1) The project aimed to improve the direct pass ratio of castings produced by SUPPLIER for CUSTOMER from 0% to acceptable standards over 2 years.
2) Initial analyses found major casting defects and non-conformances due to issues like casting defects, poor mechanical properties, dimensions, and quality control processes.
3) Actions taken included establishing quality systems, control plans, process FMEAs, improving raw material combinations, training, and establishing testing standards.
4) Results showed significant improvement over 8 quarters from 17.65% to 93.36% direct pass ratio, with over 15,000 metric tons of acceptable castings produced after the project.
Copper manufacturing process
Content
What is copper
History of copper
General property of copper
Physical properties of copper
Manufacturing process of copper
Application of copper
This above all content are available in this presentation
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Copper manufacturing process
Content
What is copper
History of copper
General property of copper
Physical properties of copper
Manufacturing process of copper
Application of copper
This above all content are available in this presentation
Proceso de cianuración de oro y los factores mas importantes que intervienen ...Raúl Gutiérrez
Estudio enfocado al proceso de la lixiviación de oro con el cianuro de sodio y los factores que afectan en el proceso (densidad de pulpa, concentración de cianuro de sodio). Un estudio muy interesante para aquellos que se enrumban en el mundo minero.
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Presentation on a solidification defect in billets. After a characterization of the defect and a discussion on the mechanism for its formation, preventive measures are analysed, taking into account several plant experiences. The evolution of the defect during rolling and further processing and application is reviewed, too.
Contenido
-Propiedades de la Plata:
-Cianuración:
Ag2S + 4 KCN → K2S + 2 KAg(CN)2
-Recuperación-Refinación por Lixiviación.
-Diagrama de Flujo de Lixiviación en montón.
Visitanos en http://apuntesdeingenieriaquimica.blogspot.mx/
Baja terdiri dari unsur-unsur paduan yang memerikan sifat-sifat yang berbeda dari setiap unsurnya. Berikut daftar dari unsur-unsur pembentuk baja beserta fungsi-fungsinya.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
The iron ore production has significantly expanded in recent years, owing to increasing steel demands in developing countries.
However, the content of iron in ore deposits has deteriorated and low-grade iron ore has been processed.
The fine ores resulting from the concentration process must be agglomerated for use in iron and steelmaking.
Bentonite is the most used binder due to favorable mechanical and metallurgical pellet properties, but it contains impurities especially silica and alumina.
Better quality wet, dry, preheated, and fired pellets can be produced with combined binders, such as organic and inorganic salts, when compared with bentonite-bonded pellets.
While organic binders provide sufficient wet and dry pellet strengths, inorganic salts provide the required preheated and fired pellet strengths.
Contenido
-Propiedades de la Plata:
-Cianuración:
Ag2S + 4 KCN → K2S + 2 KAg(CN)2
-Recuperación-Refinación por Lixiviación.
-Diagrama de Flujo de Lixiviación en montón.
Visitanos en http://apuntesdeingenieriaquimica.blogspot.mx/
Baja terdiri dari unsur-unsur paduan yang memerikan sifat-sifat yang berbeda dari setiap unsurnya. Berikut daftar dari unsur-unsur pembentuk baja beserta fungsi-fungsinya.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
The iron ore production has significantly expanded in recent years, owing to increasing steel demands in developing countries.
However, the content of iron in ore deposits has deteriorated and low-grade iron ore has been processed.
The fine ores resulting from the concentration process must be agglomerated for use in iron and steelmaking.
Bentonite is the most used binder due to favorable mechanical and metallurgical pellet properties, but it contains impurities especially silica and alumina.
Better quality wet, dry, preheated, and fired pellets can be produced with combined binders, such as organic and inorganic salts, when compared with bentonite-bonded pellets.
While organic binders provide sufficient wet and dry pellet strengths, inorganic salts provide the required preheated and fired pellet strengths.
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A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
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People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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https://alandix.com/academic/papers/synergy2024-epistemic/
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https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
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Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
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Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Communications Mining Series - Zero to Hero - Session 1
Casting manufacturing process improvement
1. Casting Direct Pass Ratio
Improvement
(Macro Report)
At SUPPLIER – India
Duration Jan-2009 to Mar-2011
Project Leader – Abdullah Ansari (ASQ CSSBB)
Team members – Seenivasa Ragavan
Senthil Nathan
Chirag Panchal
Vicky Dongade
Dhaval Vyas
2. Background
• Involvement
– In Dec-2008 CUSTOMER Supplier Quality received information that
SUPPLIER has started manufacturing castings for CUSTOMER
– CUSTOMER SQM got involved for routine inspections and setting up
system for material clearance from SUPPLIER to CUSTOMER
– 2 member team Abdullah Ansari & another member visited SUPPLIER
in Dec-2008 for system assessment & inspections.
