This webinar is going to cover what is a digital twin and how all stakeholders can benefit from their functionality. You will learn how model-based systems engineering enables digital engineering. Your host will discuss use cases, a realistic look at digital engineering and digital twins, and how you can use Innoslate to get started.
The Agenda
Here's what we're covering.
What is a Digital Twin
Benefits of Digital Twin
The Digital Engineering Path Enabled by MBSE
AR + MBSE Software
A More Realistic Digital Twin
Getting You Started with Digital Twins
Question Answer Session
Industry X.0 - Realizing Digital Value in Industrial Sectorsaccenture
Industry X.0 is a new way for manufacturing to operate. At its heart are highly intelligent, interconnected products and ecosystems that create a fully digital value chain, supplemented by new core innovation competences and deep cultural change. Learn more: https://accntu.re/2wKLK4m
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
Nurturing Digital Twins: How to Build Virtual Instances of Physical Assets to...Cognizant
To embark on the digital twin jounrey, assess your readiness, define and communicate a vision, set common data management rules and build in flexibility for intelligence.
The document discusses digital twins, which are dynamic digital representations of physical assets that allow companies to understand, predict, and optimize asset performance. Digital twins use asset data like sensor readings, events, and models to generate insights about an asset's current context, key performance indicators (KPIs), and future predictions. A digital twin platform is needed to manage digital twins at scale across edge, network and cloud environments and expose twin data and insights via APIs. This allows industrial applications to leverage digital twins without needing direct access to the underlying data and models.
What is the Digital Twin?
Digital twin is the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works. It's more than a blueprint, it's more than a schematic. It's not just a picture. It's a lot more than a pair of ‘virtual reality’ glasses. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.
Watch the video introduction of this keynote presentation from Genius of Things Summit in Munich https://youtu.be/RaOejcczPas
Using MLOps to Bring ML to Production/The Promise of MLOpsWeaveworks
In this final Weave Online User Group of 2019, David Aronchick asks: have you ever struggled with having different environments to build, train and serve ML models, and how to orchestrate between them? While DevOps and GitOps have made huge traction in recent years, many customers struggle to apply these practices to ML workloads. This talk will focus on the ways MLOps has helped to effectively infuse AI into production-grade applications through establishing practices around model reproducibility, validation, versioning/tracking, and safe/compliant deployment. We will also talk about the direction for MLOps as an industry, and how we can use it to move faster, with more stability, than ever before.
The recording of this session is on our YouTube Channel here: https://youtu.be/twsxcwgB0ZQ
Speaker: David Aronchick, Head of Open Source ML Strategy, Microsoft
Bio: David leads Open Source Machine Learning Strategy at Azure. This means he spends most of his time helping humans to convince machines to be smarter. He is only moderately successful at this. Previously, David led product management for Kubernetes at Google, launched GKE, and co-founded the Kubeflow project. David has also worked at Microsoft, Amazon and Chef and co-founded three startups.
Sign up for a free Machine Learning Ops Workshop: http://bit.ly/MLOps_Workshop_List
Weaveworks will cover concepts such as GitOps (operations by pull request), Progressive Delivery (canary, A/B, blue-green), and how to apply those approaches to your machine learning operations to mitigate risk.
What is a Digital Twin? Why is it another point of view of the IoT stack in Azure. Which are the features? How does it relates to IoT Hub and other Azure IoT services?
The breath and depth of Azure products that fall under the AI and ML umbrella can be difficult to follow. In this presentation I’ll first define exactly what AI, ML, and deep learning is, and then go over the various Microsoft AI and ML products and their use cases.
AI for Manufacturing (Machine Vision, Edge AI, Federated Learning)byteLAKE
Artificial intelligence and machine learning technologies are transforming key industries like manufacturing, finance, retail, and healthcare. Edge computing and federated learning are emerging approaches that can help address challenges around data privacy, bandwidth constraints, and latency. Edge AI runs optimized models directly on devices to analyze data and only send results rather than raw data. Federated learning leverages local AI models across edge devices to improve performance while keeping sensitive data private. Together these approaches help make AI more scalable, responsive and privacy-preserving for industries.
Introdution to Dataops and AIOps (or MLOps)Adrien Blind
This presentation introduces the audience to the DataOps and AIOps practices. It deals with organizational & tech aspects, and provide hints to start you data journey.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
Cognitive Digital Twin by Fariz SaračevićBosnia Agile
Data are driving the world today and they are becoming world's precious currency. Continuous Engineering, the default set of applications for enterprise software development, produce a wealth of data but it is hard to understand its value. What if you could find hidden patterns in your data your development teams create? What if you could discover ways to improve your team's performance? This presentation reviewed some of the different ways the Collaborative Lifecycle Management team (http://jazz.net) is utilizing Watson Analytics to gain insights into and improve efficiency with their own processes.
