INTELLIGENT TEST AUTOMATION IS THE FUTURE Improving processes and quality with automated test in today s market

Transcription

1 WHITE PAPER INTELLIGENT TEST AUTOMATION IS THE FUTURE Improving processes and quality with automated test in today s market It would be folly to underestimate the crucial role the flow of information plays in the physical aspects of advanced manufacturing. 1 Successful product testing is critical to quality and involves many factors, three of the most important of which are test automation, test data management, and digital transformation. These elements can have a big impact on a company s bottom line and need to be weighed carefully. This white paper examines these three critical issues, how each of them influences decision-making around quality improvement and Return on Investment (ROI), and how they can work in synergy within Intelligent Test Automation. 1. TEST AUTOMATION SHOULD EQUAL QUALITY PLUS SPEED When companies decide to move from a manual testing process to an automated one, there are typically three business goals driving the decision: 1. Lower costs 2. Improved process consistency 3. Increased and facilitated data collection When business leaders decide to automate, it is often as a result of an ROI calculation that reveals that automating would be a worthwhile investment; this is crucial because these leaders need to be certain that long-term costs are lower with automation before deciding to implement it. 1. Industry 4.0 and manufacturing ecosystems: Exploring the world of connected enterprises by Brenna Sniderman, Monika Mahto, Mark Cotteleer, Deloitte University Press, In some cases this is strictly due to savings achieved through eliminating manual labour costs, but often it is also the result of other factors like fewer operational errors, better data collection, and more consistent processes.

2 Automated testing is now used across all product types whether they are high-volume/low-cost or low-volume/high-value products. The type of testing equipment used will depend on which of these two product types are being tested. With high-volume/low-cost products, test times are often critical so saving seconds on product testing is key when choosing test equipment. With more complex, high-value products, the ability to perform many in-depth tests is most important, so the test equipment tends to be more sophisticated and costly. Mission-critical products products that are used for human protection or to prevent defective functioning where consequences are potentially disastrous are tested multiple times to ensure correct operation. This is particularly true in industries such as aerospace, medical, utilities, and defense where product failures could have large-scale, destructive results. Companies that produce mission-critical products like aircraft components, for example, were early adopters of automated testing because their products simply have to work well in order to avoid life or death situations. Inputs for Automated Test in Manufacturing Process Quality Speed When a new product is introduced, it can be challenging to decide what needs to be tested, when it should be tested, and whether the testing should be automated. For this reason, companies rely on New Product Introduction (NPI) teams, who work closely with R&D and Reliability groups to make these types of decisions. The R&D group provides test data from several sources, including Design Verification Test (DVT) results, characterization tests, and prototype testing. This data, as well as the software, instruments and test processes used to collect it, become critical input for manufacturing and answers such questions as what can be re-used? and which instruments, test procedures, test software, limits, and configuration settings are best to use? Meanwhile, the Reliability group provides insight from Highly Accelerated Life Testing (HALT) to help create screens, including the Highly Accelerated Stress Screen (HASS). These manufacturing screens can be used to detect critical issues like infant mortality failures. Reliability engineers often work with manufacturing teams to streamline testing processes to decide on configuration settings and specification limits. For example, some test operations performed by R&D might be seen as unnecessary and wasteful in a manufacturing setting and may also add wear-and-tear to the product. Engineers who work on NPI teams help decide what test procedures to do, when to do them, and what settings to use when performing them. Once decisions are made about what to test, the team then decides which tests should be automated and which will be performed manually. For automated tests, the team also needs to decide which ones can be done with off-the-shelf testers and which require custom test systems to be built. White Paper / P2

