Energy efficiency in manufacturing: perspectives from Australia and Europe

Energy Efficiency in Manufacturing – Perspectives from Australia and Europe

1

Joint German-Australian Research Group Sustainable Manufacturing and Life Cycle Management

2

Institute of Machine Tools and Production Technology (IWF), Product- and Life-Cycle-Management Research Group, Technische Universität Braunschweig, Germany

3

School of Mechanical and Manufacturing Engineering, Life Cycle Engineering and Management Research Group, The University of New South Wales, Sydney, Australia

Abstract

Over the last years, life cycle oriented concepts in manufacturing have been developed and introduced in research as well as in industrial practices (e.g. measures to improve energy efficiency in production) to foster sustainability. Since the implementation of these concepts depends on certain conditions and requirements, the question comes up whether the implementation is always successful in different regions of the world. Therefore this paper discusses and compares the specific conditions in Europe (specifically in Germany) and in Australia. Both regions significantly differ regarding basic aspects such as geography, climate, business as well as population, resource availability etc. In addition the paper also addresses the influence of these differentiating parameters and the specific potentials and challenges of to foster sustainability in manufacturing.

Keywords: sustainable manufacturing, energy efficiency, life cycle engineering

1 INTRODUCTION

Environmental challenges like global warming, increasing pollution and resource scarcity are getting accelerated due to ongoing global industrialization and increasing world population. The challenges are linked with unforeseeable consequences for the current and the upcoming generations. Production plays a major role since production processes involve the usage of resources and energy in order to be able to generate the intended products. Related to the processes are emissions to the environment and depletion of resources. For example the industry sector is a major consumer of energy with (e.g. case of Germany) a consumption of over 28% of the primary energy [1]. Thereby, electricity with a share of about 30% is used besides gas (37%), coal (17%) and oil (13%) in this sector [1] [2]. Focusing on electricity on a national level, the demand of industrial sector is responsible for over 47% of the total country’s consumption. From an ecological perspective, just the generation of this amount of electricity for industrial consumption through power plants sums up for about 18-20% of the total CO2 emissions in

Germany (additionally there are further 20% through direct CO2 emissions of the industry sector) with certain

consequences on global warming as well as other environmental issues (e.g. radioactive waste, land utilization) [1, 2]. As Figure 1 depicts this problem is likely to increase significantly in the next decade while emerging non-OECD countries like China or India are facing strongly growing energy demand, e.g. for the industrial sector and transportation (which also involves industrial transports) [3]. Besides this long-term perspective these developments also evoke strong economic effects (short-term) for manufacturing companies, e.g. through rising energy and material costs. For instance, electricity prices have been steadily increasing over the last years. This is not just an issue for high-cost countries like Germany and Australia but a similar trend of energy price rise can be observed internationally as depicted in Figure 2,

which shows a graphical representation of the average (as well as minimum and maximum) energy prices in the European Union over the years [1].

b a

Figure 1: Development of worldwide energy demand for the industrial sector (a) and transportation (b) [3]. Therefore it is very obvious that an isolated consideration of classical economic and technological variables (e.g. lead times, utilization) is not sufficient for manufacturing companies nowadays. In fact, Sustainable Manufacturing is the new necessary paradigm which involves the integration of an economic, environmental and also social perspective (known as the triple bottom line) for all technological and organisational measures within the normative, strategic and operative production management [4]. In the case of energy consumption, besides appropriate concepts for energy generation (e.g. renewable energy), the efficient and the effective usage of energy is a major concern in order to decouple economic growth and energy related environmental impact. However, requirements, potentials or constraints can differ worldwide which may lead to different solutions to improve energy efficiency and effectiveness in manufacturing in different countries. Therefore, this paper provides a generic framework of manufacturing systems, based on country specific variables, and the associated energy consumption related to manufacturing. Germany and Australia are used to implement the framework and to demonstrate the results

2 MANUFACTURING SYSTEM DEFINITION 2.1 Manufacturing system definition

Figure 3 shows the manufacturing system definition as applied here. It consists of three layers each with different entities and input/output flows: process/machine, factory building, and national/international supply chain. While being hierarchically structured it is important to mention that superior layers (despite not shown) naturally also subsume all elements (e.g. input/output flows) of subjacent layers.

0,00 2,00 4,00 6,00 8,00 10,00 12,00 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 €-C e n t/ k W h years

Figure 2: Comparison of electricity prices in European countries (based on [1]).

