During its beta test of TPC 4.2, Insurer reported improved productivity and time-to-value. Enhanced storage resource agents reduced scan run times. New APIs and enhanced topology maps provided an end-to-end view of the environment for better decision making. Real-time monitoring of replication models and role-based access eliminated previously time-consuming manual processes...
1. The document discusses using casting simulation software to increase profitability for foundries. It aims to reduce defects and improve productivity through simulating the casting process.
2. The simulation uses finite difference methods and considers factors like metal composition, mold properties, and solidification parameters to model how the hot metal cools and solidifies.
3. Accurately simulating the casting process can eliminate trial-and-error, reduce defects, and help optimize gating and risering designs to improve yield.
The document discusses modeling thermal management systems in automotive engines. It notes that integrated system simulation is needed because technologies to improve fuel economy may not always work well together. The modeling of engine thermal management is challenging because data is not always readily available and responsibilities are fragmented. The talk will cover overall engine thermal modeling including subsystems for the engine structure, cooling system, front-end cooling pack, cabin, engine oil, and transmission oil. It will also discuss modeling technologies to improve fuel efficiency like stop-start scenarios and dual-use heater cores. The modeling will be integrated with vehicle and control system models and simplified into response surfaces.
The document discusses fuel injection systems, including their objectives of improving power output, fuel efficiency, and emissions performance. It describes the main components of a fuel injector like the injector body and nozzle. Various injection schemes are covered such as single point injection, continuous injection, and direct injection. The advantages of fuel injection systems are better atomization and fuel control, while the disadvantages include higher costs and need for tuning. In conclusion, proper functioning of fuel injectors is important for engine performance.
This document provides an overview of modeling mechanical system interactions using Flowmaster software. It begins with an agenda that includes an overview of Flowmaster, introduction to electro-mechanical components, and case studies on an aircraft hydraulic actuation system and gasoline fuel injection system. The document then discusses Flowmaster's capabilities for analyzing incompressible and compressible fluids, steady state and transient scenarios, and its applications in aerospace, automotive, gas turbine, and oil and gas industries. It provides examples of modeling mechanical-fluid interactions and introduces concepts of fluid transients and pressure waves. Finally, it discusses challenges in modeling mechanical systems such as sizing, survivability, and system interactions.
CSEG provides expertise in collaborating computational fluid dynamics (CFD) tools to improve fluid system design through analysis-led design. Their services include calibrating simulation models with test data, integrating various simulation tools to reduce error and improve accuracy, building simplified interfaces for complex models, and optimizing key variables in systems. The presentation discusses how integrating 1D and 3D physics, leveraging the strengths of each, can make simulations more predictive for initial design. It also notes that further collaboration between fluid, mechanical, and control systems can enable optimization across entire engine systems to improve fuel economy.
This document provides an overview of modeling mechanical system interactions using Flowmaster software. It discusses electro-mechanical components and their modeling capabilities. Examples are given of modeling aircraft hydraulic actuation systems and automotive fuel injection systems. The document also introduces fluid transients and pressure surge analysis. Mechanical system challenges are discussed such as sizing, survivability, and system interactions. Standard hydraulic components like pumps are also introduced.
During its beta test of TPC 4.2, Insurer reported improved productivity and time-to-value. Enhanced storage resource agents reduced scan run times. New APIs and enhanced topology maps provided an end-to-end view of the environment for better decision making. Real-time monitoring of replication models and role-based access eliminated previously time-consuming manual processes...
1. The document discusses using casting simulation software to increase profitability for foundries. It aims to reduce defects and improve productivity through simulating the casting process.
2. The simulation uses finite difference methods and considers factors like metal composition, mold properties, and solidification parameters to model how the hot metal cools and solidifies.
3. Accurately simulating the casting process can eliminate trial-and-error, reduce defects, and help optimize gating and risering designs to improve yield.
