scholarly journals Integration of Statistical Quality Control (SQC) and Fault Tree Analysis (FTA) in the quality control of resina colophonium production in Company X

2021 ◽  
Vol 924 (1) ◽  
pp. 012062
Author(s):  
A L Rucitra ◽  
A U F Amna
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Control Method ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Statistical Quality Control ◽  
Control Analysis ◽  
Tree Analysis ◽  
Statistical Quality ◽  
A Value

Abstract Resina colophonium is a product that is produced from the processing of pine sap. This product is widely used for adhesives, additives for beauty products and mixtures of paints and varnishes. One of the companies engaged in the production of resina colophonium is Company X. Production process is an important aspect of the company, so any problems must be avoided to eliminate product defects. One way that can be done to avoid problems in the production process is to carry out proper quality control. The purpose of this study was to analyze the quality control of the production process at Company X. The quality control method used is the integration of the Statistical Quality Control (SQC) method to determine the frequency of problems and Fault Tree Analysis (FTA) to complete identification by looking for the causes of these problems so that problem did not repeat. Based on the results of the quality control analysis, it is found that the most serious problem that affects the quality of the production process lies in the labor aspect with a value number is 38.46% and the root of the potential cause is the number of workers who are not following the current work.

scholarly journals ANALISIS PENGENDALIAN KUALITAS TERJADINYA CACAT PADA PROSES PRODUKSI ADJUSTER R KWB

2018 ◽  
Vol 2 (1) ◽  
pp. 57
Author(s):  
Indrani Dharmayanti ◽  
Ajeng Rahayu (Politeknik APP)
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Statistical Quality Control ◽  
Control Analysis ◽  
Statistical Tools ◽  
Statistical Quality ◽  
Quality Control Analysis

<p>ABSTRAK<br />Penelitian ini bertujuan untuk mengetahui proses produksi produk Adjuster R KWB dan analisis jenis kecacatan dan penyebab pada PT.Dina Karya Pratama. Analisis pengendalian kualitas dilakukan menggunakan alat bantu statistik yang biasa disebut seven tools berupa Check sheet, Peta kendali p, diagram pareto diagram sebab akibat untuk kemudian dapat menjawab permasalahan diatas.</p><p>Kata kunci : Pengendalian Kulitas, Statistical Quality Control (SQC), Seven Tools</p><p>ABSTRACT<br />This study aims to find out the production process of Adjuster R KWB product and the analysis of disability and causes type in PT.Dina Karya Pratama. Quality control analysis is done using statistical tools commonly called seven tools in the form of Check sheet, Map control p, pareto diagram causation diagram to then be able to answer the above problems.</p><p>Keywords: Kulitas Control, Statistical Quality Control (SQC), Seven Tools</p>

ANALISIS PENGENDALIAN KUALITAS PRODUK PADA USAHA HOME INDUSTRY FURNITURE BAPAK KARSIDIN DI KELURAHAN LOKBAHU KECAMATAN SUNGAI KUNJANG KOTA SAMARINDA

2020 ◽  
Vol 8 (2) ◽  
pp. 162
Author(s):  
DODY AL'AZHAR
Keyword(s):  
Quality Control ◽  
Human Factors ◽  
Production Process ◽  
Product Quality ◽  
Raw Material ◽  
Statistical Quality Control ◽  
Quality Level ◽  
Control Analysis ◽  
Statistical Quality ◽  
And Control

Product quality control is very important for company or business that is willing to improve the performance. Home Industry Business or a home-based business established by Mr. Karsidin is furniture business and the products include cabinet, table, bench, TV rack and other furniture items which can be tailored to customer desires. In the production process, Mr. Karsidin's business still has product defects that can be observed at the beginning of this study that is presented in table 1.1. The study aims to determine the product quality level is still in control limits measurement of Mr. Karsidin’s Home Industry Business, analyze types of defects and control production quality using statistical quality control (SQC). The method in the study was statistical quality control (SQC) to monitor standards, make measurements and take corrective actions while the product or service is being produced. The quality control tools were Observation Sheet, Histogram, Cause and Effect Diagram and Control Diagram (p Chart). The result indicates that the product quality by Mr. Karsidin's business during the observation period from April to May 2019 is at the control limit. Further, based on p control analysis there is no point that exceeds Upper Limit or Lower Limit. The production process should be given more attention, especially at several main factors such as workers or human factors, in which there are a lot of negligence in the production process. Mr. Karsidin should make improvement to the defects directly that at the cause level, including raw material, machinery, method and human factors based on the Standard Operating Procedures (SOP).

scholarly journals PRODUCT QUALITY CONTROL ANALYSIS USING STATISTICAL QUALITY CONTROL (SQC) ON MARINE WORKS IN BUSINESS AMPLANG SAMARINDA

2020 ◽  
Vol 6 (1) ◽  
pp. 70-77
Author(s):  
Silvia Maulida Arianti ◽  
Emy Rahmawati ◽  
RR Yulianti Prihatiningrum
Keyword(s):  
Quality Control ◽  
Product Quality ◽  
Control Charts ◽  
Quantitative Research ◽  
Quantitative Methods ◽  
Control Measures ◽  
Control Limit ◽  
Statistical Quality Control ◽  
Control Analysis ◽  
Statistical Quality

