- Email: [email protected]
Planning of Flow of Material and Energy for Photovoltaics Industry
7th IFAC Conference on Manufacturing Modelling, Management, and Control International Federation of Automatic Control June 19-21, 2013. Saint Petersburg, Russia
Planning of Flow of Material and Energy for Photovoltaics Industry Sebastian Horbach*. Frank Schaarschmidt*. Robin Schulze* Jörg Ackermann*. Egon Müller* *Chemnitz University of Technology, Department of Factory Planning and Factory Management, Chemnitz, 09107 Germany (Tel: 49-371-531 35184; e-mail: [email protected]) Abstract: Due to the continuously increasing need for renewable energy, the demand for photovoltaic components is significantly growing. Therefore, many highly productive factories for solar cells will be built in the coming years. The development of tools and methods for rapid planning of state of the art and highly automated production facilities for photovoltaic equipment is the objective of the Saxon PV Automation Cluster (S-PAC). So far the focus of factory planning was strongly on discrete part manufacturing while in contrast the production of solar panels involves a lot of chemical processes with different by-products, even though the final output is discrete parts. Hence, it is investigated how methods and tools of discrete manufacturing still can be applied to photovoltaic industry or where adaptations are necessary. From a methodical point of view the Flow System Theory, comprising material, energy, information, value and personnel flow, as well as Component-based Planning, considering planning process and object components, will be in the focus. While in the past the emphasis was on the optimisation of the material flow, the significance of the energy flow is increasing. The realisation of the information flow requires appropriate tool support. The base of the tool support is provided by the concept of the Net Planning Assistant with the Production Database as central storage component. The Production Data Model as foundation for the Production Database has to be adapted to the differing object domain. A reference database of typical objects of photovoltaic cell, wafer and module production is developed as a basis for datasets of particular projects. Models for visualisation and simulation of the photovoltaic objects are connected to the data model. Interfaces to the Manufacturing Execution System (MES) and the quality management system need to be defined. Keywords: Facility Planning, Modeling, Simulation, Photovoltaics. easy access to electricity. A number of highly productive factories for solar cells will need to be built to meet the demand.
1. INTRODUCTION With the Renewable Energy Directive the European Union has set the goal of at least 20% share of renewable energy of EU’s energy consumption by 2020 (Pascal and Carolle 2011). Renewable energy is produced from solar radiation, wind, biomass, or geothermic. Solar energy has already reached grid parity in specific regions. The costs of installing solar equipment are generally declining (Branker et al. 2011, Breyer et al. 2011, European Photovoltaic Industry Association and Greenpeace 2011), which is expected to lead to a growing photovoltaic market (European Photovoltaic Industry Association 2011).
The production of photovoltaic modules proceeds in several stages (Glunz et al. 2012). There are different methods for the various stages but the general procedure is similar for different concepts of solar cells. Basic material is a block or a bar of silicon, like those used for integrated circuits. In the wafer production, the silicon block is sawed to slices, which undergo further chemical processing. Contacts for the diversion of the electrical energy are printed on the wafer, resulting in solar cells. Several cells are combined to solar modules. For that, they are laid on a layer of cleaned class and a special film and connected to each other. Hereafter, the modules are covered with several layers of foil and are laminated. Connections and frame are attached to the modules. After measuring, they are finally packed. Thus, the modules are ready for installation.
At the moment news from photovoltaic industry are rather negative. In countries, which are leading in installing photovoltaic equipment, the number of installations is stagnating due to cuts in subsidies. The market is saturated, so that production needs to get more efficient in order to stay competitive. The industry faces a phase of consolidation. There are hopes that the situation will improve in 2013. (Verlinden 2012, Hook 2012, greentechmedia 2012, Mehta 2012)
Under the slogan “We automate the PV world” six companies and four research institutions in the Central German region of Dresden - Chemnitz form the Saxon Photovoltaic Automation Cluster (S-PAC) (S-PAC Saxon Photovoltaic Automation Cluster). The goal of the project is the development of a holistic solution for the automation of the production of Photovoltaic (PV) components. It is aimed to
On the long run, the demand for photovoltaic equipment will grow due to a shortage of other energy sources and growing interest in underdeveloped countries, where sun provides 978-3-902823-35-9/2013 © IFAC
477
10.3182/20130619-3-RU-3018.00465
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
cover the whole value chain from the planning of the facility, through the construction and installation of the equipment, the automation and production control up to service and maintenance. One of the research partners is the department of Factory Planning and Factory Management of Chemnitz University of Technology. Being responsible for the sub-project “Modelling and Simulation”, the department aims to lay the production scientific foundations for the emerging PV industry. This includes the development of virtual and simulation models of the production sites as well as of reference processes for the collaborative planning of PV factories in networks.
Fig. 1. Flow Systems Theory (following Wirth [Schenk et al. 2009] )
So far factory planning has been strongly focussing on discrete part manufacturing. In contrast the production of solar panels involves a lot of chemical processes with different by-products, even though the final output is discrete. Hence, it is investigated how methods and tools of discrete manufacturing still can be applied to photovoltaic industry. Where conventional concepts are not suitable, adaptations will need to be made. There is also the possibility that a need for new methods for the planning of PV production systems will exist.
2.2 Component-based Planning The approach of using elaborated components for the faster building of systems has proven effective in different fields, such as design and software engineering (where they are also called modules). Advantages of using components are the shortening of the design cycle, the encapsulation of subsystems and the easier distribution of the workload among the designers. The shortening of the project duration is due to the fact, that elaborated modules, which were used before and therefore are tested, can be used again. Encapsulation means that not every planner needs to know the details of the different components. Having defined interfaces, the substitution of a component is significantly easier. The sharing of workload is easier in the sense that members of the team concentrate on particular components while a few architects take care of the overall system. The approach can be applied to different levels of the system. Since the approach is beneficial for products or software systems it is likely that the discussed benefits are also occuring in the case of production systems as a similar but more complex system. The deployment of optimised components is leading to competitive and sustainable manufacturing systems.
