Björn Johansson
email: bjorn.johansson@chalmers.se

Jon Andersson
email: jon.andersson@chalmers.se

Erik Lindskog
email: lindskog@chalmers.se

Jonatan Berglund
email: jonatan.berglund@chalmers.se

Anders Skoogh
email: anders.skoogh@chalmers.se

Evaluation and Calculation of Dynamics in Environmental Impact Assessment

Keywords: Discrete event simulation, sustainable production, product lifecycle, environmental analysis, sustainable manufacturing

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Conscious efforts on reducing environmental impact are valuable for companies. Such companies contribute not only to a more sustainable future, but also obtain a competitive advantage towards customers. One example from food and service industry is an award winning restaurant in Sweden called MAX. They reported a reduction of their CO 2 -emmisions by 44% [START_REF]MAX Annual Climate Report[END_REF] between 2007 and 2008 by evaluating and improving their product value chain. Moreover, market research shows that 13 times [START_REF]Interview with Pär Larshans, HR and Sustainability Manager[END_REF] more customers relate their brand to environmental friendly products compared to their main competitor. MAX's sustainability manager states that the latter figure is not the result of an increase in traditional marketing, but derives solely from communication of their products' environmental footprint. This paper describes a current research project called EcoProIT enabling manufacturing industry to evaluate, improve and advertise their environmental footprint through the developed procedure. At present, Life Cycle Assessment (LCA) standardized by ISO 14040:2006 and 14044:2006 [START_REF] Finnveden | Recent Developments in Life Cycle Assessment[END_REF] is by far the most common analysis method for evaluation of environmental footprint. However, there are inherent problems associated with LCA, which reduce its preciseness and limit its value for companies. The main associated problems with traditional LCA analyses are [START_REF] Reap | Improving Life Cycle Assessment by Including Spatial, Dynamic and Place-Based Modeling[END_REF]:

• Use lumped parameters and site-independent models.

• Static in nature and disregard the dynamic behavior of industrial and ecological systems.

• Focuses only on environmental considerations, not economic or social aspects.

Hence, it is important to complement LCA with other analysis tools, in order to effectively combine environmental and economic analysis. The EcoProIT project in particular proposes Discrete Event Simulation (DES) as a potent solution, thereby reaping the strengths of DES to perform dynamic and site-specific analyses on product flows along product value chains. Combining the advantages of DES with LCA compensates the above stated weaknesses of traditional LCA. Performing DES and LCA simultaneously in a product value chain offers the advantage to foresee the interaction between resources and helps identify opportunities to reduce waste. In other words, companies will be able to use the EcoProIT tool [START_REF] Andersson | Framework for Ecolabeling using Discrete Event Simulation[END_REF] [START_REF] Andersson | Framework for Ecolabeling using Discrete Event Simulation[END_REF] with combined capabilities of DES and LCA, to label their products and to increase competitiveness. The tool enables continuous improvement of the product realization process with regard to both efficiency and environmental footprint.

2

State of the art

Combined environmental and production systems analysis

To solve the inherent problems of LCA there are proposals on combining tools for environmental analyses (usually LCA) and tools for evaluation of industrial systems. For example, ecosystem models are combined with basic industrial models such as Activity Based Costing (ABC) [START_REF] Finnveden | Recent Developments in Life Cycle Assessment[END_REF] and in [START_REF] Ball | Zero carbon manufacturing facility -towards integrating material, energy, and waste process flows[END_REF] environmental analyses are combined with the process mapping approach Value Stream Mapping (VSM). Regarding the dynamic aspects, LCA has been combined with Monte Carlo simulations [START_REF] Frischknecht | Uncertainty analysis in life cycle inventory. Application to the production of electricity with French coal power plants[END_REF] and initial studies have also been performed on integration of LCA and DES [START_REF] Heilala | Simulation-Based Sustainable Manufacturing System Design[END_REF].

