A Bayesian Network Based Approach for Root-Cause-Analysis in Manufacturing Process

2007 ◽  
Author(s):  
Satyabrata Pradhan ◽  
Rajveer Singh ◽  
Komal Kachru ◽  
Srinivas Narasimhamurthy
Keyword(s):  
Bayesian Network ◽  
Manufacturing Process ◽  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause

scholarly journals PERBAIKAN PADA FISHBONE DIAGRAM SEBAGAI ROOT CAUSE ANALYSIS TOOL

2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Hari Agung Yuniarto ◽  
Annisa Dewi Akbari ◽  
Nur Aini Masruroh
Keyword(s):  
Bayesian Network ◽  
Root Cause Analysis ◽  
Quality Characteristics ◽  
Analysis Tool ◽  
Machine Method ◽  
Cause Analysis ◽  
Common Cause ◽  
Root Cause ◽  
Fishbone Diagram

<p>Diagram Fishbone (tulang ikan), atau biasa pula disebut ishikawa diagram ataupun cause effect<br />diagram, adalah salah satu dari root cause analysis tools yang paling populer di kalangan praktisi industri<br />untuk melakukan quality improvement mendasarkan pada usaha mengenali akar penyebab terjadinya variasi<br />pada quality characteristics tertentu yang ingin dicapai. Meski telah banyak dipakai di dunia industri,<br />disayangkan tool ini menderita kelemahan karena tidak memfasilitasi analisa korelasi antar potential root<br />causes dari masing-masing kategori yang ada (5M1E - man machine method measurement material<br />environment), selain tentu saja penyajian datanya yang hanya kualitatif. Kelemahan ini diyakini menjadi<br />kontributor utama penyebab kegagalan fishbone diagram dalam mengenali root causes yang berupa sumber<br />variasi common cause dan hanya mampu mengenali yang berasal dari sumber variasi special cause. Bertolak<br />belakang dengan karakteristik special cause variations, common cause variations adalah variasi yang terjadi<br />pada quality characteristics tertentu yang ingin dicapai di mana kemunculannya tidak mudah teridentifikasi<br />dan jikapun berhasil dikenali akan sulit dihilangkan karena sifatnya yang seolah adalah merupakan bagian<br />dari sistem (embedded in a system), cenderung berakar penyebab berupa soft factors serta kemunculannya yang<br />tidak random namun tersamar dalam pola tertentu.<br />Penelitian ini bertujuan melakukan improvement pada kelemahan yang terdapat di fishbone diagram<br />dengan mengadopsi kelebihan yang dimiliki oleh bayesian network agar mampu mengenali root causes yang<br />merupakan common cause variations. Kelebihan bayesian network mengatasi kekurangan fishbone diagram,<br />demikian pula sebaliknya. Oleh karena itu, analisa dilakukan terhadap fishbone diagram dan bayesian network<br />untuk mengenali characteristics dan kelebihan/kekurangannya. Hasil dari analisa tersebut mengarahkan pada<br />sifat-sifat komplementer dari keduanya yang diyakini mampu mengisi gap pada fishbone diagram.<br />Mendasarkan padanya, dikembangkan sebuah model untuk mengintegrasikan konsep serta sifat komplementer<br />yang dimiliki bayesian network dan fishbone diagram. Model ini merepresentasikan metodologi baru dalam<br />root cause analysis, bayes-fishbone. Metodologi yang dikembangkan ini kemudian diujikan ke sebuah case<br />study company untuk melihat applicability-nya.<br />Hasil dari penelitian ini menunjukkan bahwa metodologi bayes-fishbone yang dikembangkan terbukti<br />telah valid mampu merepresentasikan kondisi probabilitas produk cacat sebenarnya pada case study company<br />dengan prosentase perbedaan nilai yang ditunjukkan antara model yang dikembangkan dengan kondisi aktual<br />yang besarnya tidak signifikan yaitu kurang dari 1 % (0,9597%). Dengan menerapkan metode contructive<br />research approach, terbukti pula bahwa metodologi bayes-fishbone berhasil lolos weak-market test yang<br />menunjukkan bahwa metodologi yang dikembangkan applicable pada case study company atau perusahaan lain<br />yang sejenis characteristics dan production process-nya.</p>

