Turning Data Into Action: The Future Of the Surface Inspection Market

 The surface inspection market is expected to grow from USD 3.5 billion in 2021 to USD 5.3 billion by 2026, at a CAGR of 8.6% during the forecast period.

Increase in wages of manual workforce in various countries is the major driver as this would prompt companies towards automation to reduce cost. Advancements in CMOS technology make them increasingly appealing for industrial machine and helping surface inspection market to expand in more industries and offer for more complicated applications. CMOS sensors have a high frame rate and high resolution, i.e., a number of pixels; low power consumption; and improved noise characteristics, quantum efficiency; and color concepts have allowed them to be used in several applications, including the food & beverage industry, electrical & electronics industry, traffic, and medical & pharmaceuticals.

 

Integration of surface inspection system with artificial intelligence (AI), deep learning, and big data analytics would change the business landscape significantly. employs neural networks and pattern recognition to generate deep insights that would otherwise be incomprehensible to other types of programs.  Traditional image sensors can only enable a portion of inspection process automation. Sensors cannot adapt to diverse materials and shapes for the objects to be inspected, and adjustment is not possible unless sophisticated expert knowledge is available. However, an automated visual inspection technology based on AI and deep learning is capable of defecting different types of objects and is easy to set up by integrators, manufacturers, and end users as well for the automation of inspection processes. 

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 Deep learning, an advanced technology based on AI's higher intelligence, allows for the rapid identification of defective parts and products that must be removed from the assembly. Images captured by smart cameras/cameras are used to teach the software every detail, just like humans. It offers an algorithm to the deep learning suite, and, as the name implies, it learns from the details that are fed to it. The deep learning technology and AI utilizes a defect detection algorithm, input (lighting/imaging) technologies that highlight defects and driving technology that adapts to object profiles to deal with a wide range of objects and defect types. In 2019, the US Food and Drug Administration (FDA) announced plans to regulate AI systems that can update and improve themselves as they consume more training data. The agency issued a white paper proposing a regulatory framework for determining how medical products that use AI should seek approval before being released to the public. It is the FDA's most significant step to date toward formalizing oversight of products that use machine learning (ML).

The surface inspection market for automotive vertical is expected to grow at highest CAGR during the forecast period. The automotive industry requires surface inspection of complex parts such as cylinder bores and crankcases, and reflective painted parts, which are challenging to inspect with the human eye. Surface inspection systems are also required for areas inaccessible to humans and for applications that cause health hazards. The automotive industry is flourishing in most developed and emerging regions. This is due to demand from Germany and France, which are leading automobile manufacturing countries. Europe’s open economy is attracting various companies to the region. European governments are also compelling to manufacture electric vehicles. Initiatives taken by the French government’s 10-year plan have further propelled the automotive industry in Europe.  The automotive industry is witnessing decent growth in emerging countries due to various factors like increasing wages and decreasing unemployment due to industrialization. There is fierce competition in the market, with countries other than the US, Japan, and Germany manufacturing cars at lower prices.

The surface inspection market for software is expected to grow at highest CAGR during the forecast period. Development in hardware would reach saturation earlier after which software would have to aid innovation and in making systems optimum. Other components are finding replacements, but camera and software remain unreplaced, making their demand unreduced. Recent advancements in software for surface inspection systems have fueled its market with more enhanced big data analytics, artificial intelligence, and self-learning capabilities. Surface inspection software vendors, such as elunic (Germany), Bluewrist (Canada), and Nanonets (US), integrate deep learning and AI concepts with their software solutions and provide a high level of flexibility in the application and control of surface inspection systems. 

This software offers the flexibility of customization; and their capability to work with multiple hardware configurations allows the integrators to offer better and cost-effective solutions, especially for SMEs and as local bakeries, plastic and bottle manufacturing plants, and electrical & electronics SMEs that develop small components and accessories, for example, OTG cables, smartphone charging cables, headphones, and other electronic consumer products that require inspection systems Also, software contributes significantly to the cost of a surface inspection system and profit margin would be more for software manufacturing companies. The surface inspection market is moving towards robotic cell and 3D technology where software has a more important role.

The demand for collaborative robots (cobots) based inspection cell systems is expected to grow due to the ability of cobots to work safely alongside humans and better return on investment (RoI) than traditional industrial robots The robotic vision systems and sensors are used with industrial robots and cobots to ensure increased productivity. Collaborative robots are becoming more popular because they allow humans and robots to work effectively together in open or uncaged environments. They are widely adopted not only in small and medium-sized businesses but also in large-scale, traditional industries like automotive. The demand for collaborative vision systems is increasing due to the fast-changing nature of industries. 

This scenario is observed in the consumer goods industry, specifically packaging, where the shape, size, surface, or weight of the packaging is constantly changing.  Further, the demand for collaborative robots (cobots) based inspection cell systems is expected to grow due to the ability of cobots to work safely alongside humans and better return on investment (RoI) than traditional industrial robots. Therefore, they can be used to inspect hard to reach areas. Currently there are very few companies such as Kitov (Israel), ISRA VISION (Germany), Cognex (US), KEYENCE (Japan), and VITRONIC (Germany) which are offering robotic cell solutions. For instance, KEYENCE (Japan) offers XG-X Series and CV-X Series image processing systems that can be directly connected to industrial robots developed by worldwide manufacturers. Surface inspection is performed by traditional industrial robots and collaborative robots (cobots) in medical and pharmaceuticals, food and packaging, non-woven (inspection of face masks), automotive, and postal and logistics (palletizing and depalletizing). Therefore, it is a very lucrative opportunity for surface inspection manufacturers/integrators to invest in this technology.

 

APAC is expected to dominate the market by capturing a share of nearly 38% by 2026. The market is driven by Increasing investments in automation by automotive and electrical & electronics companies, especially in China, South Korea, and India, is expected to be the key driver for the market in APAC. Hence, with automation, the growing demand from automotive, semiconductor, electrical & electronics, and food & packaging industries in APAC is expected to drive the surface inspection market during the forecast period. China is expected to recover from the manufacturing slowdown due to COVID-19 in the coming years, and South Korea, India, and Thailand are pushing for further automation. Also, the increasing adoption of collaborative robot-based vision inspection systems in industries such as wood & furniture and automotive is another key trend that has fueled the demand for robotic cell-based surface inspection systems in the region. APAC has emerged as a major manufacturing hub, which is boosting the demand for surface inspection systems in this region.

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