3 Automatic Test Equipment Categories in Manufacturing There are two types of Automatic Test Equipment (ATE) used in manufacturing: 1. Off-the-shelf ATEs, such as In-circuit Testers (ICT) or boundary scan testers, which can be purchased from vendors without large design efforts. 2. Custom designed ATEs that are built specifically for a particular product. Examples of custom ATEs include: Automated Optical Inspection (AOI) or Automated X-Ray Inspection (AXI) Functional testers used for the Acceptance Test Procedure (ATP) of subassemblies or final assemblies Screen ATEs, such as HASS systems, used to catch and fix infant mortality issues Sample Verification Testers (SVT) that are only used on about 2% of products Diagnostic ATEs, used to troubleshoot products that fail at any point in a process Based on these two ATE types, generic manufacturing plans can be created, which can be instructive for understanding how automated test fits with the rest of a manufacturing process. Making these decisions is not easy, and difficulties vary based on the type of product that a company builds. So not surprisingly, many of the details related to these decisions are both customer-specific and product-specific. 2. CONSOLIDATED TEST DATA AND SMART ANALYTICS Test data is crucial for making continuous quality and process improvements across global supply chains. It provides valuable insight on manufacturing and test processes, and enables real-time machine monitoring and information on system status. It also helps derive KPIs that may include elements such as first pass yield, throughput, top defects, and Takt Time. Combined with bidirectional communication, this type of technical expertise enables manufacturers to successfully navigate Industry 4.0. The following three sections describe concrete examples of how to maximize the value of measurement data if it is consolidated from every tester within an enterprise system, and aggregated with data from manual stations (assembly, QA, packaging, etc.). White Paper / P3

4 Solving Manufacturing Execution Issues Manufacturing Execution Systems (MES) usually address factors like inventory control and yield. They allow information to be quickly gathered about: Pass/fail events on stations (which allows for the calculation of first-pass yield and roll-through yield) Troubleshooting, rework, and retest times Test times Locations of different serial numbers in the process and the time incurred from assembly to shipping Continuous Yield Improvement When yield problems such as a drop in first-pass yield from one week to the next occur, operations personnel must quickly identify what happened. If all automated testers are linked into an enterprise system, then the following questions can be answered rapidly: 1. Which station is seeing the biggest yield drop? For example, are most failures happening on HASS, on final ATP, or on SVT? Knowing this can help isolate the root cause of a problem. If all measurement data and results from all testers are going into an enterprise system, it becomes easier to find an answer. 2. Once the problematic station is identified, which tests or measurements are failing most often? Remember that a station runs a sequence of multiple measurements and compares them to specification limits. If all this measurement data is in an enterprise software system, it can quickly be determined which measurements are failing most often. This information is typically critical for root-cause analysis. 3. Are there any SPC issues on the station, such as Cpk values, falling from week to week? For example, once the problematic measurements are known, is it possible to look at the enterprise system for historic Cpk values over the past several weeks? If so, a pattern of lowering Cpk before parts begin failing may emerge. The key takeaways would be: what can be learned from the pattern and when did it start? 4. Given the information gathered above, is the issue related to subassemblies or the top-level assembly? This can usually be deduced from comparing measurement results across different testers, as well as results from troubleshooting and rework. If the problems are occurring at a subassembly, then the same set of questions can be asked about how it was manufactured. As the steps above demonstrate, inputting all measurement data from all testers into an enterprise software solution for consolidation and analysis can speed up resolution time for many yield problems. White Paper / P4

5 Accelerating Failure Analysis The previous section discussed how yield issues could be resolved through consolidated test result analysis. Likewise, you can get to the root cause of failures faster using a similar approach known as Failure Analysis. Failure Analysis is the process of looking at failures in manufacturing and in the field to: Learn why a given failure occurred Take corrective action to prevent future failures Failure analysis is often initiated when a part fails during manufacturing. A technician is then assigned to fix the problem and get the unit working. Keeping track of common problems and fixes is a valuable benefit of failure analysis. When parts fail in the field or are returned, company technicians follow a similar troubleshooting pattern to understand the failure, often using an automated tester to determine which measurements are failing. Technicians typically look up the serial number history to find out what the part measurements were at the time of manufacturing, and if it went into troubleshooting or rework at that point. Engineers working with returns often group failed parts into categories and create Corrective And Preventative Actions (CAPA) for each failure category. These CAPA results are shared with R&D, Reliability, and manufacturing to improve the design or production process. By using enterprise software tools to analyze consolidated test data, sources of failure can be quickly, consistently, and cost effectively identified and eliminated. 3. DIGITAL TRANSFORMATION IMPACTS TRADITIONAL MANUFACTURING One of the biggest challenges facing current manufactures is the speed at which technological changes are taking place. Digital transformation in the current market place which includes factors like Industry 4.0, the IoT and the merging of IT and OT means that industry processes that used to take decades to fully materialize are now changing the manufacturing landscape at a much faster pace, forcing manufacturers to either adapt quickly or fall behind. The Fourth Industrial Revolution (Industry 4.0) Industry 4.0 is a term that essentially refers to the merging of traditional manufacturing and industrial practices with the current technological market. It includes factors like the Internet of Things (IoT), Digital Twins, and the White Paper / P5

