Approaching the Changes in Cloud Evolution

Summary

Industrial manufacturers have recognized the many benefits of plant floor digitalization. Leaders in both IT and OT must work together to decide on the degree of information that needs to be collected as well as what type of analytics are required. Due to the wide range of requirements from other departments, such as operations, marketing, finance and maintenance, pre-planning is the key for any IIoT application.

New consumers of industrial data want immediate opportunities to improve efficiency and profitability as well as prevent downtime in ways that were not possible before. Cloud services and scalable storage are certainly drivers for this trend. Many controllers, for example, support the mainstream protocols commonly deployed in factories, but also add new mes­saging schemes like MQTT and REST APIs to support these new applications.

There are challenges with these approaches, for sure. Cloud provid­ers have their own set of APIs and services unique to their solution. Customers who are looking to adopt a cloud platform need to consider how portable their data is and how easily they can tie into existing systems within their organization. A controller that allows for open development, especially those that are Linux-based, will generally support more platforms than a closed system.

Cloud platforms commonly use the MQTT protocol for secure IIoT communications, leaving the integrator to determine how the JSON payload is structured; this adds flexibility but can also create interoperability challenges. (Specifications like SparkPlug help by defining the namespace to address this challenge. Note: Sparkplug B is supported, but relatively few Cloud Platforms have formally adopted it yet.)

Cloud platforms are constantly evolving. For example, if you are using AWS Greengrass on a PLC and AWS releases a new ML service, a customer can easily adopt this new feature. A new driver or update used to mean installing and licensing new software on multiple servers, hoping there are no conflicts. Fortunately, this labor-in­tensive task might soon be a thing of the past.

Data collection, storage and retrieval is the first step in digital transformation. Many cloud agents have the ability to orchestrate and manage your assets in a centralized way, allowing changes to be sched­uled and rolled back as necessary. It is also possible to remotely deploy code to a group of edge devices for non-re­altime tasks. This is a fundamental change in the way controllers can be programmed and managed, potentially making a signifi­cant impact on our industry.

Central to the Industrial Internet of Things (IIoT) approach is edge computing...collecting and pro­cessing data right where it is generated. There is a lot happening in the edge of network space. This is an enabling technology that greatly simplifies software development and testing, which is more in line with main­stream software development.

Adopting an open and easy approach to industrial controls and supporting IIoT is accomplished by designing controllers that support established protocols and programming spec­ifications, while at the same time extending support for new solutions or hybrid control schemes. This gives controls engineers flexibility to deploy the software applications that best meet their design goals.