The Steel Industry Engineering Essay

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The Steel industry is situated in Linköping, Sweden. It produces cold-drawn bar steel. The annual production is about 50 000 ton. The deliveries goes primarily to Swedish engineering industry and exports to Nordic countries, Germany, the UK and the Benelux. The company has 80 employees. The production is organized in campaigns of three weeks with production during 16 days. The production is closed during Midsummer and Christmas as well during four-week holidays in summertime. The major energy sources for the company are electricity and oil.

Since the steel industries are quite large in its structure and production processes, it uses greater amount of energy. The energy use is also high in support processes such as lighting, space heating, ventilation, etc. During the production process, they run different energy-intensive machines, for example, bulk-throwing machine, folding machine, levelling bench, triple straightening machine, drawing bench, etc. The amount of energy used has become the major concern for the company because of the consequential higher costs.

Since Sweden has joined the European electricity market, the electricity price in Sweden has raised due to the higher European electricity price. As the major electricity in Sweden comes from hydropower and nuclear power plants, its price was lower. But the price has increased to adapt with the higher European price. This has resulted in an extra burden to the industries in Sweden because they are the major energy consumer (35-40 percent) of the aggregated domestic electricity use. The industries in Sweden are electricity-intensive in compare to other European counterparts.

The global carbon-dioxide emission is another concern for the industries. The more the energy-use, greater the amount of carbon dioxide emission in the environment. This will result in a greater external cost. Though Sweden uses less fossil fuel to generate electricity, the other countries have coal-intensive thermal power plants for this purpose. This is a bigger issue relating to the resource conservation for the future, but lies outside the scope of this report.

2. Objective and Limitations

The major reasons for the necessity/urgency of reduced energy consumption cited above can only be countered by industries themselves rather than looking for solutions outside them. Therefore the main objectives of this project are as follows:

To carry out the energy survey: Dividing processes as a unit process (support and production processes), to calculate energy demand and the annual energy consumption and obtaining the balance and to find the unnecessary energy use in other purposes other than the production and its support and mismanaged energy system.

To propose the energy saving measures: After obtaining the figure in the energy survey, to propose the energy saving measures residing within the limitations and scope of this project.

There are numerous limitations that do not allow suggesting energy saving measures in this project. Since the project runs under the course and not itself as a course, it is not possible to go beyond certain boundaries. Few of them to be cited as follows:

The scope of the project does not provide the opportunity to design the models applying optimisation and simulation techniques. It is not possible to carry out the sensitivity analysis which may possibly suggest the optimal energy saving way to run the process in the industry.

Lack of knowledge in the industrial processes.

Assumption is that all the processes such as Lighting and office equipment, ventilation, etc. are running all the time during working hours.

Every aspect of energy use and loss is not considered and analysed

Limited information.

3. Method

A top-down approach has been employed to carry out the energy survey. This approach is to break down the system into the sub-system level. Then each sub-system is refined in greater details until it reaches a grass-root level.

Here total energy input is provided by grid-electricity and oil, while the monthly data of the year 2005 given in the invoice is used to calculate the annual energy consumption and costs. The average power recorded during 5 production day data at the master switchgear is considered as a reference because it is located at the top. At the master switchgear, the division of supply occurs. These divisions can be categorised into support processes and production processes. As mentioned earlier, electricity and oil are the two forms of energy source used in the industry. Electricity is used in most of the processes, whereas oil is used for space heating and ventilation.

The detailed data of 5 production days during November and the data of July (four non-working weeks) are used as a reference to calculate the power demand during production and non-production periods. To calculate the total energy demand of lighting, office equipments, fans, etc., their power specification is used.

4. Results

4.1 Energy survey

Energy consumptions are mainly coming from electricity and oil according to the invoice the company provided. We can see in 2005 statistics, the yearly electricity consumption is 3800000 kWh and oil is 2128000 kWh. At the same time we got the price of energy. The company spent 2813000 SEK and 489000 SEK respectively on electricity and oil; that means the total energy cost is 3302000 SEK. By now we got the energy input to the company. Here not much of calculations involved; we have only added the figures together and very easy to get the energy consumption we want to know.

Our main task now is doing the energy survey. This survey can help us to find where the energy consumption going during the operation then we are trying to get the way to do energy saving.

In order to do the survey, we need to know what processes the company has and how much each process uses the energy. If we know how much each process consumes the energy we can get the total energy consumptions, although it has not been possible to find data for every process. But we are trying our best to make the result more close to the reality.

In order to sort our calculations, we categorised the process to support process and production process.

First of all, we do the support process

Table1: Energy used for support processes

Equipment

Energy use(kWh/year)

El

Oil

Lights and office equipments

548000

 

Ventilation

113600

874400

Space Heating

24500

1253600

Compressed air

368600

 

 

1054800

2128000

Here the main electricity consumption is lights and office equipments, ventilation, space heating and compressed air. We can find the process power in the information provided. For example, the office ventilation power is 2 kW. Meanwhile we can give the operation time is 8736 kW that is mainly used for the space heating and ventilation. The reason is that we can not get the information about heat coming from people, sun, equipment and machine. At the same time we can not get the detailed data about heat losses due to pressure difference of indoor and outdoor and losses through walls ,doors, windows since we do not know the exact figures about the construction of building envelope although the construction detail of wall is provided. More detailed calculation is shown in the appendices.

