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This blog post series is a result of a research project I conducted in 2021. The goal was to develop a maturity model for physical asset management. I wanted to make visible what opportunities companies have to digitalize their asset management. As a result, this blog post series contains 4 articles. In part 1 to 3 I want to provide you overview of state-of-the-art techniques. I am going to define every technology you need to know when it comes to asset management. In the end of the blog post series, in part 4 I am going to present the maturity model I created last year.  

Since the beginning of the industrialization, physical assets are an important part of our economy. Due to a continuously increasing degree of automatization, companies have become more and more depending on well-functioning assets. The requirement of reliability and productivity let to the first concepts of asset management and as a result we are facing a new kind of industrial revolution. The industry 4.0 provides plenty of new concepts and approaches to bring maintenance and service to the next level.

How to define Asset Management?

Before I get into the various technologies, let me define asset management first. According to the ISO standard 55000, an asset is something that has protentional or actual value to an organization. An asset can be tangible or intangible if it provides some economic value to an organization. Assets can categorize into various forms: physical assets, financial assets, human assets, or informal assets.

The term asset management describes the coordination of all asset related activities of an organization to extract added value. This includes inspections, maintenance, and restorations. In this blog series, I will focus on physical asset management.

How to store asset data?

Now I want to take a closer look on how store asset data to enable new technologies in asset management. A well-structured asset data is the foundation for every application. In modern asset management solutions, the data is object-oriented hierarchically structured, and, in each object, properties are stored in the form of attributes.

This graphic shows a representative excerpt of an asset management data model. Here, the starting point is the class. To visualize the structure, I want to explain it by an example. Let’s assume I want to model the class “Pump”. I can now assign different subclasses of the class “Pump”. These could be various kinds of pumps, for example “Submersible pumps” or “Diaphragm pumps”. Now I can assign different models from several manufactures to this subclass. If a company owns one of these models, it will now be instantiated. After that you can assign components like “Equipment” or “Spare parts” to the model which you also instantiate as soon as you put them in operation.

What is the Internet of Things?

Besides structuring asset data, it is useful to collect data from IoT-devices to enable the full potential of modern technologies. The so-called “Internet of Things” is a term introduced by Kevin Ashton in the year 1999. It combines different technologies. IoT is defined as a system which connects different physical devices, sensors, and objects. Its architecture is the following: On the lowest layer, there are the IoT-Devices. They can be identified by a so-called “universal unique identifier”. The devices are connected by a network, which enables the communication between the devices (M2M communication). Additionally, the network recognizes new devices and builds up a connection with them. It enables collaborative execution of tasks. The next layer, the IoT-Platform, handles all service-related activities. This includes the management and storage of data. In addition, the layer provides a communication interface to the application layer via API. The top layer is called IoT-Application layer. This is the place where the data gets processed and the communication with the user takes place.

Storing data alone is not enough to face the modern challenges of asset management. In the next blog article, I want to take a closer look on how to share asset information along its asset life cycle and how to collaborate and enable new business models with the help of an asset collaboration network like SAP Asset Intelligence Network (AIN).