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Your IndustrialPhysical Environment

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Your Industrial Physical Environment

IntroductionThis document covers the hardware, software, data, and tasks you’ll need to consider when setting up your physical environment for an insights project. Setting up your environment properly is crucial for gathering good usable data, and for making sure your project runs smoothly and effectively.

This document also summarizes the various computing hardware, controller, camera, lighting, networking, and protocol decisions you’ll need to make. It also provides recommendations and refers to other Intel documents to help you make the best decisions for your insights project.

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Main ConsiderationsBefore setting up your environment, you’ll need to consider the following three things:

• What data will you use? What types of data will you need to capture? From what sources does your data come? How will you work with your initial data to develop your analytics application?

• Do you have any constraints in your physical environment? What are your environment’s unique constraints? How will these constraints effect you project choices?

• How will you iterate on your analytics application? How will you share, store, and work with your data while getting your analytics application to work properly? How will you work internally—and with external organizations—during the course of your insights project?

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Your DataHow you’ll collect usable data for your project is one of the first things you need to consider. There are three main decisions to make when acquiring data from your environment:

1. What tools or other sources is the data coming from?

2. What connections and protocols will be used to transfer and access the data?

3. How will you work with your data to get it ready for creating an analytics application?

Working with Your DataWhether your data comes from a camera, a robotic arm, or various environmental sensors, you’ll work with a data expert who will capture initial data, then label it with the right annotations and metadata to create effective algorithms.

• Computer vision data. You’ll use a digital video camera (with proper lighting) to capture vision data for your analytics application. The camera and lighting sections in this document will outline key consider-ations when choosing the right cameras and lighting for your project.

When working with computer vision data, we recommend the Computer Vision Annotation Tool (CVAT). CVAT is an open source, web-based image and video annotation tool that enables data experts to perform primary tasks, such as object detection, image classification, and image segmentation.

• Time series data. You’ll use a time series database, such as InfluxDB, to store and serve up time series data. The data can be collected using formats like JSON (via MQTT), OPC-UA objects, or Modbus messages. You will also need access to the information model or schema for any input data. For example, you may need to know how many streams are in an input, or what the size of the input stream is, per machine and operation.

When working with time series data, we suggest using Grafana, an open source interactive visual-ization web application. Grafana enables you to visualize time series data with charts and graphs, as well as create complex monitoring dashboards.

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Your Physical EnvironmentThe ability to scope your project effectively relies on an assessment of your physical environment. Aspects of your environment can have a direct impact on how you’ll approach your project, and will influence the networking, camera, lighting, controller, and computing hardware decisions you’ll need to make. For example, if the temperature and humidity in your environment is high, it may require you to choose an industrial PC that can tolerate and perform well under those conditions.

The following is a list of things to consider about your space:

• Temperature. Look at the overall temperature, temperature fluctuations, or any specific areas that have extreme temperatures in your environment.

• Limited space. Examine the proposed project space to see if there are any tight or cramped areas, or areas that will be difficult to access.

• Air quality. Assess the air quality to see if it will present any challenges for hardware or cameras to work properly (e.g. a smokey environment that prevents a camera from capturing vision data).

• Moisture. Like air quality, assess the moisture in the space to see if it will prevent hardware or cameras from working properly.

• Radio frequency (RF) interference. RF or other electrical interference can require extra grounding or added shielding for cables in order to transport data effectively.

• Worker safety. Inspect the proposed space for any potential areas where the project may create dangerous or unsafe situations for workers.

These are just a few important aspects you’ll want to consider. There may be other spe-cific characteristics of your environment that you’ll also want to take into consideration.

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Your Analytics ApplicationAt the heart of your project is the analytics application—the equations, algorithms, and code used to analyze your data and produce results about the specific situation you are examining. In addition, there is networking, communication, and computing hardware you’ll need as you iterate on your analytics application. (Later in this document we’ll cover considerations and recommendations for these hardware components.)

As you scope your project, you’ll need to consider two key aspects of how you will iterate on your analytics application:

1. How will you work with the data coming from your application? How will you access, view, store, and work with the data coming from the application?

2. How will you collaborate with others while iterating on your application? What processes will you put in place to collaborate with internal coworkers—and external organizations—to iterate on your application?