The document discusses Siemens Digital Industries Software, which provides industrial software and automation solutions. It notes that Siemens is the #1 provider of industrial software and automation in the world. It highlights the company's focus on digital transformation and creating comprehensive digital twins to optimize performance for customers across industries like manufacturing, electronics, and energy. The document also outlines Siemens' strategy to transition software offerings to cloud-based SaaS models and build out its Xcelerator integrated development platform.
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Digital Twin refers to a physical and functional description of a component, product or system together with all available operational data. This includes all information which could be useful in current and subsequent lifecycle phases. Benefit of it for mechatronic and cyber-physical systems is to provide the information created during design and engineering also at the operation of the system. The comprehensive networking of all information, shared between partners and connecting design, production and usage, forms the presented paradigm of next generation Digital Twin.
Digital Twin refers to a physical and functional description of a component, product or system together with all available operational data. This includes all information which could be useful in current and subsequent lifecycle phases. Benefit of it for mechatronic and cyber-physical systems is to provide the information created during design and engineering also at the operation of the system. The comprehensive networking of all information, shared between partners and connecting design, production and usage, forms the presented paradigm of next generation Digital Twin.
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
Digital twin technology creates a digital replica of a physical object or system that can be used to gather data, understand past and current behavior, and predict future performance. The digital twin is made possible by sensors that collect data from physical assets and IoT technology. The document discusses the history and development of digital twin technology, how it is used across various industries like manufacturing, healthcare, and aerospace to optimize operations and reduce costs, and the future potential of digital twins including using them to make decisions and interact after death.
This guide will help you get started with Innoslate, the full lifecycle systems engineering tool. It will take you through developing your requirements, creating model, simulating your models, and keeping traceability through the entire project.
- Innoslate is a cloud-native, model-based systems engineering software that supports requirements management, modeling, simulation, and verification and validation.
- It aims to improve upon traditional systems engineering tools by offering easier usability, integrated simulation capabilities, lifecycle management support, and real-time collaboration features.
- Key capabilities include real-time collaboration, discrete event and Monte Carlo simulation integrated with models, scalability tested up to millions of entities and thousands of users, and full lifecycle management across requirements, modeling, testing and documentation.
Product Lifecycle Management (PLM) has many definitions, but do they really look at all the needs across the lifecycle? Are the commonly listed domains (Systems Engineering, Program Management, Product Design, Process Management for Manufacturing and Product Data Management) enough? This webinar helps define PLM in more depth and applies model-based systems engineering (MBSE) techniques and tools to show how to improve your PLM practice. It will include a demonstration of how Innoslate meets and exceeds the requirements for a PLM tool.
GreenSocs virtual platforms allow designing, developing, and testing embedded applications as a whole system by modeling both hardware and software together. This enables sizing hardware to match software needs, integrating development, and efficiently debugging and verifying designs. GreenSocs provides integrated virtual platform solutions using open standards like SystemC TLM 2.0. They have expertise in CPU modeling through contributions to QEMU and Gem5, and provide infrastructure libraries, models, and services to help customers develop virtual prototypes.
Closing the Design Cycle Loop with Executable Requirements and OSLC - IBM Int...Modelon
Motivation: Systems Engineering and Modeling and Simulation need to converge
Open Standards we build on: Modelica, FMI, OSLC, SySML
An Ideal Process to Integrate Systems Engineering with Model Based Design
Continuous Integration to Close the Loop for Rapid Design Iterations
First Steps to Automate Requirements Formalization
Call to Action
Presentazione dello speech tenuto da Carmine Spagnuolo (Postdoctoral Research Fellow - Università degli Studi di Salerno/ ACT OR) dal titolo "Technology insights: Decision Science Platform", durante il Decision Science Forum 2019, il più importante evento italiano sulla Scienza delle Decisioni.
Deploying ML models in production, with or without CI/CD, is significantly more complicated than deploying traditional applications. That is mainly because ML models do not just consist of the code used for their training, but they also depend on the data they are trained on and on the supporting code. Monitoring ML models also adds additional complexity beyond what is usually done for traditional applications. This talk will cover these problems and best practices for solving them, with special focus on how it's done on the Databricks platform.
The Internet of Simulations and the agile development of Cyber-physical systemsSimware
Presentation made in the 2017 IEEE System of Systems conference. Co-authored by Stephen Clement, David McKee, Richard Romano and Jie Xu (University of Leeds), Jose-Maria Lopez (Simware Solutions) and David Battersby (Jaguar Land Rover)
This document outlines a proposed systematic architecture design (SAD) framework that aims to integrate non-functional requirements (NFRs) into model-driven development (MDD) processes. It presents a motivation example comparing two travel agency systems with different NFRs. It then proposes an NFR-aware MDD process with either automatic or interactive variants. The SAD contributions include tools like ArchiTech and an ontology-based knowledge system called Arteon. Future work includes further implementing and validating parts of the proposed framework through empirical studies.