However, the bottom line is that researchers in the area agree on that this is still an immature research area with significant potential [START_REF] Ball | Zero carbon manufacturing facility -towards integrating material, energy, and waste process flows[END_REF]. The potential for reducing environmental impact with means of production flow development is actually bigger than the potential of addressing individual manufacturing processes [START_REF] Cao | Mobile Agent Based Integration Framework for Flexible Dynamic Job Shop Scheduling[END_REF]. New research (NIST-Chalmers-Boeing-collaboration) show that more energy is saved by reducing the production lead-time of a product compared to reductions in energy consumption for the value-adding machining processes, which is due to the high energy consumptions during stand-by times of the machines. An additional factor regarded in this project proposal is the potential to benefit from synergy effects from analyzing production and logistic processes throughout the complete product value chain including recycling. This potential is previously evaluated by e.g. [START_REF] Nagel | Caught between ecology and economy: end-oflife aspects of environmentally conscious manufacturing[END_REF].

Data management and model credibility

Data management is one of the biggest problems in LCA [3] [4] and this has also traditionally been a problem for production development tools such as DES. An indicator is that 31% of the time for DES is spent on input data management [START_REF] Feifel | LCA, how are you doing today? A snapshot from the 5 th German LCA workshop[END_REF]. However, recent research proposes a higher level of automation and integration of data sources in the input data management process [START_REF] Robertson | Automated data collection for simulation? Simulation Practice and Theory[END_REF] [14] and the proposed project will contribute to the incorporation of environmental data in this process. One part in this work is the cooperation with the United States National Institute of Standards and Technology (NIST) on adding environmental parameters to the Core Manufacturing Simulation Data (CMSD) standardization effort [START_REF]SISO -Simulation Interoperability Standards Organization[END_REF].

Another important part for model and analysis credibility is to apply a structured and transparent work procedure. This point has recently been addressed in the DES area by efforts from the Fraunhofer Institute in Germany [START_REF] Rabe | A New Procedure Model for Verification and Validation in Production and Logistics Simulation[END_REF] and similar work has also been performed to support combined DES and LCA [START_REF] Andersson | Framework for Ecolabeling using Discrete Event Simulation[END_REF]. The proposed project will contribute to this work by extending these work procedures to regard the entire product value chain and assure correct standardized analyses and trust between involved parties enabling benchmarking between products and companies.

Project description

The EcoProIT project brings together researchers on production and environmental system analysis with industrial partners throughout the complete lifecycle of a specific product used in forklift manufacturing. The product is analyzed in three separate settings, raw material extraction/recycling, sub component manufacturing, final product manufacturing/use, and then recycled back to the raw material state again. The total cycle will be closed when all three company specific case demonstrators are done, they will then be merged into the complete lifecycle calculation of environmental footprint. There are three main scientific challenges addressed in the project:

• Efficient management of environmental data. How can required data for production performance and environmental impact be jointly collected and processed in an efficient manner?

• Selecting system delimitations. How are the system delimitations chosen to ensure objective measurements and, thus, enable comparison?

• Modeling methodology through an entire product lifecycle. How are models built and communicated between companies involved in the product lifecycle, in order to assure company integrity as well as correct standardized and credible analyses?

Level of innovation

Today, industry can evaluate and declare their products' environmental footprint only for marketing purposes. This is for example applied in several cases in food industry. However, due to limitations in the traditional LCA analysis it is problematic to detailed process analyses and specific results. These drawbacks make it impossible for a specific company to really improve their performance and compete on their environmental footprint.

Component Manufacturer

NMW

User

Volvo Cars

Recycling Stena Metal

The proposed tool enables not only declaration of environmental footprint but also continuous work with reduction of this new product value. Furthermore, the tool adds the factors time, location and economy to traditional LCA analyses. The bottom line is that companies in all lines of business can reduce environmental impact and improve economic profit simultaneously. The EcoProIT tool will be associated with competitiveness on the product values price and environmental footprint in Swedish manufacturing industry.

The significant value in definition of measurements for sustainability performance in manufacturing industry is one contribution. Moreover, the research on dynamic and site specific evaluation of environmental effects in production systems is a requested and not yet researched complement to the popular LCA analysis [START_REF] Finnveden | Recent Developments in Life Cycle Assessment[END_REF]. Several other actors are identified and collaboration is established with most of the twelve actors described by Herrmann et al. [START_REF] Herrmann | Energy oriented simulation of manufacturing systems -Concept and application[END_REF] in order to streamline work and reach interoperable and useful results for industrial applications.

