With the rise of “big data”, Industry 4.0, and the Industrial Internet of Things (IIoT), manufacturers are increasingly looking for new tools to get actionable insights from their historical data. Multivariate data analysis is a proven method to help manufacturers model their process to understand the relationships amongst and between all the available variables (raw materials, process conditions, etc.) and how these relationships impact process performance (yield and quality).
The resulting relationships uncovered by the multivariate models are easy to interpret graphically and enable manufacturers to utilize their past process data to improve quality, increase yield and reduce operating costs.
A great way to get started is through our in-person coaching services. We work with your team to format and model your data using Aspen ProMV, interpret the results, and present key findings to stakeholders. The in-person coaching is typically held at our offices in Burlington, Ontario with 2-3 key engineers to be trained on the methods.
This provides your personnel with a distraction free environment to focus on the coaching session. Our expertise in multivariate analysis, combined with your process knowledge results in valuable insights quickly. This is how it works:
1. Collecting and Formatting your Data
- ProSensus will provide guidance on data collection i.e. sample size, frequency, variance
- ProSensus will review your dataset to verify that the data is formatted appropriately
- For batch data, ProSensus may perform data alignment prior to in-person coaching to ensure more time is focused on modeling and interpreting the data
2. Modeling and Interpretation
- In-person coaching session
- Brief overview of multivariate data analysis, highlighting key methodology and interpretation (if required)
- Modeling of data and interpretation of results. For example, building models to:
- Identify key correlations amongst the observations, measurements and variables
- Highlight outliers and determine what makes them different
- Create empirical models to predict key quality variables
- Highlight measurements of importance & their contribution to critical process variables
- Analyze implications of the results
3. Key Findings & Next Steps
- ProSensus will summarize key results and present to stakeholders along with suggested next steps
Our in-person coaching services are a proven way to expedite the multivariate analysis learning curve, so you can take action on meaningful insights. Contact us, or download our multivariate data analysis templates to get started.