Master Thesis
Do not waste the energy:
A factor-tree for Energy Efficiency in a
Metal Packaging Company
University of Gro ningen Faculty of Economics and Business Msc Technology and Operatio ns Management
1 Abstract
2
Table of Contents
List of figures...3 List of tables...3 List of abbreviations ...4 1. Introduction...5 2. Theoretical Background...7 2.1. Sustainability ...7 2.2. Energy efficiency ...8 2.2.1. Electricity efficiency...9 2.2.2. Gas efficiency ...10 2.2.3. Productivity ...10 2.3. Conceptual model ...10 3. Methodology ...12 3.1. Research method ...123.2. Reliability and validity ...12
3.3. Procedure for the case study ...13
3.4. Data limitations ...14
4. Findings and Analysis ...15
4.1. Gas and electricity consumption ...15
4.2. Productivity factors for gas and electricity efficiency ...18
4.2.1. Efficiency per department ...18
4.2.2. Correlation production factors...19
4.3. Sustainability factors for gas and electricity efficiency ...23
4.3.1. Compressed air...23
4.3.2. Heating, chilling and air conditioning ...25
4.3.3. Lighting ...25
4.3.4. Management, communication and awareness...26
4.3.5. Ovens...27
5. Discussion...30
6. Conclusion ...33
Acknowledgments...34
References ...35
Appendix A: Interview format...37
3
List of figures
Figure 1. In tegrated en ergy efficiency managemen t tool addressing all levels of the o rganization ____________ 9 Figure 2. Framework facto r-tree _____________________________________________________________________ 11 Figure 3. Energy costs 2012 _________________________________________________________________________ 13 Figure 4. Gas consump tion __________________________________________________________________________ 15 Figure 5. Electricity consu mption ____________________________________________________________________ 16 Figure 6. Gas consump tion 2012 _____________________________________________________________________ 17 Figure 7. Electricity consu mption 2012 _______________________________________________________________ 17 Figure 8. Gas efficiency LDr _________________________________________________________________________ 18 Figure 9. Gas efficiency DVA/DDE ____________________________________________________________________ 18 Figure 10. Electricity efficiency LDr ___________________________________________________________________ 19 Figure 11. Electricity efficiency DVA/DDE _____________________________________________________________ 19 Figure 12. Electricity effien cy VA _____________________________________________________________________ 19 Figure 13. Factor-tree en ergy efficiency _______________________________________________________________ 30 Figure 14. Gas consumption LDr _____________________________________________________________________ 38 Figure 15. Gas consumption DVA/DDE________________________________________________________________ 38 Figure 16. Gas consumption Heating _________________________________________________________________ 38 Figure 17. Electricity consump tion LDr ________________________________________________________________ 39 Figure 18. Electricity consump tion DVA/DDE __________________________________________________________ 39 Figure 19. Electricity consump tion VA ________________________________________________________________ 39 Figure 20. Electricity consump tion Lighting ____________________________________________________________ 40
List of tables
Table 1. Sustainability KPIs ... 7
Table 2. Correla tion LDr ... 20
Table 3. Correla tion production and spoilage LDr ... 21
Table 4. Correla tion DVA/DDE ... 21
Table 5. Correla tion Production and Breakdown time DVA/DDE ... 21
Table 6. Correla tion Production and Spoilage DVA/DDE ... 22
Table 7. Correla tion VA ... 22
Table 8. Correla tion Production and Breakdown time VA ... 22
Table 9. Correla tion Production and Changeover time VA ... 22
Table 10. Summary produ ctivity facto rs ... 23
4
List of abbreviations
DVA/DDE Ends department
KPI Key Performance Indicator
kWh Kilowatt hour
LDr Printing and lacquering department
Sig. (1-tailed) Significance level
SPSS Statistical Product and Service Solutions, a statistical analyzing program
SMED Single Minute Exchange of Dies
5
1. Introduction
The largest consumers of energy are industrial facilities (Moynihan et al., 2012). According to Moynihan et al. (2012) manufacturers are looking to save money due to the rise of fuel and energy costs. Fleiter et al. (2012) mention that energy efficiency is considered as a key element in
sustainable development. But not only the manufacturers want to become more sustainable, clients also want to buy products which are made sustainable, and with the use of energy as least as possible. When a company is able to reduce their energy usages, this can improve the companies competiveness (Fleiter et al., 2012).
The main reason to start this research, comes from a company who requested an investigation study on energy efficiency. The company wants to know what important factors that influence their energy efficiency Key Performance Indicator (KPI) are, so that they know where to improve their energy efficiency. The company is a part of a large organization that makes metal and glass packaging. This company makes only metal packaging. The company is divided in three different production
departments. It is divided into a paint shop and print shop (LDr), an ends department (DVA/DDE) and a cans department (VA). In the LDr, the plates are printed that are used for the cans. In the DVA/DDE the ends for the cans are made, but also the DVA/DDE makes ends that are sold immediately to a customer. Lastly the VA makes the cans.
The company has about 350 employees working for them. The departments works in different shifts. The LDr works mainly in three shift, the DVA/DDE works mainly in five shifts and the VA works in three shifts.
The total production for each department was in 2012: LDr, total prints and coats: 168,658,000, DVA/DDE, total ends: 440,755,000, VA, total cans: 252,663,000.
Literature shows that energy consumption is important and that organization should reduce their energy consumption (Bernal, 2012; For, 2013; Grossmann & Martín, 2010; Houde et al., 2011; Ke et al., 2012; Molla, 2008; Moynihan et al., 2012; Xu et al., 2012). However, little is written about the factors which are important for energy efficiency. Moynihan et al. (2012) give some factors that are important for electrical and gas usage, but do not go in-depth for these factors. They only mention some machine which uses energy. However they give some concrete energy conservation measures to decrease energy usages. Furthermore, Xu et al. (2012) conclude after doing a survey that
6 It is not only important for a company to improve their energy efficiency, but also on a global level it is important that energy consumption will decrease due to global warming and climate change (Molla, 2008).
