Asema IoT Central

Using IoT for preventive maintenance

Chapter 1. The benefits of connectivity for maintenance operations

Preventive maintenance is critical in making a fleet of equipment run fluently. Unless you are deliberately running a "just ride until it breaks" operation, regular checkups, cleanups and replacement of wear and tear parts is an essential routine in equipment management.

Having equipment connected with Internet of Things (IoT) technology can significantly help in performing such maintenance. IoT enables constant monitoring of equipment use and strain and makes it possible to diagnose problems without having to take units out of operation. With analytics, preventive maintenance can be turned into efficient predictive maintenance where issues are spotted in due time before problems occur.

The benefits of using IoT in maintenance operation include for instance

  • Reduced downtime. Problems can be analyzed remotely from machine telematics without taking the unit to a workshop.
  • Optimized resource use. The status and location of equipment can be used to better plan routes, cargo, schedules, etc.
  • Correctly timed maintenance. Maintenance can be scheduled at moments when actual wear is visible, not just at a regular checkup point.
  • Reduced specialist on-site visits. Manufacturer engineers can diagnose issues from remote control centers without a costly on-site visit.
  • Analysis of wear and tear compared to actual operating conditions. Equipment problems can be diagnosed against statistics of actual operating conditions such as heavy wind, rain or cold temperatures.
  • Fleet level management of maintenance. Correlating the data between equipment of a large fleet can show systematic design issues in equipment models and help creating better operating profiles for them.
  • Improved staffing. Employee working hours can be tracked based on equipment activity records.
  • Real-time details of fleet. Monitor gasoline levels, tire pressures, operating temperatures and other telematics data in real time.
  • Improved operating safety. Working style that may damage equipment or make it wear out faster or cause risks of accidents can be traced and tracked.

Asema Electronics is a specialist in IoT software, hardware and connectivity. In the next chapter we'll tell how our solutions help in preventive and predictive maintenance of equipment in practice.

Chapter 2. Asema IoT Central for preventive maintenance

2.1. Asema's expertise

Asema Electronics specializes in connected data management for demanding industries. We produce both sensoring hardware and software for these solutions and produce data analysis services for our clients. As a result we are a unique one-top-shop for demanding customers who require a coherent understanding of the demands of Internet of Things. Our solutions cover the full chain of features from very low lever hardware functionality in sensors and controls to high level data management, knowledge sharing, and business logic.

As the name implies, Asema IoT Central is the central component of the solutions we offer to our clients. It is the result of nearly a decade of product development of Internet of Things solutions for data intensive industries. Asema IoT Central is a software package designed to solve the problems of connectivity, data collection, and data analysis in an efficient manner. It connects to the existing telematics and other third party sensors available in equipment as well as custom sensoring equipment we develop for specific customer cases.

A very unique feature of the Asema IoT Central is the design principle we call the “grid”. A typical IoT architecture runs at a cloud service and collects data into central databases by connecting to various local sensors either directly or through various data collection agents. This easily results in “information silos”, rather heavy vertical solutions that are too rigid to adapt into the changing requirements of new businesses. Usual symptoms of such designs include difficulties in sourcing new data – typically due to technical limitations in installing software and sensors to equipment – and limited possibilities to share the centrally stored data. Asema's software on the other hand runs as native, compact size applications that can be installed into on-board computers, handhelds, and field-engineer laptops. This versatility makes installing and running the solution significantly easier and integrations much more powerful.

Asema's IoT software is available in three different flavors

  • Asema IoT Central. A full fledged IoT server and client application that includes business logic, local and remote user interfaces server grade database support, analytics interfaces, server components for remote management, and interfaces for system integration. The Asema IoT Central would be the version used at a central monitoring location for remote maintenance.
  • Asema IoT Dashboard. A user interface oriented component, primarily for mobile devices. This version brings the collected data to the field by offering a full event driven, real-time user interface for smartphones and tablets.
  • Asema IoT Edge. A stripped down server for edge logic. This is a squeezed down version that can be installed inside monitored equipment itself and offers real-time connectivity to all other components. The Asema IoT Edge features a business rule engine and light database support as well as server components for system integration so that it can store data and react to alerts even under poor connectivity or completely offline use.

2.2. Data collection and analysis

Asema IoT Central supports multiple methods for connecting sensoring equipment and collecting data in real-time. It natively supports dedicated IoT application protocols such as HTTP, MQTT and CoAP and hardware connections via WiFi, Ethernet, Bluetooth, NFC, serial and ModBus (SCADA). Because the software can be installed into actual equipment and has been programmed with low level programming languages, custom drivers for even exotic proprietary equipment can be programmed and plugged into the predefined interfaces.

Asema IoT Central has built in support for modern high-speed databases such as Cassandra. They scale with the operation just by adding new hardware and can store thousands of data readings per second. Such designs are currently the best solutions available for e.g. telematics data.

Data captured by Asema IoT central can be viewed in real-time from the customizable monitoring dashboards that show e quipment and their measurements with easily accessible graphical gauges and graphs. These are available as both native mobile applications and as browser interfaces for maximum flexibility for working in the field.

