**6. Examples for complex structures: quality prediction for manufacturing processes**

A typical set of manufacturing processes of gas preparation equipment (GPE) on the enterprise includes:


Not to tire the attentive reader, we will not state results of modeling for all processes—in examples 3 and 4, there are only results for processes connected with the operation of entrance threads and managing processes.

increases from 1361 to 20,431 h, that is, by 15 times. It is reached at the expense of timely reaction in process control. The integral probability of the performing processes, connected with the operation of entrance threads with an acceptable quality, is 0.97 for a month of GPE operation, 0.70 for GPE operation in a year and 0.32 for GPE operation in 5 years. The last probability (0.32) means that it may be a real one or more accidents or failures for 5 years of GPE operation, when counter-emergency measures should be performed. Risk of this is about

Probabilistic Modeling Processes for Oil and Gas http://dx.doi.org/10.5772/intechopen.74963 69

**Figure 10.** Prediction of quality of production processes connected with operation of entrance threads.

And what about reliability? The maintenance and diagnostic measures are performed every half a year according to recommendations of equipment suppliers. How much it is effectively

Results of predicting reliability of equipment connected with the operation of entrance threads are demonstrated in **Figure 11**. Expected integral MTBF is equal to 5770 h. It is 3.5 times less in

Summary: The account of daily results of control and measurements is necessary. Otherwise, if it is to be guided by only guarantee recommendations of equipment suppliers' occurrence, at least one accident or failure demanding counter-emergency measures of protection annu-

comparison with 20,431 h owing to daily periodic control (see the earlier section).

0.68, that is, twice more than the probability of success.

ally is possible and for 5 years it is inevitable.

for real operation conditions on the level of predicted reliability?

Example 3: It is required to predict the quality of the production processes and reliability of equipment connected with the operation of entrance threads.

Input data for modeling are formed as an analysis result of the average statistical data and requirements for production processes of the enterprise. A separate quality of each group of processes is estimated; then, quality of productions for GPE as a whole is predicted. Let an average time of recovery of each group of the processes earlier is equal to the duration of work of one shift, that is, 8 h. The predicted period is 1 month, 1 year and 5 years at observance of set modes for processes.

Note: For a pre-emergency condition, input data can essentially differ; that will cause also change of modeling results.

For the decision the models above are used. The results of modeling of the productions connected with the operation of entrance threads are analyzed in **Figure 10**.

Results of modeling: Owing to the recovery in time technological and production processes as a result of periodic control, the mean time between failures (MTBF), affecting quality,

**6. Examples for complex structures: quality prediction for** 

• processes connected with operation of entrance threads;

• processes connected with storage and use methanol;

• managing processes in the engineering division; • managing processes in the manufacturing division;

• managing processes in booster compressor station division;

equipment connected with the operation of entrance threads.

• managing processes in the administrative department.

• processes of low temperature gas separations;

• process of economical measure of gas; • processes of gas heating and reduction; • processes of candle and torch separation;

tion and diesel fuel;

threads and managing processes.

set modes for processes.

change of modeling results.

A typical set of manufacturing processes of gas preparation equipment (GPE) on the enter-

• processes connected with storage, supply and drainage dumps of the weathered condensa-

Not to tire the attentive reader, we will not state results of modeling for all processes—in examples 3 and 4, there are only results for processes connected with the operation of entrance

Example 3: It is required to predict the quality of the production processes and reliability of

Input data for modeling are formed as an analysis result of the average statistical data and requirements for production processes of the enterprise. A separate quality of each group of processes is estimated; then, quality of productions for GPE as a whole is predicted. Let an average time of recovery of each group of the processes earlier is equal to the duration of work of one shift, that is, 8 h. The predicted period is 1 month, 1 year and 5 years at observance of

Note: For a pre-emergency condition, input data can essentially differ; that will cause also

For the decision the models above are used. The results of modeling of the productions con-

Results of modeling: Owing to the recovery in time technological and production processes as a result of periodic control, the mean time between failures (MTBF), affecting quality,

nected with the operation of entrance threads are analyzed in **Figure 10**.