The paper starts with the presentation of the theoretical background on the factory planning models and methods used. Then particular aspects of the general data model of production systems for photovoltaic components as well as models for simulation and visualisation of such systems are discussed. Finally issues of the development of interfaces to software tools of other project partners are reviewed. 2. THEORETICAL BACKGROUND 2.1 Flow System Theory The Flow System Theory (Schenk et al. 2009) assumes that all processes of a production system can be modelled and designed as flows. The flow types are divided by the object type of the flow. Mainly material, energy, information and value flow are distinguished. Occasionally also the flow of personnel is incorporated into the model as well as the equipment flow in adaptable production networks, which is included in the extended Flow System Theory.
The concept of Component-based Planning (Näser 2005), (Horbach et al. 2010) uses optimised components – also called building blocks – for making the planning process more efficient in shortening the duration and increasing the quality. Two types of components are considered. Object components on the one hand describe physical objects as structural units of the factory while on the other hand planning components describe sequences of the factory planning process, which can be reused. Planning components are not in the scope of this paper.
Three basic functions are executed on the different flows, i.e. transformation, storage and transportation. A combination of those functions is feasible e.g. having a transformation on transported or stored goods.
When an object or a process component is chosen, it has to be parameterised first. Components can be combined to other components. They should be further optimised after gaining experiences from their deployment. Standard processes for the handling of building blocks were developed (Müller et al. 2008).
Flow system theory can be applied to all levels of a production system. An overview of the Flow System Theory is given in fig. 1. Up to now the focus has been on the optimisation of the material flow. Attention is also paid to the information flow due to its high importance for the control of the production system. In line with increasing costs of energy and growing scarcity of natural resources, the significance of the energy flow is increasing (Müller and Löffler 2010).
Despite the approach of Component-based Planning was mainly developed for discrete part manufacturing its applicability for process industry has been already shown. King-Kordi (King-Kordi 2010) evaluated the approach on a factory for the combined production of sugar and ethanol fuel. 478
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
mapping of the objects and properties which are necessary for the planning and the start of the operation of the production plant. The same principle has to be applied to simulation and visualisation models. The data model is divided into certain views in order to handle the complexity of production systems. Hereby the Production Data Model is based on the view concept of socio-technical systems (Müller and Ackermann 2005) which distinguishes structural units (e.g. factory, production line, cost centre, component), targets, yields, functions as well as resources and competences as top-level classes.
Fig. 2. Component-based Planning Approach (Näser 2005) 2.3 Net Planning Assistant
First of all the data model contains the conventional properties of production objects like ID, name, measures or prices which can be defined by simple data types. For the PV industry the use of media becomes important in the mapping of resources. This includes not only electrical power, but also different types of technical gases and acids. The Facility Utility Matrix (FUM) (also called Tool Utility Matrix) contains the average and maximum consumptions for utilities like electrical power, water, compressed air, gases and chemicals as well as the requirements for cooling water and the specification for the exhaust streams and waste water (Eberhardt 2011). This implies also, that the management of the data of the building obtains growing importance. In the product view the modelling of waste or by-products needs to be taken into consideration.
The realisation of the information flow, both of the planning process as well as the eventual factory, requires appropriate tool support. The base of the tool support is provided by the concept of the Net Planning Assistant (NPA) (Horbach and Müller 2006), (Müller et al. 2009), which was originally developed for the planning of logistics structures and production plants in networks of micro-enterprises. The Net Planning Assistant (figure 2) is a modular concept with the three main components Production Database (PDB), uniform interface concept and connected planning tools. In the centre of the Net Planning Assistant is the Production Database. The PDB is the implementation of the production data model, which comprises the information necessary for the different stages of the planning of production systems. Commercial as well as proprietary software tools are connected by a uniform interface concept through the PDB. According to the uniform interface concept, data exchange can be realised by direct access to the PDB, the transformation of data to files (XML, CSV, ...) or transformation between PDB and the database used by the application.
The data model is used for both, the abstract, generic description of components as well as the description of the instances of the components as they can be found in the real factory, which will be the product of the planning process. The components can refer to different levels of the production system; there can be work stations as well as production lines or whole production sites.
In S-PAC the Net Planning Assistant will connect the planning software, especially the tools for simulation and visualisation (as emphasised in figure 2) to the software tools used by other projects, such as the Manufacturing Execution System (MES).
Other types of data such as the virtual and simulation representations of objects are not directly stored with the general data. Instead references to the respective models are kept. The Graphical User Interface (GUI) for the management of the data provides at the same time functions for the administration of the virtual and simulation models.
3. MODELLING In this research project three types of models are relevant, •
Data models of the objects of PV production systems,
•
Virtual models (2D, 3D, Virtual Reality) of the resources of PV production systems, and
•
Simulation models.
The project focusses on the stages of wafer, cell and module production (see chapter 1 for the production process). A reference database of typical objects of the different stages of production is developed as a basis for datasets of particular projects. Models for visualisation and simulation of the photovoltaic objects are connected to the data model. 3.1 Data Model
Fig. 3. Net Planning Assistant.
