Penerapan Quality Control pada Souvenir Logo PNP dengan Metode Box Plot dan Six Sigma

The quality of a product determines the level of market demand. This paper discusses the determination of the quality level of plastic molding with the sigma level method which uses the Box Plot to determine the desired quality limit. The purpose of this research is to determine the level of quality of product using statistics. The object of this research is to determine the weight variation of the souvenir of PNP logo with a weight indicator. The experiment were carried out on 200 samples taken at random.Then each sample is numbered from 1 to 200. Each sample is weighed carefully. The results obtained were processed using a box plot to obtain the numbered of rejected samples from 200 samples that were weighed. The result of data processing obtained 19 reject products from 200 products tested. From this data there are 9,5% of products that do not meet the desired specifications. Furthermore, the sigma level is determined from the results of data processing using a box plot. DPMO of 9.5% is 95000 Defects per Milion Opportunities. The result of determining the sigma level is 2.8 Sigma.

Evaluation of Quality Control Data of Hormones Using Six Sigma Metrics Tool in Clinical Laboratory

Background: In health care system it is necessary to provide high quality and reliable test results to the patients. Many clinical laboratories are using six sigma as a tool to improve the quality control in health care system. Keeping this in mind, the present study was conducted using the quality control data of hormones under NABL(National Accreditation Board for Testing and Calibration Laboratories) which were assayed in our clinical laboratory. Materials and Methods: In this retrospective study, both the internal and external quality control data of 11 hormones were collected for a period of 6 months from April 2020 to September 2020 and the six sigma analysis was done. Results: Testosterone level 1(6.8), level 2(6.5) and Folate level1(6.9), level 2(6.6) showed sigma level more than 6 and hence excellent performance. The hormones, FT3 level 1(3.7), level 2(4.8), HCG level 2(3.6), TSH level 1(4.8), level 2(4.7) and Vitamin B12 level 1(4.4), level 2(4.5) showed average performance with sigma level between 3.5 and 6. The hormones, FT4 level 1(1.7), level 2(2), HCG level 1(2.2), Prolactin level 1(3), level 2(3.3), FSH level 1(1.9), level 2(2.0), LH level 1(2), level 2(1.9) and Progesterone level 1(3.4), level 2(3.3) showed poor performance with sigma level less than 3.5. Conclusion: Stringent rules need not be applied for hormones with sigma>6. Moreover, control limits can be relaxed to 3S so that false rejections can be minimized. For hormones with sigma< 6, internal QC rules have to be strictly applied and the root cause analysis has to be done. To conclude, six sigma metrics is a powerful quality control tool which helps to improve the performance of the clinical laboratory and hence the efficiency of the health cares system.

PRODUCT QUALITY CONTROL USING SIX SIGMA (DMAIC) METHODS TO MINIMIZE WAST IN BIMA MANDIRI CIGARETTE COMPANY REMBANG, PASURUAN REGENCY

Quality is a key to be able to compete in the industrial world [16. Quality control is needed to reduce the number of defective products produced by the company, thus reducing losses experienced by the company. The Bima Mandiri Rembang Pasuruan cigarette company is a company that produces cigarettes, one of which is INNO cigarettes. The number of defective products produced by the company so that the company must make an increase in quality by using a method to reduce the number of defects that occur. The number of defective products causes the company to suffer losses. For that, we need a method that can reduce cigarette defective products which in turn can improve the quality of the company's production[12]. Six Sigma with the DMAIC stage (Define, Measure, Analyze, Improve, Control) is a method used in this research. Based on these steps, defects that often occur are less dense cigarettes as many as 289 sticks with a percentage of 25%, tearing on the cigarettes as many as 227 cigarettes with a percentage of 20% and peeling cigarettes as many as 208 sticks with a percentage of 18%. Factors that cause defects include humans, machines, methods and materials. After calculating using the Six Sigma method, before the improvement, the DPMO value is 113988.1 and the Sigma Level value is 2.722. After the improvements were made, the DPMO value decreased to 76488.1 and the Sigma Level was 2.94715. To achieve the six sigma target, the company is expected to be able to carry out improvements with a focus on the factors that cause product defects and always carry out regular control to reduce product defects. The corrective steps taken in the Bima Mandiri Rembang Pasuruan Regency cigarette company are human: regular training for machine operators and employees; methods: inspection of raw materials, blending machines and glue residue in the teat; engine: inspection of engine components; material: reprocessing less refined raw materials and using better quality glue.

