Asset Management in the Era of the Internet of Things
Asset Management in the Era of the Internet of Things
by Andrea Ceiner
Before addressing the way asset management changes in the Internet of Things (IoT) era, it is worth summarizing what has happened since information technology (IT) became one of the main forces influencing the global economy and the competition.
Figure 1 shows the historical IT waves that changed the competition. Each wave represented a big move in many businesses, asset management included. Every wave required new skills, techniques and technologies to manage a new kind of asset.
Figure 1: The four waves of IT-driven competition
It was in the second wave when a European leader in multivendor clinical engineering services designed a new enterprise software application supporting asset management. The company’s core business is all about the management of medical devices in the hospital environment, a particular kind of asset management.
The main tasks were grouped by the following services portfolio:
- Inventory and localization;
- Preventive maintenance (i.e., scheduling and executing a predefined checklist);
- Corrective maintenance, on call, with on premise repair, spare parts replacement (MRO);
- Safety and security checks, following predefined protocols;
- Replacement (e.g., obsolescence, unavailability of spare parts, unsupported by original design manufacturer (ODM), failure before maintenance too short).
The IT system was a multi-tenant web application, replicated with the single-tenant local servers spread throughout the network of hospitals served by the company. This architecture permitted the company’s technicians to work in a collaborative manner: technicians inside the hospitals performing equipment tests and measurements, and experts of regulations and senior technicians and engineers assessing remotely the results and defining the operative protocols and procedures to be shared.
This architecture was uncommon in that market niche. Most, if not all, competitors had a single-tenant local server, installed on premise at each hospital, with no replication or sharing of data. The fact that the company had all data replicated and shared gave it two competitive advantages:
- It was able to leverage the remote collaboration and knowledge sharing among technicians in different countries about different medical devices, which meant giving its customers a good quality for a nice price;
- It was able to be very precise in bid quotations, thanks to its big and historical database (one million devices, with all economical and technical data).
Unfortunately, all the data was manually inserted by the company’s IT team during working hours. If, instead, the company was in the third wave utilizing IoT, more than 60 percent of that costly quantity of data input would have been replaced by an automatic computerized process, from the medical device down to the shared database, until the backlog of the single technician, permitting the company to deliver even better service with less people. But, this is not the only benefit of IoT. It is interesting to see how IoT impacts that business. Table 1 presents a summary of the differences between the pre-IoT era (second wave) and today (third wave).
|Service||Second Wave (pre-IoT)||Third Wave (IoT-1)|
|Inventory and Localization||Manual||IoT driven: Automatic|
|Preventive Maintenance||IT aided||IoT driven: Predictive|
|Corrective Maintenance||IT aided||IoT driven: Over-the-air maintenance plus machine learning and cognitive computing suggesting intervention|
|Safety and Security Checks||IT aided||IoT driven: Over-the-air telemetrics and image detection plus machine learning and cognitive computing recalculating risks and reprofiling|
|Replacement||IT aided||IoT driven: Automatically calculated|
Here’s a deeper look at how it all changes with IoT.
- Inventory and Localization: In the second wave, the company had people who went from ward to ward and room to room throughout the entire hospital, assessing and recording on paper the medical devices. During this phase, the company collected identification data (e.g., serial number, label and other identifications), classification by type of device (e.g., defibrillator by ODM and by model), localization (e.g., building, department, floor, room) and state of the device (e.g., needs reconditioning, to be replaced, or good like new). Once the "tour" of the hospital was done, all the paper was copied into the web application to be electronically recorded, cleaned up, normalized and enriched by other information.
