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Combining simulation and optimization for improved decision support on energy efficiency in industry
Linköping University, Department of Management and Engineering, Energy Systems. Linköping University, The Institute of Technology.
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Industrial production systems in general are very complex and there is a need for decision support regarding management of the daily production as well as regarding investments to increase energy efficiency and to decrease environmental effects and overall costs. Simulation of industrial production as well as energy systems optimization may be used in such complex decision-making situations.

The simulation tool is most powerful when used for design and analysis of complex production processes. This tool can give very detailed information about how the system operates, for example, information about the  disturbances that occur in the system, such as lack of raw materials, blockages or stoppages on a production line. Furthermore, it can also be used to identify bottlenecks to indicate where work in process, material, and information are being delayed.

The energy systems optimization tool can provide the company management additional information for the type of investment studied. The tool is able to obtain more basic data for decision-making and thus also additional information for the production-related investment being studied. The use of the energy systems optimization tool as investment decision support when considering strategic investments for an industry with complex interactions between different production units seems greatly needed. If not adopted and used, the industry may face a risk of costly reinvestments.

Although these decision-making tools individually give good results, the possibility to use them in combination increases the reliability of the results, enhances the possibility to find optimal solutions, promises improved analyses, and a better basis for decisions in industry. The energy systems optimization tool can be used to find the optimal result and the simulation tool can be used to find out whether the solution from the optimization tool is possible to run at the site.

In this thesis, the discrete event simulation and energy systems optimization tools have been combined. Three Swedish industrial case studies are included: The new foundry at Volvo Powertrain in Skövde, Arla Foods dairy in Linköping and the SKF foundry in Katrineholm. Results from these cases show possibilities to decrease energy use and idling, to increase production, to combine existing and new production equipment and to decrease loss of  products.

For an existing industrial system, it is always preferable to start with the optimization tool reMIND rather than the simulation tool – since it takes less time to build the optimization model and obtain results than it does to build the corresponding simulation modeling. While, for a non-existent system, it is in general a good idea to use both the simulation and the optimization tool reMIND simultaneously, because there are many uncertain data that are difficult to estimate, by using only one of them. An iterative working process may follow where both tools are used.

There is a need for future work to further develop structured working processes and to improve the model to e.g. take production related support processes into account. To adapt the results in industries, improve the user friendliness of the tool and the understanding of the underlying modeling developments of the optimization tool reMIND will be necessary.

Abstract [sv]

Industriella system i allmänhet är mycket komplexa och det finns ett behov av beslutsstöd vid hantering av den dagliga produktionen, liksom beslut om investeringar för att öka energieffektiviteten och minska miljöpåverkan och kostnader. Simulering av industriell produktion och energisystemoptimering kan användas som beslutsstöd i sådana komplexa beslutssituationer.

Simuleringsverktyg är mest kraftfullt när det används för design och analys av komplexa produktionsprocesser. Verktyget kan ge mycket detaljerad information om hur systemet fungerar, till exempel information om de störningar som inträffar i systemet såsom brist på råvaror, blockeringar eller avbrott på en produktionslinje. Dessutom kan verktyget användas för att identifiera flaskhalsar för att indikera var arbete, material och information är försenade.

Energisystemoptimeringsverktyget kan ge företagsledningen ytterligare information om en eventuell studerad investering. Verktyget kan ge mer underlag för att fatta beslut och därmed ge mer information för den produktionsrelaterade investeringen som studeras. Behovet av användningen av energisystemoptimeringsverktyg som investeringsbeslutsstöd när man överväger strategiska investeringar för en industri med komplexa interaktioner mellan olika produktionsenheter bedöms vara stort. Om inte kan industrin istället möta en risk för kostsamma reinvesteringar.

Även om dessa verktyg kan vara beslutsstöd var för sig och ge bra resultat, så medföljer möjligheten att kombinera dessa verktyg att tillförlitligheten av resultaten ökar, såväl som möjligheten att hitta optimala lösningar, bättre analyser och ett bättre underlag för beslut inom industrin. Optimeringsverktyget kan användas för att hitta det optimala resultatet och simuleringsverktyg kan användas för att ta reda på om lösningen från optimeringsverktyget är möjlig att realisera i verklig drift.

I den här avhandlingen har diskret händelsestyrd simulering och energisystemoptimeringsverktyg kombinerats. Tre svenska industriella fallstudier är inkluderade: Volvo Powertrains nya gjuteri i Skövde, Arla Foods mejeri i Linköping och SKF-gjuteriet i Katrineholm. Resultat från dessa fall visar på möjligheterna att minska energianvändningen och tomgångsförlusterna, att öka produktionen, att kombinera ny och befintlig produktionsutrustning på ett effektivare sätt, och att minska kassation av produkter.

