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introduction

startups today face many challenges when turning technical ideas into reality:

• speed: how do you accelerate development cycles?
• savings: how can you cut costs and increase productivity?
• scale: how do you take the product from concept to market?

the answer is model-based design—an engineering approach that sets up startups for success by helping them take their products from idea to prototype, and from prototype to production.

what is model-based design?

model-based design centers on the systematic use of models throughout the development process.

the model serves as:

• a visual representation of the design based on block diagrams and other graphical or textual elements. models promote understanding of design intent—whether it is data flow or system architecture.
• an executable specification of the design. models enable simulation of system behavior across multiple domains.

with models, engineers can evaluate design tradeoffs, perform continuous verification and validation, and automatically generate code for hardware implementation.

why model-based design for startups?

for startups, the inception of a product starts from an idea, which is then refined and shaped into a design concept defined by a set of requirements—and it rapidly evolves into detailed technical specifications. building a prototype that can meet these specifications is critical for startups. a prototype demonstrates product value in an early stage, solidifies confidence among internal teams, and helps secure funding from external investors who are looking for early evidence of success. model-based design helps startups quickly go from idea to prototype.

from idea to prototype

quickly get to speed

when you start working on an idea, you might be scratching your head over a blank canvas. however, you do not have to start from scratch with model-based design. simulink and its add-on products provide reference examples and prebuilt blocks to help you get started.

you will find reference examples useful as starting points for your new design. the examples are full-system models built for specific applications, such as insulin pumps, wind farms, package delivery drones, and other applications spanning almost every industry.

as you modify your design to include detailed algorithms and build out full capabilities, you can directly add prebuilt blocks to your design. they are encapsulations of algorithmic modules that have been rigorously tested and fully documented—whether they are signal processing algorithms or control techniques. you can add, combine, or modify these algorithms to suit your design needs.

you can also apply ready-to-use and fully parameterizable blocks for modeling components in the system, such as an electrolyzer powering a green hydrogen production system or a rotor powering a vertical takeoff and landing aircraft.

voyage auto, an autonomous driving startup, used reference examples to kick-start its development process.

reduce development costs and time-to-prototype

you start the design process with many ideas in mind, facing a vast design space and massive uncertainty as you explore possible design options. however, you also often face time, budget, hiring, and other resource constraints as a startup. when you start to formalize and converge on your design choice, it is simply unrealistic to test every option with physical prototypes.

with model-based design, you build and simulate your models as virtual prototypes. you can create massive design studies, evaluate design options, and optimize design performance in a digital design environment—drastically reducing the need to build physical prototypes while mitigating risks of budget overruns.

ather energy, an electric scooter startup, used modeling and simulation to accelerate development.

carnegie wave energy, a wave energy technology startup, used virtual prototyping and simulation to fix design issues and delivered the world’s first operating wave farm.

focus on your design—not the code

after you have confirmed a design choice and developed a virtual prototype, how do you implement your design as code running on a physical prototype? you can translate your design to code by manually coding your algorithms, but such an approach involves a lot of steps and can introduce errors and inconsistencies in the process. changes to the design must be manually implemented in code and it is difficult to establish traceability between your design and your code.

model-based design enables you to automatically generate code from your models. you can go from your design to code running on functional prototypes in days, not months. the generated code is efficient, high-quality, readable, and fully traceable with the design, which means the latest generated code always reflects your most up-to-date design. code generation is a strong approach for startup software development because it lets your startups focus on the high-level design work.

ellio, an electric bike startup, sped time-to-prototype by automatically generating control code to target embedded hardware.

preceyes, a surgical robotics startup, created the world’s first eye surgery robot by implementing its software with automatic code generation.

bigfoot biomedical, a medical technology startup, developed insulin delivery systems with simulation and automatic code generation.

from prototype to production

for startups, developing a functional prototype is instrumental in demonstrating product value to investors, suppliers, and customers. however, for a startup to truly achieve commercial success at scale, it must take the product from a proof-of-concept state (often limited in functionality, quality, and performance) to a production-ready state. model-based design helps startups quickly go from prototype to production.

model once, deploy everywhere

when you go from prototype to production, there is often a need to change the hardware either to increase performance by leveraging more powerful hardware or to reduce cost in mass production by using more cost-effective and commonly available hardware. the change in hardware requirements is a challenge for startups—integrating software with a different hardware platform not only requires in-house hardware expertise, but also requires changes to the software.

model-based design enables you to decouple your software development from hardware because you can generate portable code from your model to target different hardware, such as c/c code for microcontrollers, verilog/vhdl code for fpgas/asics, structured text for plcs, or cuda^® code for gpus. mathworks partners with major hardware vendors to support hardware integration across these platforms.

the code generation support and hardware integration support make it possible for you to model your design once and deploy it to all supported hardware targets. this means you and your team do not have to become hardware experts and can focus on design work, rather than learning about hardware specifics and recoding your existing algorithms to adapt to a new product.

stem, an energy storage system startup, used model-based design to decouple control software development from microcontroller hardware.

dynisma, a motion simulator startup, scaled the design to target different microcontrollers and hardware systems.

