Modula’s Proactive Approach to Smart Manufacturing: Part 1


At Modula, when we speak of Industry i4.0 we're referring to the application of the “Internet of Things.” To be more specific, we strive to create ultra-high-speed connections between people and machines by means of a virtual network for the exchange of significant information concerning products and the operation of machinery. This type of smart manufacturing system provides an opportunity for greater real-time control of production processes as well as the end of production stage.

What does the Industry i4.0 Do?
To stay abreast of this smart technology, we’ve developed a software platform that delivers an output of the daily production programs for the machines, while receiving an input of information that includes what has been produced, in what quantities, and the stage of the production process. We're conducting this activity via a Cyber-physical system that, by means of sensors installed on the machines, keeps us informed of the status of each one: in production or idle, production rate, stopped in fault status, stopped for maintenance or stopped temporarily to accommodate a fall in throughput. The sensors send important data that is subsequently processed by our software.

Rather than denoting an automation system, when used in a Modula machine, the expression Industry i4.0 refers to the digitization of processes and efficient use of data to reduce waste, optimize the quality of control processes and standardize the information received from production plants to provide management tools that will ultimately help the decision processes. Thanks to a graphic interface and 3D technology, the plant is represented globally, allowing the production manager to maintain full control over the entire production cycle.

Proactive vs. Reactive
By developing this software we not only secure full control of the processes, but we can also take action on the machines themselves by means of predictive maintenance. We are in the process of establishing collaborative relationships with the manufacturers of our machines, based on the exchange of useful data to allow us to understand when and how to perform maintenance actions. We do this by creating a log of machine faults in order to predict potential problems before they even occur so we can perform preventive maintenance rather than repair.

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