För ett befintligt industriellt system är det alltid mer effektivt att börja med optimeringsverktyget reMIND snarare än simuleringsverktyg - eftersom det tar mindre tid att bygga en optimeringsmodell och få resultat, än det gör för att bygga en motsvarande simuleringsmodell. För ett icke-existerande system är det i allmänhet ett effektivare tillvägagångssätt att använda både simulerings och optimeringsverktyg reMIND samtidigt, eftersom det finns många osäkra data som är svåra att uppskatta, med hjälp av endast ett av verktygen. En iterativ arbetsprocess kan följa där båda verktyg används.

Det finns ett behov av fortsatt arbete bl. a. av att utveckla strukturerade arbetssätt och att kunna integrera produktionsrelaterade stödprocesser i modelleringen. För att anpassa resultaten för industrin, och förbättra användarvänligheten av verktyget, utvecklingen av optimeringsverktyget reMIND kommer att behövas.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. , 69 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1483
Keyword [en]
Energy efficiency, Integration, Optimization, Simulation
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:liu:diva-84643ISBN: 978-91-7519-757-9 (print)OAI: oai:DiVA.org:liu-84643DiVA: diva2:560912
Public defence
2012-10-30, C3, hus C, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2012-10-16Bibliographically approved
List of papers
1. Benefits of integration of energy systems optimization and discrete event simulation
Open this publication in new window or tab >>Benefits of integration of energy systems optimization and discrete event simulation
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Due to increases in energy prices in recent years and the threat of global warming, closely related to energy use, energy issues have been brought to the fore worldwide. Furthermore, due to increased globalisation,  industries are facing greater competition that is pressing companies to reduce their costs. Energy efficiency is therefore an essential task for the future as it has a significant impact on both the environment and business  profits. Different means exist to accomplish a reduction in energy costs, for example, investments in energy efficiency and load shaping. To analyse the results of such changes and provide support when choosing between different measures, different modelling tools can be used. This paper describes Energy Systems Optimisation (ESO) and Discrete Event Simulation (DES) tools and illustrates how an ESO tool and a DES tool can be applied in combination using two simplified case studies. The focus will be on the interactivity analyses between methods and how they provide the user with additional information regarding energy efficiency measures. In the first case, results from the ESO model are simulated to investigate whether the results can be applied in reality. In the second case, the results from the DES model from three different investment alternatives are used as input data to the ESO model to investigate which alternative gives the maximum process utilisation, lowest environmental impact and lowest system costs. Using these tools together improves overall process utilisation and helps provide the analysis with more information than if the tools are used separately.

Keyword
Energy efficiency; Integration; Optimisation; Simulation
National Category
Energy Systems
Identifiers
urn:nbn:se:liu:diva-84642 (URN)
Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2012-10-16Bibliographically approved
2. Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry
Open this publication in new window or tab >>Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry
2012 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 44, no 1, 410-419 p.Article in journal (Refereed) Published
Abstract [en]

To face global competition, and also reduce environmental and climate impact, industry-wide changes are needed, especially regarding energy use, which is closely related to global warming. Energy efficiency is therefore an essential task for the future as it has a significant impact on both business profits and the environment. For the analysis of possible changes in industrial production processes, and to choose what changes should be made, various modelling tools can be used as a decision support. This paper uses two types of energy analysis tool: Discrete Event Simulation (DES) and Energy Systems Optimisation (ESO). The aim of this study is to describe how a DES and an ESO tool can be combined. A comprehensive five-step approach is proposed for reducing system costs and making a more robust production system. A case study representing a new investment in part of a Swedish iron foundry is also included to illustrate the method's use. The method described in this paper is based on the use of the DES program QUEST and the ESO tool reMIND. The method combination itself is generic, i.e. other similar programs can be used as well with some adjustments and adaptations.

The results from the case study show that when different boundary conditions are used the result obtained from the simulation tools is not optimum, in other words, the result shows only a feasible solution and not the best way to run the factory. It is therefore important to use the optimisation tool in such cases in order to obtain the optimum operating strategy. By using the optimisation tool a substantial amount of resources can be saved. The results also show that the combination of optimisation and simulation tools is useful to provide very detailed information about how the system works and to predict system behaviour as well as to minimise the system cost.

