Predictive design to the fore

In the current world, most products are a mix of multiple disciplines of science, with significant interactions between them. It is, therefore, very difficult to predict the outcome of a design without building real products and testing them. If things don’t work out in testing, the process is repeated by making changes on the design aspect affecting the issue till the product finally meets the requirement. This is a long-drawn process and costs a lot of money; it, also, has a lot of dependencies including the availability of resources to build the product, budgets to build multiple iterations and availability of test facilities among others. The problem becomes compounded if the product was designed to work under different environmental conditions or usage requirements. The costs and time increase with each additional demand made of the design. Also, given the fact that many outcomes aren’t repeatable, to build confidence in the design, multiple samples are built and tested before the product is accepted for commercial launch. Many products also require regulatory approvals.

Creation of multiple iterations is easy in a mass produced or less expensive product as the time and costs involved aren’t great. However, if this is to be done on a rocket, satellite, aircraft or for that matter expensive medical equipment, the costs can be prohibitive.

This is where predictive design techniques are used to reduce design cycle times and costs by reducing the number of design iterations. This was used extensively in the Aviation and Space industry initially and later by the automotive industry and has, also, made its way to the medical device industry of late. Regulatory bodies also accept the use of predictive design as part of the design process.

Predictive design involves creating a digital model of the product and analysing it under various use cases and environmental conditions – these could be mechanical, electrical, or mixed stress analysis. Models are validated once using a physical prototype with future changes resulting from the design, environmental stress or use-case analyses being done on the digital model to predict the impact of change. This enhances the ability to take well-informed decisions on the changes. Various tools and techniques combined with computers capable of high-performance computing enable a great deal of accuracy of prediction.

Let’s look at a few advantages of using predictive design:

Reduced time to market: The digital model of the product is tested under the design boundary conditions and use cases and once desired results are achieved, the design is frozen, and the actual physical prototype is built. Changes to a digital model and subsequent testing can often be done in a day as against the process taking weeks or even months if done on a physical prototype.

Validate design changes: When changes are mandated to a design because of the use of a different supplier part or value engineering involving small changes, it is very easy to test the digital model under the changed design and test protocols and validate if there is no major change to the performance and other aspects of the product. This could involve validating functional parameters as well as physical changes including dimensions, weight, etc. and also changes to the design from the adverse effects of increased temperature, noise, etc.

Identify design flaws/fix field issues: Sometimes the product is not tested for all use cases. Following the launch, if there is an issue (either due to a missed protocol or adverse usage), it is often easy to replicate the failure on the digital model by altering the test protocols to understand the failure better.

Product enhancements: Many customers realise they could get more out of a product after it is launched. This often leads to a situation where the designer/manufacturer is unsure if the product can perform to its full functionality under the new requirements. In such a scenario, it is easy to predict the change in product performance due to the enhanced requirement, quantify the same and, if acceptable to the customer, implement the design changes.

Predict the future performance of the product over time: Often in products involving moving parts or parts that are prone to physical changes over time, the same can be incorporated using predictive design to understand how the product will perform and when it will fail to meet the requirements. This helps in planning preventive maintenance to restore the product to its original performance.

Establish the life of parts: Not all products have components or sub-systems having the same life. Certain components and sub-systems probably have 10 times the life of other components/sub-systems in the same product. Predictive design enables to predict the same, resulting in some components being re-used in a new system.

Reference for a new design: It is mandatory in the medical device industry to incorporate issues in the predecessor product as a design input. Not all aspects of the predecessor product are easy to capture if it was all in physical form. The use of predictive design enables the digital model and its changes over time to be used as a strong reference. This has significantly reduced issues after the launch of a new product.

Predictive design can usher in striking efficiencies while ensuring that safety and regulatory requirements are met while delivering products. When employed in the medical devices industry, predictive design can be a great asset in delivering healthcare products which truly meet the requirements of patients and care givers in the most effective way possible., creating a need for adaptive real estate and ensuring its long-term worth.