Root Cause Analysis of Bend Stiffener Failure During Umbilical Full-Scale Fatigue Testing

2016 ◽  
Author(s):  
Krassimir Doynov ◽  
Evyatar Belson ◽  
Hengliang Yuan ◽  
Rune Haakonsen ◽  
Ying Li ◽  
...  
Keyword(s):  
Heat Generation ◽  
Manufacturing Process ◽  
Fatigue Testing ◽  
Root Cause Analysis ◽  
Steel Tube ◽  
Fatigue Tests ◽  
Full Scale ◽  
Cause Analysis ◽  
Root Cause ◽  
Test Failure

Dynamic bend stiffeners are widely used to prevent overbending and achieve the desired fatigue life of umbilicals and flexible pipes by transferring bending moments locally to support structures on floaters. Full-scale fatigue testing of umbilical and bend stiffener assemblies has been historically used to verify umbilicals’ fatigue performance in test lab conditions. Fatigue tests on steel tube umbilicals are usually conducted by testing the critical steel tube component to failure as detected by pressure drop and leakage. During a full-scale fatigue verification test conducted while executing a deep-water project in the Gulf of Mexico a bend stiffener has failed prior to failing the critical umbilical steel tube. This test failure, which is the first one encountered on projects stewarded by ExxonMobil Development Company (EMDC), manifested itself as inner and outer polyurethane (PU) cracks extending between 3 and 9 o’clock along the bend stiffener circumference at two different locations. A root cause analysis has been performed on the test failure based on the findings of the bend stiffener and umbilical dissections and temperature measurements. Two possible failure scenarios were constructed and investigated via finite element analyses (FEA), component adhesion tests, and thorough re-verification of manufacturing process and procedures. The FEA was instrumental in confirming adequate bend stiffener strength, and the likely failure scenario of PU fatigue failure due to overheating caused by high test-strain levels required to accelerate decades long operational loading into 3-month test loading. The FEA has been performed to bound the temperature distribution inside the bend stiffener based on loading conditions and temperature measurements taken during the test. Sequential structural-thermal analysis approach has been adopted by using quasi-static and steady state analyses. Equivalent strain distribution under fatigue loading was obtained through nonlinear structural analysis, and imported as heat source input in the PU material and the thermal model. Linear relationship between the strain rate and the heat generation rate has been used. The hysteretic heat generation model and heat transfer boundary conditions were calibrated by matching temperature results to thermocouple readings positioned at various locations on both the bend stiffener and umbilical during testing. The resulting temperature distributions showed the temperature at the inner crack had exceeded the temperature limit established via PU dogbone fatigue tests. Manufacturing process and procedures have been re-verified by conducting adhesion tests, quality checks and recoating of steel work. The root cause analysis has concluded that the bend stiffener design is fit for service. Three main development opportunities are suggested for industry’s consideration to cover thermal design for operation and flex testing of bend stiffeners with umbilicals or flexible risers: a) testing methodology to establish PU heat generation with strain rate relationships, b) methodology and tools for coupled thermo-mechanical FEA, and c) non-destructive test methods for detection of coating and PU disbondments of finished products, and temperature measurement and profiling that can be used for FEA methodology and tool validation.

scholarly journals All-inkjet-printed thin-film transistors: manufacturing process reliability by root cause analysis

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Enrico Sowade ◽  
Eloi Ramon ◽  
Kalyan Yoti Mitra ◽  
Carme Martínez-Domingo ◽  
Marta Pedró ◽  
...  
Keyword(s):  
Thin Film ◽  
Manufacturing Process ◽  
Thin Film Transistors ◽  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause ◽  
Process Reliability

Root Cause analysis of SG tube ODSCC indications within the tube sheets of NPP biblis unit A

2011 ◽  
pp. 78-86
Author(s):  
R. Kilian ◽  
J. Beck ◽  
H. Lang ◽  
V. Schneider ◽  
T. Schönherr ◽  
...  
Keyword(s):  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause
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