In the third wave, this process could be automatic. The devices’ identification information is either on hardware or firmware, or also inside the embedded software, kept up-to-date in a secure manner by the ODM or service provider via over-the-air provisioning and authentication cloud services. The location could be set and determined by more than one modality, such as radio-frequency identification (RFID) tags, Bluetooth® dongles, Wi-Fi position, global positioning system (GPS) or cellular positioning, or a manual setting triggered by an alarm triggered by an accelerometer, etc. The device could autonomously publish the data to authorized subscribers (e.g., an asset management software application) via message queuing telemetry transport (MQTT) protocol over secure sockets layer (SSL), or any other secure transmission protocol. Classification and state assessment could be done through low-cost augmented reality techniques, using a webcam or smartphone in combination with image processing for device picture matching.
- Preventive Maintenance: The company would go from preventive toward predictive. Today, the metrics published continuously by the devices are a valuable source of information. They can be processed by standard normalization paths services in the Cloud that prepare the data to feed properly to the machine’s learning and cognitive computing algorithms. Statisticians analyze the output and share the results with R&D engineers, after-sale service managers and marketing managers. When a cloud service can predict a device failure 24 hours in advance with 99.8 percent precision (as evident recently in a real case), this information can be used by:
- the end user to call for help before the break occurs;
- technical assistance to avoid an intervention covered by warranty and to discover fraud;
- a backlog optimizer service for the support engineers, with automatic opening of tickets with self-documenting capabilities;
- the device itself, setting its own failure based maintenance (FBM) indicator and shutting down with an alarm notification to avoid clinical risks and costs.
- Corrective Maintenance: Connecting a device to cloud services and to the apps and web applications used by the maintenance service means performing a lot of tasks over the air, without the need to be physically in front of the device. You can have precise diagnostics and know exactly what the device’s state was before and at the time of failure. The same data can feed the machine learning algorithms, which bind that failure with the intervention procedures that best fit with it. You can connect via MQTT or virtual private network (VPN) with the remote device in alarm and change its settings, reboot and update the firmware, operative system, embedded middleware and software applications. You can have a senior engineer remotely guiding a lower skilled technician in real time by use of augmented reality. This way, you save the time and cost of moving skilled engineers here and there, and you can also design a new technical support organization and skills map.
- Safety and Security: The device could autonomously publish its events, metrics and all relevant data for safety and security checks to authorized subscribers (e.g., a risk assessment software application running in the Cloud) via MQTT protocol over SSL or any other secure transmission protocol. The full process could be computerized, requesting human intervention only at the end of the process for reading and reviewing the final report to the customer. Visual parameters could be quickly detected through low-cost augmented reality techniques using a webcam or smartphone in combination with image processing for device picture matching, avoiding moving skilled people on premise. Also, the use of machine learning and cognitive computing can have a huge impact on how clinical risks related to the use of medical devices are profiled and detected.
- Replacement: As a consequence of the radical impact of IoT on the complete lifetime of a medical device, the replacement date is calculated with precision based on the data collected all along its lifetime (e.g., real usage, events log, settings, state log).
- New Revenue Streams: IoT is more of a business model revolution rather than a technological revolution. From the technical point of view, it is a fast evolution and commoditization of IT and OT converging over the Internet protocol and available as a service at a low price. All that informatics encapsulated in easy to use services available in the Cloud opens the door to new business models as never before. One example is selling data to ODMs. Dynamic maintenance predictive paths, real use information and real objective data about warranty claims (anti-fraud detection) have a real monetary value for ODMs. Short-term, it cuts the warranty costs of their medical devices and permits the R&D and marketing staff to design new models fit for real use, which means selling more for a long time. Additionally, ODMs themselves could design their own service-oriented business model, moving from selling a product one-off toward selling a recurrent service forever.
The Internet of Things will change the asset management market, led by those companies that will design their business models as IoT-driven. To succeed, they will have to create an ecosystem of clients, partners and suppliers because IoT can only succeed by leveraging an ecosystem. No company, regardless of its size, can do it all by itself.
There are more than 360 IoT platforms and over 100 protocols available today, with an impressive concentration of venture capital in start-ups having IoT in their goals. You need to partner with a local company that has the expertise and skills to help you make the right choices for your business and helps you in designing your IoT solutions.