3. Castings produced in first phase and status in nutshell
0
20
40
60
80
Qty
Produced 26 18 60 13 2 10 12
Rejected 26 18 60 13 2 10 12
Yet to be checked 0 0 0 0 0 0 0
2.1 MW
Main Beam
2.1MW
Main Beam
2.1MW
Cross
2.1MW Hub
body
2.1MW
Main Frame
1.5 Main
Beam
1.5 Cross
Beam
Major Reasons for non-
acceptance
Casting Defects
Dross
Porosities
Blow holes
Failed in Mechanical
properties
Visual
Poor surface
Mismatch
Dimensions
Casting Acceptance – Pre Project Status
For castings produced in First phase
prior to 31 Dec 2008
Direct Pass Ratio – ZERO 0%
4. Define: Project Kick-off
• Project Scope
– To participate with Team of SUPPLIER in developing fully finished
casting components for CUSTOMER WTGs
– Castings acceptable to global standards such as EN1563, EN12680 etc
• Team
– Abdullah Ansari – Project Leader CSSBB-ASQ & SPOC from CUSTOMER
– Seenivasa Ragavan – SUPPLIER QA Head
– Senthil Nathan – NDT Expert
– R. Subramanian – Inspection & Testing
– Chirag Panchal – Analyst
– Vicky Dongade – Analyst
– Dhaval Vyas – Analyst
5. Define: Strategic Planning
• Component Prioritization
– Hub body & Main Frames are heavy section castings, CUSTOMER running
short of supplies – Priority with Average weight per piece 12MT
– Small castings such as main beam, cross beams analyzed thru make or buy
matrix. Found suitable to be bought from other source than SUPPLIER
• Core Tool
– Plan – Do – Check – Act (PDCA) at each stage
– Various tools as per applicability e.g. Pareto, trend chart, FMEA, CE matrix
• Key Measurement
– Direct pass Ratio wrt to Inspected
– Why Direct pass Ratio only to be measured?
• Direct indicator of acceptance/scrap
• Gives indication of process & action effectiveness
• Doesn’t count parts accepted under deviation
• Triggers prioritization & further detailing on which part/defects actions to be
initiated.
6. Define: Generic Process Flow
Pattern & core
box
Raw Material
Receipt
Molding Core making
Mold assemblyMelting
Magnesium
Treatment
Pouring
Knockout
Fettling & Shot
blasting
Destructive &
Preliminary
NDT
Machining &
Inspection
Non
Destructive
Testing
Surface
preparation &
Coating
Coating
Inspection
Packing &
Forwarding
7. Measure & analyze
• Old Casting Data
– Old castings rejected for multiple defects are around 141nos
– Now prioritized castings are Main Frame & hub body, amount to 13
Nos out of 141nos.
– Castings were mainly rejected because of
• Failed in tensile
• Failed in impact
• Failed in Nodularity
• Failed in visual acceptance
• Failed in Ultrasonic inspection
• Failed in Magnetic particle inspection
• Failed in as cast dimensions
• Failed in Machined dimensions
8. Analyze: Casting Process Control
Sr. No Process Stage Key controls Output
1 Receipt Inspection
Receiving inspection of all major raw
material.
Inspected and certified raw material for
production.
2 Sand mixing
Ratio of new/old sand, ratio of resin and
catalyst
Quality sand with required bonding
properties.
3 Core making Ramming to ensure fully filled core. Core without any cracks and damages.
4 Molding Ramming to ensure fully filled core. Mold without any cracks and damages.
5 Mold closing
Alignment of cope and drag by locating pin.
Vent provision for gases
Closed mold ready for pouring without
any damage & with required cavities
6 Melting
C, Si & CE and spectro analysis, Liquid metal
temperature
Liquid metal with required chemistry
ready for Mg treatment
7 Mg treatment Ramming of Mg alloy and covering
Mg treated metal in required quantity and
quality
8 Pouring
Pouring should finish within prescribed
time after treatment, metal temperature
Poured mold
9 Knockout
Cooling time to be maintained for each
item
Casting with runner & risers.
10 Cleaning & Fettling Manual operations Dressed casting, ready for machining.
9. Analyze: Cause & Effect Matrix (Casting)
10 10 10 7 10 8 8 10
1 2 3 4 5 6 7 8
Tensile
Impact
Nodularity
Visual
Ultrasonic
Quality
Magnetic
Particle
Ascast
dimension
MachinedDim.