Purpose of the study: The objectives of this study are: (i) To analyze the quality control of the products applied to the amplang Karya Bahari business based on Statistical Quality Control (SQC) tools, (ii) To find out and analyze what factors cause product damage/disability amplang work at the Maritime business in Samarinda. Methodology: This research uses quantitative methods discretionary quantitative research method that is research that is used to Investigate, find, describe, and explain the quality or features of social influences that can’t be explained or Described measured through a quantitative approach. The operational definitions of this research are (i) Quality control processes, (ii) Quality control measures. Types and sources of the data the primary use of data Obtained directly from the object of research. Data collection techniques are (i) observation, (ii) interviews, (iii) documentation, (iv) laboratory tests. Analysis of the Data used are: (i) collecting the data (check sheet), (ii) a histogram, (iii) making control charts, (iv) the causal diagrams, (v) the proposed improvements. Main Findings:  The results of the study suggest that Maritime work is applied to the already on the limit of control. It can be seen at chart, upper control limit (UCL) of 1 and the lower control limit (LCL) of 0.3362 under controlled conditions or reasonable limits, but in reality, they are experiencing product damage or defect in the production of amplang processing. Novelty/Originality of this study: This study is expected to be an additional reference for studies in the field production related to analysis quality control (quality control) and product quality by using Statistics Quality Control. This study is expected to provide information for the company about procedure control in keeping a quality product that will be produced.

scholarly journals Pengendalian Kualitas Produk Dengan Menggunakan Metode SQC dan HRA Guna Meningkatkan Hasil Produksi Tahu di IKM H. Musauwimin

2019 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Koyor Rujianto ◽  
Hana Catur Wahyuni
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Manufacturing Industry ◽  
Employee Performance ◽  
Reliability Assessment ◽  
Statistical Quality Control ◽  
Surface Type ◽  
A Value ◽  
Increase Productivity ◽  
Data Adequacy

Small and Medium Industries (IKM) H.Musauwimin is a manufacturing industry in the field of tofu production. In the production process there are still frequent product defects, including coarse tofu, tofu surface torn, soft texture, and faded color. For this reason, we need a way to minimize the possibility of product defects. The objectives of this study are (1) Identifying disability factors using the Statistical Quality Control (SQC) method, (2) Improving employee performance performance using the Human Reliability Assessment (HRA) method, (3) Minimizing product defects in the production process so as to increase productivity. The results of this study are (1) of the four types of rejects for the biggest 3 months in tearing surface type with a percentage of 46% of all rejects (2) By testing the adequacy of the data using the SQC method in the production process for 3 months then sample we tested a total of 284. From the results of the data adequacy test data obtained a value of 7,289, so the number of samples is larger than the sample that should be. (3) From the results of measuring employee performance using the HRA method. The biggest HEP value is the type of Possible Error. The operator only estimates and there is no standard in mixing vinegar acid with the filtrate. With an HEP value of 0.48. So this factor is the most dominant cause of disability and must be corrected immediately.

scholarly journals Analisis Penyebab Kecacatan Produk Weight A Handle Menggunakan Metode Fault Tree Analysis dan Failure Mode and Effect Analysis sebagai Rancangan Perbaikan Produk

2019 ◽  
Vol 12 (2) ◽  
Author(s):  
Yanuar Alfianto
Keyword(s):  
Production Process ◽  
Failure Mode ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Surface Finishing ◽  
Effect Analysis ◽  
Cold Forming ◽  
Tree Analysis ◽  
Failure Tolerance ◽  
Forming Defects

<p align="center">PT. Garuda Metalindo, which is engaged in the manufacturing industry, is currently experiencing a product failure of 2.5% in the production process and this exceeds the failure tolerance set by the company, which amounts to 10 units of 1000 units per process function or about 1% in the production process. Failure tolerance that exceeds the limit so that improvements need to be made to reduce the number of product defects in each production process. This study uses Fault Tree Analysis (FTA) to identify the causes of product defects based on the current production process, the next stage using Failure Mode and Effect Analysis (FMEA) to identify potential failures, modes, potential effects of failure, causes of failure, detection modes, and determine the rating against severity, occurrence, and detection on the risk priority number in the production process. Based on the results of the assessment on the RPN, a cold forming process with a score of 576, surface finishing with a score of 512 was obtained, machining 1 with a score of 441, and machining 2 with a score of 392. Proposed improvements for cold forming defects by monitoring and making checking tools (jigs), defect surface finishing by supervising and making product shelves, machining defects 1 with product inspection and making tools for checking (jig), and replacement of drill bit types, machining defects 2 with lamp and insert replacement and periodic inspection. By applying these proposals it is expected to reduce the level of product disability.</p>

Detection of Known Items in Adaptive Testing with a Statistical Quality Control Method

2000 ◽  
Vol 25 (4) ◽  
pp. 373-389 ◽  
Author(s):  
Wim J. J. Veerkamp ◽  
Cees A. W. Glas
Keyword(s):  
Quality Control ◽  
Control Method ◽  
Adaptive Testing ◽  
Item Parameter ◽  
Statistical Quality Control ◽  
Simulation Studies ◽  
Statistical Quality ◽  
Quality Control Method ◽  
Item Parameters ◽  
Parameter Values

Due to previous exposure of items in adaptive testing, items may become known to a substantial portion of examinees. A disclosed item is bound to show drift in the item parameter values. In this paper it is suggested to use a statistical quality control method for the detection of known items. The method is worked out in detail for the 1-PL and 3-PL models. Adaptive test data are used to re-estimate the item parameters, and these estimates are used in a test of parameter drift. The method is illustrated in a number of simulation studies, including a power study.

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