How AI can make a manufacturing business more robust?


1. Where technologies, such as AI, can improve manufacturing businesses’ output.

While your organization may not be the next Skynet, most manufacturers are surprised to see how quickly commercial solutions are adopting artificial intelligence to improve or transform traditional manufacturing processes. As you can see, artificial intelligence is rapidly being introduced into commercial solutions across the entire manufacturing value chain. In the manufacturing industry, AI machines are constantly creating the future for our improvement and convenience. The scope of artificial intelligence in the manufacturing sector is unusually wide, from real-time equipment maintenance to more advanced supply chain models that allow your business to adapt to an ever-changing market. 


Artificial intelligence algorithms can also help streamline manufacturing supply chains by stimulating market demand in advance. AI can also give manufacturers more control over their supply chains, from capacity planning to inventory monitoring and management. In addition to product development and the manufacturing process, AI can also improve manufacturing supply chains. As AI collects real-time data, manufacturers can constantly monitor their warehouses and plan their logistics better. 


With the help of artificial intelligence, manufacturers can significantly reduce labor costs while increasing the overall productivity and efficiency of their factories. With AI-driven predictive maintenance, manufacturers can increase efficiency by reducing equipment failure costs. Using AI and machine learning, manufacturers can improve operational efficiency, launch new products, fine-tune product designs, and plan future financial actions to advance AI transformation. 


From significantly reducing unplanned downtime to improving product design, manufacturers are applying AI-driven analytics to data to improve efficiency, product quality and employee safety. Today, senior executives from the manufacturing industry are investing in AI to improve operational efficiency, productivity, and productivity. According to Capgemini, equipment maintenance and quality are the main projects for the transformation of AI in manufacturing operations today. The adoption of AI for improved and efficient production and ongoing maintenance is gaining momentum as manufacturers understand the importance of AI in identifying and maintaining a useful, adequate, and timely production line, and the role of technology in reducing downtime. 

2. What aspects do businesses need to consider with AI when using it to become more agile? 

Industry 4.0 aims to identify opportunities to automate manufacturing processes and analyze data to improve manufacturing efficiency. Industry 4.0 is the automation of manufacturing through smart technologies with a focus on automation, real-time data, and machine learning. The concepts and technologies of Industry 4.0 can be applied to all types of industrial companies, including discrete and process manufacturing, as well as oil and gas, mining, and other industrial sectors. Smart Manufacturing Technology, or SM for short, can be defined as a technological approach that utilizes networked machines to control production. 


Smart technologies provide cognitive awareness of objects by using complex technologies such as the Internet, artificial intelligence, and machine learning to create intelligent manufacturing environments. Artificial intelligence can collect a combination of data from sensors, machines, and people and then apply it to algorithms designed to optimize operations or reduce production. Artificial intelligence is the process of accelerating human knowledge, aimed at obtaining information and determining the rules for transforming data into some useful and required parts, particularly with the help of machines, in particular with the help of computer systems, also known as machine intelligence. 


Digital transformation is the use of 21st-century information technologies (elastic cloud computing, big data, IoT, and artificial intelligence) to incrementally improve business process capabilities across an organization’s value chain. It is crucial to use guidelines and technologies that facilitate digital transformation; such as cloud computing, methods of processing massive amounts of data in a short period of time, artificial intelligence (AI), etc. 


Digital transformation is a spectrum, and at the far end of the spectrum, you will find highly digitalized manufacturing companies working to implement real Industry 4.0 implementations. Manufacturers will need dedicated teams to address this transformation, such as digital command centers and digital business groups tasked with leading the adoption of new digital technologies. As the semiconductor industry continues to integrate smart manufacturing technologies into the manufacturing of core electronic devices used in all other sectors, high-tech manufacturing industries will experience a digital transformation that will lead to new product development and product quality management technologies. processes and product conformity. For manufacturing businesses, the advent of artificial intelligence (AI) will change the source of value creation, new business models, and value-added services such as mass personalization, preventive maintenance, and “product maintenance” (i.e., the process of generating revenue streams for manufacturers from services, related to your product). 


To successfully implement AI and digital technologies in the enterprise, manufacturers must start with a scalable infrastructure that can handle mission-critical workloads—an enterprise-grade data-sharing model that prevents silos and end-to-end connectivity. The process involves combining advanced manufacturing technologies and operations with smart technologies integrated into organizations, people, and resources. Smart factories have smart machines that work with industry experts to optimize processes. 


Connected factories or smart factories, built using sensors and the cloud are the way forward for manufacturing. Manufacturers are integrating advanced technologies including the Internet of Things (IoT), cloud computing and analytics, artificial intelligence, and machine learning into their manufacturing facilities and all operations. In fact, 34% of leaders in manufacturing are investing in AI and 19% are investing in machine learning-based programs to grow their workforce, solve critical problems and launch their organizations for long-term transformation. A large percentage of manufacturers are also developing “Machine Learning Engineers or Specialists” (33% currently, 70% in the next five years), “Cobot Experts” (29%), “Data Quality Analysts” and “Artificial Intelligence” Programmer/Solution “Programmer”.”. Designers” (26%). 


Various manufacturing technologies are becoming smaller, smarter, and more efficient. The Capgeminis’ research team found that predicting the likely failure of machines/equipment and recommending the best time to perform maintenance (condition-based maintenance) is the most common use case for AI in manufacturing today. 

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