The aspect of modern-day manufacturing processes is changing at a faster rate and becoming far more sophisticated than ever. There have been significant changes in manufacturing environments arising from a paradigm shift in customer demand and a shorter product life cycle. This has necessitated a higher level of manufacturing technology that can respond to changes in nature. In recent years, neural networks have emerged as a truly strong solution to address the changing demands and move manufacturing technology into a new era of intelligent manufacturing.
Notable Characteristics to Sway the Market, primarily benefitting the Manufacturing Sector
The industrial sector's growing complexity and volatility necessitates better decision-making, assuring low operating costs, higher productivity, and resource sustainability. With the introduction of new methods and techniques, there has been a recent surge in the market for using artificial neural networks in manufacturing. Today's technology enables people to benefit from computer precision through processing with both static and adaptive decision-making factors. Neural networks are computer systems made up of interconnected nodes that function similarly to neurons in the brain. In unstructured decision issues, artificial neural networks have the intrinsic ability to interpret the most ambiguous and complex patterns. ANN can discover hidden patterns and correlations in raw data using algorithms, cluster and categorize it, and learn and improve over time. Following are some of the notable characteristics of the ANN:
- Artificial Neural Network in manufacturing helps in performing advanced analytics for providing early warnings. Predictive analytics having inbuilt AI allows engineers to quickly combine and evaluate large amounts of data, and detect difficulties in the early stages of development, allowing engineers to take proactive steps to enhance outcomes.
- ANN enables to detection of future trends faster and more precisely with unique algorithms, ensuring continuous product quality by automatically monitoring the health of all manufacturing processes.
The leaders of today aspire to be the vision of change. They are focused on innovating and introducing efficient and reliable means of producing and moving physical goods while considering factors other than productivity, cost reductions, and risk reduction. Manufacturers must become flexible, adopt AI-driven business processes that avoid risk, and adopt groundbreaking technologies through deep operational insights and assured decision making to survive in the future. Manufacturers will be able to customize manufacturing operations to minimize cost and risk while harnessing data as an asset to generate innovative services and high-quality items that are only possible in a connected economy.
"Defense and Aerospace sectors are touted as the early adopters of ANN"
ANN Market to Gain Popularity during Forecast Period
Moreover, ANN is gradually gaining popularity as its broad list of benefits is too compelling for businesses to ignore. Due to its growing popularity, the techniques and models used in it are becoming standard tools in information engineering and project management. The manufacturing industry is expected to grow at a robust CAGR throughout the forecast period due to the increasing demand for estimating the mechanical properties of packaged foods based on provided technological data. According to the RationalStat Analysis, the global Artificial Neural Network (ANN) market is projected to grow at a CAGR of more than 20% over the period 2022-2028 to reach more than US$ 500 million by 2028.
The COVID-19, having positively impacted the growth of ANN, has made businesses realize the significance of AI, Machine Learning, and Cloud computing, and how these technologies can further help them recover from the impact of pandemics and drive automation in the future. This is also expected to fuel the adoption of ANN in the manufacturing sector.
However, the use of ANN-based intelligence machines is still in its development stage and is expected to evolve rapidly. As per the Lead Analyst at RationalStat, Artificial Neural Network will not replace conventional computers or remove programming, rather neural networks will complement the already established technologies. ANN will be coupled with traditional computer techniques and other AI schemes, such as knowledge-based expert systems, to create smart industrial systems.
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Co-founder and Director at RationalStat
Divyanshu is an experienced market research consultant. He helps growth-driven organizations and entrepreneurs understand market entry prospects, industry assessment, and grow their revenue strategically.