Introduction: Industry 4.0

The emergence of the Internet of Things (IoT) has paved the way for the integration of sensors into almost any equipment, enabling secure data transmission to interested parties.

This technology is now being applied to the manufacturing industry. As boundaries of companies become blurred to include external supply chains, retailers and customers, global “Just in Time” supply chains can be disrupted (e.g., Suez canal March 2021) and then become unpredictable while they recover and process backlogs. Having a global view of the supply chain is essential.

With products becoming “smart connected devices” there could be a wealth of data available to the retailers and manufacturers about how their products are performing and being used.

Problem Statement

A business that operates one or more production lines will be in a constant state of flux where machines/robots are being fixed, upgraded, replaced and decommissioned.

More modern machines will be offering Industry 4.0 style interfaces that can provide a huge amount of data, older machines will vary from minimal data to that supplied by the latest machines but with the caveat that the interface and data format is proprietary.

Industry 4.0 using “Open Standards” is the future but legacy equipment will be in place for many years.

In an ideal world we want to be able to:

• • Extract a data stream from any machine that has data available and format it into a “modern” structure.
  • Turn the data streams into “business information” that is consumable by “end point systems” that require the information.
  • Enriching the incoming data, to provide sufficient “business information” for business decisions.
  • Aggregate the data providing trends over time to enable predictive maintenance.
  • Reduce the flood of data, much of the data will not have changed over a short period of time so an “Event driven architecture” is far more efficient to process the data.
  • Achieve Realtime monitoring of the machines but also a holistic view of the entire production process.
  • “Feed” a data driven architecture with relevant business information to achieve business goals.

Responsiv provide the technology and the know-how to achieve all these requirements.

Legacy Machinery

If your business is planning to move to industry 4.0 and you have some equipment that is not directly compatible, the ideal way to manage the disparity is to use an “interface & protocol changer” that queries the “old” systems extracts the data available and enhances that data using database lookups or calling existing APIs in the business and then publishes the data in the new open standard format(s).

The “legacy” feed than goes through the standard processing that the “modern” feeds are exposed to.

Enrichment of Data

Manufacturing machinery data feeds tend to be very engineering based, they “don’t know” which production line they are in, or what country the production line is in, that they reside. None of this information is of interest to the machine or engineers, but the business would require this information.

Aggregation of Data

If we check the temperature of a room every 10 seconds and we can see the temperature is fluctuating by a few degrees as the air-con switches on and off we can assume that everything is working fine. If we were then to take batches of data, filter out the air-con fluctuations and then calculate the first differential of the data we would be able to spot trends in the enhanced data that could indicate the air-con is losing pressure failing to fully cool the room.

We can now predict that at the present rate of change the problem will become critical and scheduled maintenance can be actioned. We can then improve the solution by also monitoring the time the air-con is on vs off for an even more accurate prediction.

These techniques can be applied to many of the data feeds from the manufacturing machines.

Event Driven Architecture

Being told a data point has not changed every few seconds is not efficient, this is typically called polling i.e. read values every few seconds. It is far more efficient to be told something is changing by a meaningful amount.

This technique significantly reduces load on endpoint systems databases & file systems. Conversion between polled and event driven architectures can be achieved by implementing an interface that queries the machines and compares the values to the last query and publishes the changes to the business systems.

Realtime Monitoring

IT style monitoring is well established and typically shows isolated applications are functioning along with networks and servers.

The Industry 4.0 approach can be used to give a much more business orientated monitoring solution, particularly if external sources of data are used to enhance the overall picture.

Data Driven Architecture

Any business wishing to implement the Industry 4.0 approach will need to prepare for an explosion of data and be able to process that data into useful information for the business. Careful management of the storage,  clean-up, or archiving of the data will be required to keep things manageable.

A well thought out Data Architecture will be required and this architecture is likely to be specific to your company.

Responsiv Cloud Automation Platform

With Responsiv Cloud Automation Platform (RCAP), assets are registered in an Enterprise Asset Management System where device telemetry from Robots’ data is pushed to cloud through an easy to use and robust integration technology.

Using RCAP’s built-in SNMP Monitor you can manage and detect near real-time anomalies for registered devices. RCAP is used to manage assets, create service request, work orders etc. while data is used to create business purpose visualisation of asset performance monitoring.