MATLAB and Simulink for Technical Service Providers

Analyze, design, and build systems and applications, servicing diverse engineering projects

Technical service providers use MATLAB and Simulink to solve technical problems for their customers. Building from the MATLAB computational and design platform, teams can share a common set of products to exchange work and ideas. You can also add discipline-specific toolboxes, apps, and add-on products and deploy them in specific areas while training the entire team on the capabilities of MATLAB and Simulink. These products enable you to speed up projects across industry segments such as aerospace and automotive systems, wireless communications, and medical imaging.

With MATLAB and Simulink, you can:

Develop engineering systems
Optimize embedded system designs
Simulate complex physical phenomena
Use Model-Based Design and automatic code generation to implement algorithms
Adopt agile development for systems development
Leverage cloud computing for scale

“We had all these high fidelity models and we did not want to compromise on the fidelity, but we wanted to arrive at a very low simulation time for executing this kind of iterative simulation processes.”
Aseem Routray, KPIT Technologies Limited

Using MATLAB and Simulink for Engineering Technical Services

KPIT Establishes an End-to-End Process for AUTOSAR-Compliant Software Development with Model-Based Design

DCNS Models and Simulates SAMAHE Helicopter Handling System

3T Develops Robot Emergency Braking System with Model-Based Design

Digital Transformation for Business Development

Build your engineering services organization on industry-trusted modeling and analysis tools. MATLAB and Simulink help you create a flexible and efficient team that can grow and adapt to the latest trends with compatible toolboxes and add-ons. You can use prebuilt reference applications and architectures to simplify numerous applications: from integrating with enterprise IT systems, the cloud, and production data infrastructure to scaling your computation to clusters or deploying your models and code as applications to share with users outside of MATLAB.

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Deep Learning and Image Processing

With just a few lines of MATLAB code, you can build deep learning models that use your measured data to identify objects and predict abnormal conditions. Image Processing Toolbox apps let you automate common processes like segmenting image data and batch processing large image data sets. You can use MATLAB in image processing applications such as thermal imaging of equipment, biomedical classification for health analytics, and manufacturing quality inspection. With deep learning in MATLAB, you can learn feature representations directly from image, video, or signal data.

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Dexerials Corporation Uses AI for Detecting Defects in Real Time for Film Manufacturing

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Model-Based Design and Product Development

Implement Model-Based Design with MATLAB and Simulink to reduce development time by 50% or more. In Model-Based Design, your system models become the center of your development process, which greatly reduces barriers of communication between teams and helps you verify system performance early through simulation. You can shift your resources and focus from code implementation and debugging low-level drivers to system design and testing.

With App Designer, MATLAB Compiler, and Simulink Compiler, you can create standalone applications with custom UIs and share these with others – even if they don't know how to use MATLAB and Simulink.

Virgin Orbit’s LauncherOne vehicle assembled (top), with exploded view showing the fairing, payload, and first and second stages (bottom).

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CPU, FPGA, SoC, and All Types of Hardware Deployment

MATLAB and Simulink enable you to deploy models to many deployment targets in a production environment. You can convert models to C, C++, HDL, and CUDA^® to deploy onto embedded or edge devices. With MATLAB and Simulink, you can also integrate models with in-house developed enterprise desktop or server applications. To speed up simulations and applications, you can use generated C/C++ and MEX code, GPUs, or a pool of compute nodes.

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Agile System Development

Model-Based Design extends agile principles to the development of systems that include physical components as well as software. From requirements capture, system architecture, and component design, to implementation, verification, test, and deployment – Model-Based Design spans the entire development cycle. Multidomain system simulations lead directly to working designs and facilitate customer interactions so you can quickly adjust to changing requirements. Automatic code generation produces working software that you can immediately deploy and test on a target hardware.

Simulink integrates with Jenkins™, Jira, Git™, GitHub^®, and other agile development tools.