How Multivariate Machine Vision Can Improve Operations
Machine vision is a growing field that leading manufacturers are adopting to improve their operations, product quality, and profit margins. Forecasted to be a 26.9 billion dollar industry by 20201, it also happens to be a field where we offer our clients advanced solutions.
Benefits of Multivariate Machine Vision
Manufacturers across multiple industries are embracing machine vision to obtain new measurements to tune processes, identify off-spec product, and discover new insights into product quality. To be successful with machine vision, both the right hardware and the right software is required. Given the multitude of hardware vendors and several software options, it can be a challenging space to navigate. For this reason, we offer our clients on-site trials as a first step to a complete, all-in-one machine vision solution.
Visualize Missing Data Patterns in ProMV
When was the last time you received a perfect set of data? As problem solvers in manufacturing, we are constantly analyzing data that contains correlated varables, missing values, and other messy problems that aren't handled well (or at all) by traditional regression methods.
ProMV has always handled missing data implicitly, but our latest version gives you a Missing Data Map so you can spot the missing data patterns at a glance.
Why visualize missing data patterns?
Improve Product Quality in 2015: Get the RIGHT data
Big Data was a BIG buzzword last year, but reaching your 2015 product quality goals is all about this question:
Are you collecting the RIGHT data?
Day-to-day manufacturing data can help improve product quality, but simply collecting big data sets isn’t sufficient. You need the right variables, measured often enough, and you may need weeks or months of data across different seasons.
Communicate Your Batch Trajectory Insights
As process engineers ourselves, we know it can be challenging to communicate the results of a multivariate analysis to your colleagues and managers, especially for batch processes. In ProMV 14.08 we worked hard to help you tell your stories so your co-workers can easily grasp your findings without being experts in multivariate analysis.
Released last month, ProMV 14.08 adds visual enhancements to trajectory plots and allows you to select and plot only the key trajectories for your presentations. In addition, we've completely revamped the simulation of real-time batch process monitoring, which will provide a big WOW factor in your next meeting.
Improving Product Quality in Rubber Manufacturing
During last week's International Rubber Expo in Tenessee, we introduced our BaleGuard surface inspection system to the entire rubber industry for the first time. Originally custom-designed in 2009 to detect defective rubber bales using multivariate image analysis, BaleGuard is emerging as the leading tool for quality-minded rubber bale manufacturers.
What exactly is a Rubber Bale, anyway?
Misconceptions about Latent Variable Models
While giving courses over the years, I’ve noticed that certain misconceptions about latent variable models persist among statisticians and chemometricians. At the 14th annual ENBIS conference (European Network for Business & Industrial Statistics) in September, I have decided to discuss a number of these during my plenary George Box Medal presentation. Some of the key questions include:
Would you rather do 321,000 experiments? Or 12?
One of the best-kept secrets at ProSensus is that we help clients improve their return on investment in product development. Our clients can:
• Formulate new products in half the time (compared to traditional methods)
• Achieve 20-40% reductions in raw material costs
• Create new-to-world products that capture huge market share and high margins
In the past 3 years, I've worked on some very specific applications, like frozen muffin batters, next-generation automotive fluids, and smart polymers for eye injections.
Now I'd like to explore some general aspects and best practices of product development with you.
How to Improve Productivity Using ProMV 14.02
Released almost five months ago, ProMV 14.02 makes it fast and easy for you to customize plots and share information. Ultimately you’ll save time and increase your productivity as you execute data mining projects and build multivariate models.
The feedback from early adopters has been very positive. They like the ability to create a custom template for all ProMV plots, annotate individual plots to highlight key findings, and save their workspaces to share with colleagues for review and further analysis.
Have you explored the new features yet? If not, here’s how to get started.
European Companies Invest in Better Batch Analysis
During our recent trip to Europe, our team met with several chemical and pharmaceutical clients to review & plan projects and conduct in-house seminars. The dominant theme of our trip was batch processes in manufacturing, and we maintained that focus as we delivered our advanced 3-day course Multivariate Analysis of Batch Processes in Basel, Switzerland.
We noted that in the chemical industry, a primary goal is to command a higher price by becoming a premium supplier, and this demands tighter quality control. In bio-pharma, some companies are strapped for capacity but would like to delay the huge capital costs of building new batch reactors. Both of these goals can be achieved with advanced tools for managing the quality and yield of each batch.
3 Ways to Organize Data for Multivariate Analysis
In our courses and previous blog posts, we've described the benefits of dividing your variables into logical groups and building multi-block multivariate models. But did you know there are 3 ways you can organize your data in Excel to prepare for multi-block modeling in ProMV? We added flexibility to ProMV's data import process in version 13.08 to give you these options. This 15-minute video tutorial demonstrates the 3 different ways of organizing your data and how each strategy affects the import process. Be sure to watch it in full screen mode to see all of the details.
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