On the derivation of zonal and meridional wind components from Aeolus horizontal line-of-sight wind

Since its launch in 2018, the European Space Agency’s Earth Explorer satellite Aeolus has provided global height resolved measurements of horizontal wind in the troposphere and lower stratosphere for the first time. Novel datasets such as these provide an unprecedented opportunity for the research of atmospheric dynamics and provide new insights into the dynamics of the upper troposphere and lower stratosphere (UTLS) region. Aeolus measures the wind component along its horizontal line-of-sight, but for the analysis and interpretation of atmospheric dynamics, zonal and/or meridional wind components are most useful. In this paper, we introduce and compare three different methods to derive zonal and meridional wind components from the Aeolus wind measurements. We find that the most promising method involves combining Aeolus measurements during ascending and descending orbits. Using this method, we derive global estimates of the zonal wind in the latitude range 79.7° S to 84.5° N with errors of less than 5 ms−1 (at the 2-sigma level). Due to the orbit geometry of Aeolus, the estimation of meridional wind in the tropics and at midlatitudes is more challenging and the quality is less reliable. However, we find that it is possible to derive meridional winds poleward of 70° latitude with absolute errors typically below ±5 ms−1 (at the 2-sigma level). This further demonstrate the value of Aeolus wind measurements for applications in weather and climate research, in addition to their important role in numerical weather prediction.

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.

Strengthening Hospital Capacity for the COVID-19 Pandemic: Implementation of Electronic Patient Discharge

Background: Increasing hospital capacity to cover the service demands is an important priority during an epidemic or a pandemic. The aim of this study was to increase hospital capacity using the Six Sigma method to improve the patient discharge process. Methods: This was a quantitative study. The Pre- and post-intervention study was conducted in a big hospital designated for COVID-19 patients. The patient discharge process was evaluated and improved based on seven sub-processes and following the Six Sigma model, including defining the problem, measuring time in each of the discharge stations, analysis times and process, improvement process, and control. Results: Implementation of the electronic patient discharge led to a 51.9% decrease in discharge time from 7.3 h during the pre-intervention period to 3.8 h post-intervention (P< 0.0001). According to the Sigma level, the yield and defects per million opportunities of the discharge process also improved to 55%. Conclusion: Increasing hospital capacity by improving the discharge time is a quick action to cover the demand created during pandemics. Also, about 32 beds can be obtained by applying the Six Sigma model to improve the discharge process in a short time and at a very low cost.

Six Sigma Methodologies and its Application in Manufacturing Firms

Six Sigma is a methodology for process improvement as well as a statistical concept that looks for to determine the variation intrinsic in any process. Six Sigma represents process, that is having 3.4 defects per million opportunities. i.e. 99.99966 % of the products from a Six Sigma process are perfect. Firms can impact their sigma level by combining main principles from the Six Sigma methodology into leadership styles, process management, and improvement activities. Main principle of the technique is a focus on the customer. There are many challenges in the implementation of Six Sigma. A well-run manufacturing team can make the entire firm more successful through cost-saving measures, increased quality and a larger inventory of products that the company can market. The Six Sigma objective is to make sure the process has minimum defects(3.4 defects per million chances). Every aspect of the process must be carefully planned and documented in detail in order for manufacturing to go efficiently. The main aspect of Six Sigma for enhancement in the manufacturing industry is to maximize the financial returns.

Discovery of higher-order quantum electrodynamics effect for the vacuum pair production

The higher-order quantum electrodynamics (QED) effect for vacuum pair production has been searched without success since 1954. In this paper, we show that the combined world-wide data of lepton pair vacuum production is about 20% smaller than the latest lowest order QED calculation with a 5.2 sigma-level of significance and is consistent with the corresponding higher-order QED result. We claim the discovery of higher-order effect for the QED pair production, which settles the dust of previous debates for several decades. The verification of higher-order QED effect is a fundamental scientific problem, which is an important milestone towards the nonperturbative and nonlinear regime of QED vacuum.