For decades, computers have been an integral part of product development. However, the way in which humans have used machines to create new products has changed dramatically. Today, Sentient Science’s use of prognostics can help developers confidently predict when components will fail much earlier than previously possible – here’s a quick look at how we arrived here.
Back in the 1970s, Computer-Aided Design (CAD) was the mainstream development tool, which used a mix of hardware and software to create 3D models that could be turned and flipped, giving designers a view of the potential product from every angle. By the 1980s, Computer-Aided Manufacturing (CAM) was a major breakthrough.
When paired with CAD, CAM could create physical models of the drafts that were designed on the computer. CAM is still used in manufacturing facilities to this day, optimizing manufacturing processes by increasing production speed without compromising precision and consistency.
The advancement of computer models carried into the 1990s, when Computer-Aided Engineering (CAE) became a common development tool. This system simulates how a component will perform based on mathematical models. CAE caught on in corporate America when it was realized that it could drive huge savings by cutting the time and money that went into product testing.
By using computer simulations, as opposed to physical prototypes, the entire development process could be made more efficient. By 1995, engineers had created the Product Data Management system, which can leverage all product data and make it easier to access the information on a wide range of applications. This tool optimized the operational resources managers use.
At the turn of the millennium, product lifecycle management had entered the development process, giving companies the ability to manage a product’s entire lifecycle. The process found a home in supply chain management, where leaders used it to control every aspect of the distribution process.
Fast forward to the present, and companies are now using prognostics to estimate the future conditions of any material, component or industrial system. The engineering discipline uses probability to accurately predict an asset’s lifespan.
Asset managers can use prognostics to extend the lifetime of any product, lowering the cost of maintenance and expenses related to premature failure. The system can be compared to the human genome, which gives great insight into the future health of a person. Similarly, Sentient’s metaphoric “genome” provides a glimpse into the future behavior of any asset.