While crowdfunding platforms such as kickstarter have revolutionized the way new product development can be funded, the development process still follows the same basic rules. One of these rules is, once a product design is ready to be finalized, a “beta” version of the product is being rolled out to pilot customers. Even today, with the options to model many aspects of real-life interactions in software, having actual human beings use a product in their real-life environments, remains the ultimate stress test for most products.
What are important aspects when testing prototypes?
1. Define required measurements and provide good data acquisition
Depending on what kind of product prototype you would like to test, you might or might not have the necessary data acquisition equipment on board for a field test. For instance, when car prototypes are being tested in the field, they are equipped with a variety of data loggers, monitoring bus activity and measuring additional sensors to give valuable insight into the devices under test. This includes data internal to the device, such as temperatures, rpm, data bus values. External, environmental sensor data can be just as important: Supply voltage quality, ambient temperatures, etcetera. When testing devices that typically do not include any data acquisition – for example household goods such as washers/dryers or kitchen appliances – off-the-shelf DAQ hardware should be selected and added to the device. Since these data loggers are to operate autonomously, self-contained real-time platforms such as NI CompactRIO or NI Single Board RIO are good choices that also offer a large selection of sensor interfaces.
2. Define a concept to manage distributed data sources
Key to useful prototype testing is a clever data concentration and management platform. While in some cases it might be OK to send servicing personell to visit pilot customers, gather first-hand feedback, collect acquired data and create protocols on-site, this might not always be an option. Devices might be placed in very remote locations, pilot-customers might not agree to regular visits and – first and foremost – response times could be very slow. Imagine household devices under test, such as an air-conditioning unit, to fail in mid-summer and response times to be 2-3 working days. Better not look at your Twitter feed for awhile.
Of course, the modern approach is to provide continuous monitoring of the device, therefore allowing service personell to remotely see and possibly predict failures. The system should also allow to compare different devices’ performances. With a continuous monitoring platform you can provide a better service and lower your service cost by planning maintenance visits more efficiently.
3. Work with open platforms and the right partners
Acquiring the right measurement data is already a huge step towards better insight into your own products. This data will also help you understand how the products are used and perceived by customers. Do customers understand and use all options and settings on your product? This data can be a great source of feedback to developing engineers and product marketing.
With this in mind, acquiring the data will most likely only be “Step 0” of your prototype testing strategy. With an open measurement storage and analysis platform, such as daq.io, you can start sharing valuable data with other departments. You can start in-depth analysis of your data by interfacing into analytics platforms and tools. You can create tailored dashboards for customers, managers or service staff, giving each user group the set of information they need. Once the data is available, many potential uses will come to mind. Make sure you do not limit yourself by selecting a less-than-ideal data management solution.
Finally, it is important to dedicate sufficient resources when setting up a new prototype testing strategy. To define a new test strategy, consult with experienced professionals to help you find the right solutions for your application and budget.
Validating product prototypes is a crucial step in the product development process. Continuous monitoring of relevant data and sensors can help manufacturers understand how their products are actually being used and how both their customers and environmental variables behave in real-life. All this data can be very advantageous when designing the next generation of products but also for tailoring product maintenance and other services to specific customer needs. Analyzing the prototype data will also be helpful when selecting an Internet of Things strategy for the respective product. What sensors are useful? What data update rate is required? What benefits can I provide my customer by connecting the device to the Internet of Things?
Having a good prototype test strategy will improve product quality, build customer trust and decrease both time-to-market and failures in the field.
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