The document discusses software engineering and the Unified Software Development Process (USDP). It describes the USDP which includes phases of inception, elaboration, construction, and transition. Each phase involves iterations where requirements, analysis, design, implementation, and testing are done. The goal of each iteration is to produce an executable increment that is tested and evaluated.
As data science workloads grow, so does their need for infrastructure. But, is it fair to ask data scientists to also become infrastructure experts? If not the data scientists, then, who is responsible for spinning up and managing data science infrastructure? This talk will address the context in which ML infrastructure is emerging, walk through two examples of ML infrastructure tools for launching hyperparameter optimization jobs, and end with some thoughts for building better tools in the future.
Originally given as a talk at the PyData Ann Arbor meetup (https://www.meetup.com/PyData-Ann-Arbor/events/260380989/)
This document provides an overview of software engineering. It discusses what software engineering is, common software development process models like waterfall, spiral, agile development, and the Unified Software Development Process (USDP). The USDP follows an iterative approach with phases for inception, elaboration, construction, and transition. Each phase has milestones and the process involves iterations where requirements, design, coding, and testing are done to create executable increments.
Incquery Suite Models 2020 Conference by István Ráth, CEO of IncQuery LabsIncQuery Labs
This document discusses how IncQuery Suite can be used to analyze digital threads in model-based systems engineering (MBSE) projects. It provides an overview of IncQuery Suite's features for efficiently extracting and analyzing engineering data across proprietary tools, validating documents and projects, performing graph queries and full-text search, and integrating with various tools. The document also presents two case studies, one involving integrating IncQuery Suite with Airbus's application platform to enable data continuity, and another using IncQuery Suite to provide model checking as a service for SysML models.
The document introduces an evolutionary event-driven architecture called the Enterprise Digital Transformation Platform (EDTP) for accelerating digital transformation. The EDTP is a 4-tier platform based on cloud, containers, microservices, events and streaming. It addresses challenges of data integration and decoupling through architectural concepts like event-driven design, microservices and templates. The EDTP provides full-stack deployment automation and microservice templating to accelerate development. Use cases from Toyota Financial Services are presented to demonstrate the EDTP's capabilities.
The document summarizes the emergence and evolution of software engineering approaches from the 1950s to modern times. It describes early exploratory programming using assembly languages. It then discusses the introduction of high-level languages and increased focus on control flow-based design. Subsequently, the complexity of software led to data-flow oriented design using data flow diagrams. Object oriented design revolutionized the field by enabling reuse through concepts like encapsulation and inheritance. Finally, it briefly outlines evolutionary, RAD, spiral models for iterative development.
This document discusses key concepts in software engineering and architecture. It covers the definition of software engineering as a systematic approach to software development, operation, and maintenance. It also discusses software development lifecycles like waterfall, incremental, prototyping and agile models. Additionally, it summarizes different types of architectures like enterprise, business, solution, technical and infrastructure architectures. Finally, it provides an overview of service-oriented architecture (SOA) principles and components.
Building a Scalable and reliable open source ML Platform with MLFlowGoDataDriven
This document discusses building a scalable and open source machine learning platform. It introduces MLOps and describes ING's ML batch platform use case. The machine learning lifecycle is presented, noting that operationalizing machine learning models is difficult due to infrastructure deployment challenges, lack of collaboration and standardization. An ideal MLOps approach is described with flexible, scalable, automated and standardized processes. Benefits of ING's MLOps approach include increased efficiency, speed, quality, security and auditability. Open source tools that could be leveraged are also presented.
The document discusses cyber-physical systems and the role of architecture description languages. It covers topics like heterogeneous systems, design challenges and possibilities, and examples. Architecture description languages play a key role by enabling abstraction and modeling of complex CPS, allowing exploration of design alternatives, and serving as standardized documentation. Some challenges of CPS design include interdisciplinary collaboration, security, scalability, and meeting real-time constraints.
Join us on Wednesday, October 19th, for our webinar, "What Comes After MBSE?" SPEC Innovations President and Founder, Dr. Steven Dam, will discuss the future of our industry. Since 2007, the focus has been moving from document-based systems engineering to model-based systems engineering (MBSE). With our ever-changing industry and the update to SysML V2, we believe there will be a massive move toward more data-driven systems engineering.
Dr. Dam will dive deeper into the past and present of Systems Engineering, and how this will take us into the future of Data-Driven Systems Engineering. He will share how SPEC Innovations is currently moving into this trend using Innoslate and its power of migration. There will be a time in the end for questions, so bring any you may have with you.
We know change can be intimidating. The coming release of SysML V2 can seem intimidating, as it is a product of 70 organizations and 170 people collaborating. Join us for our next webinar, “Dissecting SysML V2,” with Systems Engineer, Lilleigh Stevie. We will look closely at the next generation of OMG’s modeling language by covering its background, purpose and objectives, KerML, familiar and new concepts, pilot implementation, and where this will take us in the future. There will be a designated time at the end for questions, so bring any you may have with you. Register today and we will see you there!