Process Level

A process is generally defined as a “set of interrelated activities which transforms inputs into outputs” [5] and contains one or several activities which can be characterised as transformation, combination or transport respectively control, measure or storage [6]. Therewith processes directly (e.g. machining process) or indirectly (e.g. transportation) contribute to value creation in the form of products with desired specifications. Determined by certain process parameters they are executed by machines and/or (depending on the degree of automation) workers which also involve certain specific characteristics (e.g. machine parameters, behaviour). Referring to the definition above a process naturally involves diverse input and output flows. In contrast to former economic driven process models, an extended process understanding is very important when striving towards sustainable manufacturing. To avoid possible rebound effects, e.g. when measures decrease one input variable but lead to an increase of another variable at the same time, all relevant input and output flows and their quantitative values have to be considered. For an integrated evaluation of economic and environmental performance material and energy related input flows have to be put in relation to valuable products, discarded products, and emission flows [7]. Additionally it is crucial to understand that energy consumption and associated emissions of certain energy or material flows are not static but rather highly dynamic depending on the actual operating state.

Factory building

Referring to the definition, the “inputs to a process are generally outputs of other processes” [5] which underlines the embedding of processes into process chains. A process chain is basically a logically linked sequence of successive or parallel single processes (and associated activities) over time with one common goal namely to bring out a defined output

(one or several final products) at the very end [8]. Furthermore processes and process chains are embedded in a certain production environment, typically in a factory. Thereby three main partial systems have to be distinguished [9]: the production system itself (with machines and personnel controlled through production management), the Technical Building Services (TBS) and the building shell. In relation to the integrative process model as described above a complex control system with dynamic interdependencies between different internal and external influencing variables can be identified so that their designated objectives, production processes (e.g. machines) dynamic input flows like electricity, compressed air, steam or cooling water et cetera which are provided through TBS, are fulfilled. Another task of TBS is to ensure the required production conditions in terms of temperature, moisture and purity through cooling/heating and conditioning of the air. The essential influencing variables are not only the local climate at the production site and also the exhaust air and the waste heat that is primarily emitted by production machines but also by other production factors like transportation equipment or even personnel. TBS itself naturally need additionally energy input through electricity (which can be bought from an energy supplying company or generated directly at the production site), gas or oil. Thereby the actual energy consumption of TBS is heavily determined by its specific design and (control) parameters [9].

process FACTORY BUILDING process/ machine 1 process/ machine n energy e.g. gas, oil,  electricity technical building services (TBS) e.g. temperature,  humidity, radiation cooling heating exhaust air,  waste heat production environment energy/media e.g. comp. air,  steam, electricity MACHINE raw materials energy/media auxiliaries personnel information products by‐products , scrap/waste gas emissions heat information NATIONAL/INTERNATIONAL SUPPLY CHAIN company n company 1 customer energy e.g. fuel gas emissions e.g. CO2 transportation local climate emissions e.g. gas, waste water

Figure 3: Manufacturing system definition.

National/international supply chain

Generally a supply chain can be defined as “a set of three or more entities (organizations or individuals) directly involved in the upstream and the downstream flows of products,

services, finances, and/or information from a source to a customer.” [10] Transformation steps taking place in single companies/factories are therefore interlinked by transportation processes. These processes are realized using different modes of transportation, e.g. road, rail, flight or ship transport. The input of these processes is energy, i.e. the fuel for the different transportation modes. The output is on the one hand the transportation performance described by the mass of the freight transported over a specific distance. On the other hand, especially the use of non renewable fuels is associated with emissions to the environment, such as CO2

and other greenhouse gas emissions.

Besides the freight task in terms of lot sizes and mass especially the distances between the single actors in a supply chain are of particular importance for the energy consumption in supply chains. Actors within a supply chain may either be located within the same country as others or in another country as single manufacturing steps are nowadays allocated globally based on availability and costs of resources, production factors, human resources and expertise as well as based on the location of markets and customers [11]. Furthermore, the specific fuel type and fuel efficiency of the chosen transport mode is a determining factor for the energy consumption in supply chains as well as the associated environmental impact. Based on this sustainable supply chain management can be defined as “management of raw materials and services from suppliers to manufacturer/service provider to customer and back with improvement of the social and environmental impacts explicitly considered” [23][24].

