Intelligent product configurators or product design tools consider a wide range of parameters (e.g. regarding the intended use of the product, installation and environmental parameters, process parameters, etc.) in order to provide users with a product that is perfectly tailored to their needs. In this way, a supplier of complex products with a wide product range can provide both, its own sales force and customers, with a system that greatly simplifies and improves the product selection process. Examples of such systems include the configuration of special machines, the design of product variants for actuators and sensors, the configuration of modular controls, and solutions in building automation.

Applications in this area support users in the assessment or validation of an issue. These may be specified, for example, by legal regulations or international standards. For example, this may involve the assessment of the information security (Cyber Security) of a plant: A system containing information about the components used in the plant and their security vulnerabilities helps the user to assess or evaluate possible security risks affecting the plant. A system for evaluating the functional safety of a machine also belongs to this category.

Intelligent test systems within production or for testing hardware components can perform tests automatically and, depending on the reaction of the hardware under test, make decisions on their own (e.g. whether calibration is necessary, components need to be replaced, etc.). This saves manual work and increases product quality. Also, service technicians can be supported during on-site visits by systems that use augmented reality (AR) technologies, for example. These systems display key information and work steps to the user according to requirements during assembly or maintenance work, thus providing comprehensive support for the user's work.

Alarm and decision support systems assist the user in critical situations. These systems ideally recognize that a critical situation could occur in advance and warn the user accordingly or provide the necessary support to avoid the situation. If an exceptional situation has already occurred, the system supports the user in resolving it. Systems of this type are typically used where critical situations can occur, for example on ships, in the automotive sector or with mobile machinery such as cranes, construction or agricultural machinery.

Such systems provide the best possible support for operators of complex machines in their work. For this purpose, the operator receives, for example, information on all operating parameters of the machine, environmental parameters, consumption, etc. Often, these systems are an integral part of the human-machine interface (HMI).

In addition to supporting the operator, the focus here is also on optimizing the machine and the corresponding processes, in which the systems have access to the machine data and evaluate them, possibly using Artificial Intelligence methods.

This includes, for example:

1. Planning and optimization of capacity utilization and machine use
2. Detection of incorrect use or non-permitted use ("misuse detection")
3. Saving of energy and consumables (e.g. lubricants)
4. Real-time logistics and process control
5. Analysis and documentation functions
6. Derivation of recommendations for action

Systems of this type are used, for example, in mobile machines in mining and road construction, on ships, but also in production control stations and in the semi-conductor equipment sector.

M&M Software has already implemented numerous assistance systems, e.g. for well-known manufacturers of field devices, construction machinery and process engineering plants. Our combination of expertise in the area of Artificial Intelligence, our technology know-how in the area of Cloud and IoT, as well as our experience in the area of User Interaction Design makes us an ideal partner. When developing assistance systems, we pay special attention to the easy extensibility and adaptability of the systems; this can be achieved, for example, by integrating low-code extensions.