Does your product or system meet the requirements? Find out in this webinar. Your host will discuss a verification and validation process that has worked for hundreds of our clients to answer this question. Then you will learn how to use a model-based systems engineering tool, Innoslate, to develop your own V&V process document. Then your host will dive into Test Center. Test Center allows for easy test case capture and traceability to requirements and provides the ability to run test cases within one easy-to-use view.
This webinar will cover:
1. V&V process
2. Test Center
3. Documents View
4. Traceability Matrix
Watch recording here: https://www.youtube.com/watch?v=3h9BYZv54s4
Throughout the lifecycle, you will be performing a configuration management process. A configuration management process should store, track, and update all data related to the system or product. The key to configuration management is taking a data-driven approach. This in turn will reduce your lifecycle’s overall risk and increase maintainability. Your host will go over a quick summary of configuration management before diving into how you can do this in the model-based systems engineering tool, Innoslate.
• Importing configuration management guidelines developing
• Using Workflows for Configuration Management
• Baselining documents
• Changing reports with Innoslate’s data history feature
• Implementing Model-Based Reviews
• Managing complex data
How to Develop and Simulate Models with No Coding ExperienceElizabeth Steiner
The document summarizes a webinar on how to develop and simulate models with no coding experience. It discusses using functional analysis and risk analysis to derive requirements. It also describes how to add cost elements and human factors to simulations in Innoslate and Sopatra. The webinar demonstrates building action diagrams to model functionality and linking models to other tools like MATLAB and STK for co-simulation.
SPEC Innovations is starting its “How To MBSE” series this February 17th at 11:00 am ET. The series will begin with “How to Write Requirements.” Your host, Dr. Steven Dam, will discuss:
1. Gathering your requirements
2. Baselining and change management
3. Using AI to manage quality in your requirements
4. Checking for risk in your requirements
5. Adding relationships (traced, verified, and satisfied)
6. Creating reports and matrices
This webinar is perfect if you are just learning to write requirements or are a seasoned requirements developer and want to learn how to utilize software tools and artificial intelligence to improve your requirements. Either way, you will learn a lot in this 45-minute webinar. Stay for the Q&A to ask Dr. Dam your questions.
The “How to MBSE” series will continue with these webinars:
March 24th 2022, 11:00 am ET - “How to Develop and Simulate Models (with no coding experience!)”
https://attendee.gotowebinar.com/register/4521555073189509390
April 13, 2022, 11:00 am ET - “How to Perform Configuration Management”
May 26, 2022, 11:00 am ET – “How to Verify and Validate a System or Process”
June 21, 2022, 11:00 am ET - “How to Develop a Program Management Plan”
The document summarizes a demonstration of a digital thread for engineering a lunar rover prototype using Innoslate's systems engineering tools. It describes 4 tasks: research and design, building the prototype, testing it, and demonstrating the digital thread. Key activities included designing the rover, 3D printing components, assembling the prototype called SPECTER, simulating its mission in STK and MATLAB, and validating it meets requirements. The digital thread integrated models, documents, simulations, code, and tests to engineer a prototype lunar rover from concept to testing.
Innoslate, a model-based systems engineering solution, was developed in 2013 and is used by thousands of engineers, analysts, and program managers today. We’re now making another major feature release with Innoslate 4.5. Innoslate users can now utilize project management features such as Kanban boards, branching and forking, calendar, and timeline diagrams!
Did we mention, this fall we’re also releasing a brand new MBSE tool specifically designed for Standard Operating Procedures? That’s right, Sopatra, uses Natural Language Processing to turn SOP text into executable models. Learn how you can reduce cost and risk, while increasing the success of your operations by using Sopatra’s unique algorithms.
Watch the presentation here: https://www.youtube.com/watch?v=lw-ge_ZHo6s
A Model-Based Systems Engineering Approach to Portfolio ManagementElizabeth Steiner
Learn about the importance of The Lifecycle Modeling Language (LML) to portfolio management. LML provides an open standard ontology and diagram framework that enables more effective communications to all stakeholders in the acquisition process.
Innoslate® implements and extends LML making Innoslate easier to learn and adopt than any other tool available today in the program management and systems engineering domains. You will also learn how Innoslate is built on a modular open systems approach (MOSA) architecture and can be easily integrated with other modern tools. This webinar will also include a sneak preview of Innoslate 4.5's program management features.
This document provides an overview of a webinar on using Innoslate for requirements management. The webinar agenda includes where requirements come from, what makes a good requirement, the difference between requirements management and analysis, and a live demonstration of Innoslate's features to support requirements analysts and managers. Key Innoslate features that support requirements management and analysis are highlighted.
