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Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry
Linköping University, Department of Management and Engineering, Energy Systems. Linköping University, The Institute of Technology.
Swerea SWECAST AB, Jönköping, Sweden.
2012 (English)In: Energy, ISSN 0360-5442, 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.

Place, publisher, year, edition, pages
2012. Vol. 44, no 1, 410-419 p.
Keyword [en]
Energy efficiency; Integration; Optimisation; Simulation
National Category
Energy Systems
URN: urn:nbn:se:liu:diva-84636DOI: 10.1016/ 000308259300040OAI: diva2:560890

funding agencies|Swedish Energy Agency (SEA)||

Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2012-11-05Bibliographically approved
In thesis
1. Combining simulation and optimization for improved decision support on energy efficiency in industry
Open this publication in new window or tab >>Combining simulation and optimization for improved decision support on energy efficiency in industry
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.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1483
Energy efficiency, Integration, Optimization, Simulation
National Category
Energy Systems
urn:nbn:se:liu:diva-84643 (URN)978-91-7519-757-9 (ISBN)
Public defence
2012-10-30, C3, hus C, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Available from: 2012-10-16 Created: 2012-10-16 Last updated: 2012-10-16Bibliographically approved

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