We look forward to hearing from you and are always available to answer your questions.
For design and product development, real machine data is the window into the reality of the user.
By creating transparency it is possible to build even more robust, efficient and durable machines. We create this transparency and answer the questions of the design department by providing machine learning algorithms:
- How must the machine be designed so that the customer can use it optimally?
- What is the raw data before an error occurs?
- Are there any patterns or signs that an error is occurring?
- How long does the machine run on average after one start?
- In which performance ranges is the machine actually used?
- How often and why do excessive accelerations of the machine occur?
- In which position are the machines used and how does this affect the health of the machine?
- How do different firmware versions affect machine performance and error probabilities?
Customer service cockpit
Daily problems: Who doesn’t know that – the customer calls and complains that the machine isn’t working. So you get into the car. You drive to the construction site, you examine the machine. Often for a problem that could have been solved over the telephone (keyword: insufficient power supply). This causes empty costs – for the trade and the manufacturer.
It would be ideal if you already knew what the problem was before you went to the construction site. With ToolSense this is now possible. With one click you know what the status of the machine is, how long it has been running so far, which error codes there are and which photos of the damage the customer sends via the ToolSense app. So you can drive to the customer and take the necessary spare parts directly with you. This saves you time and money.