Industrial companies can use data science in a variety of ways to control and optimize data-driven quality, processes and services related to the manufacture of their products.
The digital industrial revolution is here. Where the introduction of the steam engine revolutionized industrial production processes more than a hundred years ago. Today, it is data, algorithms and artificial intelligence that represent the next step in industrial production.
The algorithm-based production of goods and goods enables entire manufacturing processes to be better monitored, adjusted and optimized. Machine learning models anticipate maintenance needs and defects in machines and components. Forecast models allow the customer demand for goods to be predicted. The list of possible use cases for data science in industry is as long as it is profitable.
Our team has extensive data science experience and supports you as an industrial company in the development, implementation and implementation of data science and analytics projects in your plants and headquarters.
Our solutions at HData Systems
• Data Science Consulting and Training
• Data Mining
• Deep learning
• Predictive analytics and data science
• Recommendation systems
• Natural Language Processing (NLP)
Data Science in Manufacturing
There is a large amount of data present today on products, demand, supply, consumer preference, manufacturers, etc. The main reason all of this data can be useful is that industries can now leverage knowledge to meet needs and demands of their clients without any delay or lack of quality.
Data science can be helpful with regards to manufacturing in many ways, such as:
• Demand forecast
• Product customization
• Detect any type of anomaly in the supply or product chain
• Predictive Maintenance
• Automating the entire purchase and order process
• Offer different personalized services to clients and clients.
Data sourcing for the manufacturing industry
Data is everywhere and all this data is valuable if used correctly. In a value chain, one can find various types of data like sales, supply, maintenance data, etc. Apart from that, even consumers are producing a lot of data because many of the appliances and devices today are installed with sensors that give data about the product and its behavior. This is the best way to understand product quality and how and where there is a performance anomaly.
There is also a large amount of data present in plant histories and enterprise resource planning (ERP) systems, as they are a great source of data for production, operations and processing capabilities. Maintenance records and machine readings, asset data, manuals, etc. are also good sources of data.
Benefits of Using Data Science in Manufacturing
There are many ways that big data can be implemented in manufacturing and many benefits can be gained as a result such as:
• Optimization of operations
Proper use of big data means that the industry can increase the overall responsiveness of the manufacturing sector, utilize resource capacity to the fullest, gain a clear picture of costs, and also make quick decisions regarding operations.
• Reduce risks in the supply chain.
Using data from around the world on different political, economic and climate issues, the supply chain pattern can be designed so that there can be an efficient work chain considering all other contingencies.
• Reduce costs
Using predictive data analytics, industries can now smartly invest in projects that are valuable and also focus on purchasing equipment and machinery that will lower the cost of production and improve overall performance, thereby reducing overall costs.
• Improve product quality.
By having enough data on customer information about a certain product and how a certain product performs, it can be used to improve quality. Data science is also helpful in customizing products based on consumers and their demographics.
• After-sales service
Today, marketing is no longer product and manufacturer oriented, it is totally customer oriented as it is not enough to sell a product but also to make sure that the customer receives quality service even after the sale. Through predictive analytics and customer services, the quality of the customer-seller relationship can be improved.
Why you should contact HData Systems
At HData Systems, we have experience in applying AI and Big Data to manufacturing processes. With the help of the data received from the sensors, we identify problems, analyze the properties and qualities of the parts during the process and, in general, extract all kinds of statistical information that helps improve decision-making in the event of any critical failure or even anticipate the same.