Six Sigma Approach for Industrial Quality Improvement and Defect EliminationMd. Injamamul Haque
This slide contains information about a case study of six sigma methodology, DMAIC approach. How to do an analysis, find the root cause and area to be improved through DMAIC methodology, just covered in this slide.
Six Sigma Approach for Industrial Quality Improvement and Defect EliminationMd. Injamamul Haque
This slide contains information about a case study of six sigma methodology, DMAIC approach. How to do an analysis, find the root cause and area to be improved through DMAIC methodology, just covered in this slide.
Fabrics and sewing defects of woven apparel By Engr. Aqs Zilanisaranzilani
In the textile industry, woven fabric is produced by interlacing warp and weft yarn. Faulty woven fabrics hamper the total quality of woven garments such as shirts, pants, trousers, jackets etc.
In order to get the correct appearance and good performance of seams, various considering factors, such as, stitch, seam, feed system, needle, thread, etc. Have to be correctly selected and adjusted. The sewing defects or problems that may arise during sewing, sewing defects such as Problems of stitch formation, Puckering problems, and Fabric defects along the sewing line etc.
It’s My think As a textile engineer-
We should know about the Fabrics and sewing defects of woven apparel produced during woven apparel fabric manufacturing. As its importance, this presentation has shown those Fabrics and sewing defects of woven apparel with their images, Causes and Remedies.
We took two quality control problems from the apparel/textile industry and used 2 classical QC tools to solve one of them, i.e., fishbone diagram and flowchart for the open seam defect, and 2 new QC tools to solve the other one, i.e., tree diagram and affinity diagram for the shade variation defect. We presented a report on the same.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
3. Find out of Problems
1.Selvedges
2.Width Variation
3.Crease Mark
4.Elephant
4. Selvedges
Causes:-
1. Auto Selvedges Guides not proper working
2. Near of Selvedges if any hole
3. Pin more keep
4. Without sewing only knots use
5. Pin out some area
6. Solution:
1. Auto Selvedges need to be properly work
2. All joint properly sewing
3. Manually Adjust selvedges
4. Pinning adjust if out from pin
5. Two person work in operation side
Selvedges
8. Width Variation
Causes:
1. Stenter M/c setup change within one Roll
2. Pin selvedge controller auto not proper work
3. If not proper stitch before stenter m/c
10. Solution:
1. Same setup width Full batch Finish
2. selvedge controller should work auto
3. proper stitch each rolls
4. Stenter m/c running time must be actively work of
Operators
Width Variation
12. Causes:
1. From Padder (If proper not open uncurler Roller)
2. Pin out from stenter m/c
3. If not use leading cloth in time in stenter m/c rather than ropes
4. From Dyeing (If ropes stage dyeing)
5. If edges not proper stitch and knots pass from corino
Crease Mark
14. Solution:
1. Slitting, Stenter & Compacting starting time
reject fabrics Stitch.
2. Operator all time actively follow up
3. Every joint straight sewing.
4. Any Hole Sewing
Crease Mark
18. Solution-
1. Before compactor m/c run then
everything checks.
2. Up to mark feed the over feed.
3. Taplon/ Glass fiber properly set.
Elephant Skin how to solved