This research strives to make a design for a factor-tree for energy consumption for industrial
facilities. This factor-tree includes all main factors that have an impact on the energy efficiency KPI. In this way industrial facilities will have a clear insight in their energy efficiency, and can easily find out where opportunities for improvements are.
In this thesis not only a factor-tree is designed, but also there are given guidelines how to control the factors in the company. The main point for this part is how to control the factors, and which factors should be controlled by which department. Drumm et al. (2012) mention that it is important that controlling is done in the right way.
So in this research, answers are given on the following questions:
What are the important factors which influence the energy efficiency KPI?
How should these factors be controlled throughout the organization to increase energy efficiency?
To answer these questions, a case study is done. During this case study, interviews are done, production data is analyzed and documents are analyzed. A detailed description of the procedure of the case study is given in Section 3.3.
7
2. Theoretical Background
In this chapter the theoretical foundation for this research are provided. First an explanation is given about sustainability, and what the factors for sustainability are. Second energy efficiency is handled, and an analyze is provided of what research already has be done on energy efficiency. Lastly a conceptual model is given on what factors can have influence on the energy efficiency.
2.1. Sustainability
As stated in the introduction, sustainability is becoming more important for companies (Xu et al., 2012). Stoughton & Ludema (2012) discuss different drivers for an organization to become sustainable. According to them the main driver for becoming sustainable is because outside stakeholders are demanding that the company becomes more sustainable.
Also Daily & Huang (2001) also mention that consumers are demanding for greening products and services. They also discuss how human factors can influence how sustainable a company will be. They conclude that to successfully implement an environmental management system human resource factors should be address. They gives several option to do this, which includes Top management support, Environmental training, Empowerment, Teamwork and Rewards.
Crews (2010) mentions that there are five leaderships challenges for implementing sustainability. These are Stakeholder engagement, Creating the culture, Holistic thinking, Organizational learning, Measurement and reporting.
However both articles do not give clear guidelines how to implement those factors into a company. Especially there is a lack in these articles on how to create awareness of people to become more sustainable. He does mention that reporting is important, but does not mention how to make it clear about why, or why not a company is sustainable, and where potential improvements are.
Xu et al., 2012 has done a research on sustainability KPIs of building energy efficiency retrofit (BEER) in hotel buildings. They identified six important KPIs which are shown in Table 1.
KPI 1 Quality
KPI 2 Hotel energy system management
KPI 3 Project cost benefit
KPI 4 Energy consumption & resources savings
KPI 5 Health and safety
KPI 6 Stakeholders’ satisfaction
8 Due to the fact that some of the KPIs in Table 1 are only unique for hotel building, they suggest that further research is needed to identify unique KPIs for other buildings, like industrial facilities.
In this thesis the focus is on the energy consumption KPI, and we try to determine other factors that have an impact on the energy consumption KPI.
2.2. Energy efficiency
So as mentioned above, energy is an important factor for sustainability. A recent study has been done by Kramer et al.(2010). In this study potentials savings are addressed on energy consumption for a pulp and paper industry in the United States.
Yet another study done by Fleiter et al. (2011) reviews bottom-up models that analyses the impact of implementing a new technology on the energy consumption. In this study also barriers are
mentioned why firms do not adopt a new technology. A more recent study has been done about energy efficiency in a German pulp and paper industry by Fleiter et al. (2012). In this study also assessments of potentials savings are addressed. This study mainly focuses on process technologies that can be implemented in a pulp and paper factory to decrease their energy consumption. In comparison to the other articles, this article also calculates the aggraded saving potentials.
However, none of the above articles provide an insight on when to select a certain technology. To select a certain technology, it is important to know where the highest potential savings are. On way to do this, is to have a clear insight why a company’s energy efficiency is low.
9
Figure 1. Integrated energy efficiency management tool addressing all levels of the organization
Mwasha et al. (2011) have done a research on sustainability performance indicators, and they conclude that sustainable assessment methods are often sets of economic, social and environmental indicators. They mention that also energy efficiency indicators plays a significant role in the
formation of sustainable performance decision making models. So they suggest that further research is needed to determine the level of interaction between the sustainable energy performance
indicators.
Moynihan et al. (2012) have done a case study and give some general points about machines that are using electricity and gas, however these general points are only useable for manufacturing plants.
To determine factors that has an impact on the energy efficiency, first we divide energy efficiency into two main KPIs, electricity efficiency and gas efficiency.
2.2.1. Electricity efficiency
Moynihan et al. (2012) divide the use of electricity in the use of electricity for machine and systems, and the use of electricity for the environmental condition of the building and lighting. In this research the use of electricity is divided also into process related use, and into environmental related use. An important factor that has an impact on the electricity efficiency is productivity (Herron & Braiden, 2006). See Section 2.2.3. for a description what are main points for productivity. Another factor we will analyze is unnecessary energy losses. These factors we call sustainability factors. An example of this is always letting the lights on, or using incandescent lamps instead of more energy efficient LED lamps. Another factor mentioned by Moynihan et al. (2012) is efficient a machine runs.
10
2.2.2. Gas efficiency
Gas is an important factor, because gas generates CO2 (Xu et al., 2012). Xu et al. (2012) mention that CO2 reduction is one of the most important factors to become a sustainable organization. Moynihan et al. (2012) divide the use of gas into process ovens and boilers. In this research the use of gas is divided in the use of gas for production, and the use of gas for heating the building. Also here an important factor that has influence on the gas efficiency is productivity (Herron & Braiden, 2006). See Section 2.3.3. for a description what are main points for productivity. Again also for gas we analyze if there are unnecessary losses. These factors we call the same as for electricity, sustainability factors. For example a factor can be, letting the ovens run, if there is a breakdown. Two other factors mentioned by Moynihan et al. (2012) is the isolation of the building and how efficient a machine runs.