The document discusses modeling thermal management systems in automotive engines. It notes that integrated system simulation is needed because technologies to improve fuel economy may not always work well together. The modeling of engine thermal management is challenging because data is not always readily available and responsibilities are fragmented. The talk will cover overall engine thermal modeling including subsystems for the engine structure, cooling system, front-end cooling pack, cabin, engine oil, and transmission oil. It will also discuss modeling technologies to improve fuel efficiency like stop-start scenarios and dual-use heater cores. The modeling will be integrated with vehicle and control system models and simplified into response surfaces.
The document discusses fuel injection systems, including their objectives of improving power output, fuel efficiency, and emissions performance. It describes the main components of a fuel injector like the injector body and nozzle. Various injection schemes are covered such as single point injection, continuous injection, and direct injection. The advantages of fuel injection systems are better atomization and fuel control, while the disadvantages include higher costs and need for tuning. In conclusion, proper functioning of fuel injectors is important for engine performance.
This document provides an overview of modeling mechanical system interactions using Flowmaster software. It begins with an agenda that includes an overview of Flowmaster, introduction to electro-mechanical components, and case studies on an aircraft hydraulic actuation system and gasoline fuel injection system. The document then discusses Flowmaster's capabilities for analyzing incompressible and compressible fluids, steady state and transient scenarios, and its applications in aerospace, automotive, gas turbine, and oil and gas industries. It provides examples of modeling mechanical-fluid interactions and introduces concepts of fluid transients and pressure waves. Finally, it discusses challenges in modeling mechanical systems such as sizing, survivability, and system interactions.
CSEG provides expertise in collaborating computational fluid dynamics (CFD) tools to improve fluid system design through analysis-led design. Their services include calibrating simulation models with test data, integrating various simulation tools to reduce error and improve accuracy, building simplified interfaces for complex models, and optimizing key variables in systems. The presentation discusses how integrating 1D and 3D physics, leveraging the strengths of each, can make simulations more predictive for initial design. It also notes that further collaboration between fluid, mechanical, and control systems can enable optimization across entire engine systems to improve fuel economy.
This document provides an overview of modeling mechanical system interactions using Flowmaster software. It discusses electro-mechanical components and their modeling capabilities. Examples are given of modeling aircraft hydraulic actuation systems and automotive fuel injection systems. The document also introduces fluid transients and pressure surge analysis. Mechanical system challenges are discussed such as sizing, survivability, and system interactions. Standard hydraulic components like pumps are also introduced.
This document analyzes the impact of virtualizing workloads onto servers using different generations of Intel Xeon processors, including the 7500 series. It finds consolidation ratios onto the 7500 series are 2.2-2.8 times higher than the previous generation. For a sample 554 server environment, consolidation onto the 7500 series reduced power consumption by 51% compared to the previous generation. The 7500 series also better balances CPU and memory utilization.
This document proposes a CPQ system for sizing and selecting safety relief valves. The system would generate proposals, price quotes, drawings, bills of materials, and more. It integrates with ERP systems and features attribute-based pricing, multi-level discounting, and support for multiple regions. Modules include sizing calculations, product selection, pricing management, and a rules engine. The system provides benefits like faster quotes, better profitability, and improved engineering data maintenance.
CAE FEA Services from ProSIM Bangalore (Updated 22092022).pptxprosim1
ProSIM is an engineering consulting firm with over 20 years of experience in CAE/FEA and multi-physics simulations. It has a team of over 55 engineers with post-graduate degrees and expertise in CAD, FEA, CFD and optimization across industries like energy, automotive and aerospace. ProSIM has worked with many global companies on simulation projects and has master service agreements with firms like Atlas Copco, Epiroc and GE. It offers services like 3D modeling, finite element analysis, CFD, optimization and material testing to verify designs, optimize performance and solve complex engineering problems for its clients.
