Product Monitoring System
Attaining individual context is the key to a profitable future
When built correctly, coupled with constant upkeep – it has the potential to change the way companies approach product design, development, manufacturing, and operation.
For value to be created across the lifecycle, a physical product configuration must be captured digitally once the manufacture of the product is finished. All content generated before this, in Engineering, or information recorded during the manufacturing of the product is valuable, but it should be considered part of its past and should be connected to the digital configuration of the physical product.
If you capture an individual product’s configuration correctly, you have context―which enables you to create traceability. In essence you have created the Digital Twin time machine. The context of the Digital Twin, supported by digital thread data, and analysis tools like simulation or analytics, allows you to move backwards and forwards for any product or system of products.
Let’s get started building your Digital Twin time machines and understanding the key parts required for it to be effective, so that you can start realizing the immense value it can provide.
Building your Digital Twin time machine
The reality is that many of your products, which last many years, did not come with Digital Twin configurations. This means you will need technologies and processes that enable you to record configurations, based on their maintainable components, down to their serial number. Doing this creates that foundational traceability―when a serialized component is replaced through maintenance activities. That change can be recorded with the new serialized component information, to keep the Digital Twin configuration up to date, as well as show the old component as part of its Digital Thread traceability.
Traveling into the past
For the Digital Twin to travel through time, context is key. But, to create next level of business value, your ticket to ride into the past and future―content will be king. For this you need to tightly couple the Digital Twin configuration with the related critical information that has occurred across the lifecycle―enabling traceability across the product lifecycle.
This requires a sustainable Digital Thread, which provides the ability to track a product and its digital assets all the way from concept through design, manufacturing, quality, and service. This connected information will help your organization gain crucial insights that can inform decisions throughout every aspect of the product lifecycle—improving communication and collaboration and resulting in the creation of better products, with a shorter time to market.
It is this traceability of what has happened, that gives your Digital Twin time machine the ability to travel into the past. For example, if technicians cannot locate or access information related to parts, job plans, or service bulletins―a.k.a. searching the past―productivity suffers, impacting equipment downtime and workforce productivity.
Predicting the future
With context and traceability in place, it’s time to predict the future. There is an emerging opportunity to do this with the many predictive analytics tools out there today, but those become more relevant when you use them to predict behaviors based on individual contact of product or system of products, which you now know how to build.
As simulation moves out to the field, it becomes operational simulation, which is about trying to understand what a product’s been through in its lifetime that might affect its operation once we apply an update. Simulation can have a much bigger presence in the physical world, if the context is there. Based on an individual configuration of an individual asset and use simulations, you then can predict what will happen if we replace a part, or update software.
A good example is simulating the impact of a new over the air (OTA) software update. If you don’t know each individual configuration of the product you are analyzing, you are making a guess as to its impact on the operation of the product, and that is not good for customer retention.
The other opportunity for moving out to the future, is simulating what will happen to a product operating, now. For example, let’s say that we start to see failures in the product once we reach a certain temperature, we can then use that data to predict what will happen if the temperature goes up even further than what it was when we started to see those failures. It's simulating not only the current version of the Digital Twin, but also simulating the future based on the real-time feedback that we're getting from the product.
Look for technology that adds horsepower
Existing PLM systems can trap valuable information, or worse, users have stopped capturing some of the data and decisions within them and have resorted to capturing information on their desktops. Some important information can be trapped in existing systems because they are closed. This makes it difficult to create meaningful relationship connections between all of a product’s digital assets and their revisions across the lifecycle― –bill of material(s), parts, software, electronics, CAD models, documents, requirements, process plans, service manuals, maintenance history, for example.
Let’s get started!
If you are in operations and maintenance, you can start by keeping accurate records of your inspections, track what a product’s configuration looks like when it arrives, or as it is in its operative state right now. This should not be paper based, nor a spreadsheet, as the manual maintenance and upkeep of the Digital Twin configurations would then become a daunting task. It should be in a database that is searchable, inspectable, and maintained.
Whatever the business case, the Digital Twin configuration should then be able to extend out to installation, commissioning, and operation at a customer site, allowing them to update the configuration as things change. Then from there, hopefully you're able to start capturing additional data from the field when your product is maintained. This is the Digital Twin time machine!
IoT Gateway provides following features:
MQTT connector to control, configure and collect data from IoT devices that are connected to external MQTT brokers using existing protocols.
OPC-UA connector to collect data from IoT devices that are connected to OPC-UA servers.
Modbus connector to collect data from IoT devices that are connected through Modbus protocol.
BLE connector to collect data from IoT devices that are connected using Bluetooth Low Energy.
Request connector to collect data from IoT devices that are have HTTP(S) API endpoints.
CAN connector to collect data from IoT devices that are connected through CAN protocol.
BACnet connector to collect data from IoT devices that are connected throughBACnet protocol.
ODBC connector to collect data from ODBC databases.
REST connector to create endpoints and collect data from incoming HTTP requests.
SNMP connector to collect data from SNMP managers.
Custom connector to collect data from IoT devices that are connected by different protocols. (You can create your own connector for the requires protocol).
Persistence of collected data to guarantee data delivery in case of network or hardware failures.
Simple yet powerful mapping of incoming data and messages to unified format
Smart metering solutions
Collect data from smart meters using different connectivity methods
Visualize the collected data on a custom dashboard
Analyze incoming smart meter data to derive actionable insights
Store data for reporting and historical analysis
Feed processed smart metering data into third-party applications for accounting and billing
The attached dashboard demonstrates real-time data from smart-meters that is collected using MQTT API.
We would like to highlight the following features:
low-latency updates using web-sockets;
ability to zoom-in into the charts by selecting time range with the mouse;
advanced tooltips and legend;
dashboard toolbar in the top-right corner enables global time selector and switch between dashboards.
Let’s Work Together
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