Keyword
Energy efficiency; Integration; Optimisation; Simulation
National Category
Energy Systems
Identifiers
urn:nbn:se:liu:diva-84636 (URN)10.1016/j.energy.2012.06.014 (DOI)000308259300040 ()
Note

funding agencies|Swedish Energy Agency (SEA)||

Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2017-12-07Bibliographically approved
3. Industrial decision-making for energy efficiency – combining optimization and simulation
Open this publication in new window or tab >>Industrial decision-making for energy efficiency – combining optimization and simulation
2011 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, there has been a worldwide focus on the issue of energy because of increased energy prices and the threat of increasing global warming. Furthermore, industries are facing greater competition as a result of increasing globalisation, which is forcing companies to reduce their expenses. Reducing the use of energy is therefore an essential task for the future as it has a positive impact on both the environment and the profits of any business. Reductions in energy demand can be accomplished by different means, such as investments in energy-efficient processes or load management. Analytical tools may be used to support the decision-making process, when choosing between a number of measures, and analysing the results can help to choose which changes should be made.

This paper studies two types of energy analysis tool: energy systems optimisation (ESO) and discrete event simulation (DES). The aim of this paper is to describe a method where a DES and an ESO tool are combined in order to study the potential energy and resource reduction in complex industrial energy systems. A case study representing a part of a dairy is also included to illustrate the use of the method. The system modelled includes a process where the durability or longevity of milk increases from a few days to 28 days by using steam injection.

The results from the case study show that the dairy has much higher potential production capacity than realised today. This also means that there is a potential to reduce the operation hours from a three-shift to a two-shift operation to meet the existing weekly demand. The analysis also shows that there are large potential reductions in both energy and other resources. The largest potential reductions are primarily from electricity and water. The combination of tools increases the reliability of the analysis and facilitates decision making in an industrial site.

Keyword
Energy efficiency, Integration, Optimisation, Simulation
National Category
Energy Engineering
Identifiers
urn:nbn:se:liu:diva-71877 (URN)978-86-6055-016-5 (ISBN)
Conference
24rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, Novi Sad, Serbia, 4-7 July 2011
Available from: 2011-11-09 Created: 2011-11-09 Last updated: 2013-02-27
4. Optimization as investment decision supportin a Swedish medium-sized iron foundry: a move beyond traditional energy auditing
Open this publication in new window or tab >>Optimization as investment decision supportin a Swedish medium-sized iron foundry: a move beyond traditional energy auditing
2009 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 86, no 4, 433-440 p.Article in journal (Refereed) Published
Abstract [en]

Due to increased globalisation, industries are facing greater competition that is pressing companies into decreasing their expenses in order to increase their profits. As regards Swedish industry, it has been faced with substantial increases in energy prices in recent years. Barriers to energy efficiency such as imperfect information inhibit investments in energy efficiency measures, energy audits being one means of reducing barriers and overcoming imperfect information. However, an evaluation of such energy audits in Sweden reveals that it is chiefly low-cost measures that are undertaken as a result of an audit. Moreover, these audits often tend to focus on support processes such as ventilation, lighting, air compressors etc., while measures impacting production processes are often not as extensively covered, which underlines the need for further support in addition to energy audits. Decision support is practised in a variety of different disciplines such as optimization and simulation and the aim of this paper is to explore whether investment decision support practices may be used successfully towards small and medium-sized manufacturers in Sweden when complex production-related investment decisions are taken. The optimization results from the different cases, involving a foundry’s investment in a new melting unit, indicate that with no electricity price fluctuations over the day, the investment seems sound as it lowers the overall energy costs. However, with fluctuating electricity prices, there are no large differences in energy costs between the option of retaining the existing five melting furnaces at the foundry and investing in a twin furnace and removing the holding furnaces – which was the initial investment plan for the foundry in the study. It would not have been possible to achieve this outcome without the use of investment decision support such as MIND. One of the main conclusions in this paper is that investment decision support, when strategic investment decisions are to be taken, may be a means of emphasising energy efficiency for energy-intensive SMEs beyond the level of traditional energy auditing.

Place, publisher, year, edition, pages
Elsevier, 2009
Keyword
Energy efficiency, Foundry industry, Investment decision support, Optimization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12514 (URN)10.1016/j.apenergy.2008.08.012 (DOI)000263490400005 ()
Note

Original publication: Patrik Thollander, Nawzad Mardan and Magnus Karlsson, Optimization as investment decision supportin a Swedish medium-sized iron foundry: a move beyond traditional energy auditing, 2009, Applied Energy, (86), 4, 433-440. http://dx.doi.org/10.1016/j.apenergy.2008.08.012. Copyright: Elsevier B.V., http://www.elsevier.com/

