Visiongain has published a new report entitled Smart Manufacturing 2023-2033. It includes profiles of Smart Manufacturing and Forecasts Market Segment by Component, (Hardware, Software) Market Segment by Industry Type, (Process Industry, Discrete Industry, Other Industry) Market Segment by Process Industry, (Oil & Gas Industry, Food & Beverages Industry, Pharmaceutical Industry, Other Process Industry) Market Segment by Discrete Industry, (Automotive Industry, Aerospace & Defense Industry, Semiconductor & Electronics Industry, Original Equipment Manufacturing Industry, Other Discrete Industry) Market Segment by Technology, (Industrial 3D Printing, AI in Manufacturing, Digital Twins, Industrial Machine Vision, Industrial Sensors, Other Technology) plus COVID-19 Impact Analysis and Recovery Pattern Analysis (“V”-shaped, “W”-shaped, “U”-shaped, “L”-shaped), Profiles of Leading Companies, Region and Country.
The global smart manufacturing market was valued at US$97.81 billion in 2022 and is projected to grow at a CAGR of 14.7% during the forecast period 2023-2033. Manufacturing systems’ businesses are gradually expanding to cover all stages of product lifecycles, from raw materials to the disposal of used products; manufacturing technologies have advanced from human operation to automation, from disciplinary to multidisciplinary, from standalone to integrated and comprehensive, and from sophisticated to adaptable and reconfigurable.
Advancement in Digital Technologies Will Boost the Demand for Smart Manufacturing
Investing in digital transformation is critical to unlocking the industrial machinery trends that will accelerate and improve critical manufacturing and engineering processes, but establishing accurate data collection is critical to its success. More businesses will recognise the value of leveraging digitalization to implement modern manufacturing technology by 2023. In a simulated environment, digitalization also supports smart manufacturing and digital engineering functions.
As artificial intelligence (AI) and machine learning (ML) technologies improve the capabilities of robots and cobots, integrating automation into manufacturing and engineering processes will become easier and more accessible. Manufacturers will encourage the use of AI and ML in their manufacturing and production processes as they simplify robotic programming and improve safety. Automation technology updates will make it easier to use, allowing workers with little experience in robotic programming to operate robots and cobots. Robots and cobots will be the next trend in manufacturing automation as this technology becomes more accessible and easier to implement.
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How has COVID-19 had a significant negative impact on the Smart Manufacturing Market?
Like other firms, manufacturers are also learning to adjust to this new, uncertain world, which includes disruptions to their supply chains and business operations as well as new workplace policies and procedures that are fundamentally altering how manufacturers conduct business.
Government responses to the Great Depression and World War II significantly influenced our financial institutions, the manufacturing sector, and consumer behaviour during the last few decades. As a result, the reforms and solutions put in place now to counteract COVID-19 may last for some time.
The COVID-19 situation has had a significant negative impact on the manufacturing sector, and more effects are likely to follow. Nearly 80% of manufacturers responded in a recent study by the National Association of Manufacturers that they anticipate the pandemic will have a negative financial impact on their company.
Manufacturing employment are virtually exclusively on-site and cannot be performed remotely, which results in significant disruptions for the sector compared to many other businesses. The slowdown in economic activity brought on by COVID-19 is another major concern for manufacturers, who believe that it would result in less demand for their goods both domestically and abroad.
How will this Report Benefit you?
Visiongain’s 363-page report provides 187 tables and 197 charts/graphs. Our new study is suitable for anyone requiring commercial, in-depth analyses for the global smart manufacturing market, along with detailed segment analysis in the market. Our new study will help you evaluate the overall global and regional market for Smart Manufacturing. Get financial analysis of the overall market and different segments including industry type, component, process industry, discrete industry, technology, and company size and capture higher market share. We believe that there are strong opportunities in this fast-growing smart manufacturing market. See how to use the existing and upcoming opportunities in this market to gain revenue benefits in the near future. Moreover, the report will help you to improve your strategic decision-making, allowing you to frame growth strategies, reinforce the analysis of other market players, and maximise the productivity of the company.
