1 Aug
2018

3 Factors to Consider When Choosing a Monitoring Solution

When looking at IoT and smart factory monitoring solutions for your food and beverage factory, consider factors that will be the most suitable to your factory's needs, set-up, and conditions. Here are 3 factors to consider.

Industry 4.0
Machine Monitoring
Smart Factory
IIoT
3 facteurs à prendre en compte lors du choix d'une solution de monitoring

When looking at smart factory monitoring and IoT solutions for your food and beverage factory, consider factors that will be the most suitable to your factory's needs, set-up, and conditions. No matter what, you want to spend more time on what matters: making better solutions. In the article, "Machine Monitoring and Analytics as a Path to Smart Manufacturing," Julie Fraser writes about industry insights and approaches that will make a difference.

Here are 3 factors to consider when choosing a monitoring solution

1. Scope 
 

If your factory has a well-established Enterprise Resource Planning (ERP) system in place, by adding a more focused machine monitoring system or Manufacturing Execution System (MES), you'll have a set-up that can be coordinated throughout your entire factory.   


But, if it's a considerable challenge to coordinate applications throughout your factory, implementing an ERP which includes MES and machine monitoring will offer reach and range of monitoring.

oee-machine-mointoring

Example: Overall Equipment Effectiveness is a standard for measuring overall efficiency of your equipment and a metric for identifying key problems and potential improvements that could be made. Track in real-time.

 

2. Smart & IoT 

 
If the path to smart manufacturing and IoT is on  your mind, consider whether you want a traditional on-premises solution or whether a cloud-based or SaaS solution such as machine metrics or propulsion would provide you the learning and IoT foundation you need to feel confident.

Smart manufacturing and IoT are not one-size-fits-all solutions. If you are considering these tools and methods, there are a variety of monitoring solutions to fit your needs and to move forward with confidence. Solutions can take a more traditional on-site form, be cloud-based, or SaaS based (e.g. Machine metrics or propulsion.)  

 
 

 

 

3. Report vs. Predict 

 

Some of the most powerful insights gained from machine monitoring comes from predictive analytics—data is drawn from backward-looking reporting and system insights. The ability to predict system events is key to continuous improvement.  

 

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
4
Avril 2019

Comment l'IoT changera le futur de l'industrie alimentaire

French
11
Juin 2019

IIoT Platforms: A Value Driver for Equipment and Machinery

English
24
Juillet 2018

4 Reasons to Monitor Your Downtime

English

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
30
Mai 2018

How to Get Started as a Developer in AI

For developers, the expansion of the AI field means that you have the potential to apply your interest and knowledge of AI toward an industry like the manufacturing industry.

English
6
Déc 2018

AI in Baking for Real-Time Predictions

Get to know more about Dutch powerhouse Bakkersland and their experience with the implementation of AI in their factories.

English
15
Fév 2018

Harvard Business Review Article on Artificial Intelligence

AI won’t replace managers, but managers who use AI will replace those who don’t. Learn what artificial intelligence can do for your business.

English