The purpose of the factory planning data model is not to represent all possible data of the production system but the 479
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
The Production Data model is implemented with the Production Database. Thereby, databases for different database management systems such as MS SQL-Server, Oracle or MySQL can be generated from an abstract conceptual data model. Apart from the databases for current planning projects, a database containing the generic components should be installed, e.g. as a repository of resources. 3.2 Virtual Model Virtual models (Fig. 4) are intended to give the investors and operators of the future PV factories a realistic impression of how the factory will look like. This way the acceptance of the layout by the stakeholders is increased, especially since they can easily participate interactively in the planning process. Fig. 4. VR building blocks. • Planning of the facilities, (optimisation of supply and disposal pipe systems),
Virtual models are managed with the tool visTABLE (Horbach and Müller 2006). In visTABLE the layout is provided in two-dimensional and three-dimensional representation. The three dimensional view can be extended to a representation in Virtual Reality (VR), so that the user can virtually move through the production line. Apart from the visualisation feature, visTABLE provides functionality for the planning of production facilities; particularly the optimisation of rough structure, the verification of minimum distances between objects, as well as the calculation and visualisation of the material flow. Thus, visTABLE supports the optimisation of the layout as well as material and energy flow, including the supply of media such as gases or chemicals. Different hardware can be used for interaction with visTABLE (Horbach et al. 2010), among them such devices which have become popular in consumer electronics (Wii controllers, MS Kinect). A collaborative planning through the internet is enabled by visTABLE.
•
Determination of the optimal structure (inline or cluster arrangement, depending on the optimal material flow and minimum cost facility area),
•
Support of current and future layout planning by the use, development and improvement of a PV object library containing typical machines and equipment for the production of wafers, cells and modules,
•
Presentation of the future factory to potential investors in the tendering stage,
•
Communication base for the participation of operators already in the planning stage both locally and through the internet.
First the typical equipment for the module production was modelled. Later also models of wafer and cell production equipment were elaborated, so that the whole production process is covered by the VR building block library. The library will be enhanced by models of equipment, which is currently developed by other partners. With the equipment models, models for production sites are now assembled. A first model for a module production line is completed. 3.3 Simulation Models The simulation of the material flow provides an evaluation of the dynamical aspects of the layout of the production system and the related manufacturing processes. Key performance indicators like throughput, availability of the equipment or logistical parameters like buffer size and storage durations are investigated and compared.
The planning of PV production system is supported by visTABLE in the following fields; Evaluation and optimisation of the material flow of both, products and media,
Derivation of criteria for the precise dimension and structure of transfer systems,
The elicitation of geometrical information about the equipment and the provision of their 3D-models are important prerequisites for the deployment of visTABLE.
A certain effort is necessary to generate the 3Drepresentations of objects for the use in visTABLE, e.g. with 3D Studio Max or Trimble SketchUp (bought from Google). Ideally these models are provided by the construction department and just need to be rid of unnecessary details. However, once the objects are modelled they are integrated in the extendable model library of visTABLE and can be used for all other projects. With this catalogue, a layout for a production site under construction can be quickly generated by dragging and dropping the relevant components to the layout of the planned facility (see fig. 4). The basic VR models for the components of module and wafer production were designed. For cell production the basic VR-models are still elaborated. The catalogues will need continuous updating as new technologies are developed.
•
•
The goal of simulation is the tuning of processes and capacities, which results in a better overall performance of the production system. At a later stage, bottlenecks need to be identified and eliminated. However, in addition to the traditional subject of material flow also the energy flow will be subject of simulation experiments. It will be investigated, 480
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
how by applying different operation strategies and changed start up strategies the peak capacities of the facilities can be minimised.
Simulation equipment models for module production were made available on the basis of the SimPlan library, which is further developed. In addition, models for wafer production were elaborated. For the completion of the cell production, first a decision is necessary, on which technology will be concentrated. For wafer and module production, production lines are now modelled. At the same time simulation experiments are planned.
Therefore, the following indicators are needed from the planning data of the production system; •
Electrical specifications like power, standby power, start up power as well as type, quantity and quality of media (gases, chemical etc.),
•
Production figures like availability of the equipment, statistical failure rates and durations as well as the expected output,
•
Information about the behaviour of the plant (process and waiting times, buffer sizes).
4. INTERFACES In the construction and operation of a PV production line, facility planners, simulation experts, production managers and quality managers work together. For the communication of the software systems, which are used by the different partners of the project, a central database is under development. It stores the equipment library, data about former projects and the different versions of current projects as well as performance data of running systems. The latter can be replaced by simulation data if the ramp-up has not been completed. It has been concluded that the use of XMLfiles should be preferred to the use of a relational database since the administration of different configuration scenarios can be handled easier with XML. The structure of the files is regulated by XML-Schema definitions.
For the improvement of the planning solution, simulation is expected to contribute with the following results; •
Verification of planning results comparison with target indicators,
through
•
Identification of critical bottlenecks, to which special attention needs to be paid in the further planning process,
•
Derivation of general control strategies,
•
Optimisation of the dimensioning of the facilities through reduction of the theoretical peak load,
•
Deployment of the visualisation functions of the simulation system to support equipment suppliers (transfer system) and to increase acceptance of the solution.
The general use case of communication is the exchange of data between the different sub-projects during the construction of the production system. Following the Component-based Planning approach, for the planning of the PV production system, which was specified by the investor, possible configurations can be generated from the equipment library. This draft is stored as project master data. The data is transferred to the simulation and visualisation tools. The results of simulation experiments and model optimisations are transferred back to the central database, especially as performance data. Thus, the data can be compared to the requirements of the client. It is the basis for new configuration scenarios which are stored in the configuration archive. Finally the preferred configuration is available as active project in the project master data and can be accessed by all partners when the requirements were modified by the client.
The approach of Component-based Planning will be also applied to simulation (Fig. 5). A component library with simulation representations of typical objects of PV production systems is developed. As a foundation the photovoltaic component library of SimPlan is used (SimPlan 2010), which is further developed in close cooperation with this company. The description of the objects comprises the properties of the objects (capacity, rates of failure) as well as methods which imply the behaviour of the objects. In result, the building blocks can be parameterised and combined to complex simulation models. The component library has a hierarchical and modular structure. Main types of components are general, technical, administrative, statistical and interface components.