Remember that how you set up your physical environment may have an impact on how easily you are able to iterate on your application. For example, where you store the output from the application—and if you have easy access to the data—will affect your processes. The following information is important in get-ting your project up and running as smoothly as possible:

• Data management and machine control ownership. There may be internal teams (such as IT) that manage security and access to machines and software, and other internal teams that manage the data, configuration, and control of machines. It’s important to put a plan in place to align with these teams to ensure smooth physical access to machines, network connectivity (including firewall configu-rations) timely software upgrades, remote debugging, and extracting data and results.

• Debugging expectations. It’s important to align on how and when data will be available, to avoid any confusion or wrong expectations. For example, if data is coming from a controller then a schedule of when and how the data is expected, as well as any planned downtime, is important. Also, you’ll need to know if or when any changes to the information model will occur during the project, and make sure data remains available from any software owned by an external vendor. Aligning with internal teams is important, so you’ll be notified of scheduled maintenance and patching that might impact the infrastructure or machinery you’re connected to.

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Main DecisionsOnce you’ve addressed the main considerations for your physical environment, you’re ready to make decisions on the various types of hardware you’ll use during your project. There are five main hardware areas to address, depending on the scope and situation you’re analyzing:

1. Computing Hardware. You’ll need hardware optimized to handle the ingestion, analysis, and storage needs of your project.

2. Programmable Logic Controllers (PLC). You’ll need PLCs to connect to, and communicate with, the various machines and devices for your project. The PLCs might already be in your environment, but you’ll need a detailed plan on how you intend to interface with these controllers.

3. Cameras. If your project includes collecting and analyzing computer vision data, then one or more cameras will be needed.

4. Lighting. If your project includes cameras, then you’ll need to set up appropriate lighting to make sure you collect usable vision data.

5. Networking and Protocols. You’ll need to decide on your data communication and networking hardware, to enable you to get data from one physical location to another. You’ll also need to decide on the protocols you’ll use for the project.

These five hardware areas are discussed in more detail in the sections below. You can also consult Intel’s Benchmarking & Workload Characterization report to help you make decisions on specific hardware choices. The report contains benchmarking data on various analytic workloads—across various Intel systems—to help you choose the most appropriate hardware for your particular environment.

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Computing HardwareComputing hardware is at the heart of your project, enabling you to consume, analyze, visualize, and store your data. You’ll need hardware that is optimized for your specific situation and best suited for your unique environment. Any challenging constraints in your environment can have a direct impact on the computing hardware decisions you’ll make.

With your environment in mind, consult Intel’s Benchmarking & Workload Characterization report to find the right computing hardware for your project. This report outlines how Intel’s Edge Insights for Industrial software (EII) performs on various Intel platforms and configurations. The document also quantifies different KPIs to measure the performance of EII and it contains a set of hardware and software recipes for common deployments and analytic models, helping you pick the right Intel platform for your situation.

The main computing hardware elements are:

• Industrial PC. An industrial PC (IPC) is a computer designed specifically for the various challenges of industrial environments. IPCs generally have higher standards for dependability and precision, enabling them to perform optimally under difficult circumstances.

• Accelerators. Accelerators enable computing hardware to perform certain functions more efficiently. There are hardware accelerators that can be added to an IPC to improve performance, depending on the situations you are targeting.

• Computing memory. Memory enables the effective storage and access of your project’s data. The type of memory you use will dictate how much you’ll be able to store and how quickly you’ll be able to access, share, and distribute your data. As a general rule, you will need at least 16 GB of RAM for your insights project.

• Storage. Storage enables you to hold your project’s data safely and effectively in various locations. Depending on your situation, you may need to store certain data on-premise on an edge device for a certain period of time, then transfer data to the cloud for longer-term storage.

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Programmable Logic Controllers (PLC)A PLC is an industrial, ruggedized compute device used to control manufacturing processes, such as assembly lines or robotic devices. There are many PLC designs to suit a variety of situations, such as a need for multiple inputs and outputs, working in extended temperature ranges, or functioning well with elec-trical noise, vibration, or impact.

The following are things to consider when setting up and using PLCs for your project:

• Connecting to your data. While connecting to a PLC, there are three things to keep in mind:

1. Physical connections. In certain situations, you’ll need to physically connect to a machine using an industrial interface such as Modbus.

2. Protocols. A protocol is a communication layer used in conjunction with the connection to a machine. Some protocols (like OPC-UA) have specific information models, while others (like MQTT) are more flexible.

3. Information models: The data itself may be in various formats, such as JSON. The information model associated with any older PLCs may be different from newer ones you may be using. Make sure your sys-tem design can handle multiple information models and your system is able to process the data.