See the major new features and improvements in Innoslate 4.3. The latest version of Innoslate has two brand new diagrams Interface Control Diagram (ICD) and a Risk Burndown Chart. You asked and we delivered; a ReqIF Import and Export. We've also added that Cross Project Entities will be visual noticeable in all views with a new purple symbol indicator, dashed purple lines, or purple background color. Now search has been redesigned for a more flexible user experience. All entity’s attributes can now be searched as well as searching by entity id, relationship name, and attribute name. Dr. Dam will demonstrate best practices for using all the new diagrams, features, and even some of the improvements. Stay for the question and answer session to ask any or all your questions. We look forward to having you there!
This is a perfect webinar for professors and students of systems engineering seeking to improve their academic research and professional expertise.
SPEC Innovations is dedicated to advancing the systems engineering academic community. Our engineers designed Innoslate to improve academic research and help professors expand model-based systems engineering to a new generation of students. See what benefits you have using Innoslate for Aacademia with this webinar.
Take a trip into the history and future of systems engineering to better understand how we can improve the discipline.
Your host, Dr. Steve Dam, discusses where systems engineering came from and where it is going. He includes discussions on how:
- complexity has changed our methodology
- systems engineering languages have evolved
- technology improvements enable better systems engineering
Using Innoslate for Model-Based Systems EngineeringElizabeth Steiner
Dr. Steve Dam will walk you through the process of using Innoslate’s modeling and simulation capabilities while applying a MBSE methodology.
At its core, Innoslate is a full model-based systems engineering tool. Within Innoslate, system models are formalized and capable of simulation to derive cost, schedule, and performance data.
Your webinar will cover:
Functional modeling
Functional modeling is at the heart of how Innoslate derives new requirements and ensures logical accuracy.
Physical modeling
We can describe synthesizing the physical model in Innoslate with eight different diagrams, including the Asset Diagram, Layer Diagram, Block Definition Diagram, and Internal Block Diagram.
Executing a model
Innoslate includes a ‘Discrete Event Simulator’ to verify functional diagram’s logic, calculate cost, compute time, and quantify performance.
Relating Requirements to Diagrams
Requirements traceability ensures that the lifecycle and origin of a requirement is fully tracked. Innoslate includes relationship matrices to represent traceability relationships between entities in tabular view.
Requirements Generation
After modeling the system, often an engineer will derive textual requirements from the models by hand. Innoslate includes an automatic facility that generates requirements documents in a standard format (as outlined in “The Engineering Design of Systems: Models and Methods“).
Learn how you can use Innoslate throughout the entire lifecycle of a product or system. Dr. Steven Dam, expert systems engineer, will discuss the different phases of the lifecycle from conception to disposal. He'll show you how you can use Innoslate for requirements management, modeling, simulation, and testing.
Improve Product Design with High Quality RequirementsElizabeth Steiner
The webinar discussed improving product design through high quality requirements. It emphasized the importance of understanding stakeholders, determining real needs through concept of operations documents, writing specific but not overly specific requirements, including traceability, and using tools to automatically check requirements quality. The presenter demonstrated Innoslate's requirements management tools.
Everyone talks about "data-centricity," but what does that mean in practical terms. It means that you have to have a well defined ontology that can capture the information needed to describe the architecture or system you work with or want to create. An ontology is simply the taxonomy of entity classes (bins of information) and how those classes are related to each other. In this webinar, we will discuss a relatively new ontology, the Lifecycle Modeling Language (LML). LML provides the basis for Innoslate's database schema. In this webinar, we will discuss each entity class and why it was developed. Dr. Steven Dam, who is the Secretary of the LML Steering Committee, will present the details of the language and how it relates to other ontologies/languages, such as the DoDAF MetaModel 2.0 and SysML. He will also discuss the ways to visualize this information to enhance understanding of the information and how to use that information to make decisions about the architecture or system.
This document discusses verification and validation (V&V) and developing a V&V plan using model-based systems engineering. It explains that V&V activities should occur early in the lifecycle during requirements analysis and system design. It also discusses preparing for V&V by developing an ontology, defining verifiable requirements, and creating a V&V plan. The document shows how the LML schema can be extended to support V&V and describes characteristics of good requirements that make them verifiable. Finally, it demonstrates how to develop a test plan and test cases using MBSE and simulate test execution.
Innoslate is a full lifecycle systems engineering tool that provides you with the capability to perform requirements analysis, functional and physical modeling, simulation, testing, and more all in one place.
Requirements Analysis and Management using InnoslateElizabeth Steiner
his one hour webinar will give you a step by step approach to Requirements Management and Analysis. A systems engineer will lead you through all the features in Innoslate that implement Requirements Management and Analysis.
What will be covered?
