for PEEK base coatings. PEEK and bioactive glass (45S5 BG) particles were suspended in ethanol and suspensions were stabilized with the help of citric acid. Electric field related parameters were optimized by using Taguchi DoE; an orthogonal array of L15 type with mixed levels of the control factors. Statistical tools were employed to identify the significant factors affecting deposition rate and to quantify the reproducibility of the constant voltage EPD process. It was demonstrated that both deposition voltage and time significantly influence deposition rate. Moreover, statistical confidence was elucidated by Defect Per Million Opportunities (DPMO) model, as proposed in six sigma tools. A pronounced deposition rate was obtained at 100V/cm in comparison to 110V/cm, although the adhesion strength and microstructural homogeneity were lower for 100V/cm. The optimal suspension composition and EPD conditions predicted by DoE were further verified by experiments and qualitative agreement was found between the predicted and experimental data. The experimental results and statistical analyses are discussed based on current knowledge of the EPD of ceramic materials and their co-deposition with polymeric particles.

Analisis Penggunaan Alat dan Teknik Pengendalian Mutu dalam Penerapan Sistem Manajemen Mutu pada Perusahaan Karet Bersertifikat ISO 9001:2008

The increasing competition in the global market and high consumer expectations for quality products, encourage companies to be able to produce quality products which meets international standards. One of the activities in improving quality that conform to product specifications is applying appropriate quality control system involving all aspects of the company that are integrated with the standard ISO 9001: 2008 as a guide. However, the rubber industry in West Sumatra still faces obstacles in the implementation of quality control techniques and tools of as experienced by ABC and XYZ. This study aimed to evaluate the application of quality control tools and techniques in the manufacturing company which is certified ISO 9001: 2008, ABC and XYZ. This research was conducted by calculating the value of DPMO (Defect Per Million Opportunities). Based on the results found that the two companies have different DPMO value. PT ABC obtained by 5,2σ sigma level from DPMO value of 94.33 for the types of defects whitespot and sigma level of 4,2σ of DPMO value of 3365.096 to defect type of metal, while the XYZ obtain sigma level of 5,3σ from DPMO value of 728.697 for the types of defects whitespot and sigma level of 4,8σ of DPMO value of 425.441 for the type of metal defects. From the analysis it can be concluded that the two companies have not been effective in applying the techniques and tools of quality control in accordance with the standards ISO 9001: 2008 in order to achieve continuous quality improvement. This is indicated by the key success factor of the implementation techniques and tools of quality control is not applied appropriately in achieving continuous quality improvement.

GRAFIK PENGENDALI RAGAM SAMPEL UNTUK MONITORING VARIABILITAS PROSES PRODUKSI

The control chart is a graphical display or a quality characteristic that has been measured or computed from a sample versus the sample number or time. The variance chart is used to monitoring variability of production process. It is an altenative way to check variability process rather than R chart or s chart. The problems will be done are find the parameters of variance chart, predict process capability, verify defect per million opportunities (DPMO) of process result and simulation kinds of shift sigma values. This result could be used as information to production process at the future time. The result of discussion that upper conrol limit = 0.0014, center line = 0.00073, lower control limit = 0.00028, process capability = 1.003 and DPMO = 2,620 part per million. These parameters used for information in the next production process. Keywords: Variance Chart, Process Capability, Defect per million opportunities, Shift.