A special use case is the simulation of the operation of the planned production system in dialogue between simulation system and the MES. That way it becomes possible to draw first conclusions about the performance of the production system and the MES. Different control strategies can be evaluated. 5. CONCLUSIONS Methods and tools from factory planning which have been used for discrete part production can also be used to improve the quality of planning processes and planning solutions for the photovoltaic industry. This is shown for the Flow System Theory and the approach of Component-based Planning. The Net Planning Assistant is a suitable concept for the tool support of the planning activities. The underlying data needs to be extended. Especially visualisation and simulation can be used to verify and optimise results from early stages of production. Adaptations of currently common procedures
Fig. 5. Simulation building blocks. 481
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
based Networks. In: H. Lewis, B. Gaughran, and S. Burke, eds. Proceedings of the 16th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2006, June 26-28th 2006, University of Limerick, Limerick, Ireland. Limerick: University of Limerick, Dept. of Manufacturing and Operations Engineering, 949–956. King-Kordi, A., 2010. Methodik zur bausteinbasierten Planung und Organisation von verfahrenstechnischen Produktionssystemen. Dissertation: Technische Universität Chemnitz. Mehta, S., 2012. PV Module Consolidation in 2013-2014: What to Expect. Müller, E. and Ackermann, J., 2005. Planning and Design of Logistics Structures of competence-cell-based Networks. In: E. Alvarez, et al., eds. FAIM 2005: Proceedings of the 15th International Conference on Flexible Automation and Intelligent Manufacturing : July 18th20th, 2005. Bilbao: University of Deusto Press, 794–801. Müller, E., Horbach, S., and Ackermann, J., 2009. Tool support for industrial engineering in small enterprises. In: F. Nabhani, ed. Proceedings of the 19th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2009, July 6th - July 8th, 2009, Teesside University, Middlesbrough, UK. Middlesbrough: Teesside University, 195. Müller, E. and Löffler, T., 2010. Energy Efficiency at Manufacturing Plants – A Planning Approach. In: W. Sihn and P. Kuhlang, eds. Sustainable production and logistics in global networks: 43rd CIRP international conference on manufacturing systems, 26-28 May 2010, Vienna : proceedings. Vienna: NWV Neuer Wissenschaftlicher Verlag, 787–794. Müller, E., Rösch, N., and Ackermann, J., 2008. Componentbased Planning of Flexible Assembly Systems: a Methodical Approach and its Implementation. In: Proceeding of the 2nd CIRP Conference on Assembly Technologies and Systems (CATS 2008), 41–49. Näser, P., 2005. Component based planning of manufacturing plants. In: Proceedings (CD) of the 3rd Annual Conference on Systems Engineering Research – CSER, 393–402. Pascal, A. and Carolle, C., 2011. A new era: Renewable energy. The Intelligent Energy - Europe Magazine 3: Intelligent Energy Europe. Schenk, M., Wirth, S., and Müller, E., 2009. Factory planning manual. Berlin ;, London: Springer. SimPlan, 2010. Bausteinkasten für die Solarindustrie. S-PAC Saxon Photovoltaic Automation Cluster. The Alliance - S-PAC Saxon Photovoltaic Automation Cluster [online]. Available from: http://www.s-pac.de/indexen.html [Accessed 14 Dec 2011]. Verlinden, P., 2012. The Surviving PV Companies. Future Photovoltaics [online] (July). Available from: http://futurepv.com/node/399.
need to be made to meet the growing demand for incorporation of the energy flow; however the existing tools have the potential to provide the necessary functionality. Simulation and visualisation are suitable for helping to meet the increasing complexity and growing challenges of PV production. Interfaces to software systems used by other actors are developed to achieve competitive, sustainable and globally sufficient planning solutions. In brief, existing approaches of factory planning are suitable for the planning of photovoltaic production systems. Necessary adaptations are the extension of the data and of the functionality for optimising the energy flow. Virtual and simulation building blocks for solar production equipment are available now. The building blocks will undergo further improvement and extension. They are now combined to production lines. Hence, flow investigations and simulation experiments can be started. ACKNOWLEDGEMENTS The work which is presented in this paper, as a part of the project S-PAC, is funded by the German Federal Ministry of Education and Research. REFERENCES Branker, K., Pathak, M.J., and Pearce, J.M., 2011. A review of solar photovoltaic levelized cost of electricity. Renewable and Sustainable Energy Reviews, 15 (9), 4470–4482. Breyer, C., Gerlach, A., and Werner, C., 2011. Grid Parity: Coming Sooner Than You Think. Future Photovoltaics (6), 26–31. Eberhardt, K., 2011. Large-Scale PV Manufacturing: Cost Reduction Potentials beyond Scaling. Inter.PV Global Photovoltaic Business Magazine [online] (February). Available from: http://www.interpv.net/market/market_v iew.asp?idx=355&part_code=02&page=6# [Accessed 16 Dec 2011]. European Photovoltaic Industry Association, 2011. Global Market Outlook for Photovoltaics until 2015. European Photovoltaic Industry Association and Greenpeace, 2011. Solar Generation 6: Solar photovoltaic electricity empowering the world. Glunz, S., Preu, R., and Biro, D., 2012. Crystalline Silicon Solar Cells. In: A. Sayigh, ed. Comprehensive renewable energy. Amsterdam, Boston, Mass: Elsevier, 353–387. greentechmedia, 2012. The Solar Industry’s Living Dead: 180 Module Manufacturers to Succumb to Consolidation by 2015. Financial Times, 2012. Cloud hovers over China’s solar industry. Financial Times [online], 22 Oct. Available from: http://www.ft.com/intl/cms/s/0/bef02db6 -1c26-11e2-a63b-00144feabdc0.html [Accessed 23 Oct 2012]. Horbach, S., et al., 2010. Building Blocks for Adaptable Factory Systems. In: Proceedings of the 20th International Conference on Flexible Automation and Intelligent Manufacturing – FAIM 2010, 568–575. Horbach, S. and Müller, E., 2006. The Net Planning Assistant – A Toolset to Support Planning in Competence-cell482
