Understanding the Role of Manufacturing Support Services: Insights from Tracey Johnson (Part 1)
As Vice President of Operations at Actemium Avanceon, I’ve had a front-row seat to how crucial manufacturing support services are in today’s fast-moving industrial world. With technology advancing so quickly, it’s more important than ever to have the right support in place to keep everything running smoothly.
Key Support Services
At Actemium, we offer a variety of support services designed to address the specific needs of different manufacturing environments. These services can generally be grouped into four categories:
● Emergency Support: Available 24/7, this service ensures that clients can get immediate assistance when they face unexpected issues.
● Block of Hours: This service provides a set number of engineering hours each month, which clients can use for a range of activities, from minor system improvements to training or in-depth troubleshooting.
● Preventative Maintenance: Regular maintenance of equipment is essential to prevent unexpected breakdowns and ensure that production runs smoothly.
● Data Analytics: With data becoming an integral part of manufacturing, we offer analytics services to help clients interpret the data they collect, turning it into useful insights for decision-making.
Our team works across a variety of technology platforms, including well-known systems like Rockwell, AVEVA, and Siemens, as well as older or custom-built systems. We don’t take a one-size-fits-all approach; instead, we find that working closely with each client to develop a support plan that fits their specific operational needs—whether they operate a small facility or a network of larger plants. This individualized approach is key to being able to operate any plant to its fullest potential in the future.
Evolving Focus on Data Analytics
We all know that data is king right now. Therefore each and every plant should be focusing on how to improve their data analytics capabilities. There are many types of data any plant can be collecting at any given time, but it’s best to focus that data into useful buckets. Here are some of the buckets we like to consider:
● Descriptive Analytics: What happened?
● Diagnostic Analytics: Why did it happen?
● Predictive Analytics: What’s likely to happen next?.
● Prescriptive Analytics: How can we influence future outcomes?
For many manufacturers, managing and extracting value from large volumes of data can be overwhelming—because it is! Being able to harness your data in a way that both makes sense and lends itself to making pivotal decisions is the goal. Data should be driving decision-making if it is used correctly.