Unfortunately in literature, also for gas efficiency no more factors are given that have an impact on the gas efficiency, so we have to determine more factors during empirical research .
2.2.3. Productivity
Productivity is measured by the amount of output which is generated in a certain amount of time (Ruch, 1982). Productivity is an important factor for determine the energy efficiency, because when more products are made with, in relation with the increase of products, less amount of energy, the energy efficiency will increase. Mann & Kehoe (1994) mentions a number of productivity factors, that can be used for our factor-tree, these are change over time, scrap/spoilage, line efficiency and machine breakdowns.
2.3. Conceptual model
During the literature research for articles about energy efficiency, we find that little is mentioned about factors that have an influence on the energy efficiency. Only one important relation is
11 The following framework, presented in Figure 2, is used as starting point for the research. In Chapter five the framework is expanded with the right factors. The outcome is a factor-tree that can be used to determine potential savings.
Energy efficiency
Electricity Factors Gas Factors
Productivity Productivity
Control of Factors by different levels in the organization
Sustainability Sustainability
Change over time
Line efficiency
Breakdown time
Spoilage
Change over time
Line efficiency Breakdown time Spoilage Letting lamps/PC/ Monitors on Use of inefficient lamps Letting ovens always run Unnessary heating the building Isolation of the building Inefficient machines Inefficient machines
12
3. Methodology
In this chapter the methodology for the research is described. Also in this chapter the way data is collected is analyzed. Lastly the data limitations are given.
3.1. Research method
We want to develop an insightful relationship between different factors and energy efficiency. Also the research is mainly about exploring the factors that have an influence on the energy efficiency. Furthermore, not much research has be done yet on this topic. Based on the above mentioned criteria, Wacker (1998) and Karlsson (2008) suggest an empirical research in the form of a case study is most suitable. Meredith (1998) mentions three points why for this research a case study is most suited. These three points are;
The phenomenon can be studied in its natural setting and meaningful relevant theory can be generated from the understanding gained through observing actual practice
The case study allows the questions of why, what and how to be answered with a relatively full understanding of the nature and complexity of the complete phenomenon
The case study lends itself to early, exploratory investigations where the variables are still unknown and the phenomenon not at all understood
So for this research a case study is done. In Section 3.3. the procedure how the case study is done is described.
3.2. Reliability and validity
Yin, (2009) describes how a case study should be done. He mentions four conditions that should be addressed to have a qualitative case study. These four conditions are; Construct validity, Internal validity, External validity, Reliability
Within this case study, we address the above condition in the following way:
13
3.3. Procedure for the case study
For the case study, one company is selected to perform the research. The company selected is a large industrial facility, that produces metal packaging for baby food. The company not only makes the cans, but also lacquers and prints the cans. The company uses both gas and electricity. In Figure 3 the energy costs are shown based on the consumption of gas and electricity, for the year 2012. For this reason, we assume that this company is a reliable company for which the research can be done. The company has just started an energy efficiency program, due to the fact that they have to reduce their energy consumption with 14% before 2017, in comparison with 2010.
Figure 3. Energy costs 2012
For collecting the right data, the first step was doing interviews with the management, to find out which data is available and where this data can be obtained from. Also interviews has been done with both the management and the shop floor employees to determine what they think has an effect on the energy efficiency, and how they think this could be improved. The purpose of these interviews was to determine factors that have an impact on the energy efficiency. In total eight interviews has been hold to determine import factors. These interviews has been hold with four technical assistants, the group leader for the electricity department, the facility manager, the environmental coordinator and the engineering manager. In Appendix A the format of these interviews is given.
The second step was to collect measurements of the gas and electricity consumption of the
company. These measurements of the gas and electricity are done on a monthly bases, on every first day of the month by the company. The measurements are manually put in an Excel file. The company does keep records of the amount of energy uses for each department, production line and machine. With this data it is possible to determine which department, production line and machine uses the most energy, and a selection can be made on the importance of each department, production line and machine. The measurements that are used for this research are the data from January 2008 till and up to December 2012.
The third step was collecting data from the company’s information systems. In these information systems, the company keeps records of the amount of products made, the amount of spoilage, the
€ 845.102
€ 1.384.525
Energy costs
14 amount of changeovers, the amount of breakdowns and the line efficiency. Each department uses their own information systems. Due the fact that the energy measurements are done monthly, also the productivity data has been converted to monthly data if this was not the case. Again, for the productivity data, the data from January 2008 till and up to December 2012 is used.
The fourth step was to determine the productivity factors that have to an impact on the energy efficiency. This has been done by analyzing the relations between the different factors and the energy efficiency, by checking if there is a correlation between them. So we analyzed on a monthly bases if, changeovers, breakdowns, spoilage and line efficiency has an correlation with the gas efficiency and/or the electricity efficiency. The program SPSS is used to test this.
The fifth step was to analyze documentations made by the organization. These documents are called “Best Practices” documents. These documents can be used by all companies which are part of the organization. In these documents guidelines are described how to coop with for example, safety, environment, spoilage and also energy consumption. By analyzing these documents, another number of factors are determined that have an impact on the energy efficiency. The findings of both
analyzing and interviewing has been combined.
The seventh step was to determine how each factor should be controlled, and who should be controlling each factor. To determine this, the “Best Practices” documents has been used, because these documents describes already some guidelines how to control these factors, and also the interviews which are done has been used to determine this.
The eight step was making the final factor-tree. All the factors that has been determined has been put into one tree.
The ninth step was to describe a guideline how the factor-tree can be applied.
The last step was to generalize the findings. To do this interviews has been hold with other companies of the same organization. Two other companies has been visited, and in each company one interview has been done with the environmental coordinators. During the interviews, the same question has be given as given in Appendix A, and the results are discussed to determine if the findings also could be used for those companies, which was the case for this research.