Capturing requirements using the automated parser
Writing requirements
Checking quality of requirements
Tracing requirements to other model entities
Baselining requirements
Social media management system project report.pdfKamal Acharya
The project "Social Media Platform in Object-Oriented Modeling" aims to design
and model a robust and scalable social media platform using object-oriented
modeling principles. In the age of digital communication, social media platforms
have become indispensable for connecting people, sharing content, and fostering
online communities. However, their complex nature requires meticulous planning
and organization.This project addresses the challenge of creating a feature-rich and
user-friendly social media platform by applying key object-oriented modeling
concepts. It entails the identification and definition of essential objects such as
"User," "Post," "Comment," and "Notification," each encapsulating specific
attributes and behaviors. Relationships between these objects, such as friendships,
content interactions, and notifications, are meticulously established.The project
emphasizes encapsulation to maintain data integrity, inheritance for shared behaviors
among objects, and polymorphism for flexible content handling. Use case diagrams
depict user interactions, while sequence diagrams showcase the flow of interactions
during critical scenarios. Class diagrams provide an overarching view of the system's
architecture, including classes, attributes, and methods .By undertaking this project,
we aim to create a modular, maintainable, and user-centric social media platform that
adheres to best practices in object-oriented modeling. Such a platform will offer users
a seamless and secure online social experience while facilitating future enhancements
and adaptability to changing user needs.
Unblocking The Main Thread - Solving ANRs and Frozen FramesSinan KOZAK
In the realm of Android development, the main thread is our stage, but too often, it becomes a battleground where performance issues arise, leading to ANRS, frozen frames, and sluggish Uls. As we strive for excellence in user experience, understanding and optimizing the main thread becomes essential to prevent these common perforrmance bottlenecks. We have strategies and best practices for keeping the main thread uncluttered. We'll examine the root causes of performance issues and techniques for monitoring and improving main thread health as wel as app performance. In this talk, participants will walk away with practical knowledge on enhancing app performance by mastering the main thread. We'll share proven approaches to eliminate real-life ANRS and frozen frames to build apps that deliver butter smooth experience.
Development of Chatbot Using AI/ML Technologiesmaisnampibarel
The rapid advancements in artificial intelligence and natural language processing have significantly transformed human-computer interactions. This thesis presents the design, development, and evaluation of an intelligent chatbot capable of engaging in natural and meaningful conversations with users. The chatbot leverages state-of-the-art deep learning techniques, including transformer-based architectures, to understand and generate human-like responses.
Key contributions of this research include the implementation of a context- aware conversational model that can maintain coherent dialogue over extended interactions. The chatbot's performance is evaluated through both automated metrics and user studies, demonstrating its effectiveness in various applications such as customer service, mental health support, and educational assistance. Additionally, ethical considerations and potential biases in chatbot responses are examined to ensure the responsible deployment of this technology.
The findings of this thesis highlight the potential of intelligent chatbots to enhance user experience and provide valuable insights for future developments in conversational AI.
20CDE09- INFORMATION DESIGN
UNIT I INCEPTION OF INFORMATION DESIGN
Introduction and Definition
History of Information Design
Need of Information Design
Types of Information Design
Identifying audience
Defining the audience and their needs
Inclusivity and Visual impairment
Case study.
2. Agenda
• What Is Digital Engineering
• What Is a Digital Twin
• Developing Digital Twins in
Innoslate
2
3. • SPEC Innovations provides software, training, and
consulting to the defense and aerospace industries
and the intelligence community
• Our flagship software product, Innoslate is the first
cloud-native, model-based systems engineering
software solution made solely in the United States
of America
• Our engineers built Innoslate to help systems
engineers develop full lifecycle solutions to
complex system of systems
• Innoslate software supports Requirements
Management, Modeling and Simulation,
Verification and Validation, and more in one
seamless package
About Us
We are the experts in systems engineering
3
4. AskUsYourQuestions
• Ask us your questions using
the panel on the right
• This presentation is being
recorded and will be made
available to you
• Contact us after the webinar
through
• support@Innoslate.com
• Call 571.485.7800
• LinkedIn Innoslate User Group
• Twitter
4
5. MeetYourHost
5
• Senior System Engineer
• Manager of Innovation, IAOIP
• Veteran – U.S. Navy
• Masters in Systems Engineering
• michael.campbell@specinnovations.com
6. WhatIsDigitalEngineering
“The crux of digital engineering is the creation of computer readable models to represent all aspects of the
system and to support all the activities for the design, development, manufacture, and operation of the
system throughout its lifecycle. ”
~ Systems Engineering Book of Knowledge (SEBoK)
The Goal of Digital Engineering is to Develop Digital Twins
The digital twin is a high-fidelity model of the system which can be used to emulate the actual system. An
organization would be able to use a digital twin to analyze design changes prior to incorporating them into
the actual system.
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8. BenefitsofDigitalTwins
• Visualize the system in real-time
• Make effective decisions quickly
• Traceability in complex systems-of-systems
• Predict necessary maintenance
• Troubleshoot issues from geographically disperse areas.
• Test in the digital environment rather than the physical (lower cost and reduced risk)
• Update analytics in real-time to all stakeholders and allow in-field operators to adjust the
system’s assets when needed
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9. WhatRoleDoes MBSEPlayinDigitalTwins
“These models would have to be connected to the physics-based models used by other engineering
disciplines such as mechanical and electrical engineering.”