minimize defects and ensure quality

a key objective when moving from the prototyping stage to the production stage is reducing defects and ensuring product quality. however, startups often face the risk of identifying errors late in the development process. these errors require significant rework and are time-consuming and costly to fix.

model-based design enables you to continuously verify and validate your design by providing tools for you to perform analyses, checks, and tests in every major phase of your development process—all the way from requirements and early design verification to system integration testing.

with simulation, you front-load your verification efforts by shifting time and resources from physical testing to virtual testing. the “left shift” helps cut testing costs associated with equipment and physical prototypes and can eliminate entire categories of errors before you test the product in real-world conditions. virtual testing also helps you answer “what if” questions and simulate test scenarios or edge cases that are difficult and sometimes impossible to replicate in a real operating environment.

supporting the complete v&v workflow

bpg motors, an electric motorcycle startup, used simulation-based tests to identify product issues and move the product from prototype to preproduction.

airnamics, an unmanned aerial system startup, eliminated most software bugs by testing the system virtually before their first flight.

achieve certification

for startups developing safety-critical applications in industries such as aerospace, automotive, medical devices, and renewable energy, the software in the system not only has to pass rigorous testing, but also must adhere to functional safety standards outlined by international standards organizations or industry working groups. it is a challenge for startups to identify the proper tools to use and the right processes to follow for certification workflows.

model-based design provides tools for you to whether your model and the code that you generate from it complies with the industry standard.

in addition, iec certification kit provides tool qualification artifacts, certificates, and test suites, and generates traceability matrices. this kit helps you qualify code generation and verification tools, such as embedded coder^®, hdl coder™, and the polyspace^® product families, and streamline certification of your embedded systems to iso^® 26262, iec 61508, en 50128, iso 25119, and related standards such as iec 62304 and en 50657. certificates and assessment reports from the certification authority tüv süd are included in the kit for the supported products and standards.

stem, the energy storage system startup mentioned earlier, also used power systems simulations to pass product tests and achieve ieee^® 1547 certification faster.

reuse design for next-gen products

when you are ready to build upon the initial success of your first product launch, model-based design helps you accelerate development efforts for your next-generation products by enabling the from previous iterations in your new design. you can also easily create and manage design variants when you are scaling the product to reach customers with different needs.

vonsch, a power electronics equipment company, reused design models to rapidly launch new products with a small engineering team.

how can startups adopt model-based design?

phased adoption

even with the potential benefits of using model-based design, startups often consider the risks of adopting a new development process. this is especially true for smaller startups that do not have dedicated staff to pilot a new process and learn new tools.

successful startups have mitigated this risk by introducing model-based design incrementally. they usually start with a single project, identifying early wins that can be achieved using model-based design versus using the current practice. successful introduction of model-based design involves taking incremental steps that can help a project along without slowing it down:

1. experiment with a small piece of the project.
2. build on initial modeling success.
3. use models to solve specific design problems.
4. stick with the basics.
5. leverage the experience of mathworks experts.

to understand the experiences and approaches to adoption for small teams, see the white paper how engineering teams adopt model-based design.

a three-person engineering team at océ adopted model-based design in one to two weeks with the help of mathworks training.

measure the return on investment (roi)

adoption of model-based design can lead to significant savings during the system engineering phase, the development phase, and the testing phase. organizations that adopt model-based design realize savings ranging from 20 to 60%, when compared with traditional methods.

to understand how to quantify expected savings of model-based design over a traditional development approach, see the white paper measuring the return on investment of model-based design.

vanderhall motor works, an electric vehicle startup, adopted model-based design and built an all-electric utility task vehicle (utv) with a limited crew of engineers in less than a year.

the mathworks startup program

the mathworks startup program offers qualified startups low startup pricing, support from application engineers and technical support, training options in local languages, including 50% off training credits, and co-marketing opportunities to showcase your technology or products. the extensive support and resources from mathworks are especially helpful for startups that may not have the same level of in-house expertise or resources as larger organizations.

rangeaero, an autonomous cargo helicopter startup, worked with the mathworks application engineering team to adopt model-based design tools and solve complex problems.

monarch tractor, an autonomous tractor startup, adopted model-based design and delivered its launch vehicle with the support from the mathworks startup program.

the mathworks accelerator program

the mathworks accelerator program helps startups in partnering accelerators advance their development. startups are treated as full commercial customers with technical support and guidance from domain experts while receiving free access to industry-proven software.

forge, an accelerator in india, partnered with the mathworks accelerator program and enabled its startups to adopt model-based design and technical computing tools in development.

xfinito biodesigns, a startup company that received incubation support from dayananda sagar entrepreneurship research & business incubation foundation (derbi foundation), used mathworks support to deliver a novel medical device for treating diabetic neuropathy.

success with model-based design

whether it is creating renewable energy systems to address the climate challenge; defining the future of mobility on the land, in the air, or sea; or advancing quality of life with new medical devices, startups in many industries have consistently achieved immediate and tangible results with model-based design.

with an incremental approach and support from mathworks, startups can successfully adopt model-based design and deliver innovations quickly, cost-effectively, and efficiently, scaling from idea to production.