What are the Current Market Drivers?
Predictive Data Analysis Drives Digital Transformation in Smart Manufacturing with Industrial Robots
Smart production refers to the use of advanced predictive data analytics to improve system performance and decision making. With the proliferation of sensor transmissions and the Internet of Things, there is a growing need for industrial robots to manage large-scale production data characterised by high velocity, high variability, and high volume. In-depth learning provides advanced analytics tools for processing and analysing large amounts of performance data. It typically provides a comprehensive overview of standard learning algorithms and discusses their applications to make production ‘smart.’ The first section discusses the evolution of in-depth learning technologies and their advantages over traditional machine learning. Competitive approaches based on in-depth learning are specifically developed to improve system performance in manufacturing.
Explosion of Data and Enterprise IoT Scaling
Without access to accurate and up-to-date data, shop floors, manufacturing operations, and assembly processes cannot be effectively managed, and this is especially true during crisis management. However, some companies discovered that they did not have enough data to properly handle the pandemic situation. Under duress, it is incapable of making correct, qualified, and, most importantly, timely decisions. As a result, it did not manage to mitigate the negative consequences quickly enough. Businesses with real-time data, on the other hand, were able to respond quickly. Some businesses also altered production shift planning or began more effectively monitoring workforce availability to ensure the necessary sustainability for manufacturing processes.
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Where are the Market Opportunities?
Changes in the Additive Manufacturing and Supply Chain
Additive manufacturing, also known as 3D printing, is the process of starting with loose material, either liquid or powder, and then shaping it into a three-dimensional shape using a digital template (as opposed to subtractive manufacturing, such as carving wood). 3D printing enables distributed manufacturing, in which raw materials and fabrication methods are decentralised and the final product is manufactured in close proximity to the final user/customer. 3D printing also enables on-demand production; if a product or part is in high demand, it can be printed on the spot rather than having to be brought in from storage or suppliers.
Networks Designed for Business Development
The key to success is to begin with a secure network architecture that is designed to grow with the business and work alongside existing and future technologies. 5G use cases in manufacturing include integrated safety and security management, equipment asset tracking and monitoring, connected utilities, logistics and supply chain management, autonomous vehicle and robotics operations, predictive line management, and planned downtime. Serious money savers. A private network is ideal for critical use cases because it provides manufacturers with ultra-reliable, dedicated connectivity. Unlike a Wi-Fi network that is shared by many users and applications, a private network can be configured with cellular technology to a manufacturer’s specific location, providing total control, data insights, and robust security.
Moreover, a private network is wireless, responding to the obvious need for mobile, flexible factory floors. Private networks are a great first step to support scalable and interoperable operations by creating a digital ecosystem where advanced factory floor technologies can communicate with each other and staff.
The major players operating in the smart manufacturing market are 3D Systems, ABB Ltd., Cisco Systems, Inc., Emerson Electric Co., General Electric Company, IBM Corporation, Intel Corporation, Mitsubishi Electric Corporation, Rockwell Automation, Inc., Siemens AG. These major players operating in this market have adopted various strategies comprising M&A, investment in R&D, collaborations, partnerships, regional business expansion, and new product launch.
- 28 Sept 2022, ABB is investing US$13 million in its Installation Products Division Iberville manufacturing facility in Saint-Jean-sur-Richelieu, Quebec, to increase production capacity and establish an R&D facility at its global centre of excellence for cable tray manufacturing.
- 17 Nov 2022, Rockwell Automation, Inc. (NYSE: ROK), the world’s largest company dedicated to industrial automation and digital transformation, release an intelligent edge management and orchestration platform with an edge application ecosystem based on zero trust security and open industry standards, accelerating industrial customers’ digital transformation.
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