How is data science changing manufacturing sector?

Data science is an interdisciplinary field that includes AI, maths, statistics, and analytics. Industry 4.0 is backed by data science which takes the help of both structured and unstructured, qualitative and quantitative data to increase productivity, reduce wastage, minimize risk, fast execution, and production boost.

Product design and development
Data is helping manufacturers understand their customers. Understanding the preference game and demands to fulfill the customer needs is a fast-paced sport. Data aids in designing a product with features and specifications which can attract customers and assess the competition risk. It helps launch a new product or up-gradation of an existing product.

Predictive analysis
Data analysis is utilized to forecast and avoid unpredicted risks and problems, learn from the mistakes, and get equipped not to repeat the same in the future. Manufacturing hubs use the collected data to monitor the company functions, access bottlenecks and find optimum solutions.

Fault predictions and preventive maintenance
It is forecasting the failure of critical equipment, which might hamper production and provide an edge in the competition. This helps the maintenance departments to stay equipped beforehand to perform preventive maintenance or stay alert before a breakdown. For the analysis time based and usage-based methods are employed. It helps in avoiding delays and failures.

Price optimization
Setting the price of a product has a plethora of variables. Cost of raw material, supply chain, process cost, maintenance, labor cost, etc. Manufacturers want prize optimization to reach the best price for their product. Too low, and there are chances of loss increases but too high, and they might get out of the market competition. Data science helps achieve a competitive edge by analyzing pricing and cost data from both primary and secondary data and landing at the best price.