Analisis Pengendalian Kualitas Produk Part Housing SUV Menggunakan Metode Statistical Process Control di PT. Y DOI Creative Commons

Nurul Fadhilah,

Jauhari Arifin

Industrika Jurnal Ilmiah Teknik Industri, Journal Year: 2024, Volume and Issue: 8(2), P. 459 - 470

Published: April 29, 2024

In the increasingly advanced world of manufacturing industries, course, companies need to innovate for tighter competition. The role product quality will be very influential get results with good and in accordance standard operating procedures, must carry out control by paying attention level defects order approach zero defects. Therefore, this study aims analyze reduce occurrence defective products provide improvement proposals. method used is Statistical Process Control (SPC) total production SUV Housing Parts as many 34740 units. 4 types were produced, namely Coak Blank 40 units, Overlap 37 Ngecap Scrap 13 Flatness NG 11 factors causing type disability are human factors, machines, materials, environment, methods. Thus, proposals given providing regular training operators, carrying routine machine maintenance, using ear plugs while working, measuring material dimensions, checking materials that enter machine. Based on research conducted, SPC can help identify suggestions or solutions problems occur. Keywords: Defect, Quality Control, Repair,

Language: Английский

Data-driven evolution of water quality models: An in-depth investigation of innovative outlier detection approaches-A case study of Irish Water Quality Index (IEWQI) model DOI Creative Commons
Md Galal Uddin, Azizur Rahman, Firouzeh Taghikhah

et al.

Water Research, Journal Year: 2024, Volume and Issue: 255, P. 121499 - 121499

Published: March 20, 2024

Recently, there has been a significant advancement in the water quality index (WQI) models utilizing data-driven approaches, especially those integrating machine learning and artificial intelligence (ML/AI) technology. Although, several recent studies have revealed that model produced inconsistent results due to data outliers, which significantly impact reliability accuracy. The present study was carried out assess of outliers on recently developed Irish Water Quality Index (IEWQI) model, relies techniques. To author's best knowledge, no systematic framework for evaluating influence such models. For purposes assessing outlier (WQ) this first initiative research introduce comprehensive approach combines with advanced statistical proposed implemented Cork Harbour, Ireland, evaluate IEWQI model's sensitivity input indicators quality. In order detect outlier, utilized two widely used ML techniques, including Isolation Forest (IF) Kernel Density Estimation (KDE) within dataset, predicting WQ without these outliers. validating results, five commonly measures. performance metric (R2) indicates improved slightly (R2 increased from 0.92 0.95) after removing input. But scores were statistically differences among actual values, predictions 95% confidence interval at p < 0.05. uncertainty also contributed <1% final assessment using both datasets (with outliers). addition, all measures indicated techniques provided reliable can be detecting their impacts model. findings reveal although had architecture, they moderate rating schemes' This finding could improve accuracy as well helpful mitigating eclipsing problem. provide evidence how influenced reliability, particularly since confirmed effective accurately despite presence It occur spatio-temporal variability inherent indicators. However, assesses underscores important areas future investigation. These include expanding temporal analysis multi-year data, examining spatial patterns, detection methods. Moreover, it is essential explore real-world revised categories, involve stakeholders management, fine-tune parameters. Analysing across varying resolutions incorporating additional environmental enhance assessment. Consequently, offers valuable insights strengthen robustness provides avenues enhancing its utility broader applications. successfully adopted affect current Harbour only single year data. should tested various domains response terms resolution domain. Nevertheless, recommended conducted adjust or revise schemes investigate practical effects updated categories. potential recommendations adaptability reveals effectiveness applicability more general scenarios.

Language: Английский

Citations

37
Implementation of artificial intelligence approaches in oncology clinical trials: A systematic review DOI

M. SAADY,

Mahmoud Eissa,

Ahmed S. Yacoub

et al.

