17 Jul
2018

Where do food manufacturers begin the journey toward smart manufacturing?

Where do food manufacturers begin the journey toward smart manufacturing? This article focuses on cost control.

Food Manufacturing IIoT
Industry 4.0
Lean Manufacturing
Smart Factory
IIoT
Where do food manufacturers begin the journey toward smart manufacturing?

How can IIoT help the manufacturing industry?

According to Mark Nott, the VP of Sales at Hitachi Consulting, the manufacturing sector will be spending more money on IIoT technologies than any other sector between now and 2021. What is the biggest related priority on the horizon? Managing cost control. Nott says smart manufacturing can "create value by controlling costs in three ways:"

  • Predicting and preventing downtime,
  • Predicting and preventing bottlenecks,
  • Predicting and preventing defects. 


Setting up a smart factory-where to begin?

With all of the information available online and in the media about digitization in the manufacturing and other industries, how does one distinguish the valuable information from the ineffectual? Consider cost control approaches such as monitoring giveaway and overproduction, gaining real-time production insights or monitoring downtime.

Nott and his colleague Greg Kinsey, VP of Industrial Solutions & Innovation at Hitachi Vantara put together this list of phases to conceptualize the process.

Level 1: Visualization 

The first phase is getting some basic digitization on the shop floor. This might mean installing cameras or microphones or other kinds of sensors to start to visualize what is happening in operations  

Level 2: Integration 

Companies then move up to the point where they can make sense of the data in an integrated way so that the upstream and the downstream parts of the process can begin working more hand  in hand. 

Level 3: Analysis 

At this level, companies improve control over factory processes through analysis of historical data as well as descriptive analysis. Companies can understand what’s happening in a factory at any given moment and manage processes more effectively.  

Level 4: Predictive 

Predictive analytics can unlock a great deal of value—for example, alerting companies  that, at current course and speed, bottlenecks and quality problems are likely to arise.  

Level 5: Prescriptive 

Here, not only do technologies predict what will happen, they will also provide suggestions or prescriptions of what to do to minimize the negative impact of the event.  

Level 6: Symbiotic

The final and most advanced stage is a factory that has a high level of intelligence built into the systems. Using artificial intelligence, the factory can be self-healing and self-adjusting.

 

Source + read the whole article 

Want to learn more?
Download the ebook
Related blog articles

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
3
Aug 2023

Adopter l'IIoT: la voie intelligente pour permettre aux fabricants d’équipement d’origine de prospérer grâce à un partenaire expert en technologies d’usine intelligente IIoT

French
3
Aug 2023

Embracing IIoT: The Smart Path for OEMs to Thrive with a Leading IIoT Smart Manufacturing Partner

English
21
Jul 2023

CDAP: $15,000 Grant To Jump Start Canadian Manufacturing Digital Transformation Projects

English

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
28
Jun 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
Jun 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
27
Jun 2023

Going Beyond the Numbers: Maximizing ROI with Data Analytics in Manufacturing

Technology has given rise to data – reams of it. In fact, in today’s digital environment there is more data available to manufacturers than in all of history combined. Yet for many manufacturers big data is a big problem.

English