Planning of Flow of Material and Energy for Photovoltaics Industry Sebastian Horbach*. Frank Schaarschmidt*. Robin Schulze* Jörg Ackermann*. Egon Müller* *Chemnitz University of Technology, Department of Factory Planning and Factory Management, Chemnitz, 09107 Germany (Tel: 49-371-531 35184; e-mail: [email protected]) Abstract: Due to the continuously increasing need for renewable energy, the demand for photovoltaic components is significantly growing. Therefore, many highly productive factories for solar cells will be built in the coming years. The development of tools and methods for rapid planning of state of the art and highly automated production facilities for photovoltaic equipment is the objective of the Saxon PV Automation Cluster (S-PAC). So far the focus of factory planning was strongly on discrete part manufacturing while in contrast the production of solar panels involves a lot of chemical processes with different by-products, even though the final output is discrete parts. Hence, it is investigated how methods and tools of discrete manufacturing still can be applied to photovoltaic industry or where adaptations are necessary. From a methodical point of view the Flow System Theory, comprising material, energy, information, value and personnel flow, as well as Component-based Planning, considering planning process and object components, will be in the focus. While in the past the emphasis was on the optimisation of the material flow, the significance of the energy flow is increasing. The realisation of the information flow requires appropriate tool support. The base of the tool support is provided by the concept of the Net Planning Assistant with the Production Database as central storage component. The Production Data Model as foundation for the Production Database has to be adapted to the differing object domain. A reference database of typical objects of photovoltaic cell, wafer and module production is developed as a basis for datasets of particular projects. Models for visualisation and simulation of the photovoltaic objects are connected to the data model. Interfaces to the Manufacturing Execution System (MES) and the quality management system need to be defined. Keywords: Facility Planning, Modeling, Simulation, Photovoltaics. easy access to electricity. A number of highly productive factories for solar cells will need to be built to meet the demand.
1. INTRODUCTION With the Renewable Energy Directive the European Union has set the goal of at least 20% share of renewable energy of EU’s energy consumption by 2020 (Pascal and Carolle 2011). Renewable energy is produced from solar radiation, wind, biomass, or geothermic. Solar energy has already reached grid parity in specific regions. The costs of installing solar equipment are generally declining (Branker et al. 2011, Breyer et al. 2011, European Photovoltaic Industry Association and Greenpeace 2011), which is expected to lead to a growing photovoltaic market (European Photovoltaic Industry Association 2011).
The production of photovoltaic modules proceeds in several stages (Glunz et al. 2012). There are different methods for the various stages but the general procedure is similar for different concepts of solar cells. Basic material is a block or a bar of silicon, like those used for integrated circuits. In the wafer production, the silicon block is sawed to slices, which undergo further chemical processing. Contacts for the diversion of the electrical energy are printed on the wafer, resulting in solar cells. Several cells are combined to solar modules. For that, they are laid on a layer of cleaned class and a special film and connected to each other. Hereafter, the modules are covered with several layers of foil and are laminated. Connections and frame are attached to the modules. After measuring, they are finally packed. Thus, the modules are ready for installation.
At the moment news from photovoltaic industry are rather negative. In countries, which are leading in installing photovoltaic equipment, the number of installations is stagnating due to cuts in subsidies. The market is saturated, so that production needs to get more efficient in order to stay competitive. The industry faces a phase of consolidation. There are hopes that the situation will improve in 2013. (Verlinden 2012, Hook 2012, greentechmedia 2012, Mehta 2012)
Under the slogan “We automate the PV world” six companies and four research institutions in the Central German region of Dresden - Chemnitz form the Saxon Photovoltaic Automation Cluster (S-PAC) (S-PAC Saxon Photovoltaic Automation Cluster). The goal of the project is the development of a holistic solution for the automation of the production of Photovoltaic (PV) components. It is aimed to
On the long run, the demand for photovoltaic equipment will grow due to a shortage of other energy sources and growing interest in underdeveloped countries, where sun provides 978-3-902823-35-9/2013 © IFAC
477
10.3182/20130619-3-RU-3018.00465
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
cover the whole value chain from the planning of the facility, through the construction and installation of the equipment, the automation and production control up to service and maintenance. One of the research partners is the department of Factory Planning and Factory Management of Chemnitz University of Technology. Being responsible for the sub-project “Modelling and Simulation”, the department aims to lay the production scientific foundations for the emerging PV industry. This includes the development of virtual and simulation models of the production sites as well as of reference processes for the collaborative planning of PV factories in networks.
Fig. 1. Flow Systems Theory (following Wirth [Schenk et al. 2009] )
So far factory planning has been strongly focussing on discrete part manufacturing. In contrast the production of solar panels involves a lot of chemical processes with different by-products, even though the final output is discrete. Hence, it is investigated how methods and tools of discrete manufacturing still can be applied to photovoltaic industry. Where conventional concepts are not suitable, adaptations will need to be made. There is also the possibility that a need for new methods for the planning of PV production systems will exist.
2.2 Component-based Planning The approach of using elaborated components for the faster building of systems has proven effective in different fields, such as design and software engineering (where they are also called modules). Advantages of using components are the shortening of the design cycle, the encapsulation of subsystems and the easier distribution of the workload among the designers. The shortening of the project duration is due to the fact, that elaborated modules, which were used before and therefore are tested, can be used again. Encapsulation means that not every planner needs to know the details of the different components. Having defined interfaces, the substitution of a component is significantly easier. The sharing of workload is easier in the sense that members of the team concentrate on particular components while a few architects take care of the overall system. The approach can be applied to different levels of the system. Since the approach is beneficial for products or software systems it is likely that the discussed benefits are also occuring in the case of production systems as a similar but more complex system. The deployment of optimised components is leading to competitive and sustainable manufacturing systems.