6 Smart Factory IT + OT Industry 4.0 convergence of Information Technology (IT) and Operations Technology (OT), all of which represent advancements that come with their own set of challenges. A prime example is the rise of the so-called Smart Factory; a term that refers to the transition from traditional automation to fully connected systems that use continuous streams of data from connected operations and production to facilitate new demands. For manufactures, the Smart Factory is a doubleedged sword that promises smarter, more connected products, but also unprecedented competition. The benefits can be significant more efficient and agile systems, less production downtime, a greater ability to adjust to changes in a broader network but late adopters will pay a price. These changes in technology have facilitated the shift towards a more flexible, adaptive production system, but they have also made it necessary for manufacturers to make this shift, often at great cost. So what do manufacturers do to maintain or advance their position in the market? Well first they need to clearly understand the industry changes taking place. A New Market Reality One key change is the arrival of the IoT, a broad term that largely refers to the number of smart, connected products now proliferating the marketplace. This includes everything from mechanical or digital machines and computing devices, to animals or even people! The main stipulation is that they are all somehow interconnected (think an electric toothbrush with Bluetooth capability that sends data on your brushing habits to your smart phone or a heart monitor that delivers life-saving data to another interconnected mobile device). All of these products represent new opportunities and new competitive challenges that manufacturers need to be aware of. The challenge of combining IT and OT is another major change that cannot be ignored. Both IT and OT are associated with hardware and software infrastructure, but while IT is dedicated to managing, tracking, and supporting business operations and information systems, OT is devoted to designing, manufacturing, and repairing products. Bringing IT and OT together has the potential to solve certain manufacturing challenges in Industry 4.0, such as minimizing production downtime, facilitating the use of mobile technologies, and decreasing waste. But bringing these two departments together in a typical manufacturing plant,for instance, is not an easy task and requires a specific type of expertise. The concept of a Digital Twin represents yet another change associated with Industry 4.0, one that can be particularly instrumental in connecting industrial assets to the digital world. A Digital Twin is basically a digital model White Paper / P6

7 of a physical system that allows advanced testing and simulations to be performed in order to efficiently confirm designs. This type of technology can increase financial savings and reduce the amount of time and effort required in design. But again, this is an advancement that can be a huge benefit to manufacturers only if they take advantage of the technology in a timely manner. Superior Testing Is Key At the heart of this technological revolution is the need for these sophisticated and connected products to work well, and work well together, which is where targeted testing becomes key. Rather than do it all themselves, manufacturers must recognize the need to partner with companies that have the level of test expertise required to navigate the new market reality, which includes extensive knowledge of ATEs. Conclusion INTELLIGENCE IN TEST AUTOMATION IS THE FUTURE As a global Test & Quality Solution leader, Averna partners with product designers, developers and OEMs to help them achieve higher product quality, accelerate time to market and protect their brands. Founded in 1999, Averna offers specialized expertise and innovative test, vision inspection, precision assembly and automated solutions that deliver substantial technical, financial and market benefits for clients in the aerospace, automotive, consumer, defense, life sciences, semiconductor, telecom and other industries. Averna has offices around the world, numerous industry certifications such as ITAR registration, and is partnered with National Instruments, PTC, Keysight Technologies, M3 Systems, Ettus, MaxEye Technologies and JOT Automation. There is no doubt about it: intelligent test automation is the future. Factors like automated testing that lowers cost while providing more consistent processes, test data that is key to consistent quality and process improvements, and an unrelenting digital transformation that continues to blur the lines between traditional manufacturing and the present technological market are proof that, in fact, the future is already here. In this new market reality, manufacturers need to adapt quickly to keep up with the competition. There is a great ROI in automation that generates value by reaching business objectives such as time-to market. But it must be deployed in digital transformation to ensure future success in an increasingly competitive Industry 4.0. To bring clients cutting-edge Test & Quality solutions, Averna thinks outside the box. And to celebrate almost 20 years as a global solutions leader, we re sharing our hard-earned expertise on RF, automation, vision systems, wearables, medical devices, station replication and more. averna.com Canada United States Mexico Europe Japan Averna is a trademark of Averna Technologies Inc. All other brand names, product names or trademarks belong to their respective holders Averna. All rights reserved. 09/2018