Vision

Product Lifecycle Management (PLM) systems are widely used in large manufacturing companies. They are used to support collaborated work throughout a products life cycle. To conduct the analysis explained in this paper, a structured work method and a helpful tool is needed. However, to support collaborative work between companies and other actors in a life cycle a larger data management system is needed. This project proposes to use PLM likewise software and database structure to enable sharing of results and information. All companies that are involved in a products lifecycle connect to the database structure and share up to date result and analyze. This enables up to date emission declaration for the products analyzed in the system. Figure 2 show how the close linked companies share all information and final result to the public server available for other companies to use in similar studies.

Present status

The project has reached halfway and two of three parts in figure 1 are completed. The first case study show several advantages with the proposed method compared to LCA concerning the level of details, scalability and dynamical emission values. Results from the study indicated that a large part of the total emission value was related to processes outside the studied company, which directs the need for applying the method to the entire life cycle. The first case study resulted in a proposed method for future work with focus towards the process of gathering environmental input data.

The second case study show how to build a structured output data format that supports validation and verification of the model. Practical experiences show that it is important to early identify the expected input data and information that is possible to retrieve. A DES model built for LCA calculations need other types of information from the real system, i.e. energy consumption and resource consumption for specific processes. Depending on available information the model can be alternately designed.

Future Research

There are additional efforts ongoing within the field of DES-LCA combination. Examples stated in [START_REF] Thiede | State of Research and an innovative Approach for simulating Energy Flows of Manufacturing Systems[END_REF][START_REF] Hesselbach | Energy Efficiency through optimized coordination of production and technical building services[END_REF][START_REF] Dietmair | A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing[END_REF][START_REF] Heilala | Simulation-based sustainable manufacturing system design[END_REF][START_REF] Hornberger | Vom Energiemanagementsystem zur Simulation der Energieverbrauchswerte auf Prozessebene. Elektronik ecodesign congress[END_REF][START_REF] Johansson | Discrete Event Simulation to generate Requirements Specification for Sustainable Manufacturing Systems Design[END_REF][START_REF] Junge | Simulationsgestützte Entwicklung und Optimierung einer energieeffizienten Produktionssteuerung[END_REF][START_REF] Löfgren | Capturing the life cycle environmental performance of a company's manufacturing system[END_REF][START_REF] Rahimifard | Minimising Embodied Product Energy to support energy efficient manufacturing[END_REF][START_REF] Solding | Using simulation for more sustainable production systems -methodologies and case studies[END_REF][START_REF] Weinert | Concept for Energy-Aware Production Planning based on Energy Blocks[END_REF][START_REF] Wohlgemuth | Combining discrete event simulation and material flow analysis in a component-based approach to industrial environmental protection[END_REF] are many different approaches on how to describe instantiated DES-LCA case studies. The majority of these researchers are now working together to find a common solution on how to utilize DES and LCA in a methodological manner to calculate benefits of the combination.

Figure 1 .

 1 Figure 1. For development and demonstration of the EcoProIT tool, the project will regard companies through the lifecycle of a product.

Figure 2 .

 2 Figure 2. Conceptual data repositories for lifecycle assessment data.

8

The authors would like to acknowledge support from ProViking through the EcoProIT project and VINNOVA (Swedish Agency for Innovation Systems). This work has been carried out within the Sustainable Production Initiative and the Production Area of Advance at Chalmers. The support is gratefully acknowledged.


Juhani Heilala
email: juhani.heilala@vtt.fi

Marja Paju
email: marja.paju@vtt.fi

Jari Montonen
email: jari.montonen@vtt.fi

Reino Ruusu
email: reino.ruusu@vtt.fi

Mikel Sorli
email: mikel.sorli@tecnalia.com

Alberto Armijo
email: alberto.armijo@tecnalia.com

Pablo Bermell-Garcia
email: pablo.bermell-garcia@eads.com

Simon Astwood
email: simon.astwood@eads.com

Santiago Quintana
email: santiago.quintana@eads.com

Discrete Part Manufacturing Energy Efficiency Improvements with Modelling and Simulation

Keywords: Energy efficiency, modeling and simulation, manufacturing

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In order to win future markets, industrial firms are under pressure to achieve sustainability targets related to their products and services. The reduction on materials and energy on products and production systems is acknowledged as a key strategy in this journey [START_REF] Krajnc | Indicators of Sustainable Production[END_REF]. Also the directives and legislation [START_REF]Summaries on Legislation[END_REF] are drivers for environmantal end energy efficincy improvements in manufacturing.

