Every day an absurd amount of data is produced, not only in the industry, but in virtually every segment. However, the production of data itself and even the collection of this data, is useless if there is no analysis of this information. It’s no wonder that data analysis is so popular in the market, as if used intelligently, it can become a powerful tool and help companies optimize processes, improve quality, and increase productivity.
Why is data analysis important in manufacturing?
From conception to delivery to the end customer, many steps are involved in the manufacturing process, making it a complex process. And each of these steps can generate a significant amount of data.
Therefore, it is through this data generated from quality control to inventory management that companies can perform analysis and identify trends and patterns.
Thus, based on the acquired information, industries can make necessary adjustments to optimize their processes and increase their productivity and revenue.
What are the benefits of data analysis in manufacturing?
Data analysis enables more informed decision-making, leading to more accurate results. Among the main improvements that data analysis can bring to manufacturing are:
- Improved product quality: it becomes possible to identify faults and problems in the manufacturing process that may affect product quality. Thus, improvements can be made in the process.
- Cost reduction: areas where waste or inefficiencies in the production process occur can be identified. Thus, leading to reductions in production costs.
- Increased efficiency: to increase efficiency, it is also possible to discover areas where the production process can be optimized. This can lead to increased production without increasing costs.
- Demand forecasting: through data analysis, it is also possible to predict future demand for products. This allows for adjusting production to meet market needs, thus avoiding overproduction or insufficient production.
Where to start?
Before starting data analysis in manufacturing, it is necessary to identify the available data sources in your processes, such as automation systems, sensors, production records, among others. Now you can start collecting and storing the data.
Raw data can contain errors and inconsistencies, so before starting data analysis, it needs to be cleaned and prepared. Only in this way is it possible to ensure that the results are accurate and reliable.
Collecting and analyzing data can be complex and laborious. But, through COGTIVE’s software, you can have data and insights from your factory floor in the palm of your hand and without much effort.
