“If you want to change your life you have to raise your standards” Tony Robbins

Industry 4.0, much like the previous three industrial revolutions, demands, and drives change. It requires changes to be made in business strategy, leadership commitment, process technology, IT, value chain-wide integration, personnel engagement, and most importantly, in communication.

Yes, the new industrial revolution is far more holistic, demanding changes to be made in all aspects of the way business is done. It emphasizes developing the ability to generate, harness, and manipulate large amounts of data which consequently generates value in business through better operational knowledge to inform strategic decisions taken in the short and long term respectively.

Perhaps the most important aspect of this fourth industrial revolution is that it extended the information infrastructure to the ‘edge.’ It relies on the ability of smart devices and applications to communicate with each other and take autonomous decisions in real-time to create value. The accuracy and speed of communications become paramount and must happen constantly, automatically, securely, and precisely.

Manufacturing organizations willing to invest in the new industrial revolution are thereby required to integrate their shop floor with the rest of the business to gain the new efficiencies coming from the edge. Achieving this efficiency entails harnessing process and equipment-derived data from every transaction from the shop floor and connecting it with higher-level applications like MES. The results are process and operational knowledge to inform immediate, intermediate, and long term actions and decisions, depending on event severity, data analysis timelines, and business flow.

However, the integration between MES with process equipment is not always straightforward. A mix of legacy, custom, and current equipment, software, and data infrastructure brings a host of complexity. Many times, off-the-shelf integration methods are not available.

Equipment-level communication and data transfer standards and protocols do exist to make interfacing with control and higher-level applications more reliable and easier. However, depending on the age of the equipment, the need for multiple interfaces, and the necessary co-existence of modern and legacy equipment and applications, the level of complexity that may exist in a single plant itself might be quite high. Once the number of plants separated by geography and technology increases, so does the overall complexity rise exponentially. 

Continuous Communications is a Necessity

For manufacturers, this need to communicate constantly comes with many challenges. A typical production unit will likely have equipment from various vendors, the types and complexity depending on the industry and production process. This complexity may range from very little variation to high complexity with each device or piece of equipment coming from a different vendor.

Another layer of complexity is added when each piece of equipment uses native software (and protocols) to operate. This is especially true when the equipment is old, or used within applications where interoperability wasn’t required or designed into the process, such as in older packaging lines or custom-built process equipment designed for a single, specific operational step. 

The third level of complexity comes when upgrading to more modern control architectures, especially those including IIoT or edge sensing. Whether you have a single plant or multiple sites, designing and implementing an architecture that is IIoT-ready, has the correct interfaces (protocols) and the existing MES/ERP or business-level communications in place requires a lot of preparation. This scenario of dealing with various standards and protocols, coupled with the need to transfer data continuously yet securely to higher-level applications and generate results that make an Industry 4.0 digitization project successful is no easy feat.

MES Interconnectivity Brings Insight

Before we get into data transfer standards and protocols, let’s first concentrate on the role higher-level applications must play in making Industry 4.0 adoption a success.

An ideal MES application should first and foremost have the ability to support all relevant and established communication standards and data transfer protocols for the industry segment it covers.

Your MES should be capable of integrating the entire shop floor, which means being able to connect securely with each piece of equipment, each IoT-enabled device, and panel, while also integrating with business-level applications like ERP or PLM. The real role of the MES application goes beyond just being able to retrieve data from process equipment and integrating with the existing interfaces.

The MES application should also be able to create and enable a data platform that acts as a true waystation; that not only receives data from process equipment in real-time, but also can process the data at the edge, and preserve the data by configuring and storing it for future applications, from simple reporting to big data/analytics, to applications like machine learning which develop patterns and trends to allow senior management to make strategic, longer-term decisions based on this data.

This is where MES applications need to raise their ‘standard;’ a Modern MES needs to go beyond their original role of modeling and process execution to provide the data platform necessary for unleashing industry 4.0 in its true sense; facilitating the creation of the cyber-physical environment which leads to predictive and pre-emptive operational decisions which are either fully or partially autonomous.

MES can achieve this by effectively communicating with the lower level applications and equipment, all the while ensuring data is being obtained directly without dependency on the internet and in the most secure manner. In doing so the MES is needed to be able to communicate effectively using protocols that exist at the control layer, equipment integration layer, and which manage the equipment-to-host communication. The critical aspect here is not to dwell on the standards which exist, rather the ability of the MES to comply and support existing standards to derive maximum value through the engagement of full standard functionality, resulting in effective harnessing and manipulation of equipment data.

Existing Standards of Note

As far as process equipment communication-related standards are concerned, depending on the industry segment, there are many which exist. We’ll look at some of the more prevalent ones here:

  • Level 1 (Control-level, Equipment-Level): OPC-UA; OPC-DA; SECS/GEM and IPC-CFX; for IIoT, it includes BLE and MQTT
  • Level 2 (Automation-level): BatchML, PackML, MIMOSA
  • Level 3 (IT-level): REST, B2MML, ODBC

These interfaces normally have published APIs which are used to configure the integration, determine the data to be shared, as well as the methodology, timing, and cadence to be used. Some APIs offer ‘deterministic’ performances (confirmed transmission) while others must be manipulated from the application side for confirmation.

The Real Value of Interfacing

To reemphasize, all of these standards and protocols exist for the simple purpose of ensuring data transferred from process equipment to relevant server/applications in the IT infrastructure are understood and maintain the integrity, and the speed, of the transmitted data. It ensures that the transfer occurs precisely and securely, without losing the data’s inherent value and meaning, in real-time or near real-time. 

From an MES perspective, technically it’s important that your MES have a functional ‘knowledge’ of the myriad of equipment communications and integration standards that exist within your operations, and have the means of using the published standards to access and use the equipment output within the application. Your MES developers will require this to ensure that your MES can truly interoperate with the rest of your control and information- level sources. 

So when you are making an MES decision, it’s critical that the MES being considered can support the relevant standard/s applicable to your specific industry segment, plants, right down to individual equipment/devices, and is it truly able to ensure that the data which is harnessed can be both processed at the edge of manufacturing, right where it is generated and also be stored in requisite data lakes/databases for use by other higher application modules to generate deeper more intelligent business responses to your shop floor data.

While standardization and protocols make the retrieval of data from the process equipment easier, unless the application which must use the data –the MES– is truly capable of delivering on real-time edge processing, near real-time automated process control, and detailed data analytics through machine learning, simply complying with given standards and harnessing this data will not have the desired impact from an Industry 4.0 perspective. Stored data is useful, but the real value comes in the ability of your MES to push it further—use advanced analytics, machine learning, and other applications which allow you and your organization to make better-informed decisions that impact not only the operations at hand but support the organization’s long term strategy and goals. That is the real impact of Industry 4.0 digitization.