**manufacturing processes**

68 Probabilistic Modeling in System Engineering

prise includes:

**Figure 10.** Prediction of quality of production processes connected with operation of entrance threads.

increases from 1361 to 20,431 h, that is, by 15 times. It is reached at the expense of timely reaction in process control. The integral probability of the performing processes, connected with the operation of entrance threads with an acceptable quality, is 0.97 for a month of GPE operation, 0.70 for GPE operation in a year and 0.32 for GPE operation in 5 years. The last probability (0.32) means that it may be a real one or more accidents or failures for 5 years of GPE operation, when counter-emergency measures should be performed. Risk of this is about 0.68, that is, twice more than the probability of success.

And what about reliability? The maintenance and diagnostic measures are performed every half a year according to recommendations of equipment suppliers. How much it is effectively for real operation conditions on the level of predicted reliability?

Results of predicting reliability of equipment connected with the operation of entrance threads are demonstrated in **Figure 11**. Expected integral MTBF is equal to 5770 h. It is 3.5 times less in comparison with 20,431 h owing to daily periodic control (see the earlier section).

Summary: The account of daily results of control and measurements is necessary. Otherwise, if it is to be guided by only guarantee recommendations of equipment suppliers' occurrence, at least one accident or failure demanding counter-emergency measures of protection annually is possible and for 5 years it is inevitable.

Modeling allows one to compare the quality of various productions on a uniform scale, to establish levels of acceptable quality, taking into account expenses, to allocate "bottlenecks" in each of these processes and also to develop the general and separate recommendations about process improvements. For example, the comparative results of modeling of produc-

Thus, with other things being equal, a more complex structure of processes, as a rule, pos-

On the basis of the analysis of modeling results, numerous logical decisions should be made

Example 5: There is system which consists of a 560-km pipeline for pumping liquefied natural gas across the South American territory (the source of modeling data is a technical report of one of the oil companies). All lay of the line conventionally is divided into three parts (subsystems) by service conditions: first part through the jungle (200 km), second part through the mountains (300 km) and third through the plains (60 km). These characteristics of pipeline subsystems are presented in **Table 3**. It is assumed that the annual profit of operation of the pipeline in the first 5 years is 1500.000 and after is 2500.000 conventional units of accounts per year. It is required to predict the risks taking into account profits and the estimated costs (in conventional units of account) for the construction and maintenance of various sections of the

**jungle (200 km)**

**Table 3.** Characteristics of hazards, measures of control, monitoring and maintaining pipeline integrity.

**Part through the mountains (300 km)**

15 times a year 10 times a year 50 times a year

1 month 1 month 1 week

1 day/1 year 1 day/1 year 1 day/1 year

228.1 days 331.8 days 1217 days

10 days

1000 c.u. per year 2000 c.u. per year 200 c.u. per year

**Part through the plains (60 km)**

Probabilistic Modeling Processes for Oil and Gas http://dx.doi.org/10.5772/intechopen.74963 71

by enterprise management according to the criterion "quality-risks-cost."

**8. Examples of complex structures: modeling pipelines**

tion processes are demonstrated in **Table 2**.

sesses more risks. It should be considered.

pipeline between 10 and 50 years of its operation.

**Characteristics Part through the** 

The frequency of potentially hazards impacts on 100 km lay of the line (technical, natural,

The period between system controls the

The mean time to failure of monitoring tools at the area (without using or using existing/

The resistance of areas (the average time of preserving the integrity) for the dangerous influences statistically and in comparison

Average recovery time pipeline integrity after

The average cost of construction and maintenance of the area, over 1 km,

human or criminal, etc.)

prospective monitoring tools)

integrity of area

with analogues

occurrence of the fault

**Figure 11.** Predicted reliability of equipment connected with operation of entrance threads.
