Plant-wide data audit - Get your plant ready for Industry 4.0!
With Industry 4.0 being the new manufacturing buzzword, companies are working hard to make their production facilities ready for the next industrial revolution. The core principle of Industry 4.0 is having a fully connected production plant that utilizes industrial data for process monitoring all along a manufacturing process.
Accelerated Modeling Sessions: Expert Guidance to get Meaningful Results Faster
Do you have data that you are eager to analyze? No time to brush-up on your MVA knowledge and software? An Accelerated Modeling Session with ProSensus may be just what you need. Work alongside an expert as we efficiently extract valuable process insight from your dataset. Expedited model-building is achieved by face-to-face collaboration of your process expert with a ProSensus MVA expert, all in a distraction-free environment. In addition, you will obtain an impartial view of your data, absent of inherent observer bias.
Applying Multivariate Modeling to ExxonMobil's Product Development Database
Dr. David Fiscus, Staff Chemist for ExxonMobil Chemical Company provided a talk at the Polymer Technology Center (Texas A&M University) on April 25th, summarizing a recent project with ProSensus on applying multivariate modeling to EMMC’s product development database. The complete abstract for David’s talk "Developing Structure-Process-Property Relationships using Multivariate Analysis" and speaker bio can be found below.
How to Replicate your Product Across Multiple Scales or Sites
When is the day done for a product formulator? Although it can be tempting to walk away once the product has been perfected in the lab, some believe that product formulation is not truly complete until the product is successfully produced at the final manufacturing scale or site.1 Replicating lab-scale results at a larger manufacturing scale can be a challenging task. What is more, completing this task in a cost- and time-effective manner is critical to the successful release of a new product to market.
IFPAC 2018 and the Role of Multivariate Models in Rapid Product Development
Join us at the 2018 International Forum on Process Analytical Chemistry (IFPAC) Global Conference in North Bethesda, Maryland (Washington, D.C.), February 11th – 14th. IFPAC brings together pharmaceutical, biotechnology, and food industry professionals to discuss the latest advancements in process analytical technologies, quality by design, process understanding and control, and real-time analytics and their industrial applications. ProSensus Project Engineer, Dr. Brandon Corbett, will be presenting during the Wednesday AM-III session which is focused on the “Role of Models and Model Maintenance.” Brandon’s talk will explain how ProSensus’ framework for rapid product development (ProFormulate) has been applied to the rapid development of hydrogels for drug delivery.
Channel Sales Agreement with AspenTech Officially Announced
It has been more than a year since we sold our ProMV software suite to Aspen Technology Inc. (AspenTech), and a lot has happened since then. In June of 2017 AspenTech released ProMV as a part of their Asset Performance Management (APM) suite of products. ProSensus became an official Implementation Service Provider (ISP) to AspenTech to help manufacturers use multivariate data analysis (MVA) to troubleshoot and optimize their processes. ProSensus also became an official Training Service Provider (TSP), providing MVA and ProMV training in Europe, MENA, and North America. ProSensus is now happy to announce that we have entered into a Channel Sales Agreement (CSA) with AspenTech to expand our existing relationship.
Empirical Models for Analyzing “BIG” Data – What’s the Difference?
“BIG Data” is a current buzzword across almost all businesses and plays a key part in Industry 4.0. The term “BIG Data” is most appropriately used to characterize data that is not just large but complex in nature. Furthermore, there is not just one issue with BIG data – there are different purposes or objectives depending upon whether one is in sales, marketing, finance, manufacturing, etc. and there are many different issues to be solved (data collection, warehousing, integration, and analytics). But ultimately most of the issues (e.g. collection, warehousing, integration, cloud services) are just infrastructure issues that need to be improved in order to ultimately be able to use the data to extract actionable information. The focus in this blog is therefore on the data analysis tools and issues that one must consider to effectively extract such information.
How can Rubber Manufacturers Automate Quality Control using CrumbGuard
We’ve helped manufacturers deliver high quality rubber since 2009. Our BaleGuard system, engineered to provide 360 degree surface inspection and automatic rejection has inspected millions of rubber bales, preventing costly customer complaints. However, BaleGuard is more than just the last line of defense for quality assurance. Using the logged defect data from BaleGuard, rubber manufacturers were able to improve their operations by understanding what process conditions were contributing to out-of-spec rubber bales.
ProSensus has a New Head Office!
We’ve moved! ProSensus is now located at 4325 Harvester Road, Burlington, Ontario. The past 6 years in the Ancaster Head office have been great. However, we felt the need to find a new location that could better accommodate our growing team. We believe our new space absolutely achieves this objective, and will encourage an even more collaborative environment for us to better serve our clients.
What Does Becoming an AspenTech ISP and TSP Mean for You?
In September 2016, ProSensus sold our ProMV software to Aspen Technology Inc. (AspenTech). ProMV, an off-line multivariate data analysis software tool helps manufactures get actionable insights from their complex data sets. We’re happy to announce that Aspen Technology Inc. has just released “Aspen ProMV” as a part of their new Asset Performance Management (APM) suite. The APM suite intends to minimize unplanned shutdowns by predicting problems from data, and prescribing solutions before a problem occurs. The rationale for the suite is simple, a highly optimized plant isn’t any good if a process-induced shutdown occurs.