16 Apr
2019

How to Avoid Costly IIoT Related Mistakes

It is not necessary for IoT projects to be on a large scale to have a positive impact. And they are not reserved for big players in the industry either.

Smart Factory
IIoT
Comment éviter les erreurs coûteuses liées à l'IIoT

Discussions on IIoT and Industry 4.0 can quickly lead to the potential benefits of large-scale connectivity, but these projects do not need to be large in size to have a positive impact. And they are not reserved for big players in the industry either.


An IIoT solution can be very simple and be limited, for example, to the use of a sensor counting the number of units which pass every hour a certain point on a conveyor, then to the transmission of this data to a display screen installed in a production site and a smart phone of a manager. This system simply replaces the manual method by which a person counts the units, records this information in a notebook, reports the numbers to a whiteboard, and copies them back to a spreadsheet.

 

 

IIoT solutions are within the reach of SMEs

Small and medium-sized enterprises (SMEs) in many sectors, including agribusiness, can benefit from the implementation of the Industrial Internet of Things. Believing that IIoT projects are out of reach can be a costly mistake for an SME. As said by the author of "Smaller Manufacturers Can't Afford to Dismiss the IIoT" in an article from Industry Week, "Though many small and midsized manufacturers may view adopting the IIoT as an onerous and expensive project, implementing these technologies will not typically require a significant financial investment."

Failure to implement IIoT solutions can have many costs, including unnecessary waste, reduced quality, preventable downtime, and strategic errors due to incomplete data. An example of a connectivity solution that affects continuous improvement is the automatic tracking of downtime causes. Being able to grasp the causes of downtime and disseminate data on this type of incident allows supervisors and maintenance managers to analyze this information based on the cause, frequency, and duration of downtime. stop to find out what corrective action to make. The action plan to solve the problem as well as the schedule and the response team can all be linked together. Staff, particularly senior management, can immediately see what corrective action is being taken, and who is responsible. By collecting data on the causes of downtime and centralizing corrective action information, you can benchmark and track the progress of continuous improvement programs.

 

 

3 examples of agribusiness companies that benefit from IIoT solutions

Downtime tracking is just one example of how an IoT solution can reduce costs. Amongst other potential applications for SMEs, we can include production monitoring and real-time visibility.

  • Amalgamated Dairies implemented an IIoT solution to improve productivity and reduce downtime by using only five sensors. Thanks to real-time production monitoring, the company achieved excellent results: increased uptime by 7%, reduced downtime by 15% and reduced labour costs.
  • Leader in the bakery industry, Première Moisson installed sensors on two production lines to monitor productivity, which allowed it to reduce by 27% downtime and to record a productivity gain of 3%. The information obtained from this monitoring helped the company make decisions about increasing its production capacity.
  • Viau Food Products began using analytical tools to track productivity, downtime, and yield after installing nine sensors. The company was able to improve its performance and reduce overproduction. The operations manager said the intelligent production system that Viau has put in place through data analysis is now helping him identify business opportunities.

While Key Performance Indicators (KPIs) for downtime, productivity, and performance can quickly reveal the benefits of an IoT solution, improving the quality and visibility of data can have a significant long-term impact, including influencing a company's major business strategies and investments.

Learn more about follow-up solutions for 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.
22
mai 2019

Quel type de leader 4.0 êtes-vous?

French
23
Oct 2019

How To Know If You Are Receiving Reliable Data from Your Production Line

English
19
Avril 2021

Learn How to Improve Raw Materials Yield by Connecting Your Scales and Checkweighers

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.
17
Août 2018

5 Digital Transformation Predictions for 2018 - an infographic

An infographic presenting 5 Digital Transformation Predictionsfor 2018 and Beyond affecting manufacturers: emerging technologies, robotic process automation, cloud computing and artificial intelligence.

English
6
Juin 2018

10 Ways Machine Learning Is Revolutionizing Manufacturing In 2018

Machine learning algorithms are helping manufacturers find new business models, fine-tune product quality, and optimize manufacturing operations.

English
20
Déc 2018

A New Look on the Food Processing Industry with AI

Significant changes will be noticed in the food processing industry as investments in artificial intelligence are on the agenda of an increasing number CIOs in the coming years.

English