The basics of smart factory and discrete automation connectivity

A smart factory is a facility that digitizes all aspects of manufacturing or production that allows for digitization. This operation continuously records data through connected devices and systems and then disseminates this data, allowing the machine to run self-optimizing programs. Such programs help factories reduce production time for a given end product, proactively prevent machinery problems, and streamline interrelated manufacturing tasks. A comprehensive approach to building smart factories that leverages cloud tools, artificial intelligence, industrial IoT, and big data analytics to monitor supply chain forecasts and trigger production lines to respond is becoming increasingly adaptable.

Network supporting smart factory functions

Now let’s take a look at the specifics of smart factory connections. Industrial protocols that support smart factory functionality often require physical components to be authenticated. CAT5e and CAT6 and Power over Ethernet (PoE) connections are increasingly common in automated machines and robots. In addition, flexible CAT5e and CAT6 cables support CC-Link Industrial Ethernet (IE) networks, and cable carrier bundled assemblies are available for the North American market with UL certification.

Consider an industrial controller that supports the CC-Link IE Field industrial network and allows data exchange to 1 millisecond for real-time device control. Some such controllers also leverage the network for remote monitoring, edge computing, data computing, and hardware and software integration. These controllers typically come with Windows 10 IoT installed, but can also use the operating system VxWorks and the open platform Edgecross to process and distribute data. Some of these industrial computers even include touch screens that double as human-machine interfaces (HMIs).

The main advantage of HIPERFACE DSL is that it allows motor power and position feedback to be routed through a single cable, thereby reducing complexity and cost. Plus the smart HIPERFACE DSL encoder includes internal memory that stores motor information so on initial connection the servo drive can query this information to aid in automated motor debugging.

Similarly, single-cable solutions based on Ethernet or even Digital Subscriber Line (DSL) cables improve machinery containing linear actuators, often providing compatibility with amplifiers from different manufacturers to allow controllers to communicate with Fast and seamless integration of actuators.

Single-cable IO-Link is also increasingly used for industrial connections. Some smart motor suppliers have begun integrating IO-Link entry-level products into core products to support connectable sensors for decentralized automation concepts. Of course, motors that can communicate via Industrial Ethernet or CAN bus do not need to be connected to the IO-Link network as auxiliary devices.

IO-Link can also digitize traditional analog connectors on components to enable bi-directional communication and faster commissioning times. No wonder some people use IO-Link connections on the control side to support multiple protocols and interface with serial interfaces.

Protocols and Cloud Connectivity Serving Smart Factory Functionality

Consider the various protocols and communications used in Industrial IoT connectivity, such as SCADA, MES, and enterprise resource planning (ERP) architectures. These are the most involved in IT/OT (operational technology) convergence - typically involving enterprise-level tasks, gateways and other connections to enable system configuration via a standard web browser...as well as operational adjustments and other management operations.

To be clear, a comprehensive SCADA installation excels at big data capture and processing, maintenance and use of historical data, and execution of analytical routines. However, smart factory solutions allow faster setup of remote access networks, edge computing systems, and central or on-machine (HMI) control of associated machine settings and data.

Structured Query Language (SQL) used in many IIoT installations allows programming to synchronize data and event logs to MySQL and MS SQL database servers. The benefit of this is that IT staff access is easier to implement than alternatives that rely on controls. This is true whether the system utilizes basic control such as a Raspberry Pi, or a complex PC-based IoT database interface that often requires additional hardware and software.

In addition, infrastructure, platform and software as a service (IaaS, PaaS and SaaS respectively) or cloud services are also heavily adopted to support a multi-pronged IIoT design approach (involving software, hardware and connectivity) . These include Alibaba Cloud, Tencent Cloud, Google Cloud, IBM Cloud and Oracle Cloud. However, in the United States, the two leading public cloud service providers for machine automation today are:

• Amazon Web Services Inc. and AWS cloud software and services
• Microsoft Azure IoT Edge cloud software and services

This type of cloud service mainly supports the use of databases— — Online and on-premises applications and on-demand computing power through products like Amazon Simple Storage Service or S3 buckets and Amazon DynamoDB managed database service. Related to the latter is the AWS Lambda service, which allows Python, Node.js, Java and C# programming to run on the service's servers. HMI allows end users to take full advantage of these Industrial IoT capabilities.

Of course, cloud services also have other functions. Part of the push for AWS and Azure for industrial IoT is that more and more engineers have become accustomed to building their own infrastructure on these platforms. After all, cloud-based data services free engineers from the additional design work of the underlying hardware and software—as the provider performs the IT tasks. AWS and Azure also allow the use of software that abstracts data flow and communication - simplifying some design work through a development environment with an attractive GUI, freeing engineers from dealing with programming details.

