Predictive maintenance - real-time information creates new service experiences

Many manufacturing companies are increasingly looking at effective PaaS models based on IoT. OEMs (Original Equipment Manufacturers) in particular want to be able to plan the entire maintenance process in advance with the help of IoT-enabled products and spare parts. The underlying goal is clear: to drastically reduce machine downtime - while at the same time drastically increasing productivity and service quality.

The Internet of Things enables companies to create new service experiences through real-time information. The development from the traditional break-fix service model to the Servitization/PaaS model takes place in four stages, which we would like to illustrate here using the automotive industry as an example:

1. Reactive service

The status quo, which is still frequently encountered in the automotive sector in particular: customers are dependent on a breakdown service that responds to the breakdown of their vehicle or the failure of certain spare parts - a purely reactive service. There is no digital data transmission between manufacturers and products, so repairs can only be carried out when the vehicle is at a standstill, as pure maintenance.

2. Preventive service

The next stage: manufacturers are not yet digitally connected to their product, but are already pursuing a more mature service strategy. This includes, for example, regular maintenance, via which failures or machine downtimes are to be preemptively avoided. In the automotive industry, for example, manufacturers instruct their customers to bring their vehicles in for maintenance at certain time or distance intervals. If a breakdown nevertheless occurs, the manufacturer provides its customer with a rental car during the repair phase. So even with this form of preventive maintenance, there is still downtime. The goal, however, is to completely avoid unplanned downtime. This is the only way to significantly reduce inventory and maintenance costs in the long term.

3. Predictive service

Predictive service requires, at least in part, that manufacturers be digitally connected to products - and that they do so through the increased use of IoT-enabled products and parts. Using digital data transmission, manufacturers can now access information about the vehicle's location, hours of operation and usage. This gives them insights into how customers use the products - information that they can ideally use to make predictions about potential maintenance that may be needed. Manufacturers receive this information at regular intervals. In contrast to the preventive approach outlined earlier, they no longer make service forecasts in a blanket manner, but develop them individually based on actual usage data. This is an information advantage that enables manufacturers to develop a personalized maintenance strategy.

Typically, under this predictive model, manufacturers sell an all-inclusive contract that includes a service level or uptime warranty. Instead of a traditional product sale including after-sales service, they now offer access to a product, including all parts and services needed during the contract period. This transfers the risk of parts failure from the customer to the manufacturer. The risk for manufacturers in this service model, therefore, lies in correctly forecasting and analyzing the cost of parts and services consumption by the customer.

4. Proactive service

In this model, manufacturers are finally fully digitally connected to products. IoT-enabled parts provide them with real-time information, and deployed sensors provide values on location and product usage, as well as on temperature, vibration, pressure, energy turnover, etc. If manufacturers successively combine this sensor data with AI technologies, they receive information on potential product or part failures: The best prerequisites for service providers to now be able to develop and offer an optimally coordinated maintenance strategy!

A proactive customer service can not only predict failures, but also tailor its service precisely to each customer and their individual requirements - depending on their needs, to a high service level with corresponding preventive maintenance or also to a lower service level with a combination of reactive services and partial preventive maintenance. Customers no longer pay for a product in the proactive service model, but for a result.

IoT - key to convincing service and service models of the future

The Internet of Things definitely has the potential to revolutionize long-established customer service and maintenance process models. This applies not only to global players, but also to medium-sized companies. Service-centric business models offer companies many interesting opportunities to reposition their business and realize enormous growth opportunities.

This includes, for example, the introduction of subscription-based offer models for the respective product access including maintenance. In the areas of maintenance, repair and operations (MRO), IoT applications already offer solutions that go far beyond pure process optimization. For example, the combination of sensor technology and digital networking enables significantly higher response speeds in the event of bottlenecks or failures, makes such disruptions more predictable, and makes it possible to respond to them proactively.

For machinery involved in service-oriented business models, the increased use of IoT components means improved opportunities for the following areas in particular:

Improved production and maintenance processes
Determination of demand
Forecasting
Situation assessment
Planning
Optimization
Research / Discovery / Artificial Intelligence

Digitalization via IoT thus leads to increasing analytical capabilities, the implementation of ever new machines and components, and higher levels of networking. All these points are indispensable prerequisites for a veritable paradigm shift: away from pure problem solving to the creation of decisive market advantages through a customer-oriented, efficient development, production and maintenance chain.

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