• Connecting to HMIs and sending alerts. Connecting to an HMI enables you to visualize and work with your data, and alerts provide an important way for you to know when errors occur. When setting protocols for generating specific alerts, it’s important to consider how and when people will handle the alerts. For example, you’ll need to understand how often certain alerts will trigger and if they are serious enough to require human intervention.

• Considering the cells within your environment. Each cell in an industrial environment usually has multiple machines and controllers. If you are con-ducting your project within a cell, you will need to consider your machine configurations, data loads, and network set up, to effectively handle the data coming from multiple controllers. You will also need to consider data backup and data retention policies for the cell. If your project will span more than one cell, you may need to understand how firewalls will affect your project, or how best to establish connections between cells.

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Video camerasIndustrial video cameras let you capture vision data to be used for video analytics, such as detecting defects on an assembly line or monitoring for trespassers in a secure area. Below are some key aspects of industrial video cameras to help you decide which type of camera is right for your insights project.

Type of video cameras

What you are trying to analyze will dictate the type of camera you’ll need. The following are the main industrial video camera types, and their capa-bilities, with examples of what they are typically used for.

• Line scan cameras. Line scan cameras process very narrow bands, one at a time. They capture single rows of pixels in quick succession, while the camera is moved over an object or objects pass under the camera. Line cameras are used when there is a need to analyze many items in a row without stopping, or when trying to capture a very long image.

• Area scan cameras. Area scan cameras use a matrix of pixels to capture a scene, similar to how the camera on your smartphone works. They have a fixed resolution and are easier to install and set up. Area scan cameras are more general purpose and are often used to capture a defined area quickly, where an image can be segmented into regions to look for specific objects.

• Internet protocol (IP) cameras. IP cameras send video over an IP network. They can receive controls, such as play, pause, and record, and they don’t require a local recording device. IP cameras are typically easy to install, and they can have very fast frame rates or work well in very low light situations. IP cameras are often used for surveillance situations.

Choosing lenses

Depending on your situation, you may need a specific type of lens for your cameras. More expensive lenses that produce high resolution and high quality images can reduce processing times, while lenses that produce more basic imaging resolutions are more cost effective. Below are some factors to consider when choosing lenses:

• Sensor and image circle sizes. It is important to choose a lens that is large enough not to create any vignette at the edge of the sensor area, but not so large that there is “extra” area in the image circle that is not used.

• Resolution. If you need a high resolution image, you’ll need a lens with a high megapixel count that can resolve the pixel size. Lens resolutions help you know how large pixels can be while still being able to resolve them.

• Focal length. The focal length determines the angle of view, or how large of an area a lens can capture. The focal length you’re able to use is deter-mined by the width of the camera’s sensor. The focal length must match the sensor size.

• Aperture and lighting conditions. It is important to choose a lens that has sufficient f-stops (settings that allow the aperture to be more open or closed) for your environment’s lighting conditions. The lower the f-stop number, the wider the aperture will open, but this will also reduce the depth of field.

• Filters. You may need a filter to attach to your lens, such as a polarizing filter to help reduce glare on reflective objects. Certain colored filters can also help highlight important areas on inspected objects.

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Camera interfaces

There are a number of camera interfaces to choose from, depending on the cameras you’re using and what you’re trying to accomplish with them. The following are the most common camera interfaces, and when they are typically used:

• FireWire (IEEE 1394). FireWire is a popular interface due to the extensive availability of FireWire ports on computers. This interface has slower transfer rates, but it enables the connection of multiple cameras and provides power through the cable.

• Camera Link. Camera Link is an interface specifically designed for machine vision situations, such as automated inspections. This is a high speed serial interface, but a Camera Link capture card is required, along with special cabling and a separate cord to supply power.

• GigE. GigE is a gigabit ethernet internet protocol that uses standard Cat-5 or Cat-6 cables. Switches, hubs, repeaters, and other standard ethernet hardware can be used to connect multiple cameras.

• USB. USB 2.0 is pervasive because it is so common on computers. It isn’t high speed, but it is convenient. Cables are easily available and sometimes included with purchased computers. USB 3.1 maintains the plug-and-play benefits of USB 2.0, but has higher data transmission rates.

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LightingMaking sure you have the right lighting for your insights project is just as important as having the right cameras. Having the proper lighting is critical for enabling your cameras to capture usable vision data for your project.