• Modeling
• Simulation
• Verification and Validation
• Requirements Management
• Architecture Development
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10. OntologiesAreNeededforDigitalTwins
“One challenge remaining for digital engineering is the integration of MBSE with physics-
based models.
• Foundation to digital engineering is the representation of the system data in a format
sharable between all stakeholders (Giachetti et al. 2015; Vaneman 2018). SysML 2.0 is
one of several future developments promising to provide a representation sufficient to
support digital engineering. An ontology defining the entities and relationships between
them can be used to define the concepts relevant to systems engineering. Such a
representation is necessary to create the digital thread linking all the models together in
a cohesive and useful manner.” – SEBoK
• Lifecycle Modeling Language is already there!
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11. LifecycleModelingLanguage(LML)
• LML was developed by a group of systems engineers
who realized that SysML was not meeting the needs
of the systems engineering and program
management communities
• The group is led by Dr. Warren Vaneman, USN CAPT
(retired) and Professor of Practice at the Naval
Postgraduate School (NPS)
• LML is taught in over 200 universities around the
world, including MIT, George Mason University,
Stevens Institute of Technology, West Point, NPS, Air
Force Academy
• LML is easy to learn, use, and extend
• Visit http://www.lifecyclemodeling.org
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LML has proven to provide a strong ontology for
systems engineering and program management
14. Innoslate’sDigitalTwinSoftwareIntegrationApproach
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Goals of Integration:
1) Use data to create
information between
tools;
2) Minimize data
duplication between
tools.
Already implemented in v4.4
• Innoslate® provides a complete
MBSE environment
• We added MATLAB, STK, and
GitHub integration in version
4.4
• A Java Web Application (JWA)
is used to interface between
the Innoslate cloud native tool
and desktop tools
• We are in the process of
integrating with the Ansys tool
suite, LabView, and Selenium
to complete the digital thread
software
15. IntegrationEnabledUsingInnoslate®’sMOSAArchitecture
• Plugins are viewpoints of the Innoslate
database
• Plugin features
• Not a standalone application (requires
Innoslate Core)
• All authentication is through Innoslate Core
with the options for:
• Single-Sign-On CAC (Default)
• Native Email/Password (Optional)
• LDAP (Optional)
• All data is stored in the U.S. Government
managed MSSQL database using Innoslate Core
(no data lock)
• Innoslate REST API facilitates plugin data
exchange
Modular Open Systems Approach
(MOSA) Architecture Enables
Architecture to Operations (DEVOPS)
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16. DocumentsView
• Innoslate enable you to capture and
develop your documentation
• It provides the means to capture
pictures, create table, use diagrams
and charts from Innoslate, and create
live tables
• You can develop your own custom
template or pick from a number of
built-in templates
• You can use these to perform model-
based reviews
• The Benefit: show users and
customers information in a simple
form they can easily understand, yet
be reusable and traceable to other
parts of the design
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17. RequirementsView
• A special type of document that
includes by default, the
rationale field, quality score and
quality checker
• Can also see indicators for key
traceability relationships
• Has all the benefits of any
document in Documents View,
including baselining, formatting,
acronym extraction, find &
replace, etc.
• Uses workflow to manage
requirements
• Use labels for sorting and
identifying verification methods
• The Benefit: A digital document
for your living requirements
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18. Modeling
• Create high level to detailed
models of functional and physical
elements of the design
• Functional model (Action Diagram)
provides means to allocate decision
points and use Resources explicitly
• Allocates Actions to Assets
automatically (functional to
physical mapping)
• View/use models in many different
formats, including SysML, IDEF, etc.
• Reuse portions of models in other
models, including across Innoslate
projects
• The Benefit: Develop the functional
requirements and physical
constraints
Functional Modeling
Physical Modeling
Traceability
26 Diagram types, 2 Charts, and
counting. All the 9 SysML
diagrams.