The paper starts with the presentation of the theoretical background on the factory planning models and methods used. Then particular aspects of the general data model of production systems for photovoltaic components as well as models for simulation and visualisation of such systems are discussed. Finally issues of the development of interfaces to software tools of other project partners are reviewed. 2. THEORETICAL BACKGROUND 2.1 Flow System Theory The Flow System Theory (Schenk et al. 2009) assumes that all processes of a production system can be modelled and designed as flows. The flow types are divided by the object type of the flow. Mainly material, energy, information and value flow are distinguished. Occasionally also the flow of personnel is incorporated into the model as well as the equipment flow in adaptable production networks, which is included in the extended Flow System Theory.
The concept of Component-based Planning (Näser 2005), (Horbach et al. 2010) uses optimised components – also called building blocks – for making the planning process more efficient in shortening the duration and increasing the quality. Two types of components are considered. Object components on the one hand describe physical objects as structural units of the factory while on the other hand planning components describe sequences of the factory planning process, which can be reused. Planning components are not in the scope of this paper.
Three basic functions are executed on the different flows, i.e. transformation, storage and transportation. A combination of those functions is feasible e.g. having a transformation on transported or stored goods.
When an object or a process component is chosen, it has to be parameterised first. Components can be combined to other components. They should be further optimised after gaining experiences from their deployment. Standard processes for the handling of building blocks were developed (Müller et al. 2008).
Flow system theory can be applied to all levels of a production system. An overview of the Flow System Theory is given in fig. 1. Up to now the focus has been on the optimisation of the material flow. Attention is also paid to the information flow due to its high importance for the control of the production system. In line with increasing costs of energy and growing scarcity of natural resources, the significance of the energy flow is increasing (Müller and Löffler 2010).
Despite the approach of Component-based Planning was mainly developed for discrete part manufacturing its applicability for process industry has been already shown. King-Kordi (King-Kordi 2010) evaluated the approach on a factory for the combined production of sugar and ethanol fuel. 478
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
mapping of the objects and properties which are necessary for the planning and the start of the operation of the production plant. The same principle has to be applied to simulation and visualisation models. The data model is divided into certain views in order to handle the complexity of production systems. Hereby the Production Data Model is based on the view concept of socio-technical systems (Müller and Ackermann 2005) which distinguishes structural units (e.g. factory, production line, cost centre, component), targets, yields, functions as well as resources and competences as top-level classes.
Fig. 2. Component-based Planning Approach (Näser 2005) 2.3 Net Planning Assistant
First of all the data model contains the conventional properties of production objects like ID, name, measures or prices which can be defined by simple data types. For the PV industry the use of media becomes important in the mapping of resources. This includes not only electrical power, but also different types of technical gases and acids. The Facility Utility Matrix (FUM) (also called Tool Utility Matrix) contains the average and maximum consumptions for utilities like electrical power, water, compressed air, gases and chemicals as well as the requirements for cooling water and the specification for the exhaust streams and waste water (Eberhardt 2011). This implies also, that the management of the data of the building obtains growing importance. In the product view the modelling of waste or by-products needs to be taken into consideration.
The realisation of the information flow, both of the planning process as well as the eventual factory, requires appropriate tool support. The base of the tool support is provided by the concept of the Net Planning Assistant (NPA) (Horbach and Müller 2006), (Müller et al. 2009), which was originally developed for the planning of logistics structures and production plants in networks of micro-enterprises. The Net Planning Assistant (figure 2) is a modular concept with the three main components Production Database (PDB), uniform interface concept and connected planning tools. In the centre of the Net Planning Assistant is the Production Database. The PDB is the implementation of the production data model, which comprises the information necessary for the different stages of the planning of production systems. Commercial as well as proprietary software tools are connected by a uniform interface concept through the PDB. According to the uniform interface concept, data exchange can be realised by direct access to the PDB, the transformation of data to files (XML, CSV, ...) or transformation between PDB and the database used by the application.
The data model is used for both, the abstract, generic description of components as well as the description of the instances of the components as they can be found in the real factory, which will be the product of the planning process. The components can refer to different levels of the production system; there can be work stations as well as production lines or whole production sites.
In S-PAC the Net Planning Assistant will connect the planning software, especially the tools for simulation and visualisation (as emphasised in figure 2) to the software tools used by other projects, such as the Manufacturing Execution System (MES).
Other types of data such as the virtual and simulation representations of objects are not directly stored with the general data. Instead references to the respective models are kept. The Graphical User Interface (GUI) for the management of the data provides at the same time functions for the administration of the virtual and simulation models.
3. MODELLING In this research project three types of models are relevant, •
Data models of the objects of PV production systems,
•
Virtual models (2D, 3D, Virtual Reality) of the resources of PV production systems, and
•
Simulation models.
The project focusses on the stages of wafer, cell and module production (see chapter 1 for the production process). A reference database of typical objects of the different stages of production is developed as a basis for datasets of particular projects. Models for visualisation and simulation of the photovoltaic objects are connected to the data model. 3.1 Data Model
Fig. 3. Net Planning Assistant.
