Structuring Search for Problem

Point 1: generating problem statements

Problem of prediction:

-When analyzing an arbitrary event, the system measures the data incorrectly.

-predicting when certain consumables will run out (cleaning chemicals/battery if battery powered)

Problem of explanation: Hardware being used doesn’t advertise the point at which the data readings would be accurate

Problem of invention: Hardware that doesn’t have different settings that can be changed to adapt to its environment.

Point 2: Techniques and strategies

Statement-Restatement Technique:

Problem 1 - The data measured is of small sample size. The hardware does not measure small readings accurately. Plan to have 2 subsystems within the system, one to handle small readings, another to measure large readings. Inputs and outputs would be relatively the same between the two, however certain conditions can impact the readings of data. In theory, these conditions would impact the lesser readings since there would be a larger percentage of change than a larger reading.

Problem 2 - Consumers use a system only to find that the system doesn’t accurately measure data at which the readings would be accurate. The system does work, although only to an extent. Goals would include accurately describing the possible applications of the system before use. Inputs and outputs would stay the same although conditions of the user could have an impact on whether the system is a good fit

Problem 3 - There hasn’t been a need for inventing hardware that can handle data on a relatively small scale. The constraints of inventing a new alternative would be if the previous method/materials can physically handle being scaled down or accurately reading data at a lesser scale. An example of this would be changing the material of a wire from gold to steel. Does steel have enough conductivity to be on par with gold in the wire? These are the unknowns that would need to be tried and tested for the specific system.

Point 3 KT Situational analysis:

Given our recent problems, we know that the system should accurately read and display data. In theory, this happens chronologically by some event occurring, the system reading the data, and finally the system displaying the readings.

Point 4 KT Problem analysis:

What? - We know that the system is not correctly displaying data for small magnitude sizes. Goals are to be able to have one system that can read both small and large data

When? - The problem occurred when trying to correctly read a small magnitude. It would be beneficial to deploy the solution to future releases of the system.

Who? - In order to fix this problem, the development team of the system would need to be in on it obviously, but also consumer representatives. The source of information would be the consumer, however the problem would need to be tested by the producer to make sure that it wasn’t a local event.

Where? - The conditions in which the system is deployed can have an effect on the problem. For example, whether conditions, light exposure, system tampering, etc.. In addition to this, how the system was transferred to the consumer whether it be the hardware or the software.

Why? - The problem is important because consumers using the product without its intended purpose either promulgates that the system wasn’t correctly advertised or the system isn’t performing as intended.

How? - This is related to other problems in that they are, or we believe, this to be a common mistake. Whether it be consumer or producer error, this can be fixed by either updating the current system, or releasing a new system that has the problem fixed.