An empirical evaluation of cost-based federated SPARQL query Processing EnginesUmair Qudus
Finding a good query plan is key to the optimization of query runtime. This holds in particular for cost-based federation
engines, which make use of cardinality estimations to achieve this goal. A number of studies compare SPARQL federation
engines across different performance metrics, including query runtime, result set completeness and correctness, number of sources
selected and number of requests sent. Albeit informative, these metrics are generic and unable to quantify and evaluate the
accuracy of the cardinality estimators of cost-based federation engines. To thoroughly evaluate cost-based federation engines, the
effect of estimated cardinality errors on the overall query runtime performance must be measured. In this paper, we address this
challenge by presenting novel evaluation metrics targeted at a fine-grained benchmarking of cost-based federated SPARQL query
engines. We evaluate five cost-based federated SPARQL query engines using existing as well as novel evaluation metrics by using
LargeRDFBench queries. Our results provide a detailed analysis of the experimental outcomes that reveal novel insights, useful
for the development of future cost-based federated SPARQL query processing engines.
Key strategies for discrete manufacturers j caie arc japan 2008ARC Advisory Group
Discrete manufacturers face challenges from rapidly increasing resource, material, and energy costs. Key strategies to address these challenges include rethinking manufacturing strategies to focus on relentless cost reduction and optimal resource use. Automation and controls, operations management systems, and digital manufacturing tools can help manufacturers efficiently adapt by enabling cost reductions, optimized designs and processes, and flawless execution. Research communities focused on these areas can help identify best practices and supplier requirements to further aid manufacturers.
The Functional Mockup Interface: FMI overview
Modelica: a very brief overview
A Real-World Example: Active Grill Shutter Controls
Vehicle Thermal Management with Modelica
Continuous Validation of System Requirements
- Intermediate results from ITEA3 MODRIO project
Iterative Controller Development Using Modelica
Conclusions
Today's fast paced product market has shorter lifecycles and tighter budgetary concerns. Tolerance analysis software provides an ideal solution to reduce the number of crucial steps needed to optimize a product at the design step itself. 3DCS Variation Analyst is the world's most used tolerance analysis software that is fully integrated into NX/ CATIA V5/ Creo and CAD Neutral Multi-CAD. 3DCS Variation Analyst is designed to use a consistent format and set of mathematical formulae that create reliable results, enabling engineers to gain a complete insight into their design. The software empowers design engineers to control variation and optimize their designs to account for inherent process and part variation, which in turn reduces non-conformance, scrap, rework and other associated costs.
3DCS Variation Analyst
Used by the world’s leading manufacturing OEM’s to reduce the cost of quality, 3DCS Variation Analyst comes in two flavours:
1) 3DCS Variation Analyst (NX / CAA V5 or Creo Based) is an integrated solution for NX / CATIA V5 or Creo. Since it is an integrated solution, users can not only activate 3DCS workbenches from within the modelling solution, they can use many of its inbuilt functionality to support their modelling.
3DCS Variation Analyst provides three analysis methods:
Monte Carlo Analysis
High-Low-Mean (Sensitivity Analysis) and
Geofactor Analysis (Relationship)
This is a partial preview of the document found here:
https://flevy.com/browse/business-document/Cost-Drivers-Analysis-76
Description:
Competitive Cost Analysis is a valuable strategic business framework, as it helps identify potential areas of competitive advantage. Competitive Cost Analysis requires the analysis of relative cost structures of competitors (or potential competitors) within our industry. The relevant unit of analysis should be as focused and specific as possible—for instance, at the business unit or the product level.
There are three techniques primarily used when conducting Competitive Cost Analysis: Financial Ratios Analysis, Value Chain Analysis, and Cost Drivers Analysis. This document will focus on Cost Drivers Analysis.
Tridiagonal Solutions provides customized engineering solutions and develops products by harnessing computational modeling. It focuses on developing solutions from initial concepts to commercial practices through various stages including CFD modeling, process engineering, pilot plants, and product development. Tridiagonal has expertise in industries like oil/gas, chemicals, pharmaceuticals, power and manufacturing.
The document discusses performance evaluation of computer and telecommunication systems. Performance evaluation aims to quantitatively predict a system's behavior and is used to compare designs, plan for capacity, and debug performance issues. It involves modeling, simulation, and testing approaches of varying cost and accuracy. Key metrics include counts, times, sizes, productivity, response time, and reliability measures. Workload characterization analyzes how systems are used, while benchmarks compare performance across systems running standardized tests.
