Author's Latest Posts


Transforming Vision Inspection With Machine Learning


How auto-manufacturers can apply ML & AI algorithms to enhance image analytics on their factory floor and to ensure higher product quality? Discover the next generation visual inspection in our new case study. In this case study , you will learn about: Current limitations of image inspection in the manufacturing industry. The O+ end-to-end solution, which brings machine learning and... » read more

Industry 4.0 And The Rise Of QPaaS


McKinsey & Company frames this shift as a matter of moving the industry from its current approach of “firefighting” – responding to failures and vulnerabilities after they’re brought to OEMs’ attention – toward proactively preventing such episodes in the first place. How can the industry achieve this objective? By embracing quality protection as a service (QPaaS) — an approach... » read more

Cloudy With A Chance Of Better Analytics


How can you create product-oriented analytics on the factory floor while leveraging cloud capabilities at the same time? In our article, you will learn about: The importance of moving from machine analytics to product analytics. The benefits of migrating your analytics infrastructure to the cloud. How OptimalPlus successfully partnered with AWS to create an end-to-end analytics so... » read more

Defect Image Classification And Detection With Deep Learning


Authors: Dan Sebban and Nissim Matatov Inspection means have increasingly been incorporated into typical manufacturing of boards, substrates and/or systems. A significant number of automatic inspections rely on the analysis of images that are acquired by a multitude of means such as optical, X-ray, infrared, acoustic microscopy. In contrast to automatic inspections, traditional visual inspec... » read more

3 Big Data Mega Trends For 2020


What are the greatest trends and challenges that will define the automotive and semiconductor industries in 2020? Our e-book delves deep into three of these megatrends: Artificial intelligence and machine learning at scale Holistic quality solutions Connected supply chains With automotive and semiconductor manufacturers under mounting pressure to manufacture products of the hig... » read more

5 Steps To Becoming A Data-Driven Manufacturer


What does it take to become a data-driven manufacturer. There are five fundamental steps: Get the data you need Organize the data Analyze and present the data Automate analytics Innovate Companies constantly strive to become data-driven. In this way, their decisions can become more objective and more likely to achieve the desired results. In fact, many companies understand t... » read more

The 3 Main Obstacles To Zero DPPM And How To Overcome Them


As we all well know, there are multiple mission critical applications in today’s “Age of Smart,” that are calling for zero DPPM (defective parts per million) in semiconductors and electronic systems. In industries such as automotive, medical, aerospace, and more, where lives are at stake, defective parts are not an option. The quality imperative However, with the ever-growing complexity o... » read more

Big Data Trends Shaping Industry 4.0


In today’s highly competitive economy, automotive OEMs are under pressure to shorten production cycles and fully leverage production capacities, with no compromising of quality and safety. This ebook covers the three big data mega trends for the automotive value chain: ML and AI to streamline processes Actionable Insights Optimized product reliability Don’t lag be... » read more

Smart Manufacturing Solutions: Build or Buy?


Enterprise smart manufacturing platforms have become an important part of the manufacturing ecosystem, especially in domains such as semiconductors and electronics. McKinsey & Company estimates, for example, that the quantity of process, product, and machine data collected on a daily basis in a typical fab quickly exceeds terabytes. If you add to this in-line and end-of-line inspection as w... » read more

The 3 Big Data Mega Trends For Manufacturing


By Michael Schuldenfrei In today’s global, highly competitive economy, industrial companies are under intense pressure to lower manufacturing costs and streamline processes without compromising quality. Production managers are expected to contribute to improved business outcomes through ultra-efficient use of raw materials, near-zero production downtime, streamlined labor costs, and agile wo... » read more

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