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19. Simulation
• Innoslate® provides built-in discrete
event and Monte Carlo simulators
• Decision points come with pre-built
scripts for probability and Resource
selection, as well as iterations for loops
• JavaScript can be used to enhance the
simulation execution
• Can access web resources using APIs
• Integration with MATLAB/Simulink and
STK through special APIs
• Major enhancements to simulators in
development for v4.5
• The Benefit: derive performance
requirements for timeliness and
quantity using distributions and
Resources
Current Innoslate®
simulators v.4.4
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20. Analysis
• Innoslate® supports various types of
analyses:
• Textual analysis (using Natural Language
Processing (NLP) algorithms)
• Requirements quality analysis
• Traceability assistance
• Modeling heuristics (Intelligence View)
• Dynamic Analysis
• Discrete event simulation
• Monte Carlo simulation
• Static Analysis
• Attribute roll-up
• Diagram warnings (errors, unit mismatch)
• Risk and Cost Analysis
• Integration with other tools adds to
Innoslate®’s capabilities
• MathWorks® MATLAB/Simulink
• Ansys/AGI Systems Tool Kit (STK)
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21. MathematicalAnalyticswithMATLAB
• Use the MATLAB APIs to
interoperate with MATLAB/Simulink
models that perform detailed
calculations
• Simple GET and POST commands
move data between Innoslate and
MATLAB
• Use Setting option to show pathway
to MATLAB on desktop
• The Benefit: Reuse models created
in MATLAB to perform more
detailed calculations
MATLAB Rover Function Script
New APIs: matlab.post and matlab.get
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22. GeospatialVisualizationandAnalysiswithSTK
• Use the STK integration
to visualize and take
advantage of the STK
analysis tools
• APIs designed to get to
the critical parameters
in STK
• Use the information to
alter the simulation
performance in co-
simulation
• The Benefit: Includes
geo-spatial constraints
in the discrete event
simulation for more
realistic analyses
STK Rover Model with
Search Pattern and
Communications Satellite
New APIs
for STK
“Initiate Survey Process
Variables” Script
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23. CAD/CAM
• New CAD Viewer provides
capability to view CAD files
and convert CAD data into
Innoslate objects/BOM
• Export other information
from CAD tools using CSV
and import into Innoslate®
for further analysis
• Added other filetypes: GLB,
gITF, 3DS, PLY and ZIP (with
OBJ and MTL combined)
• The Benefit: Enables
verification of the design
and links back to
requirements
CAD Viewer
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24. SoftwareDevelopmentIntegration
• New GitHub View provides
capability to directly interface with
GitHub using a special set of
dashboards
• Provides entire new viewpoint to
enable program managers and
systems engineers to more
effectively monitor software
development progress and capture
results
• Version 4.5 will include capability
to create Class Diagrams from code
to enhance traceability between
requirements and code
• The Benefit: Capability to monitor
software development progress
and verify code meets
requirements
Statistics for GitHub View
Kanban Board for GitHub View
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Dashboard for GitHub View
Issues in GitHub View
Commits in
GitHub View
Pull Requests in
GitHub View
25. AR/VR
• Innoslate is browser-based making it easy to use with AR/VR technologies such as Hololens
• Useful when field operatives need to be able to view the digital information such as standard operating
procedural diagrams, test plans, or metrics
• The Benefit: Enhanced visualization of design elements during operations
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26. OperationsSupport
• Coming soon: Sopatra®, powered by
Innoslate®
• Text to Diagram autogeneration used
to transform written standard
operating procedures (SOP) to Action
Diagrams for analysis
• Advanced NLP algorithms developed
• Automatically adds best practice
actions, such as “See and Decide”
• Special Monte Carlo Analysis of the
Allowable Operational Time Window
(AOTW) and Time of Procedure (ToP)
• Advanced analytics to calculate the
Procedure Buffer Time (PBT)
• The Benefit: More accurate SOPs
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27. GetStartedwithyour
DigitalTwins
Create an account of Innoslate at
cloud.Innoslate.com/sign-up
Utilize your resources
Help.Innoslate.com
Innoslate.com/resources
Reach out for help
https://www.innoslate.com/contact-us/
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30. IfyouaregoingtoINCOSEIS
Stop by and see us at our booth or at the following sessions
• Modeling and Analysis of SOP Tutorial (Saturday, July 17, 1:00-5:00 pm EDT)
• To "Vee" or not to "Vee" Debate (Monday, July 19, 10:00-11:30 am EDT)
• SPEC Innovations Live Session (Monday July 19, 4:45-5:30 pm EDT)
• SPEC Innovations Live Session (Wednesday, July 21, 7:00-7:45 am EDT)
• Return on Investment in Model-Based Systems Engineering Software Tools (SPEC sponsored research by
GMU - Wednesday, July 21, 12:30-1:10 pm EDT)
• MBSE Components in the Supply Chain, Spring 2021 Student Capstone Project (SPEC sponsored research
by GMU - Wednesday, July 21, 2:00-2:40 pm EDT)
• Analyzing Standard Operating Procedures Using MBSE Diagrams (Thursday, July 22, 10:30-11:10 am EDT)
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31. MoreResources
SPEC Innovations offers training, books, videos, documentation, trials, and more
Training: specinnovations.com/training
Books: “Real MBSE” textbook and lab manual available on
Amazon
Videos: Visit the SPEC Innovations Youtube channel
LinkedIn: Innoslate and Systems Engineers User Group
Documentation: help.Innoslate.com
Trial: cloud.Innoslate.com
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32. SPEC Innovations offers training, books, videos, documentation, trials, and more
Thank you!
Visit cloud.innoslate.com for a trial.
SPEC Innovations
@Innoslate
Innoslate User Group
Innoslate.com/blog
571.485.7800
innoslate.com
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