Artificial Intelligence in Medicine, Journal Year: 2025, Volume and Issue: 161, P. 103066 - 103066

Published: Jan. 18, 2025

Language: Английский

Citations

0
Auditing the clinical usage of deep-learning based organ-at-risk auto-segmentation in radiotherapy DOI Creative Commons

Josh Mason,

Jack Doherty,

Sarah Robinson

et al.

Physics and Imaging in Radiation Oncology, Journal Year: 2025, Volume and Issue: 33, P. 100716 - 100716

Published: Jan. 1, 2025

Language: Английский

Citations

0
Quality control study of cervical cancer interstitial brachytherapy treatment plans using statistical process control DOI
Xiaohong Chen,

Xiangxiang Shi,

Huai‐wen Zhang

et al.

Brachytherapy, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Development and external multicentric validation of a deep learning-based clinical target volume segmentation model for whole-breast radiotherapy DOI Creative Commons
Maria Giulia Ubeira-Gabellini, G. Palazzo,

Martina Mori

et al.

Physics and Imaging in Radiation Oncology, Journal Year: 2025, Volume and Issue: unknown, P. 100749 - 100749

Published: March 1, 2025

Language: Английский

Citations

0
Automated segmentation in planning-CT for breast cancer radiotherapy: A review of recent advances DOI Creative Commons

Zineb Smine,

Sara Poeta,

Alex De Caluwé

et al.

Radiotherapy and Oncology, Journal Year: 2024, Volume and Issue: 202, P. 110615 - 110615

Published: Nov. 1, 2024

Postoperative radiotherapy (RT) has been shown to effectively reduce disease recurrence and mortality in breast cancer (BC) treatment. A critical step the planning workflow is accurate delineation of clinical target volumes (CTV) organs-at-risk (OAR). This literature review evaluates recent advancements deep-learning (DL) atlas-based auto-contouring techniques for CTVs OARs BC planning-CT images RT. It examines their performance regarding geometrical dosimetric accuracy, inter-observer variability, time efficiency. Our findings indicate that both DL- methods generally show comparable across CTVs, with DL slightly outperforming consistency accuracy. Auto-segmentation most achieved robust results segmentation quality planning. However, lymph node levels (LNLs) presented greatest challenge auto-segmentation significant impact on The translation these into practice limited by geometric metrics lack dose evaluation studies. Additionally, algorithms showed diverse structure sets, while training datasets varied size, origin, patient positioning imaging protocols, affecting model sensitivity. Guideline inconsistencies varying definitions ground truth led substantial suggesting a need reliable consensus dataset. Finally, our highlights popularity U-Net architecture. In conclusion, automated contouring proven efficient many breast-CTV, further improvements are necessary LNL delineation, analysis, building.

Language: Английский

Citations

2
Analisis Pengendalian Kualitas Produk Part Housing SUV Menggunakan Metode Statistical Process Control di PT. Y DOI Creative Commons

Nurul Fadhilah,

Jauhari Arifin

Industrika Jurnal Ilmiah Teknik Industri, Journal Year: 2024, Volume and Issue: 8(2), P. 459 - 470

Published: April 29, 2024

In the increasingly advanced world of manufacturing industries, course, companies need to innovate for tighter competition. The role product quality will be very influential get results with good and in accordance standard operating procedures, must carry out control by paying attention level defects order approach zero defects. Therefore, this study aims analyze reduce occurrence defective products provide improvement proposals. method used is Statistical Process Control (SPC) total production SUV Housing Parts as many 34740 units. 4 types were produced, namely Coak Blank 40 units, Overlap 37 Ngecap Scrap 13 Flatness NG 11 factors causing type disability are human factors, machines, materials, environment, methods. Thus, proposals given providing regular training operators, carrying routine machine maintenance, using ear plugs while working, measuring material dimensions, checking materials that enter machine. Based on research conducted, SPC can help identify suggestions or solutions problems occur. Keywords: Defect, Quality Control, Repair,

Language: Английский

Citations

0