TECHNOLOGY

Human-based inspection fails to produce consistent and standard results, which is a major challenge for modern manufacturing. Manufacturers strive to apply a standard measurement for the inspection of their products regardless of the time, the site and the worker performing the inspection.

Based on our research, manufacturers spend over $18B every year on manual visual inspection to ensure they meet customer requirements.  In most markets and across most industries, labor costs are on constantly rising. In some markets regulators encourage manufacturers to automate tedious inspection processes for various reasons. Often, it is not only a matter of cost. In many markets it has become a question of availability of skilled workers, who have become a scarce resource. Shortages in quality control workers often create a bottleneck in production. In a competitive marketplace, time-to-market is a critical factor in the successful introduction of new products and should not be delayed due to quality control issues. At the same time, manufacturers would prefer to engage their skilled workforce in higher-value activities with better return on investment and higher economic gains, such as analyzing and eliminating defects.

As part of their Industry 4.0 strategy, smart manufacturers are looking for ways to leverage artificial intelligence, robotics and big data to stay ahead of the game. In recent years manufacturers have shown increased interest in machine vision technology as an enabler of Good Manufacturing Practices (GMP) as well as  trackability.

An automated, smart visual inspection solution can offer smart manufacturers access to data that was not available in the past. A comprehensive database that includes inspection results with images of defect and defect-free products is a gold-mine of information that can be transformed into actionable intelligence. With the help of big data analytics technology manufacturers, OEMs and ODMs can analyze and track quality, trends, common defects and evolving quality issues, as well as proactively introducing improvements in the production process, product design and supply chain management.

In a survey conducted by Tata Consulting Services (TCS) “Product quality and tracking defects” was ranked with the highest priority among the other potential drivers and benefits of using big data in manufacturing.

As manufacturers increasingly adopt mass customization and endorse personalization in production, they seek ways to deal with increased variance in their production environment. Variance in products, models and design, as well as in materials and components is becoming a major challenge. In order to address increased variance, manufacturers require flexible inspection technology as a key step in their journey towards comprehensive digital transformation.