The purpose of the factory planning data model is not to represent all possible data of the production system but the 479
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
The Production Data model is implemented with the Production Database. Thereby, databases for different database management systems such as MS SQL-Server, Oracle or MySQL can be generated from an abstract conceptual data model. Apart from the databases for current planning projects, a database containing the generic components should be installed, e.g. as a repository of resources. 3.2 Virtual Model Virtual models (Fig. 4) are intended to give the investors and operators of the future PV factories a realistic impression of how the factory will look like. This way the acceptance of the layout by the stakeholders is increased, especially since they can easily participate interactively in the planning process. Fig. 4. VR building blocks. • Planning of the facilities, (optimisation of supply and disposal pipe systems),
Virtual models are managed with the tool visTABLE (Horbach and Müller 2006). In visTABLE the layout is provided in two-dimensional and three-dimensional representation. The three dimensional view can be extended to a representation in Virtual Reality (VR), so that the user can virtually move through the production line. Apart from the visualisation feature, visTABLE provides functionality for the planning of production facilities; particularly the optimisation of rough structure, the verification of minimum distances between objects, as well as the calculation and visualisation of the material flow. Thus, visTABLE supports the optimisation of the layout as well as material and energy flow, including the supply of media such as gases or chemicals. Different hardware can be used for interaction with visTABLE (Horbach et al. 2010), among them such devices which have become popular in consumer electronics (Wii controllers, MS Kinect). A collaborative planning through the internet is enabled by visTABLE.
•
Determination of the optimal structure (inline or cluster arrangement, depending on the optimal material flow and minimum cost facility area),
•
Support of current and future layout planning by the use, development and improvement of a PV object library containing typical machines and equipment for the production of wafers, cells and modules,
•
Presentation of the future factory to potential investors in the tendering stage,
•
Communication base for the participation of operators already in the planning stage both locally and through the internet.
First the typical equipment for the module production was modelled. Later also models of wafer and cell production equipment were elaborated, so that the whole production process is covered by the VR building block library. The library will be enhanced by models of equipment, which is currently developed by other partners. With the equipment models, models for production sites are now assembled. A first model for a module production line is completed. 3.3 Simulation Models The simulation of the material flow provides an evaluation of the dynamical aspects of the layout of the production system and the related manufacturing processes. Key performance indicators like throughput, availability of the equipment or logistical parameters like buffer size and storage durations are investigated and compared.
The planning of PV production system is supported by visTABLE in the following fields; Evaluation and optimisation of the material flow of both, products and media,
Derivation of criteria for the precise dimension and structure of transfer systems,
The elicitation of geometrical information about the equipment and the provision of their 3D-models are important prerequisites for the deployment of visTABLE.
A certain effort is necessary to generate the 3Drepresentations of objects for the use in visTABLE, e.g. with 3D Studio Max or Trimble SketchUp (bought from Google). Ideally these models are provided by the construction department and just need to be rid of unnecessary details. However, once the objects are modelled they are integrated in the extendable model library of visTABLE and can be used for all other projects. With this catalogue, a layout for a production site under construction can be quickly generated by dragging and dropping the relevant components to the layout of the planned facility (see fig. 4). The basic VR models for the components of module and wafer production were designed. For cell production the basic VR-models are still elaborated. The catalogues will need continuous updating as new technologies are developed.
•
•
The goal of simulation is the tuning of processes and capacities, which results in a better overall performance of the production system. At a later stage, bottlenecks need to be identified and eliminated. However, in addition to the traditional subject of material flow also the energy flow will be subject of simulation experiments. It will be investigated, 480
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
how by applying different operation strategies and changed start up strategies the peak capacities of the facilities can be minimised.
Simulation equipment models for module production were made available on the basis of the SimPlan library, which is further developed. In addition, models for wafer production were elaborated. For the completion of the cell production, first a decision is necessary, on which technology will be concentrated. For wafer and module production, production lines are now modelled. At the same time simulation experiments are planned.
Therefore, the following indicators are needed from the planning data of the production system; •
Electrical specifications like power, standby power, start up power as well as type, quantity and quality of media (gases, chemical etc.),
•
Production figures like availability of the equipment, statistical failure rates and durations as well as the expected output,
•
Information about the behaviour of the plant (process and waiting times, buffer sizes).
4. INTERFACES In the construction and operation of a PV production line, facility planners, simulation experts, production managers and quality managers work together. For the communication of the software systems, which are used by the different partners of the project, a central database is under development. It stores the equipment library, data about former projects and the different versions of current projects as well as performance data of running systems. The latter can be replaced by simulation data if the ramp-up has not been completed. It has been concluded that the use of XMLfiles should be preferred to the use of a relational database since the administration of different configuration scenarios can be handled easier with XML. The structure of the files is regulated by XML-Schema definitions.
For the improvement of the planning solution, simulation is expected to contribute with the following results; •
Verification of planning results comparison with target indicators,
through
•
Identification of critical bottlenecks, to which special attention needs to be paid in the further planning process,
•
Derivation of general control strategies,
•
Optimisation of the dimensioning of the facilities through reduction of the theoretical peak load,
•
Deployment of the visualisation functions of the simulation system to support equipment suppliers (transfer system) and to increase acceptance of the solution.
The general use case of communication is the exchange of data between the different sub-projects during the construction of the production system. Following the Component-based Planning approach, for the planning of the PV production system, which was specified by the investor, possible configurations can be generated from the equipment library. This draft is stored as project master data. The data is transferred to the simulation and visualisation tools. The results of simulation experiments and model optimisations are transferred back to the central database, especially as performance data. Thus, the data can be compared to the requirements of the client. It is the basis for new configuration scenarios which are stored in the configuration archive. Finally the preferred configuration is available as active project in the project master data and can be accessed by all partners when the requirements were modified by the client.
The approach of Component-based Planning will be also applied to simulation (Fig. 5). A component library with simulation representations of typical objects of PV production systems is developed. As a foundation the photovoltaic component library of SimPlan is used (SimPlan 2010), which is further developed in close cooperation with this company. The description of the objects comprises the properties of the objects (capacity, rates of failure) as well as methods which imply the behaviour of the objects. In result, the building blocks can be parameterised and combined to complex simulation models. The component library has a hierarchical and modular structure. Main types of components are general, technical, administrative, statistical and interface components.