Cloud services also facilitate advanced engineering through virtual machines that run operating systems and applications...design engineers have control over these virtual machines. More importantly, cloud services can accommodate various communication services on protocols that adopt publish-subscribe principles, becoming the master service for all these services. This eliminates the need for time-consuming addressing during system setup.

All of these capabilities facilitate advanced capabilities, including machine learning to classify and extract data, and make predictions to prompt machine and production adjustments.

A related trend is the increasing use of pre-curated cloud portals by vendors. These portals are online services that connect user controllers and touchscreen HMIs, giving engineers an easy way to get started with IIoT. Engineers can then customize HMI screens and dashboards based on trends and configure HMI email notifications using the rules engine managed by the cloud portal. The list of functions goes on. Some arrangements allow for remote software updates of components, as well as remote viewing of web visualizations of components.

Touchscreen HMIs and controllers certified with AWS GreenGrass Core essentially leverage AWS, including AWS Lambda and Things Graph, to let connected edge devices, such as sensors and actuators, process the data they generate locally and Use the cloud for data management, storage and analysis. With AWS IoT Greengrass, connected devices can also run Docker containers from Docker Inc’s containerization service.

Recall that in the context of industrial programming, a container is a piece of executable software that contains the code, system tools, runtime, libraries, and settings needed to run an application independently. In many machine designs, containers are designed to communicate and synchronize data with other systems, or perform various predictions—even when disconnected from the Internet. Advantages of building applications in containers include:

• Easy to deploy to devices
• Portability of the software, allowing use on different platforms
• Through Providing a sandbox for engineers' applications to increase security services.

Anywhere an HMI is connected to the cloud, it is likely to provide information for enterprise analytics and continuous operational improvements in some form of IIoT capability. This is true for automated installations involving one to hundreds of machines. Protocols supporting IIoT functionality, including various forms of data communications and HMI connections to edge devices, include:

Open Platform Communications Unified Architecture (OPC UA)

Representational State Transfer or (REST) ​​and its application programming interface (API)
• Advanced Message Queuing Protocol (AMQP)
• Message Queuing Telemetry Transport or MQTT
• MQTT is one of many At the heart of the IoT connectivity fabric is a protocol that supports scalable communication between sensors and mobile devices. Any built-in device support for MQTT is useful as it applies to Amazon AWS IoT services. In addition, MQTT (like AMQP) is streamlined and standardized, and MQTT can be implemented on gateway HMIs that handle field device data on-site and in cloud systems. HMIs that provide the most MQTT support should be connected to value-added services to provide data processed at the edge in third-party systems and run through cloud services. Such HMI can act as an MQTT publisher (and send messages to the broker) or subscriber (and request messages from the broker) or broker (and manage data and connections to the publisher or subscriber).

The interoperability standard OPC UA is also indispensable to fully exploit the prospects of connected HMI technology. OPC UA includes publish-subscribe communication in its specification definition, so it can be used as an alternative to MQTT for transmitting data to the cloud. The field of motion control attaches most importance to the standardized communication protocol of OPC UA, supplemented by Time Sensitive Network (TSN) as a vendor-independent fieldbus for decentralized automation. OPC UA with TSN can even make an additional PLC unnecessary – for example, in machines using integrated servo motors. After all, more systems now than ever benefit from distributed architectures containing smart motors and other components capable of processing commands and performing tasks such as motion and others while communicating with other devices in real time. In some cases, the latter can include an HMI as an edge gateway to handle process logic for certain axes, as well as connections to ERP systems and the cloud.

Example of how HMI uses MySQL database connection

The SQL mentioned earlier is used in many Industrial IoT installations. This relational database management system is free, open source, and widely supported. It is also safe and therefore can be safely integrated into the controller HMI and panel PC. One benefit of SQL is that IT staff access is easier to implement than control-dependent alternatives (which often require additional hardware and software). This is true whether it is simple system control like a Raspberry Pi or as complex as a PAC with an IoT database interface.

In fact, SQL also works with some controller HMIs to collect and display machine data for easy monitoring and analysis. For example, connecting such an HMI to a MySQL database can collect, organize and store data in a flexible and trusted database, making it easy to access and optimize business operations.

Some vendor design software can help engineers use MySQL through smart HMI and place the data in an Excel spreadsheet (or tabular data in a file in other commonly used software) to:

• Display information in HMI interface
• Synchronize data and event logs to a remote MySQL server on the local network
• Manage data on the server

Then, Engineers can use MySQL and MS Excel to collect, analyze and respond to data to make smarter decisions and optimize operations.

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