Proactive performance monitoring with adaptive thresholdsJohn Beresniewicz
Presentation given at UKOUG 2008 conference on the Adaptive Thresholds technology in Oracle database 10.2+ and Enterprise Manager 11. Adaptive Thresholds allows users to do consistent and effective performance monitoring across systems and architectures by using statistical characterization of metric streams to automatically set and adapt monitoring thresholds independent of application workload.
The presentation outlines a methodology of queuing model-based load testing of large (with thousands users) enterprise applications deployed on premise and in the Cloud
Performance modeling provides important insights for capacity planning and system sizing without costly full-scale testing. While sophisticated mathematical modeling was common in the past, today's complex systems are difficult to model formally and existing tools are outdated. However, minimal modeling with common-sense approximations using metrics like resource usage per transaction and hardware capacity can still be useful. Keeping even informal models in mind helps performance engineers understand systems, but complex systems benefit from documenting models. Reviving the art of performance modeling can add value to modern continuous performance testing approaches.
This document provides an introduction to computer simulation. It begins with defining key concepts like systems, models, simulation, and discrete event simulation. It discusses how simulation is used to imitate the operations of a system by developing a model and evaluating it numerically. The document then covers topics like the process of developing a simulation model, different types of simulation models, components and organization of discrete event simulation models, and time advance mechanisms used in simulation. Finally, it provides an example of simulating a single server queueing system to estimate performance measures like average delay in queue.
The document describes the functionality of a sales configurator for heat exchangers. It allows users to select heat exchanger type and parameters, fluids, materials, and accessories. It then generates a product shortlist, specifications, drawings, pricing, and proposal package. The configurator integrates with other systems and provides analytics and workflow automation to improve the sales process.
What Is Your PLM Challenge - Decrease downtime and minimize production problemsDawn Collins
This document summarizes a 3-part webinar series on PLM challenges. Part 2 focuses on decreasing downtime and minimizing production problems. It describes how King Automation used Siemens' Tecnomatix Process Simulate software to successfully complete a project involving new software, training, and execution of customer requirements. Partnering with Waltonen and Geometric Solutions helped minimize risks and ensure success. The solution allowed King Automation to increase their scope of work, complete more offline, and build strong partner relationships.
Augmenting Machine Learning with Databricks Labs AutoML ToolkitDatabricks
<p>Instead of better understanding and optimizing their machine learning models, data scientists spend a majority of their time training and iterating through different models even in cases where there the data is reliable and clean. Important aspects of creating an ML model include (but are not limited to) data preparation, feature engineering, identifying the correct models, training (and continuing to train) and optimizing their models. This process can be (and often is) laborious and time-consuming.</p><p>In this session, we will explore this process and then show how the AutoML toolkit (from Databricks Labs) can significantly simplify and optimize machine learning. We will demonstrate all of this financial loan risk data with code snippets and notebooks that will be free to download.</p>
Simulating Heterogeneous Resources in CloudLightningCloudLightning
In this presentation, Dr Christos Papadopoulos-Filelis (Democritus University of Thrace, Greece) discusses resource characterisation, simulation tools and the elements of simulation used in CloudLightning.
This presentation was given at the National Conference on Cloud Computing in Dublin City University on 12th April 2016.
This document discusses various metrics that can be used to measure agile processes. It begins by defining what a metric is and explaining common process improvement cycles. It then outlines different categories of metrics including business, process, code, design, testing, and automation metrics. Examples are provided for each category. The document notes that choosing the right metric is important and should encourage desired behavior, be easy to measure, and provide periodic feedback. It emphasizes that both leading and lagging metrics should be considered to measure productivity, predictability, quality, and value.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
This document analyzes the impact of virtualizing workloads onto servers using different generations of Intel Xeon processors, including the 7500 series. It finds consolidation ratios onto the 7500 series are 2.2-2.8 times higher than the previous generation. For a sample 554 server environment, consolidation onto the 7500 series reduced power consumption by 51% compared to the previous generation. The 7500 series also better balances CPU and memory utilization.