Asema IoT Central's equipment management bookkeeping allows maintenance engineers to record performed operations and upcoming tasks in visual plans. The visuals give one glance to the history and upcoming schedule of each piece of equipment. To remind of upcoming work, alarms can be set to the calendar or programmed as warnings into the data-analyzer. With programmable business rules engineers get an immediate notification when sensors in the equipment show potential malfunction.

In Asema IoT Central, anything can create an event and any event can be a basis for a business logic decision. Logical rules can be created using a graphical editor or be freely programmed with a scripting language. Events such as critical limits on wind speed or temperature can be propagated to multiple listeners who can then independently decide how to act to the given event.

Each unit in the system can be geographically tracked. The fleet can be viewed and managed in the form of basic tables or with a map view that plots the location of units in the field. The maps support for instance routing and navigation algorithms. Asema IoT Central embeds maps from suppliers such as HERE, MapBox, MapQuest and OpenStreetMaps and can use advanced mobility features such as geocoding.

2.3. Advanced connectivity

A key strength of Asema's solutions is advanced internet connectivity. Asema IoT Central emdeds in its core code the so called CloudRoute, a managed VPN solution that securely connects different units. Such connections are the basis of being able to securely collect data from sensors 24/7.

The CloudRoute VPN can be used to manage remote connectivity not only to the IoT software but also other software. So for instance if an on-board computer has a remote desktop connection available, that remote connection can be automatically tunneled through the CloudRoute VPN. Operators of the system can centrally open connections to the on-board computers on a per-need basis. CloudRoute offers one common connection point to external experts an isolates their access to the desired equipment only.

Asema IoT Central also offers a range of application programming interfaces (APIs) for connecting data to other systems. The software can serve other systems in real time and push data to them as it arrives. Similarly, it can serve as a client for other systems, making it possible to use data from various other resource handling and operating systems. The aggregated data is then shown in common monitoring dashboards.

2.4. Data sharing and management

A major differentiator in Asema IoT Central's connectivity and integration is what we call the Smart API. Smart API makes it possible to open the system to partners and contractors in a very flexible and advanced manner by using linked data.

Linked data is data that describes relationships. Common ICT system data, the non-linked one, treats data as simple assignment of values. For example A = 2, color = blue, speed = 20. Such value assignments are the basis of a vast majority of databases that store our digital world today. A database has rows with items and columns that assign items values. A product database could for instance have values in columns that could describe a bicycle like this: wheel_size = 28", color = gray, frame_size = medium.

Linked data describes the links between those items. Instead of just an assignment i.e. X [equals] Y, the relationship can be anything. Equipment A [is maintained] Pete. Lorry B [is driven by] Mary. Piston C [lifts the hook] of crane D. Such relationships form graphs, which are the core technology for storing linked data. And they make it possible to describe in detail and accuracy for instance the structure of a machine, including connections such as what components may cause a malfunction in which part of the machine.

Linked data also allows for managing data in a more consitent manner by defining it in terms of context. Consider an example where we would operate a fleet of excavators working at a constructions site. For preventive maintenance, we'd like to habe a tracking system that has a bookkeeping of the operating hours those machines. As an operator in this example, we would not own the equipment but lease it from three different companies. To get the operating hours we download the data from the systems of the leasing firms. But, these companies may well calculate and offer their data in formats that are not compatible. For example:

  • Leasing firm A: Average daily operating hours = recorded hours per month divided by 30
  • Leasing firm B: Average daily operating hours = recorded hours per week divided by the number of business days of that week
  • Leasing firm C: Average daily operating hours = recorded hours per day, each weighed by the type of load and strain on parts, averaged over a period of five days of operation

Making the same conclusions based on data from firm A would result in vastly different results than that of the other two if we do maintenance based on how many hours the machine has been operating since last checkup.

If we use linked data, such differing meanings are marked with a prefix. Instead of having just a measure AvgOperatingHours, we use three variables: leasingA:AvgOperatingHours, leasingB:AvgOperatingHours, and leasingC:AvgOperatingHours. The part before the double-colon, the prefix, tells not only the source of the data, but also its definition of the data. The technically advanced part of linked data is that software that supports linked data can be configured to automatically understand the differences between contexts. In this case it would automatically convert the data to arrive to one uniform set of values we can rely on when deciding on the maintenance of equipment.

Chapter 3. Example use

3.1. Software features

3.1.1. Real-time monitoring

Asema IoT Central is all about real-time data. The uniquely designed event system sends events on every change of value in the system to authorized users, administrators, and partners that have access into the system.

Following and analyzing the data in real-time gives equipment operators an in-depth view on how machines operate on daily basis. Action can then be taken to optimize the tasks, reduce the use of constly items such as fuel, prevent overloading of equipment by new drivers, and improve safety.

Asema IoT Central offers system operators fully customizable monitoring dashboards that give them a view to each unit in detail. The system can have master dashboards for the whole fleet and each unit can have its own, custom monitoring view.

