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.
16
Avril 2019

How to Avoid Costly IIoT Related Mistakes

English
2
Avril 2019

Smart Factory Strategies to Manage Risk During Industry 4.0 Deployment

English
11
Mars 2020

Les avantages des technologies IIoT pour les entreprises manufacturières

French

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.
28
Juin 2023

Investir dans l'industrie 4.0 : c'est désormais plus important que jamais pour les manufacturiers d’agroalimentaire et boissons de toutes tailles

La clé est d'adopter l'innovation pour naviguer dans des conditions en constante évolution et rester à l'écoute des demandes des consommateurs, tout en maximisant la rentabilité.

French
28
Juin 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

Faced with challenges that include labor and raw material shortages, tightened regulations ,and skyrocketing costs, companies like you are struggling to produce and price products to meet the demands of increasingly cost-conscious consumers and anxious stakeholders alike.

English
27
Juin 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French