# Solving a selected problem

**Problem and problem-solving goal**

The problems are finally defined and we can proceed to the second stage of the work – solving them.

At the first stage, we have studied the machine structure and operation, identified the conflict, proposed working hypotheses, i.e. determined the variants of conditions under which the conflict disappears. Some hypotheses are easy to implement and they are in fact problem solution variants. If it is not clear how to implement a hypothesis, we formulate a problem on its basis. The hypothesis suggests that some change should be made in the system and the problem brings up a question of how to implement the change in the circumstances of a specific useful system.

Problem solving is aimed at correcting the problem-generating circumstances in the operational zone. To do that, it is necessary to transform the problem system and obtain its alternative versions that are free of the original disadvantage.

**Hill-shaped scheme**

A problem-solving process based on any model is well described by a hill-shaped scheme that includes three transitions:

- from a problem statement to an abstract model of the problem
- from the abstract model of the problem to an abstract solution model
- from the abstract solution model to a specific solution

The reasoning chain is built in the following way.

The *problem* that refers to some real objects is transformed into its *abstract model *which reflects, in a simplified form, the main properties of the objects being improved or the relationships between them. In this case, it is not the problem itself that is transformed, but its model at the abstract level. The abstract model is transformed into a *solution model*, i.e. a general idea of what change is required for achieving the goal. Then it is necessary to understand what resources we can use to implement the abstract idea *at the real level*.

The following procedure is evident:

- build a problem model
- transform it into a solution model
- determine resource requirements
- generate a solution

For example: “it is necessary measure the distance to some object – initial point and object – initial point and object supplemented with some measuring device – apply a laser rangefinder.”

**Supporting the hill-shaped scheme with TRIZ tools**

The approach illustrated by the hill-shaped scheme is unconsciously used by a person for solving any problem. It also turned out to be very promising for solving inventive problems. The difference between the inventor's thinking and ordinary, non-reflective thinking is that when performing all three transitions of the hill-shaped scheme, we can transform them using standard models and heuristic tools developed in TRIZ. These are various types of contradictions, su-field models, smart little creatures, simplified physical copies of the system being improved, graphic, mathematical and other models.

Thus, we can use standard problem models developed in TRIZ. The models can be transformed into solution models using respective heuristic tools: methods of eliminating technical and physical contradictions, standard solutions to problems, rules for transforming other models. The result of these actions will be an abstract description of the problem solution.

As for the third step - transition from a solution model to a technical solution, you need to identify resources required for problem solving and to incorporate them into the solution model in an optimal way. The best way is doing this in two steps: first, making a detailed description of a required resource, a kind of a "resource sketch", and then finding a resource (or a set of resources) that satisfies these requirements.

This provides us with a serious methodological support in solving the problem.

Thus, within the hill-shaped scheme, we act in the following manner:

- Formulate the existing disadvantage, what exactly we want to improve.
- Find the principal idea of how to obtain the required result, what action should be performed for this purpose.
- Think about what resources we need to implement this idea and use it for improving a particular machine, find those resources and turn the idea into a real solution.