Total
1 Molding Gating system 8 10 8 8 300
2 Melting & pouring Chemical composition 8 8 8 240
3 Molding Sand mixing ratio 8 8 8 200
4 Melting & pouring Time to pour after Mg treatment 8 10 180
5 Molding Chills 6 8 6 170
6 Melting & pouring Residual Mg 8 8 160
7 Knockout Time to Casting cooling 8 8 160
8 Melting & pouring Deslagging 10 8 150
9 Melting & pouring Pouring temperature 8 8 136
10 Molding Venting 8 6 128
11 Melting & pouring Inoculation 8 6 122
12 Melting & pouring Treatment temperature 8 80
13 Molding Refractory painting 8 56
Rating of Importance to Customer
Sr. No Process InputsProcess Step
11. Improve – Actions Taken (on Casting)
Improvement Need Score Actions Tool To address issue of
Gating system 300
Correction in ingate size,
Runners & Risers
Magma Simulations for mold filling
& solidification
Visual, UT, As cast, Machined
Chemical composition 240 Establishment of charge mix DOE, Regression Tensile, Impact, nodularity
Sand mixing ratio 200 Sand mixing
Control plan for mixing ratio of
sand, resin & hardnere
Visual, As cast, Machined
Time to pour after Mg
treatment
180
Establish time range to be
followed
DOE Impact, Nodularity
Chills 170 Fixing chill positions & sizes
Magma Simulations for mold filling
& solidification
Visual, UT, MPI
Residual Mg 160 Establishment of charge mix DOE, Regression Impact, Nodularity
Time to Casting cooling 160
Establish time range to be
followed
Generic recommendation & trials Tensile, Impact
Deslagging 150
Establish Deslager quality &
training
Supplier development & training Visual, UT
Pouring temperature 136 Establish temperature range Generic recommendation & trials Nodularity,Visual
Venting 128
Correction in ingate size,
Runners & Risers
Magma Simulations for mold filling
& solidification
UT, MPI
Inoculation 122 Establishment of charge mix DOE, Regression Nodularity,Visual
Treatment temperature 80 Establish temperature range Generic recommendation & trials Nodularity
Refractory painting 56 Even coated film on mold Training Visual
12. Improve – Actions Taken Summary (Overall)
Sr Issue Actions for improvement
1 Skill enhancement Establishment of Quality System & training
2 Process Control FMEA, Control plan, Process adherence audits
3 Casting Defects Raw material combinations, Process control
HR On the job trainings, Process redesign
class room trainings on International Standards
4 Machining Explanations on drawing & specifications
5 Corrosion Protection Coating specifications, acceptance criteria, training
6 Packaging Development of specification & prototyping
7 Tracking Establishment of tracking mechanism for each castings
8 Inspection & testing Establish testing laboratory & right practices
14. Take Away of Project - Quality
Supplier ISO certified & Quality culture established
Trained & Skilled human resource
Control parameter establishment thru FMEA
Technical Register for melting
Inspection & test procedures
Lessons learned for defects & causes
Knowledge of errors in testing leading to flaws in acceptance
Process for Corrosion protection & acceptance criteria
Validated Packing guidelines
Tracking mechanism of each individual component
Ongoing measurement of process adherence index
Ongoing measurement of Direct Pass Ratio
All components PPAP completed
15. Take away of Project - Commercial
SUPPLIER 1st Indian Supplier to develop & supply >80% of
CUSTOMER requirements of hub & main frame castings in fully
finished condition
During Project at SUPPLIER, important numbers (Cummulative)
[Average Casting weight considered-12MT]
– Details Qty. Weight %
– Castings Produced : 2653 Nos. 31836 MT 100
– Castings Direct OK : 1859 Nos. 22308 MT 70
– Castings Conc OK : 288 Nos. 3456 MT 11
– Castings Rejected : 506 Nos. 6072 MT 19
Castings direct OK in last quarter of Project – 93.36%
Development at SUPPLIER
– Main Frame & Hub for all CUSTOMER WTG models, Total 4 models
16. Important Numbers
During Project:
Castings Produced :2653 Nos.
Castings Direct OK :1859 Nos.
Castings Conc OK : 288 Nos.
Castings Rejected : 506 Nos.
DPR % @project handover:93.3
4 quarters data after project handover
Castings Produced :1251 Nos.
Castings Direct OK :1102 Nos.
Castings Conc OK : 08 Nos.
Castings Rejected : 42 Nos.
Castings WIP: 99 Nos.
DPR % @ Q4 FY11-12:97.2
Effectiveness of Project
More than 15000 Metric Ton of castings produced after project
with DPR more than 93.3 consistently