Industry 4.0 ROI model first draft

model-23-july-2018

The first model draft (Might need correction later if any).

I split to 3 potions namely:

Portion 1:

the Big Data variables which I identified there are 2 levels of variables namely the main variables and the secondary variables.

The Secondary variables:

Variety – mean different type of data retrieve from the different feedback hardware raw sensor feeds or web service APIS. and this will contribute to the velocity as well as the veracity where the feedback hardware speed will affect the velocity and the accuracy of the feedback data will affect the veracity.

Value – mean different data type by priority, some data is more important amongst others and otherwise. this variable affecting the  veracity.

Visibility – mean data which will determine the trend and correlations to sharing amongst partners and different department in a manufacturing proceesing line. therefore the trend and correlations affect the veracity and the data sharing affect the velocity.

The main variables:

Velocity – mean the data processing time and transfer time, this variable will have direct impact to the productivity whereby if the velocity is slow down the existing manufacturing line then the productivity efficiency will reduce as well.

Veracity – mean the accuracy of the data.

if the data accurately to predict the equipment downtime or routine maintenance then it will reduce the unnecessary machine downtime.

if the data accurately to predict the equipment failure to affect of the product quality then it will able to reduce the reject rate.

the veracity contribute to the productivity were it will affect the production output.

Portion 2 and 3:

Production Output and perunit cost

according to the average cost theory, when the production output is increasing then the perunit cost will reduct and when the production output is decreasing then perunit cost will increase.

On the other hand for the reject rate, when the reject rate is increasing then the perunit cost will increase and if the reject rate is reduce the perunit cost will reduce as well.

and both production output and reject rate is affecting by equipment capital and expenditure.

Return of Investment.

When the productivity increasing and the reject rate is reduce then this will improve the ROI rate.

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