This document proposes a CPQ system for sizing and selecting safety relief valves. The system would generate proposals, price quotes, drawings, bills of materials, and more. It integrates with ERP systems and features attribute-based pricing, multi-level discounting, and support for multiple regions. Modules include sizing calculations, product selection, pricing management, and a rules engine. The system provides benefits like faster quotes, better profitability, and improved engineering data maintenance.
CAE FEA Services from ProSIM Bangalore (Updated 22092022).pptxprosim1
ProSIM is an engineering consulting firm with over 20 years of experience in CAE/FEA and multi-physics simulations. It has a team of over 55 engineers with post-graduate degrees and expertise in CAD, FEA, CFD and optimization across industries like energy, automotive and aerospace. ProSIM has worked with many global companies on simulation projects and has master service agreements with firms like Atlas Copco, Epiroc and GE. It offers services like 3D modeling, finite element analysis, CFD, optimization and material testing to verify designs, optimize performance and solve complex engineering problems for its clients.
An empirical evaluation of cost-based federated SPARQL query Processing EnginesUmair Qudus
Finding a good query plan is key to the optimization of query runtime. This holds in particular for cost-based federation
engines, which make use of cardinality estimations to achieve this goal. A number of studies compare SPARQL federation
engines across different performance metrics, including query runtime, result set completeness and correctness, number of sources
selected and number of requests sent. Albeit informative, these metrics are generic and unable to quantify and evaluate the
accuracy of the cardinality estimators of cost-based federation engines. To thoroughly evaluate cost-based federation engines, the
effect of estimated cardinality errors on the overall query runtime performance must be measured. In this paper, we address this
challenge by presenting novel evaluation metrics targeted at a fine-grained benchmarking of cost-based federated SPARQL query
engines. We evaluate five cost-based federated SPARQL query engines using existing as well as novel evaluation metrics by using
LargeRDFBench queries. Our results provide a detailed analysis of the experimental outcomes that reveal novel insights, useful
for the development of future cost-based federated SPARQL query processing engines.
Key strategies for discrete manufacturers j caie arc japan 2008ARC Advisory Group
Discrete manufacturers face challenges from rapidly increasing resource, material, and energy costs. Key strategies to address these challenges include rethinking manufacturing strategies to focus on relentless cost reduction and optimal resource use. Automation and controls, operations management systems, and digital manufacturing tools can help manufacturers efficiently adapt by enabling cost reductions, optimized designs and processes, and flawless execution. Research communities focused on these areas can help identify best practices and supplier requirements to further aid manufacturers.
The Functional Mockup Interface: FMI overview
Modelica: a very brief overview
A Real-World Example: Active Grill Shutter Controls
Vehicle Thermal Management with Modelica
Continuous Validation of System Requirements
- Intermediate results from ITEA3 MODRIO project
Iterative Controller Development Using Modelica
Conclusions
Today's fast paced product market has shorter lifecycles and tighter budgetary concerns. Tolerance analysis software provides an ideal solution to reduce the number of crucial steps needed to optimize a product at the design step itself. 3DCS Variation Analyst is the world's most used tolerance analysis software that is fully integrated into NX/ CATIA V5/ Creo and CAD Neutral Multi-CAD. 3DCS Variation Analyst is designed to use a consistent format and set of mathematical formulae that create reliable results, enabling engineers to gain a complete insight into their design. The software empowers design engineers to control variation and optimize their designs to account for inherent process and part variation, which in turn reduces non-conformance, scrap, rework and other associated costs.
3DCS Variation Analyst
Used by the world’s leading manufacturing OEM’s to reduce the cost of quality, 3DCS Variation Analyst comes in two flavours:
1) 3DCS Variation Analyst (NX / CAA V5 or Creo Based) is an integrated solution for NX / CATIA V5 or Creo. Since it is an integrated solution, users can not only activate 3DCS workbenches from within the modelling solution, they can use many of its inbuilt functionality to support their modelling.