3.4. Data limitations
15
4. Findings and Analysis
In this chapter we summarize the main findings. First we give the findings of the companies
consumption of gas and electricity. This is done per department. Next we give the findings about the factors that have an impact on the gas efficiency and electricity efficiency. This is separated into production related factors and sustainability factors. For the production related factors, there is tested if there is a correlation between the factors and the gas and electricity efficiency. For the sustainability factors, the findings of analyzing the “Best Practices” documents and the outcomes of the interviews are used. The “Best Practices” documents, are documents made by the organization. These documents can be used for each company within the organization. The documents are mainly guidelines how a company should work. These “Best Practices” documents also contain documents about how to deal with energy efficiency. Thirdly, after all factors are determined that have an impact on the energy efficiency, a total factor-tree is made. Lastly based on the “Best Practices” documents and interviews the findings are given on how the different factors should be controlled throughout the organization, and which department should be responsible for a factor.
4.1. Gas and electricity consumption
First we give the findings of the gas and electricity consumption of the company. This is divided into consumption for production, lighting and heating. Next the gas and electricity consumption per department are given. The data from 2008 up to 2012 is used.
Figure 4. Gas consumption
16 In Figure 4 the gas consumption is given. Obviously there is a seasonal pattern, due to more heating of the building during the winter..
Figure 5 shows the electricity consumption. The consumption for gas and electricity, divided per department is given in Appendix B.
In Figure 6 and 7, the gas and electricity consumption are shown per department for 2012. As can seen from the figures, we find that the VA does consume gas. Also from Figure 6, we find that that the LDr is the largest user of gas, and that the DVA/DDE only use 3% of the total gas consumption. From Figure 7, we find that the VA, LDr and lighting uses most of the electricity.
Next we determine the gas efficiency and electricity efficiency per department, and try to determine the productivity factors that have an impact on both the gas efficiency and electricity efficiency. We describe the sustainability factors as a whole for the whole company, separated into gas efficiency and electricity efficiency.
Figure 5. Electricity consumption
17
Figure 6. Gas consumption 2012
Figure 7. Electricity consumption 2012
18
4.2. Productivity factors for gas and electricity efficiency
Next we describe the gas and electricity efficiency per department, and determine factors that correlate with the gas and/or electricity efficiency. For the productivity factors that can influence the efficiency, we look at the following factors; breakdown time (minutes per month), spoilage (amount per month), changeover time (minutes per month), and line efficiency.
4.2.1. Efficiency per department
Figures 8-12 show the gas efficiency and the electricity efficiency for each department. The gas and electricity efficiency is calculated by dividing the monthly gas consumption or electricity consumption with the production of that month. When analyzing the figures we can conclude that over the last five years, each department has become slightly more efficient, less gas and electricity is used to make a product.
Figure 8. Gas efficiency LDr
Figure 9. Gas efficiency DVA/DDE
0 5 10 15 20 25 30 35 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 M 3 G as pe r pr od uc t Date
Gas efficiency LDr
LDr 0 0,05 0,1 0,15 0,2 0,25 0,3 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 M 3 g as p e r p ro d u ct DateGas efficiency DVA/DDE
19
Figure 10. Electricity efficiency LDr
Figure 11. Electricity efficiency DVA/DDE
Figure 12. Electricity effiency VA
4.2.2. Correlation production factors
To test if a productivity factor correlate with the gas and electricity efficiency, we gathered
production data from the three different departments. We determine for each department if a factor
0 2 4 6 8 10 12 14 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 kW h pe r pr odu ct Date
Electricity efficiency LDr
LDr 0 0,5 1 1,5 2 2,5 3 3,54 4,55 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 kW h pe r pr odu ct DateElectricity efficiency DVA/DDE
20 correlate with the gas and electricity efficiency. The gas and electricity efficiency is calculated by dividing the gas or electricity consumption for one month with the amount of products made in that month. The factors that are tested are, breakdown time (minutes per month), spoilage (amount per month), changeover time (minutes per month), and line efficiency. To test these factors, SPSS is used to determine if there is a correlation. This is done by analyzing the Sig. (1-tailed). The Sig. (1-tailed) is a number that indicates if a correlation exists. Further we look at the Pearson Correlation. The Pearson Correlation is a number that indicates if a factor is positively or negatively related to the energy efficiency.
In Table 2, the correlation of the factors are given for the LDr. We find that for electricity efficiency, the line efficiency has a Sig. (1-tailed) of 0.000, this means that there exist a strong correlation between the electricity efficiency and the line efficiency. The Pearson Correlation shows a negative number of -0.500, which mains that when line efficiency increases, less electricity is needed to make a product, so efficiency increases. Also the changeover time has a strong significant correlation with the electricity efficiency with a Sig. (1-tailed) of 0.005. The Pearson Correlation has a positive number of 0.333, this means that when the changeover time increases, the electricity needed for a product will increase, so efficiency decreases. Lastly spoilage has also a strong correlation with a Sig. (1-tailed) of 0.032. However we expect to see that spoilage would have a negative effect on the efficiency, but looking at the Pearson Correlation, the number is negative with -0.240, which means that less electricity is needed when spoilage is increased. When analyzing why this is the case a obvious reason can be given, due to increasing production spoilage also increases (see Table 3). This causes the positive effect on the electricity efficiency when spoilage increases.
For the gas efficiency, both spoilage and line efficiency has a significant correlation, with a Sig. (1-tailed) of 0.003 and 0.001. Again, also here holds that the positive effect between the gas efficiency and the increase of spoilage is due to that when production increases spoilage increases. For line efficiency it holds that when this increases the gas efficiency increases, less gas is needed per product.