2.2 Efficiency indicators

The general concept of Sustainable Development has been defined by the The World Commission on Environment and Development (Brundtland Commision) as “development that meets the needs of the present without compromising the ability of future generations to meet their needs.” [12] However, the implementation and operationalization of this concept requires concretion and transformation into strategies and principles. To implement ecological sustainability, three strategies are commonly distinguished [13]:

 Efficiency - Optimization of the cost-benefit ratio of the economy regarding use of resources and damage to the ecosphere

 Sufficiency - Overall limitation and reduction of the effects of the economy on the environment involving change of behavior of usage and consumption

 Consistency - Adaptation of material and energy flows to fit to biological process capacities.

Focus of this paper is the efficiency strategy. In general, efficiency (E) is defined as the ratio between output (O) generated and the input (I) required to achieve it [14, 24]:

I

O

E



Thereby, the energy input required to produce a desired output is commonly specified in [kWh]. However, in addition to the amount of energy also other figures can be used to calculate energy efficiency [15]:

 Energy consumption is on the one hand connected with costs (see Figure 2) which can be used to calculate the economic input caused by the energy usage.

 The generation and provision of energy, on the other hand, is associated with environmental impact, e.g. greenhouse gas emissions (GHG), land use and resource depletion. These impacts differ according to the means of energy generation and can be evaluated, e.g. by conducting a life cycle assessment, and utilized to calculate the eco-efficiency of energy usage.

To provide a framework for the analysis of macroeconomic and geographic parameters on the energy efficiency of manufacturing systems the same output is assumed in terms of transportation and transformation of products. Thus, the focus of the subsequent argumentations is on the energy input (and associated costs and environmental impact) necessary to enable these transformations and transportations.

3 IDENTIFYING COUNTRY SPECIFIC VARIABLES

Based on the definition of the manufacturing system and efficiency indicators four major country specific factors with an influence on energy efficiency can be identified. These are climate, distances, energy sources and prices. Considered as average on a national scale, other factors such as qualification levels, the degree of automation or the average age of machines also significantly differ between different countries. However these factors are not depended on the geographic location. In contrast to the identified factors above, they are transferable and their actual state depends on the specific case of each manufacturing company.

Climate

Referring to the definition of the Intergovernmental Panel of Climate Change (IPCC), climate is “the ‘average weather’ or more rigorously […] the statistical description in terms of the mean and variability of relevant quantities over a period of time […]. These relevant quantities are most often surface variables such as temperature, precipitation, and wind.” [16] Depending on the geographical location on the globe, the climate naturally differs between different regions in the world as depicted in Figure 4. The most popular climate classification system developed by Köppen/Geiger based on the average monthly temperature and the precipitation values (other factors like cloudiness, wind or radiation are not considered). This system distinguishes between five major climate regions and diverse sub-classifications [17, 18] (Figure 4). As described in the last section in the case of air conditioned production the local climate naturally has an impact on energy consumption of technical building services. For instance, while striving to keep certain production conditions constant higher outside temperatures are likely to cause higher energy consumption for cooling. However, general statements about the actual effect are difficult to know as they are strongly depend on the very specific case (e.g. dimension and isolation of building shell, configuration of TBS, actual progression of temperature and radiation, internal heat loads).

Figure 4: Climate zones worldwide based on classification of Köppen/Geiger [17, 18].

Energy sources

Different means of electrical energy production and provision are available. Generally, three different energy sources can be distinguished:

 Conventional thermal energy generation by incineration of non renewable resources such as coal or gas  Nuclear power generation

 Energy generation from renewable resources, such as wind, water or solar power

Figure 5 shows the energy mix composition for the electricity net generation in different countries worldwide. Significant differences can be observed between countries largely depending on conventional thermal energy generation with certain high GHG emissions, such as Australia or Saudi Arabia, and countries already mainly switched to renewable energy sources like Brazil or Norway. However, renewable energy sources do not lead to zero impact, e.g. a substantial amount of CO2- and CH4-emissions of the electrical energy

system in Brazil are liberated by the submerged plants at the flooded area of dams in hydropower stations [25]. Thus, energy consumption in specific countries is associated with a specific environmental impact depending on the sources.

20% 2% 24% 15% 2% 15%24% 77% 3% 34% 14% 0% 19% 0% 4% 0% 0% 42% 0% 0% 9% 17% 9% 17% 17% 62% 16% 14% 85% 1% 6% 20% 21% 7% 20% 18% 0% 55% 5% 100% 71% 81% 67% 68% 82% 24% 61% 10% 12% 64% 80% 81% 61% 93% 76%_82% 100% 3% 96% 0% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Nuclear Renewables Conventional Thermal

Figure 5: Electricity Net Generation 2008 by type and country (top 20 countries) [3].