3DCS Variation Analyst provides three analysis methods:
Monte Carlo Analysis
High-Low-Mean (Sensitivity Analysis) and
Geofactor Analysis (Relationship)
This is a partial preview of the document found here:
https://flevy.com/browse/business-document/Cost-Drivers-Analysis-76
Description:
Competitive Cost Analysis is a valuable strategic business framework, as it helps identify potential areas of competitive advantage. Competitive Cost Analysis requires the analysis of relative cost structures of competitors (or potential competitors) within our industry. The relevant unit of analysis should be as focused and specific as possible—for instance, at the business unit or the product level.
There are three techniques primarily used when conducting Competitive Cost Analysis: Financial Ratios Analysis, Value Chain Analysis, and Cost Drivers Analysis. This document will focus on Cost Drivers Analysis.
Tridiagonal Solutions provides customized engineering solutions and develops products by harnessing computational modeling. It focuses on developing solutions from initial concepts to commercial practices through various stages including CFD modeling, process engineering, pilot plants, and product development. Tridiagonal has expertise in industries like oil/gas, chemicals, pharmaceuticals, power and manufacturing.
The document discusses performance evaluation of computer and telecommunication systems. Performance evaluation aims to quantitatively predict a system's behavior and is used to compare designs, plan for capacity, and debug performance issues. It involves modeling, simulation, and testing approaches of varying cost and accuracy. Key metrics include counts, times, sizes, productivity, response time, and reliability measures. Workload characterization analyzes how systems are used, while benchmarks compare performance across systems running standardized tests.
Proactive performance monitoring with adaptive thresholdsJohn Beresniewicz
Presentation given at UKOUG 2008 conference on the Adaptive Thresholds technology in Oracle database 10.2+ and Enterprise Manager 11. Adaptive Thresholds allows users to do consistent and effective performance monitoring across systems and architectures by using statistical characterization of metric streams to automatically set and adapt monitoring thresholds independent of application workload.
The presentation outlines a methodology of queuing model-based load testing of large (with thousands users) enterprise applications deployed on premise and in the Cloud
Performance modeling provides important insights for capacity planning and system sizing without costly full-scale testing. While sophisticated mathematical modeling was common in the past, today's complex systems are difficult to model formally and existing tools are outdated. However, minimal modeling with common-sense approximations using metrics like resource usage per transaction and hardware capacity can still be useful. Keeping even informal models in mind helps performance engineers understand systems, but complex systems benefit from documenting models. Reviving the art of performance modeling can add value to modern continuous performance testing approaches.
This document provides an introduction to computer simulation. It begins with defining key concepts like systems, models, simulation, and discrete event simulation. It discusses how simulation is used to imitate the operations of a system by developing a model and evaluating it numerically. The document then covers topics like the process of developing a simulation model, different types of simulation models, components and organization of discrete event simulation models, and time advance mechanisms used in simulation. Finally, it provides an example of simulating a single server queueing system to estimate performance measures like average delay in queue.
The document describes the functionality of a sales configurator for heat exchangers. It allows users to select heat exchanger type and parameters, fluids, materials, and accessories. It then generates a product shortlist, specifications, drawings, pricing, and proposal package. The configurator integrates with other systems and provides analytics and workflow automation to improve the sales process.
What Is Your PLM Challenge - Decrease downtime and minimize production problemsDawn Collins
This document summarizes a 3-part webinar series on PLM challenges. Part 2 focuses on decreasing downtime and minimizing production problems. It describes how King Automation used Siemens' Tecnomatix Process Simulate software to successfully complete a project involving new software, training, and execution of customer requirements. Partnering with Waltonen and Geometric Solutions helped minimize risks and ensure success. The solution allowed King Automation to increase their scope of work, complete more offline, and build strong partner relationships.
