Sook-Hua Wong, Industry Segment Manager at Keysight Technologies, explains how the Internet of Medical Things emphasizes the importance of investing in high-quality manufacturing testing strategies.
Rising health care costs and consumer demand for better health care are driving the widespread use of IoT in health care. This evolution is commonly known as the Internet of Medical Things (IoMT). Today, it’s easy to find connected medical devices such as ultrasound imaging systems, blood glucose monitors, bedside monitors, pacemakers, hearing aids, and wearable health monitors. With IoMT devices, non-essential patients can stay home and be monitored through these devices, reducing hospitalizations and reducing costs. We can see that the IoT has a significant impact on every aspect of the healthcare segment, from monitoring to diagnostics, surgery and patient care.
Medical device manufacturers face unique challenges when embedding the IoT. Many medical devices are used in mission-critical applications. Therefore, they need to be very reliable and long lasting. The wireless connection must be on 24/7, reliable, and work seamlessly in difficult physical environments. These requirements pressure medical device manufacturers to implement reliable, efficient, and cost-effective manufacturing testing strategies.
Importance of effective manufacturing testing
Many medical devices undergo a thorough characterization at the design stage to ensure the quality of the device. However, variations in the manufacturing assembly process, deviations in supply chain components, test system reproducibility, and operator processing errors can cause device failures. Some of these defects may not be detected during manufacturing tests due to lack of test system coverage. A unit that passes slightly can cause field failures during actual use due to poor performance.
To stay competitive in the market, manufacturing tests are usually optimized for faster test times and lower cost testing to meet market cost expectations. Devices can only be tested under certain minimum conditions that appear to be sufficient. For example, wireless medical device OEMs have recently faced issues with the effectiveness of manufacturing test setups. A custom version of a Bluetooth Low Energy (BLE) device has passed all manufacturing tests, but later turned out to have intermittent connectivity issues. Troubleshooting revealed that the device’s antenna pattern was distorted and some BLE channels were significantly reduced in power. In production testing, only very simple connectivity tests were performed that could not detect these intermittent connectivity issues during the actual operation.
Capital equipment costs and potential savings
Defects detected during the early manufacturing stages may not cost much to fix. However, the cost increases exponentially after production testing or when detection is made in the field of the end-user application.
During the New Product Implementation (NPI) phase, it is important to invest in the right test solution. Investing in RF testers and the necessary operators to run the test correctly may seem expensive. There is also an annual maintenance and calibration cost. However, the potential savings of detecting failures early in manufacturing saves direct and indirect or hidden costs of field failures. The hidden costs of warranty, troubleshooting of failures, handling of replacement units, loss of sales due to bad reputation, or penalties resulting from the use of defective products can be potentially enormous. With the right test strategy implemented in production, manufacturers can easily recover their initial investment in RF testers within the first year.
The next section describes how medical device manufacturers can optimize manufacturing tests to ensure device quality, improve manufacturing yields, increase test system flexibility, and increase manufacturing throughput.
Case Study 1: Ensuring the quality of BLE wireless chargers
This was the first attempt by a medical device company to incorporate a wireless connection into their products. This company was developing a BLE compatible wireless charger. By enabling a wireless connection to the charger, users can easily monitor charge status and battery level to extend battery life. During the design phase, engineers needed to verify that the antenna and matching circuit were functioning according to their design goals. Since the product was developed using RF modules, engineers skipped full parametric testing according to Bluetooth requirements. RF performance is guaranteed by the module manufacturer. The engineer has modified the reference design and antenna to meet the form factor requirements, so the engineer has performed full validation at the end device level to ensure that the device is properly transmitting and receiving BLE signals in different end user scenarios. I had to confirm. The company used a wireless (OTA) wireless tester specifically designed for IoT applications to perform transmitter output power measurements and receiver packet error rate (PER) and sensitivity measurements. Engineers used OTA measurements to verify the overall performance of the transmitter and receiver of the device, including the antenna. Engineers can also choose to test all 40 BLE frequency channels or selectively test the channels of interest. This feature allows engineers to verify the performance of the radio over the entire BLE frequency band.
Manufacturers use the same test setup for manufacturing tests because they are cost-effective and simple enough for operators to use. The production test is optimized by running the TX power and RX PER tests on only three frequency channels, the lowest, middle, and highest frequency channels, to quickly verify device performance across the BLE frequency band. This has allowed medical device manufacturers to accelerate production and minimize frequent correlation issues due to the various test settings used in design and manufacturing.
In this case, manufacturers ensure device quality by saving weeks of test development during the pilot phase, reducing time to market, and adopting effective test solutions that provide the required test coverage. did.
Case Study 2: Improve Yield on Wireless Control Surgical Machines
Manufacturers faced yield issues with high-end surgical machines, including wireless subsystems for remote control. The wireless subsystem was functioning properly until the failure began. This became a big issue and affected shipping. The failure was discovered only after the full machine was built and tested. When a subsystem failed, it took a long time to troubleshoot, repair, and retest. This caused a pile of inventory and a delivery error. To resolve this issue, we used a simple and cost-effective IoT signaling tester to perform a wireless module pre-screening test before installing the wireless module in the machine’s wireless subsystem. Identifying defective modules prior to installation has saved manufacturers significant testing and repair time. Ultimately, this allowed manufacturers to reach their daily production and yield goals.
Case Study 3: Increase production flexibility for contract manufacturers of small quantities of medical wearables
Leading consignment manufacturers have manufactured various brands of medical wearables. Its existing test solution was based on a non-signaling one-box tester. The test was run in non-signaling mode, so special test firmware had to be loaded on the device before the test. Then, after the test was complete, it had to be removed and replaced with the final product firmware. Maintenance of these large firmware sets for various products has been a pain for the manufacturing team. Operator mishandling was also an important risk to them, as they manufactured different devices from different customers. To increase production flexibility and eliminate operator processing errors, manufacturers have switched to IoT wireless testers that enable OTA test signaling with final production firmware. This streamlines the testing process and allows operators to easily switch between different product versions and brands. The tester also supports major short-range formats such as BLE 4.2, BLE 5, WLAN 2.4 GHz, and 5 GHz, so you can test devices in different wireless formats using the same test setup. Production flexibility is important for outsourced manufacturers to respond to volume fluctuations from customers.
Case Study 4: Improve manufacturing throughput for high volume wearables and reduce test costs
A major wearable maker was investigating a next-generation test platform. Part of the goal was to achieve higher throughput and reduce test costs without sacrificing test coverage. The company knew that quality could not be compromised in the medical industry. Existing test solutions were time consuming and burdensome for operators. This required manually putting the DUT in the shield box, running the test, removing the DUT from the shield box when the test was complete, inserting a new unit, and repeating the process. It was running in sequential mode. By switching to a test solution that allows parallel testing of multiple devices, test time has been significantly reduced. The operator can put four devices in the same shield box at a time and run the required TX and RX tests on all four devices at the same time. When the test was complete, the operator removed them all and replaced them with four new units to continue the test. The parallel test feature allows manufacturers to reduce test time by more than four times, resulting in significantly higher throughput and lower test costs.
Connected medical devices are on an exponential growth trajectory. Adding wireless connectivity to medical devices brings tremendous convenience to patients, enables better medical delivery, and reduces medical costs. The success of this megatrend depends on the ability of medical device manufacturers to produce reliable, high-quality connected medical devices that do not fail prematurely in the field. Effective manufacturing testing plays an important role in ensuring the quality of devices by capturing defective or slightly passed devices that can fail in end-user applications. By choosing an effective testing strategy, you can minimize this risk without incurring high manufacturing costs.
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