Energy prices

As depicted in Figure 2, since 2000/2001 electricity prices show a steady trend upwards which is mainly caused by likewise rising resource prices (e.g. oil, gas) [1]. Studies underline that this general trend is very likely to continue in the next years despite temporal fluctuations due to changing economic conditions. However, the figure also underlines that energy prices strongly differ between different countries due

to the specific structure of energy supply (e.g. availability of energy sources), market conditions (supply/demand and competition situation) and political/legal background (e.g. taxes, subsidies). Therewith local energy prices are naturally a major location factor, which directly affect the cost structure of producing companies.

Distance

On the supply chain level, especially the distances to be covered during transport are of major influence for the energy consumption. This parameter is influenced by country specific aspects in two ways. On the one hand, the size of a country determines the distances to be covered in national transport. Furthermore, the location of the sources and the destinations of transportation within the country determine the transport distances as well as in some cases the transport mode, e.g. road, rail or ship transport. The location of manufacturing sites and industry zones is mainly related to the location of major metropolitan areas as these areas at the same time supply workforce for the operations and provide access to markets and infrastructure. On the other hand, the location of a country on the world map in relation to its major trading partners determines the energy consumption for international freight transport. Furthermore, the location also determines available modes of transportation. An island location, such as Australia or Japan, allows only air or ship freight transport for international trade. On the contrary, international trade within Europe can mainly be conduct using domestic shipping, rail and road transportation.

4 CASE STUDY GERMANY - AUSTRALIA

Based on the identified country specific variables, Germany and Australia will be used to demonstrate the actual impact of these factors. The study focuses on the example of a chocolate factory which produces diverse variety of chocolate products under climate controlled production conditions.

Climate

In a first step the coherences between outside temperature and electricity demand for air conditioning (AC) in summer were analyzed based on detailed measurements (sample rate of one minute over several days). Plotting daily values of (apparent) power and temperature in a diagram reveals the strong correlation of both variables (Figure 6). In fact, this coherence can be described trough a linear or polynomial equation with sufficient accuracy.

poly. trend line y = ‐154,11x2_{+ 7247,5x ‐ 64663} R² = 0,9028 linear trend line y = 1742,6x ‐ 17005 R² = 0,8476 0 5.000 10.000 15.000 20.000 25.000 10,00 12,00 14,00 16,00 18,00 20,00 22,00 24,00 ap pare n t po we r  [V A] temperature [°C]

Figure 6: (Apparent) Power of AC in relation to outside temperature (daily averages based on own measurements). The equations can also be used as a simplified model to predict air condition related electricity consumption in the considered temperature range. Figure 7 shows the average

monthly temperature of Germany’s and Australia’s biggest cities, Berlin and Sydney [19]. With an annual average of 17.7°C Sydney is significant warmer than Berlin (avg. 9.8°C). The three hottest months are December to February with average temperature of 21-22°C whereas Berlin summer (June-August) sees average temperatures of 17.5-19.2°C. Based on this temperature information the prediction models (linear and polynomial) were used to estimate air condition related electricity consumption of the chocolate factory (ceteris paribus) for the three hottest months (normalized to same amount of days) of the average year.

0,0 5,0 10,0 15,0 20,0 25,0 Ja n u ar y Fe b rua ry Ma rc h Ap ri l Ma y Ju n e Ju ly Au gu st Se pt e m be r Oc to b e r No ve m b e r De ce m b e r av g.  te mp e ra tu re  in  °C Sydney, Australia Berlin, Germany

Figure 7: avg. temperatures in Sydney/Berlin (monthly) [19]. Figure 8 shows the results of this calculation which confirm that, holding all other influencing variables constant, higher temperatures (in Sydney summer) lead to significantly higher energy consumption. Depending on the applied prediction model the difference adds up to approx. 20% (polynomial equation) or 27% (linear equation) respectively.

0,00 5.000.000,00 10.000.000,00 15.000.000,00 20.000.000,00 25.000.000,00 30.000.000,00 35.000.000,00 40.000.000,00 45.000.000,00 50.000.000,00 December (AUS)  June (GER) January (AUS) July (GER) February (AUS) August (GER) en er gy  c o n sum pt io n  /  VA h Sydney, cumulatitve energy  consumption per month (linear) Sydney, cumulative energy  consumption per month (polynom) Berlin, cumulative energy  consumption per month (linear) Berlin, cumulative energy  consumption per month (polynom) +27,6% (linear) +20,5% (polyn.)

