The challenge:
From the time of delivery, manufacturers often no longer know anything about the use of the tools and systems they produce. They have no direct information about usage behavior, capacity utilization and damage caused by the customer. Warranty claims can therefore not be substantiated or refuted with well-founded knowledge.
Due to a lack of information on the device status, no proactive maintenance can be suggested and after-sales potential remains untapped. The fact that technicians have to be called out repeatedly due to a lack of expertise or the wrong spare parts also leads to increased costs for customers and manufacturers. In addition, it is not possible to distribute technician assignments to times with low capacity utilization.
Usually, no follow-up contracts are possible after the end of a 24-month maintenance period because manufacturers either do not offer such contracts or it is too expensive for customers. Machines must therefore continue to be serviced via internal maintenance.
And finally, manufacturers also lack information on how to improve their own products and how to achieve objective savings (electricity, water, materials, etc.). Product development reacts correspondingly slowly and leaves enormous potential untapped.
The solution:
The aim of the project is to create a template for a digital twin of the real machine or tool. The first step is to analyze the device in question together with the customer. Neuralgically important components and functions are discussed and it is defined how these can be detected by sensors. The next step is to find out where and in what quantities these tools are used, what service promises the customer receives and what service challenges they face.
Once the technical and economic factors have been clarified, the IT design is created. This defines what hardware is required on the machine, what the service of the device looks like and what data is required to realize an economic benefit. This is followed by an evaluation of the information already provided by the machine control system and, if necessary, additional sensors are integrated during prototyping.
This is followed by the concept of how the data is sent to the central analysis platform. Among other things, it is specified here whether this project should/can be done via WLAN or LTE. In this step, relevant environmental factors such as safety or standards are also taken into account.
Once the design has been completed, the product development department produces the first digital twin as a prototype. Data quality and availability are tested, as are the connection and the established cloud platform. Subsequently, data mining, analytics and BI design are used to generate the right dashboard and provide the necessary API interfaces to connect service departments, ERP, CRM and sales as required.
Furthermore, there are many possible options for integrating additional modules that further improve aftersales and service and enable premium functions.
The benefits:
Machine condition monitoring makes information available from globally distributed tools and systems. In the event of warranty claims by the customer, it is now possible to determine whether the appliance or system has been used properly and the tool has not been overloaded. It is now also possible to proactively inform the customer, for example to suggest a necessary service call.
Maintenance and service levels can now also be better fulfilled by determining the machine condition, maintenance situation and age of the machine. This includes the targeted deployment of service technicians or the timely stocking of important spare parts and replacement tools.
Detailed information about the machine allows manufacturers to grant longer contracts at sometimes more favorable conditions. If the customer complies with all parameters, the contract is continuously extended using a monthly pay-per-use model.
And product development also benefits. They can identify weak points in their own products at an early stage and react to them or explore optimization potential during ongoing operations.
Text taken over from the original and translated – ACP Digital
