The manufacturing industry is one of the oldest industries in the world. It has benefited immensely from various technological and scientific advances over the years. Leveraging data science to achieve some of its goals is one of the recent scientific advancements the industry is benefiting from. Manufacturing companies are always on the lookout for things that can help them maximize profit, minimize risk, and stay productive. Manufacturing companies can use data science in several ways to achieve these objectives.
One of the problems manufacturing companies have to deal with is scrap. Lowering the scrap rate in a manufacturing plant is a goal continually pursued by manufacturing companies. The data gotten from monitoring the performance of the plant’s machines as well as the quality of parts or products manufactured can be used to create models that predict scrap rates. This can then be used to optimize the machines to reduce the scrap rate in a company. Of course, for this to work, a real-time data collection system for the machines should be in place.
Data science is also used in the manufacturing industry for fault prediction and preventive maintenance. Besides analyzing real-time data of the machines to improve performance, the data can also be analyzed to predict and prevent machine failure in the manufacturing plant. This is crucial as it reduces the occurrence of unplanned downtimes in the manufacturing company, thereby reducing the cost of production and minimizing risk.
Another very important application of data science in a manufacturing company is supply chain optimization. Supply chain management is a critical activity of every manufacturing company and requires evaluating several variables and events such as market scarcity, shipping cost, and local weather. Using data science to process these variables as data points, one can predict events such as market changes and anticipate worst-case scenarios to prepare for them.
Besides the above mentioned use cases, data science can also be used in product design and development, inventory management and demand forecasting, and energy consumption optimization.
SynctacticAI is a data science as a service platform familiar with all these use cases for data science and is used across several industries including the manufacturing industry. It has a lot of features designed to make data analysis and other data science techniques easy and seamless for manufacturing companies.
It offers real-time analytics enabling the analysis of real-time data streamed from machines in the manufacturing plant. It also provides reporting and dashboards for visualizing your KPIs such as scrap rate, overall equipment effectiveness, and so on. It offers prediction and forecasting as well, which would prove useful in inventory management, demand forecasting, and supply chain management.
Just as several technological and scientific advances have improved the manufacturing industry over the years, data science also has a lot to offer, as you have seen above. SynctacticAI makes applying these data science techniques to your manufacturing company’s operations easier, bringing you closer to your goal of maximizing profit, minimizing risk, and staying productive.