Figure 8: Cumulative estimated energy consumption of AC. Energy supply (sources and prices)

As described environmental impact as well as actual energy costs also strongly depend on the country’s specific characteristics. Against this background the calculated electricity consumption for air conditioning of the chocolate factory was converted into costs in US$ and kg CO2

emissions are exemplarily chosen as a relevant green house gas emission. Australia’s electricity generation is heavily relying on coal as primary energy source which results in very high CO2 emissions per kWh [3]. As a consequence, in the

considered case 20% higher AC electricity demand caused by higher temperature results in drastically more CO2

emissions. Altogether, according to these simplified calculations, running the same chocolate factory in Australia accounts for more than twice the amount of CO2 compared to

Germany. In contrast to that, even though energy consumption is higher, the resulting energy costs are lower due to lower energy prices in Australia.

Table 1: Impact of predicted AC energy consumption. Supply Chain

The third part of the case study examines the impact of distances and the country-specific fuel efficiencies on the energy consumption in supply chains for the example of Germany and Australia. It is based on the assumption that the same chocolate factory is located in the largest metropolitan area, Berlin and Sydney, respectively, and final goods are transported to customers in the four next major metropolitan areas. Transport intensity is weighted by the number of potential customers, i.e. the population. The basic data for the calculation, the metropolitan areas, their population and distances to the production location are listed in Table 2. The distances for road freight transport have been calculated using route planner function of google maps.

City Population Distance to Sydney

Melbourne 3,371,888 881km

Brisbane 1,676,389 960km

Perth 1,256,035 3952km

Adelaide 1,040,719 1375km

City Population Distance to Berlin

Hamburg 1,770,629 288km

Munich 1,311,573 586km

Cologne 995,397 575km

Frankfurt 659,021 545km Table 2: Metropolitan areas in Germany and Australia. The fuel efficiency in road transport in both analyzed countries differs slightly. This is caused by various reasons, such as different prevailing technology in vehicles, road conditions and the general character of road structures, e.g. share of metropolitan areas and rural areas, as well as differences in speed limits and driving behavior. The fuel efficiency for Australia (taken from [20] and weighted according to [21]) is 0.4945 kt km / GJ whereas the value for Germany (calculated from statistical data from [22]) comes up to 0.6005 kt km / GJ. Based on this input data the energy consumption for road freight transport to the major metropolitan areas in Australia and Germany can be calculated in dependence of the mass transported (see Figure 9).

Germany Australia

electricity emission factors (carbon dioxide) based on energy source mix [3]

0.539 kg CO2/kWh

0.924 kg CO2/kWh

avg. local price per kWh

electricity as of 2004 [3] 0.077 US$/kWh

0.061 US$/kWh Berlin summer climate

predicted electricity consumption for air conditioning and connected economic and environmental impact, polyn. prediction model 37.030 kWh 19.959 kg CO2 2.851 US$ 37.030 kWh 34.215 kg CO2 2.259 US$ Sydney summer climate

predicted electricity consumption for air conditioning and connected economic and environmental impact, polyn. prediction model 44.629 kWh 24.055 kg CO2 3.436 US$ 44.629 kWh 41.237 kg CO2 2.722 US$

0,00 2.000,00 4.000,00 6.000,00 8.000,00 10.000,00 12.000,00 14.000,00 16.000,00 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 En er gy  C on su m p ti on  [G J] Freight [kt] Energy consumption AUS [GJ] Energy consumption GER  [GJ] ‐74,6%

Figure 9: energy consumption for road freight transport. The difference in energy consumption for road freight transport can be clearly observed: To complete the same transport task, i.e. to deliver a freight of finished products to the major metropolitan areas, is connected with almost 75% less energy consumption in Germany than in Australia. Although the two countries show a difference in fuel efficiency the major influencing parameter is the distance between the major metropolitan areas in the two countries.

5 CONCLUSION/ OUTLOOK

Based on the definition of a framework of manufacturing systems and the efficiency indicators, this paper presents basic country specific variables with influence on energy consumption behavior: climate, energy source and prices and distances. A case study based on Germany and Australia was used to provide quantitative evidence for the hypotheses. As a future work, more case studies should be conducted in order to gain deeper understanding, and derive generalized conclusions. This could then be used an input in optimization models, which could be used as a decision support tool for both countries as well as companies (e.g. selection of locations for production, e.g. [26]).

ACKNOWLEDGEMENT

This paper was compiled by the Joint German-Australian Research Group “Sustainable Manufacturing and Life Cycle Management” funded by the BMBF under reference AUS 09/AP1 and managed by the International Bureau of the BMBF at DLR.

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