21
Table 3. Correlation production and spoilage LDr
In Table 4, the correlation of the factors are given for the DVA/DDE. As can seen, breakdown time, changeover time and line efficiency are significantly correlated with the electricity efficiency with a Sig. (1-tailed) of 0.007, 0.005 and 0.008, respectively. For breakdown time this means that when the breakdown time increases, electricity efficiency increases. This was not expected. For this factor the same holds as for spoilage in the LDr. When production increases, the breakdown time also increases (see Table 5). This is the reason that an increase of the breakdown time has positive influence on the electricity efficiency. When line efficiency increase less electricity is needed per product, so an increase of line efficiency will have a positive effect on the electricity efficiency . Also for the
DVA/DDE, the changeover time is correlated significantly with the electricity efficiency, also here the changeover time has a negative effect on the electricity efficiency. So when the changeover times increases, more electricity is needed per product. For the gas efficiency, spoilage, changeover time and line efficiency are significantly correlated with the gas efficiency with a Sig. (1-tailed) of 0.040, 0.000 and 0.000. Again here holds that the positive effect on the gas efficiency due to increasing spoilage, is due to that when spoilage increases also production increases (see Table 6). Also for the Gas efficiency of the DVA/DDE changeover time has an negative effect on the gas efficiency, and line efficiency has an positive effect.
Table 4. Correlation DVA/DDE
22
Table 6. Correlation Production and Spoilage DVA/DDE
In Table 7, the correlation of the factors are given for the VA. The VA uses only electricity. As can seen, breakdown time and changeover time are both significantly correlated with the electricity efficiency with a Sig. (1-tailed) of 0.004 and 0.000. The breakdown time has a positive effect on the electricity, but this is also due to an increase of production when breakdown time increases (see Table 8). However, changeover time is not in line with the findings before. The Pearson Correlation for the changeover time is negative with -0.562. This means that when changeover time increases, less electricity is needed, and thus has a positive effect on the electricity efficiency. The only reason that can be given, is the same as for the breakdown time, when production increases in the VA, also the changeover times increases (see Table 9). The reason for this is that when a line is not producing for some time, and when it starts producing, first a changeover is needed. For the VA, line efficiency has a significant level of 0.12, however this is not strong, it is a moderate significance. So also for the VA, it holds that when line efficiency increases, less electricity is needed per product, and thus increases the electricity efficiency.
Table 7. Correlation VA
Table 9. Correlation Production and Breakdown time VA
In Table 10, a summary is given of all the productivity factors for each department, with the significance level.
23
Table 10. Summary productivity factors
4.3. Sustainability factors for gas and electricity efficiency
In this chapter we give the main findings about the sustainability factors that have impact on the gas and electricity efficiency. The results given here are mainly the result of the interviews that are done, and from analyzing the “Best Practices” documents. The sustainability factors are divided into five different categories, which are: Compressed air, Heating, chilling and air conditioning, Lighting, Management, communication and awareness and Ovens. For each of these categories, sustainability factors are determined. Moreover we determine if a factor is qualitative or quantitative.
Furthermore, in this chapter we also mention how each factor should be controlled, and who is responsible for this controlling.
In Table 11 an overview is given of all the sustainability factors. Factors indicated with “ * ” are qualitative factors and factors indicated with “ ** “ are quantitative factors.
4.3.1. Compressed air
Compressed air, is air that is used for blowing the products through the production line, creating vacuum to pick up plates, etc. From analyzing the “Best Practices” documents and doing the interviews, the following sustainability factors for compressed air are determined which influence the energy efficiency.
The first factor is the use of dirty air filters. This causes pressure losses and the compressors will not be efficient anymore when it is not maintained well. To ensure this factor to be controlled well, regular checks and regular servicing of the air filters should be done. This control should be done by
Department Electricity/Gas Factors Significance level Significant correlation Pearson correlation Effect
Breakdown time 0.458 No -0.014 Positive
Spoilage 0.032 Strong -0.240 Positive
Changeover time 0.005 Strong 0.333 Negative
Line efficiency 0.000 Strong -0.500 Positive
Breakdown time 0.244 No 0.091 Negative
Spoilage 0.003 Strong -0.356 Positive
Changeover time 0.112 Moderate 0.160 Negative
Line efficiency 0.001 Strong -0.402 Positive
Breakdown time 0.007 Strong -0.317 Positive
Spoilage 0.083 Moderate -0.182 Positive
Changeover time 0.005 Strong 0.331 Negative
Line efficiency 0.008 Strong -0.309 Positive
Breakdown time 0.327 No -0.059 Positive
Spoilage 0.040 Strong -0.228 Positive
Changeover time 0.000 Strong 0.416 Negative
Line efficiency 0.000 Strong -0.458 Positive
Breakdown time 0.004 Strong -0.337 Positive
Spoilage 0.231 No 0.097 Negative
Changeover time 0.000 Strong -0.562 Positive
Line efficiency 0.122 Moderate -0.153 Positive
24 Facilities. This factor cannot be measured, however an observation can be made to check if an air filter is dirty or not. Therefore, this factor is qualitative.
The second factor for this category is produce more compressed air then necessary. This is mainly caused due to the fact that the compressors are designed based on the maximum required compressed air delivery rate. This causes that the compressor is always ove rrated for the average demand. To control this factor, the use of variable compressors is advised, or use one fixed compressor and one variable compressor for peak loads. Those variable compressors should be controlled automatically by a control system. This control should be done by Facilities. This factor can be measured, by checking how much compressed air is used over time. Therefore this factor is quantitative.
The third factor for this category are pressure drops. Pressure drops can occur by using too small pipe diameters, sharp bends and long distances. When pressure drops can be decreased, this means a energy saving of 5% for every 10% decrease in pressure. This factor can be controlled by doing audits of the compress air network, to identify places where pressure drops occur. The control of this factor should be the responsibility of Facilities, but the audits could be done by the different
departments on their own. The departments can then report their findings to Facilities which can take actions to improve the findings. This factor cannot be measured. For this factor there will be looked at characteristics of the pipes to identify places where pressure drops can occur. Therefore, this factor is qualitative.
