Reasons to Invest in Digital Data and AI Tools in Manufacturing

But why should the manufacturing industry invest in digital data and artificial intelligence? How can technologies like machine learning, automation, robotics, IoT, edge computing, smart manufacturing, etc., help the sector become stronger and better? Let’s find out below.

Better Quality Control : There’s no point in increasing production if the final products don’t clear quality checks. AI technology also helps in maintaining and improving product quality by indicating the potential defect in a product. In fact, a report by Statista shows that 59% of manufacturers use artificial intelligence for quality control.

Production Agility : Today’s customers are not happy with limited selections and stock designs. They prefer personalized products and more variety to choose from. Achieving such production agility without increasing costs is not possible unless the manufacturer uses the latest technology. For example, MUD technology helps create more varied parts through injection molding for the same cost and within the same duration. 

Predictive Maintenance : Predictive maintenance is the most important aspect of smart manufacturing. The last thing an enterprise wants is an unexpected equipment breakdown, which disrupts the entire production cycle. Predictive analytics use the data provided by IoT devices to determine when a machine needs maintenance. These sessions can be scheduled during off days so that the production period continues to be free of disruptions. It also helps detect minor issues in the equipment and repair them before they cause greater damage.

Optimizing Operations : Automation, robotics, better communication, data-driven decision-making models, etc., can optimize factory operations and increase efficiency to manufacture more products in less time using fewer resources. This will reduce the working capital and costs, allowing manufacturers to create more products for a lesser investment.

Smart Factory Revolution : Adopting digital technologies empowers the manufacturer to revolutionize the concept of the factory by creating a robust and interconnected environment. This streamlines the data flow within the factory and helps drive real-time actionable insights to make faster and more effective decisions. A smart factory is always ready to adapt to the changes and satisfy customer requirements.

Higher Customer Satisfaction : The markets have changed from being product-centric to customer-centric. Manufacturers should consider customer preferences when developing new products. From product research to transparency in the supply chain and after-sales customer service, all aspects can be effectively handled by using insights from data analytics. Customer analytics provide in-depth insights about what customers want from a business.

Enhance Value Chain : Artificial intelligence tools can enhance the entire value chain of the enterprise by increasing production capacity, reducing losses due to wastage of raw materials, minimizing the count of defective products, improving delivery lead times to take the product faster to the customers, etc. This helps the manufacturer and its partners in gaining a competitive edge in different markets.

Adapt to Hype-Competitive Market Conditions : The local, national, and global markets are no longer static. With more businesses entering the scene, there’s an increase in competition between startups, MSMEs, and large enterprises. A traditional manufacturing unit cannot survive in these hyper-competitive markets for long. They are not equipped to adapt to the changes quickly. However, by investing in AI tools and digital transformation, the manufacturer can become agile and sustainable in the long run.

Cost Efficiency and Greater ROI : When a manufacturer can minimize the risk of losses and uncertainties, optimize the use of resources, and speed up production, it naturally leads to greater and improved cost efficiency of the enterprise. This will convert to a higher return on investment while improving customer experience. It also boosts the brand value and reputation of the manufacturer.

Streamlining Supply Chain : The Covid-19 pandemic has caused severe supply chain disruptions a couple of years ago. Manufacturers who went the digital way could sustain the abrupt changes and come up with alternative options. AI technology and cloud computing solutions can streamline the supply chain, provide real-time insights about transportation and deliveries, and make the enterprise sustainable.

Data-Driven Decision Making : Making decisions based on instinct or blindly copying a competitor can be risky for an enterprise. AI tools analyze large volumes of data to provide actionable insights and recommendations that form the basis for effective decision-making. They allow executives to combine insights and personal experience to make better and faster decisions. Data-driven decision-making can boost operational efficiency.