Augmenting Machine Learning with Databricks Labs AutoML ToolkitDatabricks
<p>Instead of better understanding and optimizing their machine learning models, data scientists spend a majority of their time training and iterating through different models even in cases where there the data is reliable and clean. Important aspects of creating an ML model include (but are not limited to) data preparation, feature engineering, identifying the correct models, training (and continuing to train) and optimizing their models. This process can be (and often is) laborious and time-consuming.</p><p>In this session, we will explore this process and then show how the AutoML toolkit (from Databricks Labs) can significantly simplify and optimize machine learning. We will demonstrate all of this financial loan risk data with code snippets and notebooks that will be free to download.</p>
Simulating Heterogeneous Resources in CloudLightningCloudLightning
In this presentation, Dr Christos Papadopoulos-Filelis (Democritus University of Thrace, Greece) discusses resource characterisation, simulation tools and the elements of simulation used in CloudLightning.
This presentation was given at the National Conference on Cloud Computing in Dublin City University on 12th April 2016.
This document discusses various metrics that can be used to measure agile processes. It begins by defining what a metric is and explaining common process improvement cycles. It then outlines different categories of metrics including business, process, code, design, testing, and automation metrics. Examples are provided for each category. The document notes that choosing the right metric is important and should encourage desired behavior, be easy to measure, and provide periodic feedback. It emphasizes that both leading and lagging metrics should be considered to measure productivity, predictability, quality, and value.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
In our second session, we shall learn all about the main features and fundamentals of UiPath Studio that enable us to use the building blocks for any automation project.
📕 Detailed agenda:
Variables and Datatypes
Workflow Layouts
Arguments
Control Flows and Loops
Conditional Statements
💻 Extra training through UiPath Academy:
Variables, Constants, and Arguments in Studio
Control Flow in Studio
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
Getting the Most Out of ScyllaDB Monitoring: ShareChat's TipsScyllaDB
ScyllaDB monitoring provides a lot of useful information. But sometimes it’s not easy to find the root of the problem if something is wrong or even estimate the remaining capacity by the load on the cluster. This talk shares our team's practical tips on: 1) How to find the root of the problem by metrics if ScyllaDB is slow 2) How to interpret the load and plan capacity for the future 3) Compaction strategies and how to choose the right one 4) Important metrics which aren’t available in the default monitoring setup.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
GlobalLogic Java Community Webinar #18 “How to Improve Web Application Perfor...GlobalLogic Ukraine
Під час доповіді відповімо на питання, навіщо потрібно підвищувати продуктивність аплікації і які є найефективніші способи для цього. А також поговоримо про те, що таке кеш, які його види бувають та, основне — як знайти performance bottleneck?
Відео та деталі заходу: https://bit.ly/45tILxj
2. We are a group of experts in simulation
We hire best and the
brightest
Everyone has a LOT
of experience doing
simulation
We are very fast at
what we do (and we
will teach you how
to)
6. “We are focused on delivering product
and don’t have time to
develop our simulation methodologies”
(but we talk about it in every meeting on how we need to
do more simulation)
7. OR
do not
“We are investing in the software, but
have the complete know-
how to get it to do what we want to do.”
(But we will never admit it)
8. OR
“We’d like to do simulation but buying
the right software tools, training and
developing people
seems daunting!”
(So we will continue to test and just claim that simulation
does not work)
9. YOU NEED CSEG.
We don’t sell software. We bring our modeling expertise
and make your CAE software do
advanced stuff.
The stuff you bought the
software to do to begin with.
14. Thermo-Fluid System Analysis
Roadmap
Deliver
• Fuel economy benefits with
effective thermal management
strategy
• Predictive analytical capability
reducing prototype costs
Collaborate
Value
• Provide trade-off across multiple systems (cooling,
Lubrication, AC, transmission, front-end cooling
pack)
• Value-added partnership with customers and
suppliers
Analysis basics in place.