The fourth factor for this category is use compressed air when equipment or lines are not in use. This causes unnecessary pressure losses. To control this factor, compressed air should be shut off when equipment is not in use. Mainly the control for this factor is the responsibility of a department on their own. For operators is should be possible that they can turn of the compressed air. The Technical Assistant should be having the responsibility that the operators do this, and communicate to them when this is not be done correctly. This factor can be measured, by checking if and how much compressed air is used when this is not needed. Therefore this factor is quantitative.
The fifth factor for this category are air leakages. This causes pressure losses throughout the
25
4.3.2. Heating, chilling and air conditioning
Heating, chilling and air conditioning are done to create a workable environment throughout the building. From analyzing the “Best Practices” documents and doing the interviews, the following sustainability factors for heating, chilling and air condition have been determined which influences the energy efficiency.
The first factor is not reuse hot air that is created by the ovens. When this is not done, hot air that could be used for warming the building will be lost, and additional gas is needed to heat the building. To control this factor, hot air from the ovens should be reused. This can create substantial savings. The control for this factor is the responsibility of Facilities. However, there should be a budget for Facility to do this. This budget should be given by the Top Management. If there is no budget for this factor, no responsibility should be given to Facility to control this factor. This factor cannot be measured, but is a improvement of the heating system. Therefore, this factor is qualitative.
The second factor is have a too warm working environment in places where this is not necessary. In a environment where physical work is done, the temperature does not have to be higher than 19˚C. In environments where no physical work is done, the temperature should be about 20-21˚C. When the temperature is higher, this will result is unnecessary use of gas. To control this factor, ovens should be shut down, when the desired temperate reached. This should be monitored carefully. Controlling the temperature is a responsibility for Facilities, they should control the temperature, and turn the ovens off when is a warm enough in the factory. This factor can be measured, by checking the temperature of a department. Therefore this factor is quantitative.
The third factor is bad isolation of the building. This causes unnecessary heat losses and gas
inefficiency. To control this factor, locations where isolation is bad should be improved. This can have a significant improvement on the gas efficiency for heating the building. Again for controlling this factor, the responsibility should lay with Facilities. However, also here holds that there needs to be a budget to improve the isolation. If there is no budget, Facilities cannot be hold responsible for this factor. This factor cannot be measured. Observations and audits has to be done to check if there are places with bad isolation. Therefore, this factor is qualitative.
4.3.3. Lighting
26 The firs factor for this category is use too high illumination levels. When illumination levels are higher than necessary, too much lights are used, and this results in that too much electricity is used. To control this factor, illumination levels should be checked in each department and decrease this illumination when possible. If for example the illumination level is twice as high as is necessary, one lamp could be taken out. The responsibility for controlling this factor should be given to facilities. They should start a project to determine where illumination levels are too high, so this can be improved. The illumination levels of a location can be measured. Therefore this factor is quantitative The second factor is use inefficient lamps. Inefficient lamps, costs a lot more electricity than efficient lamps. Using efficient lamps could achieve a 50% energy savings on lighting. To control this factors, a check should be done to determine which lamps are used, are replace inefficient lamps with
efficient lamps. Facilities should be responsible for controlling this factor. However budget has to be given to facilities to change the lamps. This factor cannot be measured, but there has to be checked what kind of lamps are used. Therefore, this factor is qualitative.
The third factor is let the lamps on unnecessary. It is known that throughout the company many lamps are on while no one is in that location. This results is inefficient use of electricity. A couple of things can be done by controlling this factors. First motion sensors can be placed, whe n no one is in a room for a number of minutes, lights will be turned off. This can especially be used in toilets and changing rooms. A second method to control this is to use light zoning. With the method the illumination of a light will increase when someone becomes near. The last method is to turn off the lights when leaving a location. To achieve this, the behavior of both employees and employers should be changed in such a way, that it becomes a automation to turn off the lights. Mainly the
responsibility for controlling this factor, is for each employee in the organization. Management and Facilities should do audits to determine if employees do this, and should also determine where motion sensors can be placed, and where light zoning can be used. This factor cannot be measured, but can be observed when doing audit to check if lamps are on when this is not necessary. Therefore, this factor is qualitative. However, men can discuss that this factor is quantitative, because it is time related. But it will be almost impossible to measure when and how long a lamp is on unnecessary, therefore we will determine this factor as qualitative.
4.3.4. Management, communication and awareness
27 The first factor for this category, is no awareness about energy efficiency. This can result in both unnecessary use of gas and electricity. The control for this factor, awareness should be created by changing the behavior of employers and employees. This can be archived by educate people and inform them about energy efficiency. Management should be responsible for creating awareness. They should organize workshops and presentation to inform all employees about energy efficiency. The second factor is not have energy meters. In this way, departments do not know how much energy they consume, and where they can improve. This can results in both gas losses and in electricity losses. To control this factor, energy meters should be installed so energy consumption can be monitored. To gain the most benefits of this, real time monitoring should be done. As mentioned by Houde et al. (2011), when monitoring the energy consumption with real time feedback, the energy consumption could be decreased with about 10%. This factor is mainly the responsibility for the management. They should be start a project to install the right meters at the right places.
The third factor is no control of management on letting lights, computers, monitors, heating etc. on unnecessary. People tend to forget to turn out lights or their PC when they leaving. This can result in both electricity and gas losses. To control this factor, audits should be done frequently to check if everything is out. A so called “Green House Keeping”. When people know that audits are done to control is everything is turned out, awareness could increase to turn everything out when leaving. Success should be rewarded, and failures should be highlighted. Management should be responsible for doing the audits, and should report their findings to all the employees.
4.3.5. Ovens
Ovens are used mainly for drying the sheets in the LDr. From analyzing the “Best Practices” documents and doing the interviews, the following sustainability factors for ovens have been
determined which influences the energy efficiency. All the factors described below for the ovens, are time related, and can therefore be measured. Thus these factors are quantitative.
