For manufacturing companies, process control is essential— even for those producing low-cost items such as small plastic parts. That’s because even when units are small and inexpensive, the cost of defects becomes exponentially higher when they reach the next manufacturing step at another plant.
All manufacturing industries need good control and good overview of their production processes. As already discussed in a previous blog post, SIMCA-online enables you to apply advanced multivariate data analytics in real time to monitor your production processes, for example to make sure that your production process is behaving as it should or that the quality is what it should be.
Using real-time data analytics monitoring has become the accepted way to monitor processes in several industries. The goal is to detect and diagnose issues as they happen, which is a great leap forward compared to traditional analysis conducted in retrospect. This has been highlighted in a previous blog post.
Using advanced data analytics models in real time opens up a whole new world of possibilities for improving your production processes. Not only does real-time process monitoring provide a level of confidence in your process performance, it can also help improve the overall quality of your production output.
The key to process manufacturing success is a mixture of knowledge and experience supported by mastery of data. A presentation I recently attended put this into sharp focus. A major paper manufacturer was faced with the challenge of maintaining paper smoothness during production. They approached this problem in a way that gave them enormous insight into their process, the ability to control it in real time, and ultimately lead to cost savings and maintained quality. There were also a few added benefits, including the ability to spot, diagnose and solve problems in real time.