The manufacturing industry estimates a significant share of the global workforce to develop organizations’ materials across various sectors. It is one of the essential wealthiest-generating sectors of the worldwide economy. The manufacturing industry has always focused on reducing costs by increasing operational efficiency, creating a safer work environment, and improving the customer experience.

The industry faces modern globalization challenges, volatile demand, increasingly differentiated, personalized, and complex products. Ongoing production line machinery and equipment maintenance is a significant expense, impacting the bottom line for even the leading players in the manufacturing industry. This industry is confronting uncertainties in the face of digitization and new customer expectations. Some of the significant challenges faced today are productivity, efficiency, budget constraints, and the number of designs that can be considered. Today, the manufacturing industry needs employees with different skills as specific tasks that have become automated. Each project typically is quality sensitive with restrictions on cost and time handcuffed by deadline constraints. Manufacturers are also facing the need to improve data mining capacities to improve real-time decisions.With real-time data connectivity, the manufacturers can securely connect to their production line assets, collate data, analyze the same, and use the results to create data-based models to optimize their production line. Further, using the AI-based solution being offered by Chemdelve, the manufacturer can holistically visualize the entire manufacturing process in detail, identify process issues, if any, and correct the same before actually getting into the manufacturing process. Using the digital twin visualization method, a virtual twin with all the actual product attributes going through the production process, the production team can identify anomalies quickly and correct the same before getting into the actual production process of the existing production line. With data helping identify these anomalies in advance, it becomes easier for manufacturers to avoid creating unwanted waste, leading to environmental pollution.

Artificial intelligence algorithms can also optimize manufacturing supply chains, helping companies anticipate market changes, moving from a reactive response mindset to a strategic one. AI is destined to change the way we manufacture products and process materials. From the design process to the production floor of the supply chain, all the way to the administration, is all based on real-time contextual data that empowers you to make critical business decisions. AI and machine learning algorithms help in inventory optimization across the entire supply chain management. AI-powered technologies can produce more reliable designs and eliminate waste. Chemdelve’s AI-enabled tools predict when each equipment is due for maintenance that enables manufacturers to maximize efficiency in a way that equipment rarely fails.