Because gathering usable vision data often requires capturing small or hard-to-reach areas, parts, or products, the ambient lighting in your environment will likely not be sufficient. You’ll need to have supplemental lighting to properly illuminate the area you need to capture. Be-low are lighting issues you’ll need to assess in the context of your specific environment:

• Angle of light. Is your environment open or accessible enough to place supplemental lighting in the right positions to properly illuminate the desired area, part, or product?

• Shadows. Are there areas in your environment that have deep or extensive shadows that you’ll need to work within? Similarly, can you place lighting in ways to reduce or eliminate any cast shadows in the visual inspection area?

• Reflectivity. Are there reflective surfaces in the areas, parts, or products you are trying to capture? Are there reflective surfaces around or near the visual inspection area?

• Color. Are there colored surfaces within or around the visual inspection area which may affect the lighting? Are there regions in the area, parts, or products that are colored differently that might affect lighting needs?

Getting lighting “just right” for your project can be an iterative process. You may need to make multiple adjustments to various aspects of the lighting in order to capture usable data. For example, you may need to adjust the lighting placement, angle, color, and intensity several times before achieving the proper lighting.

Kinds of lighting

There are many types of lights you can use for your project. Lighting can vary in portability, power supplies, quality of light (e.g. “daylight” or diffused), and kind of light (e.g. halogen, incandescent, LED, etc.). The following are some typical lights that have been used for insights projects:

• Soft box or umbrella lighting. These lights produce softer, diffused light over a broader area.

• Ring lighting. These lights produce an even and direct light in a targeted area, minimizing shadows.

• Bar or panel lighting. These lights produce a bright, intense light that can cover a large area.

Your environment may require multiple kinds of lights, with various portability and power needs, depending on the complexity and number of areas you’ll need to inspect as a part of your project.

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Networking and ProtocolsThe networking and protocols you use will depend on the scope of your project, but also, the age and sophistication of the tools or sensors you are trying to connect with. For example, you may need physical cabling or need to work with several different communication protocols if you are trying to capture data from a variety of older tools, whereas newer tools or sensors may allow for wireless connectivity.

The following are hardware elements of networking and protocols that you’ll need to decide on for your project:

• Routers. It is important to have a router that can handle the data transfer for your project. For example, with some cameras a 10/100/1000 switch is required to handle the full bandwidth of the camera. Without it, you may experience a stuttering in the video stream.

• Wi-Fi & signal strength. If appropriate, you’ll have to consider the strength of the Wi-Fi signal within your environment. If there is weak Wi-Fi within your environment it may limit or prevent you from using wireless communication.

• Cabling. If you are using cabling to physically connect devices, you’ll need to consider how far away your input devices are from your compute device, and how many input devices you’ll need connected. The longer the cabling, the greater the risk of interference or degradation of signal integrity. Make sure to use newer ethernet cables to accommodate various needs for greater bandwidth.

• Protocols. There are many machine-to-machine communication protocols for industrial automation, such as MQTT, OPC-UA, and others. You’ll need to explore the protocols needed, depending on device needs and security functionality for authentication and authorization.

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Typical SetupBelow is an example of a typical setup for an industrial physical environment. The specific constraints of your environment will impact your setup, but this example will give you a sense of the high-level setup steps you’ll need to follow. This setup assumes you have already acquired the appropriate hardware, based on the requirements and assessments of the environment in which your project will take place.

Find the right location. Select a location for your IPC, controllers, cameras, lighting, and networking hardware that is near your project, easy to access, and easy to make adjustments to.

Perform initial wiring and connections. Complete all the power and network connections between all the devices and tools that are a part of your project. Note: you may need to change or adjust the location of certain hardware based on your power and networking needs.

Conduct various lighting and equipment tests. Conduct initial tests on your lighting, camera placement, and networking over different times of day and days of the week. This will help validate that the setup will work under various conditions. Note: you may need to change or adjust the location of certain hardware to take advantage of the best conditions throughout a day or week.

Perform initial data collection. Once you’ve conducted your initial tests, you can begin collecting data to see if your solution produces usable data.

Adjust or update hardware (if applicable). Depending on the results of your initial data collection, you may need to add or change your hardware to meet the requirements of your project.

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COMPUTER VISION SETUP TIME SERIES SETUP

ITERATIVE HARDWARE SETUP FLOW

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Contact Us

If you have any further questions about choosing hardware or setting up your physical environment, please contact your Intel account representative.

We’re here to help, and make sure your project is a success!

Intel technologies may require enabled hardware, software or service activation. No product or component can be absolutely secure. Your costs and results may vary.

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