28 The second factor is let the chain run unnecessary. When no sheets are fed, for example when there is a changeover, the chain does not have to run. This will cause unnecessary electricity losses. This can be controlled by stopping the chain automatically when no sheets are in the oven. Also the chain could be stopped manually during a changeover. If this is done automatically, the Technical Assistant should be responsible for integrating this is the production line. If this is not done automatically, operators should be given the responsibility that they can stop the chain. The Technical Assistant should then control if this is done in the right way.
29
*. Qualitative factor **. Quantitative factor
Table 11. Summary sustainability factors
30
5. Discussion
In this chapter we discuss the finding, and describe what the scientific and practical contributions are of our research.
First the factor-tree is made for the energy efficiency KPI based on all the factors we determine in the previous chapter. The tree is shown in Figure 13.
Energy efficiency
Electricity Factors Gas Factors
Productivity Sustainability Sustainability Productivity
Change over time
Line efficiency
Change over time
Line efficiency
Dirty air filters
Overated compressor for average demand Pressure drops Use compressed air when equipment not is used Air leakages
Not using hot air from ovens
Too warm working enviroment Bad isolation Too high illumination levels Use inefficient lamps Unnecassery letting the light on
No awareness No energy monitoring No control on letting lights, monitors, etc. unnecessary on.
Letting the cooling fans run unnecessary
Letting chain run unnecessary
Letting ovens run unnecessary
Heating, chilling and air conditioning Compressed air Lighting
Management, communication and awareness
Ovens
Figure 13. Factor-tree energy efficiency
31 increase the energy efficiency. Looking at the sustainability factors, there are many factors a
company can focus on. In this research we have formed five categories for sustainability factors, including compressed air, heating, chilling and air conditioning, lighting, management,
communication and awareness and ovens. For each category a number of factors are given. For each of these factors, we determined how a factor should be controlled and which department should be responsible for this controlling.
To apply this tree in a company, the following procedure is advised to follow, first the factor-tree as given in Figure 13 should be analyzed if and which factors can be used. To determine this, discussions has to be hold with different departments and people throughout the organization. As a guideline, a facility employee, technical assistants and the environmental coordinator should at least be spoken with.
When the factor-tree has been discussed, the second step is to determine if factors should be taken out or if new factors should be taken in to account. When new factors are determined, try to fit that factor within a category if possible.
The third step is to determine the importance of each category. We advise to look first at the amount of energy each category uses (except for the management, communication and awareness category, the factors in this category should be taken care of at any given time).
When there has been determined how much energy each category uses, the fourth step is to focus on the category that uses the most energy, because there the most improvements can be made most of the time.
The fifth step is to check the factors in that category. There should be determined which factor is most important, by determine the factor that has to most impact on the energy efficiency. Here it is important to discuss this again with the departments involved to determine the most important factor.
The six step is to give the responsibility for controlling that factor. When that factor is under control, the next factor within the category should be taken care of. When all factors within the category are taken care of, the company should focus on the next category. And follow again step five and six.
32 thesis enriches the findings of Drumm et al. (2012), by determine the factors that has to be
controlled by whom, to control the energy consumption. Lastly this thesis provides a methodology how a factor-tree can be made for energy efficiency for a company. This methodology can be used for other research beyond energy efficiency.
This research has also several managerial implications. The most important implication is that
33
6. Conclusion
In this chapter we give the answers on the research questions, the limitations of this research and avenues for further research.
To give an answer to the research questions formulated, for the first research question: “What are important factors that influence the energy efficiency KPI?”, a factor-tree has been made, shown in Figure 13. Here all factors founded in the company by doing interviews and analyzing the “Best Practices” documents are given. In total we have determined two important productivity factors and seventeen sustainability factors separated in five categories. Based on these factors a company can choose a focus point to increase their energy efficiency, by decreasing their consumption on both electricity and gas.
To give an answer to the second research question:” How should these factors be controlled throughout the organization to increase energy efficiency?”, we have looked at how the factors can be controlled based on the interviews and based on the “Best Practices” documents. Also we have used the article of Drumm et al. (2012), where is determined how to control the energy consumption for each level of the organization, as shown in Figure 1 in Section 2.2.We have also determined which department should be hold responsible for each factor. Each factor has its own methods to be controlled for, which are given in Sections 4.2 and 4.3. Mainly two important conclusions can be drawn for this question, the first is that facilities has most of the responsibilities to control the different factors, of course with the necessary help of the other departments. The second conclusion is that facilities can only hold responsible for some factors, if there is budget to control these factors. Management should create a budget for this, otherwise facilities should not hold responsible for the factors where money is needed for the controlling.
The research has some limitations. One main limitation of this research is that data is used from only one company. However, the expectation is that the findings also hold for other companies. But to be sure the theory should be tested in other environments. Another limitation of this research is that the data used for the productivity factors, and energy consumption are all manually put into a system by employees. Of course we trust that everyone does do this in an honest and right way, mistakes can always happen. When mistakes are made, they can have an influence on the outcomes, so when reading this thesis this should be kept in mind.
34 other environments, to find out if the factor-tree made in this research can be used in these other environments. Another interesting topic for further research is that in this research we have
determined the sustainability factors that can have an influence on the energy efficiency, but not yet how much impact a sustainability factor has on the energy efficiency. When this impact has been determined, a company will have more insights on what are the most important sustainability factors, however this can differ between companies. For example a company that uses a lot of gas, and another company that uses a lot of electricity, the importance of the factors can differ.
Acknowledgments
First I want to thank all people from the company where the case study took please for their help to get the right data and doing the interviews. My special thanks go to Dr. Piet de Vries who facilitated the case study at the company, and gave me support and feedback on my research.
