The Industrial Internet of Things (IIoT) has been growing steadily in recent years, with IDC predicting worldwide spending on IoT will pass the $1.0 trillion mark in 2022, led by discrete manufacturing and process manufacturing. Data scientists are now tasked with connecting to the factory floor to utilize Big Data analytics, Machine Learning and Artificial intelligence, and these new requirements are driving a need for change.
Digital Transformation will lead to increased performance, increased efficiency, and reduced maintenance and downtime. The benefits ultimately lead to increased revenue, market share, and increased profit. In order to realize these benefits, companies must bridge the OT/IT gap and feed the machine with data in a secure, easily consumable, and cost-effective way.
The industry is embracing MQ Telemetry Transport, or MQTT, to implement an open standard architecture for Digital Transformation. MQTT eases access to data and works with best-in-class ML and AI applications, allowing companies to extract value from process data previously unavailable to achieve their business goals. This article will look at the problems with proprietary manufacturing protocols and discuss how the open-standard MQTT can enable Digital Transformation.
Digital Transformation Starts Where Data is Produced
Data may be produced on the factory floor, or at the edge of a SCADA solution. Factory automation and telemetry technology has remained virtually unchanged for 40 years, primarily using proprietary poll/response protocols from PLCs and sensors. Raw data is sent with cryptic register mappings to an MES or SCADA/DCS host. The data is usually manually configured to enter contextual items to each tag – which is extremely inefficient.
Poll/response protocols force the host to ask over and over for the same information, even though most of the time it hasn’t changed by a significant amount or even at all. This is what we call "tightly coupled device," meaning the data producers are tied to one proprietary application, such as the SCADA/DCS host (Figure 1). As a result, overall system response is slow and operations can’t retrieve other data in the field due to bandwidth limitations, making real Digital Transformation nearly impossible.
Figure 1: Poll/response protocols have limited use for Digital Transformation, with one data producer and one data consumer
There are hundreds of these complex industrial protocols across various hardware manufacturers each with their esoteric language which creates barriers to the information. Any other data consumers within the Enterprise are constrained by what operations will give them and must use complex APIs to extract the data, turning the SCADA system into a bad messaging middleware service. Completing this exchange of data is often referred to as bridging the OT/IT gap, but traditional industrial manufacturers are not doing it very well.
Figure 2: Traditional SCADA systems isolate OT data and can’t handle multiple data consumers
A traditional system is shown in Figure 2, where SCADA owns the data path that was built for operations, or OT data. Now, new consumers are requesting OT data and other data as well. New application or custom code is written to get this data out of SCADA. The SCADA host is now polling for data it does not need for OT operations. This goes on as new data consumers are added, building a brittle enterprise of applications that is costly to manage and comes to a point where it does not address the needs of the organization and is too complex to change. No innovation happens and the organization is trapped from moving to new technology without tremendous costs and operational disruption.
MQTT Enables Multiple Data Producers and Consumers
In order for Digital Transformation to be successful, the data must be decoupled and provided with an enterprise-wide solution architecture. Data must be able to flow to enterprise applications in a one-to-many approach.
I co-invented MQ Telemetry Transport (MQTT) in 1999 with Dr. Andy Stanford-Clark of IBM as an open standard for running a pipeline. The project was for Phillips 66, and they wanted to use VSAT communications more efficiently for their real-time, mission critical SCADA system. Multiple data consumers wanted access to the real time information (Figure 3).
Figure 3: MQTT was invented to serve multiple data consumers and multiple data producers
MQTT is a publish/subscribe, extremely simple and lightweight messaging protocol. It is designed for constrained devices and low-bandwidth, high-latency or unreliable networks. MQTT minimizes network bandwidth and device resource requirements while attempting to ensure reliability and some degree of assurance of delivery. MQTT is based squarely on top of TCP/IP so we use those standards for best-in-class security.
MQTT solves the problems created by poll/response protocols with the publish/subscribe method. Instead of the host asking for the same data points over and over again, MQTT only reports the data if it changes – report by exception. Replacing a poll/response network with an MQTT-based network drastically reduces network utilization, saving 80 to 95% of bandwidth. That means changes can be sent faster and data availability is increased overall.
MQTT also allows for multiple data consumers (Figure 4). You can publish the data from a manufacturing asset and multiple applications can consume it, all at the same time. MQTT allows for a single source of truth for data and that data is standard and open source, so anyone can use it.
Figure 4: The basic MQTT architecture allows for unlimited clients over a publish/subscribe protocol.
Moving to a publish/subscribe model with MQTT enables this transition from a one-to-one to a one-to-many approach, encouraging innovations while making it easy to adopt new technologies. Data producers publish the data in Sparkplug B format to an MQTT server. The MQTT server enables those who have secure access to subscribe to the data. The OT application will subscribe to the data instead of polling for it in a bi-directional connection that is also used for control. If a new setpoint needs to be sent, the OT application will publish a command message to write the value to a PLC or device.
MQTT technology has been used for mission critical industrial applications at Fortune 100 organizations for over 20 years. Today with the emergence of IIOT, MQTT is the most-used messaging protocol because it enables companies to gain access to more data from their plants and processes, and share throughout the enterprise.
MQTT Provides Access to Data from Legacy Equipment
Industrial manufacturing is largely a brownfield environment for equipment and systems. Manufacturing assets are expensive and may last upwards of 20 or 30 years, so it doesn’t make much sense to replace legacy systems if they still work. However, OT data is proprietary and cryptic in nature and typically has no context as to naming, engineering units, or scaling. For true Digital Transformation to happen in the business enterprise, proprietary brownfield data must be standardized and turned into IT-consumable data.
IIoT powered by MQTT provides a cost-effective solution for access to data on brownfield devices. MQTT can transport the data from a sensor, to a device (such as a PLC), to an Edge gateway, and then up to the SCADA/MES system on the factory floor.
IIoT solutions are frequently narrow, with limited effectiveness for use across the entire enterprise. Adopting solutions using a common, open-standard approach is the goal. We recently created a specification within the Eclipse Tahu project called Sparkplug that defines how to use MQTT in a mission-critical, real-time environment. Sparkplug defines a standard MQTT topic namespace, payload, and session state management for industrial applications while meeting the requirements of real-time SCADA implementations. Sparkplug is an open standard that is license-free to use and is a great starting point for how to use MQTT. The Sparkplug B specification provides the context data needs to define a tag value for use with OT, also providing data to IT, making it 100% self-discoverable and easy to consume.
Digital Transformation is the use of new, fast and frequently changing digital technology to solve problems. In the industrial world, a complete strategy for Digital Transformation must enable insight across enterprise value chains with data standardization and easy integration with various data consumers ranging from cloud services to AI and ML applications. Too often, failed projects are based on proprietary solutions specific to one process. The proprietary result is not scalable and fails to meet ROI expectations.
Utilizing MQTT with the open-standard Sparkplug data representation provides the tools for organizations to build a cost-effective solution for Digital Transformation across their enterprise. With minimal risk and cost, MQTT allows OT data to be consumed with simple configurations on proven software tools that securely bridge the OT/IT gap and provide contextual information for the data scientists to use Big Data Analytics, ML, and AI to gain insight and increase productivity and profit.