A special use case is the simulation of the operation of the planned production system in dialogue between simulation system and the MES. That way it becomes possible to draw first conclusions about the performance of the production system and the MES. Different control strategies can be evaluated. 5. CONCLUSIONS Methods and tools from factory planning which have been used for discrete part production can also be used to improve the quality of planning processes and planning solutions for the photovoltaic industry. This is shown for the Flow System Theory and the approach of Component-based Planning. The Net Planning Assistant is a suitable concept for the tool support of the planning activities. The underlying data needs to be extended. Especially visualisation and simulation can be used to verify and optimise results from early stages of production. Adaptations of currently common procedures
Fig. 5. Simulation building blocks. 481
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
based Networks. In: H. Lewis, B. Gaughran, and S. Burke, eds. Proceedings of the 16th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2006, June 26-28th 2006, University of Limerick, Limerick, Ireland. Limerick: University of Limerick, Dept. of Manufacturing and Operations Engineering, 949–956. King-Kordi, A., 2010. Methodik zur bausteinbasierten Planung und Organisation von verfahrenstechnischen Produktionssystemen. Dissertation: Technische Universität Chemnitz. Mehta, S., 2012. PV Module Consolidation in 2013-2014: What to Expect. Müller, E. and Ackermann, J., 2005. Planning and Design of Logistics Structures of competence-cell-based Networks. In: E. Alvarez, et al., eds. FAIM 2005: Proceedings of the 15th International Conference on Flexible Automation and Intelligent Manufacturing : July 18th20th, 2005. Bilbao: University of Deusto Press, 794–801. Müller, E., Horbach, S., and Ackermann, J., 2009. Tool support for industrial engineering in small enterprises. In: F. Nabhani, ed. Proceedings of the 19th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2009, July 6th - July 8th, 2009, Teesside University, Middlesbrough, UK. Middlesbrough: Teesside University, 195. Müller, E. and Löffler, T., 2010. Energy Efficiency at Manufacturing Plants – A Planning Approach. In: W. Sihn and P. Kuhlang, eds. Sustainable production and logistics in global networks: 43rd CIRP international conference on manufacturing systems, 26-28 May 2010, Vienna : proceedings. Vienna: NWV Neuer Wissenschaftlicher Verlag, 787–794. Müller, E., Rösch, N., and Ackermann, J., 2008. Componentbased Planning of Flexible Assembly Systems: a Methodical Approach and its Implementation. In: Proceeding of the 2nd CIRP Conference on Assembly Technologies and Systems (CATS 2008), 41–49. Näser, P., 2005. Component based planning of manufacturing plants. In: Proceedings (CD) of the 3rd Annual Conference on Systems Engineering Research – CSER, 393–402. Pascal, A. and Carolle, C., 2011. A new era: Renewable energy. The Intelligent Energy - Europe Magazine 3: Intelligent Energy Europe. Schenk, M., Wirth, S., and Müller, E., 2009. Factory planning manual. Berlin ;, London: Springer. SimPlan, 2010. Bausteinkasten für die Solarindustrie. S-PAC Saxon Photovoltaic Automation Cluster. The Alliance - S-PAC Saxon Photovoltaic Automation Cluster [online]. Available from: http://www.s-pac.de/indexen.html [Accessed 14 Dec 2011]. Verlinden, P., 2012. The Surviving PV Companies. Future Photovoltaics [online] (July). Available from: http://futurepv.com/node/399.
need to be made to meet the growing demand for incorporation of the energy flow; however the existing tools have the potential to provide the necessary functionality. Simulation and visualisation are suitable for helping to meet the increasing complexity and growing challenges of PV production. Interfaces to software systems used by other actors are developed to achieve competitive, sustainable and globally sufficient planning solutions. In brief, existing approaches of factory planning are suitable for the planning of photovoltaic production systems. Necessary adaptations are the extension of the data and of the functionality for optimising the energy flow. Virtual and simulation building blocks for solar production equipment are available now. The building blocks will undergo further improvement and extension. They are now combined to production lines. Hence, flow investigations and simulation experiments can be started. ACKNOWLEDGEMENTS The work which is presented in this paper, as a part of the project S-PAC, is funded by the German Federal Ministry of Education and Research. REFERENCES Branker, K., Pathak, M.J., and Pearce, J.M., 2011. A review of solar photovoltaic levelized cost of electricity. Renewable and Sustainable Energy Reviews, 15 (9), 4470–4482. Breyer, C., Gerlach, A., and Werner, C., 2011. Grid Parity: Coming Sooner Than You Think. Future Photovoltaics (6), 26–31. Eberhardt, K., 2011. Large-Scale PV Manufacturing: Cost Reduction Potentials beyond Scaling. Inter.PV Global Photovoltaic Business Magazine [online] (February). Available from: http://www.interpv.net/market/market_v iew.asp?idx=355&part_code=02&page=6# [Accessed 16 Dec 2011]. European Photovoltaic Industry Association, 2011. Global Market Outlook for Photovoltaics until 2015. European Photovoltaic Industry Association and Greenpeace, 2011. Solar Generation 6: Solar photovoltaic electricity empowering the world. Glunz, S., Preu, R., and Biro, D., 2012. Crystalline Silicon Solar Cells. In: A. Sayigh, ed. Comprehensive renewable energy. Amsterdam, Boston, Mass: Elsevier, 353–387. greentechmedia, 2012. The Solar Industry’s Living Dead: 180 Module Manufacturers to Succumb to Consolidation by 2015. Financial Times, 2012. Cloud hovers over China’s solar industry. Financial Times [online], 22 Oct. Available from: http://www.ft.com/intl/cms/s/0/bef02db6 -1c26-11e2-a63b-00144feabdc0.html [Accessed 23 Oct 2012]. Horbach, S., et al., 2010. Building Blocks for Adaptable Factory Systems. In: Proceedings of the 20th International Conference on Flexible Automation and Intelligent Manufacturing – FAIM 2010, 568–575. Horbach, S. and Müller, E., 2006. The Net Planning Assistant – A Toolset to Support Planning in Competence-cell482