35
References
Bernal, E. (2012). The Development of a Model of Sustainability Management , based on Biological Ethics. International Journal of Management, 29(3), 177–189.
Crews, D. . (2010). Strategies for implementing sustainability: five leadership challenges. SAM Advanced Management Journal, 15–22.
Daily, B., & Huang, S. (2001). Achieving sustainability through attention to human resource factors in environmental management. International Journal of Operations & Production Management, 21(12), 1539–1552.
Drumm, C., Busch, J., Dietrich, W., Eickmans, J., & Jupke, A. (2012). STRUCTese® – Energy efficiency management for the process industry. Chemical Engineering and Processing: Process
Intensification.
Fleiter, T., Fehrenbach, D., Worrell, E., & Eichhammer, W. (2012). Energy efficiency in the German pulp and paper industry – A model-based assessment of saving potentials. Energy, 40(1), 84–99. Fleiter, T., Worrell, E., & Eichhammer, W. (2011). Barriers to energy efficiency in industrial bottom-up
energy demand models—A review. Renewable and Sustainable Energy Reviews, 15(6), 3099– 3111.
For, D. (2013). Energy Management Systems: State of the Art and Emerging Trends. IEEE Communication Magazine, (January), 114–119.
Grossmann, I. E., & Martín, M. (2010). Energy and Water Optimization in Biofuel Plants. Chinese Journal of Chemical Engineering, 18(6), 914–922.
Herron, C., & Braiden, P. M. (2006). A methodology for developing sustainable quantifiable productivity improvement in manufacturing companies. International Journal of Production Economics, 104(1), 143–153.
Houde, S., Todd, A., Sudarshan, A., Flora, J., & Armel, K. (2011). Real-time Feedback and Electricity Consumption: A Field Experiment Assessing the Potential for Savings and Persistence. The Energy Journal, 34(1), 87–103.
Karlsson, C. (2008). Researching Operations Management (p. 322). Taylor & Francis.
Ke, J., Price, L., Ohshita, S., Fridley, D., Khanna, N. Z., Zhou, N., & Levine, M. (2012). China’s industrial energy consumption trends and impacts of the Top-1000 Enterprises Energy-Saving Program and the Ten Key Energy-Saving Projects. Energy Policy, 50, 562–569.
Kramer, K. J., Masanet, E., & Worrell, E. (2010). Energy Efficiency Opportunities In the U.S. Pulp and Paper Industry. Energy Engineering, 107(1), 21–50.
36 Meredith, J. (1998). Building operations management theory through case and field research. Journal
of Operations Management, 16(4), 441–454.
Molla, A. (2008). GITAM: A Model for the Adoption of Green IT. 19th Australasian Conference on Information Systems B2 - 19th Australasian Conference on Information Systems.
Moynihan, G. P., Triantafillu, D., & Affairs, V. (2012). Energy Savings for a Manufacturing Facility Using Building Simulation Modeling: A Case Study. Engineering Management Journal, 24(4), 73– 84.
Muchiri, P., Pintelon, L., Gelders, L., & Martin, H. (2011). Development of maintenance function performance measurement framework and indicators. International Journal of Production Economics, 131(1), 295–302.
Mwasha, A., Williams, R. G., & Iwaro, J. (2011). Modeling the performance of residential building envelope: The role of sustainable energy performance indicators. Energy and Buildings, 43(9), 2108–2117.
Ruch, W. A. (1982). The measurement of white-collar productivity. National Productivity Review, 22– 28.
Stoughton, A. M., & Ludema, J. (2012). The driving forces of sustainability. Journal of Organizational Change Management, 25(4), 501–517.
Wacker, J. (1998). A definition of theory: research guidelines for different theory-building research methods in operations management. Journal of Operations Management, 16(4), 361–385. Xu, P. P., Chan, E. H. W., & Qian, Q. K. (2012). Key performance indicators (KPI) for the sustainability
of building energy efficiency retrofit (BEER) in hotel buildings in China. Facilities, 30(9), 432– 448.
37
Appendix A: Interview format
1. How well do you think the companies energy efficiency currently is? 2. What projects has already been done to increase energy efficiency? 3. What projects are planned to be done in the near future?
4. What is your part within the energy efficiency project?
5. Is energy efficiency an urgent/important topic within the company? Does this differ between different levels within the company?
6. How is top management involved in this?
7. How well is the energy efficiency communicated throughout the company? 8. What factors are important factors that influences the energy efficiency? 9. How could these factors be controlled?
38
Appendix B: Gas and electricity consumption
Figure 14. Gas consumption LDr
Figure 15. Gas consumption DVA/DDE
Figure 16. Gas consumption Heating
0 50.000 100.000 150.000 200.000 250.000 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 M 3 g as Date
Gas consumption LDr
LDr 0 1.000 2.000 3.000 4.000 5.000 6.000 7.000 8.000 9.000 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 M 3 g as DateGas consumption DVA/DDE
DVA/DDE 0 50.000 100.000 150.000 200.000 250.000 300.000 350.000 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 M 3 g as Date
Gas consumption Heating
39
Figure 17. Electricity consumption LDr
Figure 18. Electricity consumption DVA/DDE
Figure 19. Electricity consumption VA
0 50.000 100.000 150.000 200.000 250.000 300.000 350.000 400.000 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 kW h Date
Electricity consumption LDr
LDr 0 20.000 40.000 60.000 80.000 100.000 120.000 140.000 160.000 180.000 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 kW h DateElectricity consumption DVA/DDE
40
Figure 20. Electricity consumption Lighting
0 50.000 100.000 150.000 200.000 250.000 300.000 350.000 ja n -08 ap r-08 ju l-08 o kt -08 ja n -09 ap r-09 ju l-09 o kt -09 ja n -10 ap r-10 ju l-10 o kt -10 ja n -11 ap r-11 ju l-11 o kt -11 ja n -12 ap r-12 ju l-12 o kt -12 kW h Date