Second, we do the production process

Table2: Energy used for production processes

Bulk throwing machine

547500

Folding machine

368600

Levelling bench

174300

Triple straightening machine

396000

Drawing bench

762200

Air curtain

67300

Since the power of every machine they are using is changed from time to time, we cannot get the stable power of each machine. And we cannot use the average figure to calculate because the average figure cannot give the exact information of the power. So we have used the probability of operation power. For example, Drawing machine. The probability of power between 5 kW and 20 kW is 16 %. So the power need is (20+5)/2=12,5, 12,5*0,16=2. we have calculated every power and added them to get the total power of this machine. In the end multiplying with the operation time get the energy consumption of each machine.

Table3: Probability of occurrence

n(5<P<20) =

0,16

12,5

2

n(P=21,26) =

0,46

21,26

9,7796

n(21,26<P<150) =

0,065

85,63

5,56595

n(150<P) =

0,31

344,225

106,70975

0,995

124,0553

Here the operation time is 6144 hrs. Since the production is organized in campaigns of three weeks with production during 16 days, i.e. (52-4)*16/3*24=6144 hours

Total energy demand for all processes

Table4: Total energy demand for all processes

Processes

Equipment

Energy use(kWh/year)

Electricity

Oil

Support Processes

Lights and office equipments

548000

 

 

Ventilation

113600

874400

 

Space Heating

24500

1253700

 

Compressed air

368700

 

Sum

 

1054800

2128000

production processes

Bulk throwing machine

547500

 

 

Folding machine

368700

 

 

Leveling bench

174300

 

 

Triple straightening machine

395900

 

 

Drawing bench

762200

 

 

Air curtain

67300

 

Sum

 

2315700

 

Others

 

429500

 

Total

 

3800000

2128000

Energy balance is energy input equal to output. The energy input we can get from the invoice

in 2005; electricity consumption is 3800000 kWh and oil is 2128000 kWh. Through calculation above we know the electricity of support process is 1054800 kWh and 2315700 kWh from production. So the total electricity use is 3380500 kWh. Here 429500 kWh we can not figure out where they are going. So we use the category others instead.

Here 'others' in the table means that we cannot calculate where they are using this energy for. The main reasons are:

1, some data we cannot find at the homepage so by now we can say we did not do all the energy consumption calculations. We have omitted some processes.

2, energy leakage is very common during the transfer. Such as, electricity leak from the grid.

3, energy cost also happens during the fixing work. For instance, the equipments maintenance and repairing.

4.2 Energy savings

The main idea of what we are doing the energy survey for is to find out how to reduce the energy consumption.

After our calculation we have got some ideas on how to reduce the energy consumption which is as following:

using lower power light (support process) or using the controlling switch to adjust the power need for lighting.

reducing the operating time for ventilation. They do not need to let the ventilation run on all the time. We suggest they should be used only during the production time

reducing the heat demand through decreasing the heat loss by improving the insulation quality of the building envelope.

substitution, using biofuel to replace the oil is a way to reduce the energy cost and make the production more environment-friendly. Since we do not have the data about this kind of substitution they are not considered for the calculation.

load management. Reorganizing the operation of machines can help to reduce the power demand and energy usage.

improving the equipment efficiency can lead to the energy use more efficiency.

Table5: Savings in light

Table6: Savings in Ventilation

Also the saving measures of spacing heating and compressed air are considered. Detail in the appendices.

The improved total energy consumption after suggesting energy saving measures:

Table7: Improved total energy consumption

Processes

Equipment

Energy use(kWh/year)

Electricity

Oil

Support

Lights and office equipments

326200

 

Processes

Ventilation

79900

201100

 

Space Heating

24200

1253700

 

Compressed air

337900

 

production

Bulk throwing machine

547500

 

prosesses

Folding machine

368700

 

 

Levelling bench

174300

 

 

Tripple straightening machine

395900

 

 

Drawing bench

762200

 

 

Air curtain

67300

 

Others

 

75500

 

Total

 

3159000

1454800

5. Discussions

After proposing few energy saving measures especially in the support processes in the industry, we have got significant decrease in energy use. In our case, electrical energy-use reduction is from 3800 MWh to 3150 MWh (approximately 650 MWh per year). This obviously implies that there is a prominent reduction in costs. Therefore, we can say that even the small changes in the behaviours in the use of the energy in the industrial system will have the major impact.

Here, due to the limited boundary of the project other extensive measures cannot be suggested. Preparing the mathematical models and experimenting with the optimization, sensitivity analysis and simulations can result in high-flying impact in energy use. Thus the industry can benefit by optimal use of energy and savings significant amount of money in companies' scheme of things.

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