Available from: 2008-09-30 Created: 2008-09-10 Last updated: 2017-12-12Bibliographically approved
5. Using simulation for more sustainable production systems: methodologies and case studies
Open this publication in new window or tab >>Using simulation for more sustainable production systems: methodologies and case studies
2009 (English)In: International Journal of Sustainable Engineering, ISSN 1939-7038, E-ISSN 1939-7046, Vol. 2, no 2, 111-122 p.Article in journal (Refereed) Published
Abstract [en]

The increased competition in the global market-place is forcing industrial manufacturers to develop their production systems by increasing flexibility, improving quality and lowering production costs. With the help of simulation techniques, the understanding of manufacturing systems can be enhanced and alternative solutions can be tested. Simulation has, therefore, played an important role in industrial development in recent years. At the same time, energy-related costs have been neglected by Swedish industry due to historically low energy costs in Sweden, in comparison with such costs in other European countries. The developments in the energy market, with uncertainty concerning future prices, have increased the need for energy efficiency. The research described in this paper focuses on methodologies developed to enhance the efficient analyses of energy systems in manufacturing plants by using discrete event simulation. The focus is on electricity use. The paper briefly presents the main features of the methodologies and describes the results from four case studies carried out in the Swedish foundry industry. The methodology improves efficiency by identifying those processes that are important, the activities that must be undertaken and the types of analyses that can be undertaken.

Place, publisher, year, edition, pages
Taylor & Francis, 2009
National Category
Energy Systems
Identifiers
urn:nbn:se:liu:diva-84638 (URN)10.1080/19397030902960994 (DOI)
Note

Special Issue: Selected Papers from FAIM 2008, the 18th International Conference on Flexible Automation and Intelligent Manufacturing.

Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2017-12-07Bibliographically approved
6. Timing and sizing of investments in industrial processes– the use of an optimization tool
Open this publication in new window or tab >>Timing and sizing of investments in industrial processes– the use of an optimization tool
2011 (English)In: ECOS 2010 Volume IV (Power plants and Industrial processes): Proceedings of ECOS 2010 Conference in Lausanne / [ed] Daniel Favrat, MER Francois Maréchal, 2011Conference paper, Published paper (Refereed)
Abstract [en]

Investments of different kinds are vital for industries to stay competitive. However, there are several issues that need to be considered before investing, e.g. the timing and size of the investment. In this paper a methodology is presented for analysing investments form the point of view of optimal size and timing. The energy systems optimization tool reMIND is used as the basis of the modelling, and has been used in several industrial energy systems studies for various purposes. reMIND is based on Mixed Integer Linear Programming (MILP) and has been further developed to consider investments of different kinds. The different constraints needed to model the investment properly are presented together with the variables included in the objective function. A simple case study is also included to illustrate how the method is used. The results from the case study show that the timing and size of the different investments change, depending on the size of the proposed increase in production rate.

Keyword
Energy efficiency, Investments, MILP, Optimization
National Category
Engineering and Technology Energy Engineering
Identifiers
urn:nbn:se:liu:diva-71876 (URN)145630318X (ISBN)9781456303181 (ISBN)
Conference
23rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, 14-17 June, in Lausanne, Switzerland
Available from: 2011-11-09 Created: 2011-11-09 Last updated: 2017-10-16
7. Considering start-ups and shutdowns using an optimization tool: including a dairy production planning case study
Open this publication in new window or tab >>Considering start-ups and shutdowns using an optimization tool: including a dairy production planning case study
(English)Manuscript (preprint) (Other academic)
Abstract [en]

There are many different aspects a production-planning model has to be able to handle to make a model adequate for the purpose. One aspect is the handling of start-ups and shutdowns for different processes. The production plan is likely to be changed when considering, for example, a cost connected to the start-up and/or shutdown of processes. Besides costs associated with start-ups and shutdowns, waste may be produced during the start-up and shutdown. However, there is also the possibility of carrying out soft start-ups and shutdowns or limiting the number of start-ups and shutdowns. Thus, start-ups and shutdowns have to be handled in an adequate way in models to produce reliable and accurate results. In optimisation tools, this may be dealt with by introducing certain constraints, including integers. In this paper, the implementation of alternative ways to consider start-ups and shutdowns are presented. This is done in the energy system optimisation tool reMIND, which deals with Mixed Integer Linear Programming (MILP) problems. The purpose of this paper is to show four alternatives to consider start-ups and shutdowns in optimisation models. This involves, in total, almost 50 constraints. Also, a simple dairy case study is included in the paper to visualise the effect of implementing the different alternatives to shutdowns.

Keyword
MILP, optimisation, production planning, start-up, shutdown
National Category
Energy Engineering
Identifiers
urn:nbn:se:liu:diva-84639 (URN)
Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2012-10-16Bibliographically approved

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