Most companies Troubleshoot and Optimize
are here • Transient behavior of system providing insight
into delivering a robust design
• Optimization of system variables
Ensure accurate system operation
• Flow balancing to ensure all components have
adequate flow
• Evaluate individual component performance
Functionality
15. Specific system modeling capabilities
for automotive customers
Capabilities Benefits
• Calibrated heat • Temperature gradient within the
cooling system to evaluate hot spots
transfer cooling (nucleate boiling etc.)
Evaluate thermal performance of heat
system models
•
exchangers,
• Coolant pump sizing
• Engine warm-up analysis (warm-up
• Transient cooling has significant effect on fuel economy)
system analysis •
•
Engine thermostat characterization,
Evaluate engine coolant system
performance under different drive
cycles and conditions of operation
16. Specific system modeling capabilities
for automotive customers
Capabilities Benefits
• Calibrated lubrication •
•
Ensure sufficient bearing supply pressure,
oil heating characterization,
model • characterize leakage flow through the
valves,
• model potential cavitation through oil
suction lines and cross-drilling lines
• Oil Pump sizing
• Oil Cooler sizing
• Determination of parasitic loads on
engine
Pump pressure ripple modeling (and
• Transient Lubrication
•
their effect in the system)
system modeling
• Water-hammer effect and pressure
pulsation within the lube system
• Warm-up model to be linked to cooling
system for oil sump temperature
determination
• Evaluate engine coolant system
performance under different drive cycles
and conditions of operation
17. Specific system modeling capabilities
for automotive customers
Capabilities Benefits
• Optimization of • Optimization of various parameters in
the engine cooling and lubrication
systems system for cost savings and improved
fuel economy
• Vehicle Engineering • Cooling pack sizing service to
customers (picking the correct heat
exchanger and location of each of the
heat exchangers in the cooling pack –
Heat Exchanger, Charge-air cooler, Oil
cooler, Condenser)
• Fuel Economy • Accurate parasitic load and frictional
calculations loss determination to enable accurate
fuel economy calculations.
18. leapfrog Deliver
You
+ to the bottom-line
CSEG
Collaborate and Integrate
Value
Analysis basics in place.
Most companies Troubleshoot and Optimize
are here
Ensure accurate system operation
Functionality
20. Our Approach
• We focus on the problem, combining the right
tools to provide accurate answers for your simulation
challenge – not the tool any one company is selling. CSEG
maintains licenses for best in class COTS tools providing instant
technical capability expansion to your projects.
System Tools CFD Tools
• Flowmaster* • Ansys Fluent
• Amesim • STAR-CD
• Gamma Technologies
Other
Optimization Tools • Matlab/Simulink
• iSight* • Can integrate your
• ModeFrontier in-house software
with COTS
21. Our Services
1. Calibrate: 2. Integrate:
We integrate various
We build accurate
simulation tools for a
simulation models and
specific problem to
calibrate them with test
reduce error and
data
improve accuracy
4. Optimize: 3. Interface:
We build optimization We build simplified
tools or integrate with interfaces for complex
existing ones to models to enable faster
optimize key variables and wider use of
in the system simulation models
22. Our Deliverables
• Detailed simulation report with simulation results,
inferences, possible design changes, software used,
modeling approach, physics assumptions etc.
• Simulation models (for e.g., Flowmaster models, CFD
models) of the system that was built.
• Training on simulation models and modeling approach
• Recommended process to tackle similar problems in the
future.
• Help you positively identify the right tools for such
problems.
24. LIKE TO FIND Sudhi Uppuluri has over 14 years of
experience in the simulation industry. He
OUT MORE?
worked as a consulting engineer and sales
manager at Flowmaster USA for 8 years
.He has various technical publications on
related subjects in SAE and AIAA journals.
He holds a Masters in Aerospace
Engineering from the University of Illinois
CALL OUR
at Urbana-Champaign and a Certificate
in Strategy and Innovation from the MIT
Sloan School of business.
P.I. Contact:
Sudhi Uppuluri
Principal Investigator
Sudhi.uppuluri@cseg.us
(781) 640 2329
www.cseg.us