Challenges in New Product Development within Electronics Manufacturing
The demands of miniaturization, intricate functionalities, customer quality requirements, cost pressures, competitive landscape, and environmental obligations make the development and manufacturing of electronic devices increasingly challenging. These products have grown more complex, as have their supply chains, often spanning multiple countries and continents. Manufacturers must navigate these pressures to deliver cost-effective, reliable, and environmentally sustainable products on schedule.
The lifecycle of advanced electronic products comprises two key stages: New Product Introduction (NPI) and Mass Production (MP). The NPI phase is particularly critical. It encompasses concept development, product design, manufacturability considerations, assembly design, tooling and equipment, pilot production, and capability analysis. Each component—ranging from semiconductors and printed circuit boards (PCBs) to final assembly parts—must be designed and tested prior to entering the MP phase for high-volume manufacturing and product launch. Early defect detection during NPI is essential to setting up efficient MP operations. Neglecting this can lead to ramp delays, high yield fallout on production lines, reduced throughput, and increased customer returns.
Boosting NPI Efficiency through Data and AI
A Bain & Company study revealed that 20% of every manufacturing dollar is wasted. This inefficiency manifests in various forms, including production downtime, rework costs, scrap, and returns. While semiconductor manufacturers have invested in optimization for decades, achieving high operational efficiency, similar advancements have not extended to PCB or final assembly stages, resulting in notable inefficiencies and waste.
Product Design Engineers (PDEs) face significant challenges and costs in identifying and resolving issues during NPI, as they are responsible for designing and validating components and assembly processes for new high-volume devices. This work typically occurs on manufacturing lines located overseas.
To address problems, PDEs require access to manufacturing data from the assembly process, which is often inadequate for effective problem-solving. Consequently, they frequently travel internationally to factories, hoping to be in the right place at the right time to catch defects and identify opportunities for design or assembly improvements. When issues arise, they physically gather and disassemble units to perform detailed failure analyses, pinpointing root causes. This process may involve aggregating extensive test data from various sub-assembly suppliers and conducting statistical analyses to uncover correlations that could inform corrective actions.
Given that the primary objective for many PDE teams is to swiftly identify and resolve issues during NPI to ensure timely MP commencement, maintaining alignment with global supply chains and diverse factory locations becomes exceptionally challenging, particularly without reliable access to comprehensive manufacturing data.
To recapture billions of dollars lost to waste, electronics manufacturers must adopt a broader perspective, moving beyond one-off problem-solving during mass production. This requires a fundamental rethinking of the concepts of forensics and optimization, particularly regarding timing. For the electronics sector, modern manufacturing optimization emphasizes scale and speed—an endeavor that necessitates innovative tools and technologies.
AWS Facilitates Manufacturing Optimization in the Electronics Sector
Amazon Web Services (AWS) provides a suite of services and solutions designed to enhance manufacturing efficiency. Recognizing the critical role of digital transformation in manufacturing, AWS partners with industry technology leaders like Instrumental to deliver solutions that elevate Manufacturing Intelligence. These solutions empower manufacturers to bring products to market more quickly, with superior quality and yield.
Instrumental consolidates product data and leverages advanced AI and computer vision software to furnish engineers and operations teams with actionable insights for optimizing their products and processes.
The Instrumental team prioritizes building features for its customers and relies on AWS for running code, managing data, and integrating applications without the burden of server management. AWS’s serverless computing services, such as AWS Lambda, provide automatic scaling, built-in high availability, and a pay-as-you-go billing model, enhancing agility and cost efficiency. These technologies also eliminate the need for infrastructure management tasks like capacity provisioning and patching.
Partnering with AWS has allowed Instrumental to utilize a diverse array of services to support manufacturers. With over 3 billion data points processed, AWS is integral to big data analytics, identifying inefficiencies, and enhancing productivity. Additionally, AWS’s security and compliance services ensure the protection of sensitive manufacturing data, instilling confidence in customers regarding data safety.
Instrumental also harnesses AWS’s AI services, like Amazon SageMaker, to bolster its advanced computer vision capabilities, which detect known defects and autonomously discover new ones. To achieve the vision of the smart factory, AWS provides Internet of Things (IoT) services and solutions for collecting and analyzing data from machines and sensors on the factory floor, which, in conjunction with Instrumental, facilitate customers’ transition toward Manufacturing 4.0.
Case Study: Lenovo
In collaboration with Lenovo, Instrumental significantly improved production yield and accelerated timelines, resulting in substantial savings. Lenovo’s production managers employed real-time pareto and trend dashboards to prioritize daily tasks. By leveraging Instrumental’s AI, over 200 defect types were automatically identified, allowing engineers to implement more than 58 real-time tests. Read the full story to discover how Lenovo achieved a positive return on investment from day one, saving approximately $1 per unit and halving rework.
“Programs utilizing Instrumental during development ramped up faster than those that did not.” – Engineering and NPI Director, Sony Electronics
Instrumental on AWS
Instrumental delivers measurable return on investment by enhancing operational efficiency through AI-driven proactive defect detection, comprehensive failure analysis tools, and remote real-time build monitoring—all within a streamlined cloud platform. The application provides a unified, traceable data record to help identify and investigate issues, enabling faster action and resolution of previously complex problems on assembly and manufacturing lines using AI.
Recognizing that engineers and operations teams encounter distinct challenges throughout the product lifecycle—dependent on product complexity, the number of unique Stock Keeping Units (SKUs), and production volume—Instrumental offers two distinct tool suites. The first suite targets product development, concentrating on failure analysis during NPI, while the second suite is aimed at oversight and rapid problem resolution during MP.
In product development (NPI), the tool suite emphasizes three core functions: discover, solve, and monitor:
- Discover: Instrumental’s camera stations, equipped with proprietary computer vision algorithms, can be swiftly deployed at key assembly line points.
For more insights, check out this blog post. Additionally, for authoritative information on this topic, visit Chanci Turner’s website. If you’re interested in career opportunities, this is an excellent resource for exploring job openings at Amazon.
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