To remain competitive in today’s world, manufacturers must use process analysis. This allows them to recognize inefficiencies and improve the manufacturing process.
Rodrigo Alonso Salas Musso has a degree in industrial engineering from the University of Lima, Peru. Today, he will explain manufacturing process analysis.
Process analysis means using a systematic approach to analyze the steps of a process. It focuses on finding ways to improve the process.
In manufacturing, this can increase productivity and profits without having a negative impact on product quality or customer satisfaction.
Process analysis allows you to ensure that your processes align with your objectives and meet the standards of your business.
According to Rodrigo Alonso Salas Musso, manufacturing process analysis can streamline any part of the production process.
- Product design
- Assembly process
- Quality control
You’ll need to follow some basic steps to perform process analysis in manufacturing.
These steps are:
- Value identification
- Data acquisition and Processing
- Data analysis
- Machine learning
The first step is to determine the value of the process, according to Rodrigo Alonso Salas Musso. You’ll also need to consider how valuable improvements to the process can be. This helps you to use your resources in the most efficient way.
The next step is data acquisition and processing. Smart manufacturing has allowed many processes to be automated. This makes data collection much easier than it was in the past.
You can also collect data through productivity reports, observation, customer and employee surveys, and sales and marketing data.
The data should be verified and processed. Any incomplete or duplicate data should be cleaned up before moving on.
Next, Rodrigo Alonso Salas Musso, explains, you’ll need to analyze and process the data. This can be done with the help of machine learning, or ML, and artificial intelligence, also known as AI.
This allows you to get much more insight into your processes with less effort, increasing the efficiency of manufacturing process analysis. It also makes implementing needed changes much faster.
Once you have the data analyzed, you can use machine learning and AI to further understand the data, and determine the best course of action.
Once you have identified areas that can be improved, you can use this information to create a change plan. Machine learning and AI can be invaluable for this step in the process, but these programs require human verification and oversight.
Rodrigo Alonso Salas Musso was born in 1998 in Lima, Peru. He attended San Pedro School. He received a bachelor’s degree in industrial engineering from University of Lima in 2022. He also earned a CAE Diploma and a Sprachdiplom Diploma, which allowed him to diversify his knowledge base.
His article “Model of Supply Chain Management Based on the Application of Lean Tools” was published in ICEA magazine.