Creating such monitoring dashboards is easy, just select the controls and monitors that are needed and drag & drop them in place. Asema IoT Centrals property and event system handles the details of getting data to the dashboard automatically. If something is still missing, system integrators can easily create more controls and customizations.

3.1.2. Asset handling

Each unit in Asema IoT Central is an asset that can be attached with various data and details needed in running maintenance operations. Part number, pictures, instruction manuals and the like can be entered into the system for joint use and dissemination between maintenance team members.

Various types of equipment can have their own, custom fields that apply to that type of equipment only. The source of the data can be manual entry or it can be fetched from an external system such as an existing asset management system.

For such integration, Asema IoT Central supports linked data. The technology, originating from the semantic web, is the key in creating unified, mashup views to corporate data. As the name implies, with linked data content from various sources can be fetched and processed. The idea is similar to the classical hyperlinks, but with a special emphasis on automated processing and measurement data. The technology is used for instance by car manufacturers to automatically produce interactive instruction manuals that help in troubleshooting of vehicles by automatically pointing to the correct instruction pages based on analysis of the telematics data.

3.1.3. Events and tasks handling

When something happens to equipment or something is planned to happen, various calendar events can be added to it either manually or automatically. Interactive event timelines then give a holistic view on what is actually going on with the fleet of equipment.

While Internet of Things technology makes it possible to monitor and adjust things remotely, sometimes even fix issues, most maintenance operations are still done on site at repair shops by trained personnel. Asema IoT Central therefore includes a task management and work allocation system. While such features are common from nearly any work management system, Internet of Things gives additional power to the process through automation. As machinery that is connected to the Internet can "call home", it can also automatically order its own repair.

Asema IoT Central's configuration features include ways to create tasks for workers based on measurement values from e.g. telematics data. If for instance engine temperature tends to reach a critical limit repeatedly during operation, this limiter can automatically generate a task that orders a maintenance operator to visit the vehicle and inspect it.

3.1.4. Data analytics

Internet of Things is all about data, in most cases massive amounts of data. Vehicle telematics can produce gigabytes of data every single day, something that is not possible to analyze without automation. This is why Asema IoT Central integrates with statistical tools such as the popular "R" statistics package.

With data analytics integration, massive amounts of data can be processed at regular intervals to find anomalies and patterns that may reveal malfunctions that eventually break the equipment. R is a widely used statistics package where such analysis algorithms can be programmed in as scripts that automatically crunch the data according to instructions. As R is used in a variety of industries and well-known to data analysts, designing such analytics is happens in a familiar environment with Asema IoT Central. And because of the underlying integration, when the analysis does find something to reach to, the scripts can create events that then build into concrete tasks for maintenance personnel to take a look at or automatic remote adjustments of the equipment at hand.

3.2. Customization and integration

Many of the features presented above, including monitoring dashboards, remote controls, and data analytics, are items that are available straight out of the box in each Asema IoT Central installation. However, while these features already support a vast variety of customization possibilities, it is very common that the functionality needs to be customized to fit the unique features of the operation of a user organization.

For this purpose Asema IoT Central is extensively programmable. During the roll-out of such a system, IT personnel and system integrators will mold the user interfaces and implement additional logic to the system. This is perfectly fine and possible with Asema IoT Central. The system ships with a variety of library components and APIs that the integrators can use to create such customizations. In fact, many of the features presented in this document have been implemented by using those exact APIs and libraries themselves.

3.3. Installation and configuration

Let's take a typical example and a simple task of periodic maintenance of a fleet of reachers. As you'd expect, in our example case maintenance personned keeps track of the maintenance periods by marking the maintenance into a ledger. A regular checkup should be done every 180 operating days and that information is available in the maintenance log of the reacher. However, we know for fact that all of the reachers do not have the same usage, performance or durability. Some can smoothly run for more than 300 days without issues while some other could not reach even a 100 day mark. Moreover, the new reachers are quite complex in their automation and in case of malfunction, it is usually advisable to have the engineers of the manufacturer to participate in the checkup.

Adding Internet of Things connectivity to help in the task, with Asema IoT Central, the process would involve the following steps:

  1. Install Asema IoT Central into a central server.
  2. Connect the IoT Central to possible existing equipment and maintenance databases and import all readily available historic information.
  3. Connect the telematics systems of reachers either directly (if possible) or by installing Asema IoT Edge into the reachers to collect data
  4. Choose parameters to monitor and setup the monitoring dashboards of Asema IoT Central in a way that operators can see vehicles, routes, performance measures, and other data of interest in the real time.
  5. Establish and setup the critical parameters of reacher performance that would be used as alerts and triggers of action.
  6. Input the details of the fleet into the system, including manufacturers' specifications, age of the vehicle, number and types of malfunctions, number of accidents and damage severity, type of the engine, etc
  7. Connect the system into sensors for operating conditions like humidity, temperature, wind speed, rainfall, etc
  8. Setup the business rules per tracked variable and action to take.
  9. Open the system for maintenance personnel and other operators by giving them access to the browser interfaces and by deploying Asema IoT Dashboard onto their mobile devices.
  10. Open secure VPN connections to equipment manufacturers and offer them access to the telematics.


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