Satisfactory results on manufacturing systems often require detailed studies to understand where and how the energy has been used. This transparency to energy utilization is the basis for optimizing the energy use performance on production systems. Once visibility is achieved, a question remains on the choice on improved decision support methods and tools guiding practitioners on energy efficient investments in manufacturing systems. A current gap is the availability of software supporting production engineers in this type of decision making. This is not a simple task since it involves balancing conflicting criteria such as financial costs, energy consumption, equipment reutilization, and manufacturing system availability.

The sustainability assessments of a product, and its corresponding processes, have different emphases. The manufacturing processes, serve to implement a product design, and their constraints are decided by the current product design. To evaluate a manufacturing process, its fulfilment of product design features and requirements need to be considered. For sustainability assessment of a product design, the overall product sustainability performance is the ultimate criteria and the process assessment is only one of the sub-elements. To be specific, the sustainability assessment of a process would not cover the other phases of the manufactured product's life-cycle [START_REF] Lu | A Framework of Product and Process Metrics for Sustainable Manufacturing[END_REF].

An optimized manufacturing process routine does not necessarily mean that the product is optimal concerning its sustainability performance. On the other hand, to achieve optimal overall sustainability performance when designing a product, the corresponding manufacturing processes need to be optimized based on some sustainability criteria and this is one of the aims in the EPES project [START_REF]EPES -Eco-process Engineering System for Composition of Services to Optimize Product Life-cycle[END_REF].

Typical tools for eco efficiency analysis of discrete part manufacturing system and processes are Life Cycle Assestment (LCA), Value Stream Map (VSM) and Discrete Event Simulation (DES). This paper reviews those tools for assesstment of energy efficiency in manufacturing, shows challenges and development need as well research results.

Manufacturing Sustainability with Modelling and Simulation

In addition to the problems for traditional manufacturing modelling and simulation, there are some new challenges for simulation of sustainable manufacturing, such as the lack of [START_REF] Shao | Interoperability for Simulation of Sustainable Manufacturing[END_REF]:  Source of the sustainability information, sustainability metrics and indicators  A reference model to identify appropriate information  Information models that support simulation for sustainable manufacturing  Modeling methods for simulation of sustainable manufacturing  Measures to evaluate sustainability.

Sustainability indicators

In industry today sustainability measures are common. Ideally measures can be a guide to where you are, where you are heading and how far you are from the ultimate vision. There are parameters (figures you measure), indicators (figures that indicate something) or index (several indicators combined into one). They can be used for benchmarking, decision making, measuring or guiding to improvement on the operational level or enabling companies to identify more innovative solutions to sustainability challenges [START_REF] Oecd | Eco-innovation in industry: enabling green growth[END_REF].

Feng & Joung, 2009 [START_REF] Feng | An Overview of a Proposed Measurement Infrastructure for Sustainable Manufacturing[END_REF] describes a multitude of various measurement initiatives for measuring sustainability metrics. It has been recommended to pursue a multi-level approach for metrics, with simple metrics at the highest level. Methodology for sustainable production indicator development has been presented by Velava & Ellenbecker [START_REF] Veleva | Indicators of sustainable production: framework and methodology[END_REF]. Examples of indicators have also been presented by Krajnc and Glavic [START_REF] Krajnc | Indicators of Sustainable Production[END_REF]. It should be noted and identifyi the interdependencies between the different indicators. For instance, carbon dioxide emissions are dependent e.g. on the energy consumption and sulfur dioxide air emissions from transportation are dependent e.g. on the sulfur contents of the fuel.

Research on Manufacturing System Modelling and Simulation With Energy Use Parameters

The methods, specifically decicated to production system development are production and material flow simulation, e.g. Discrere Event Simulation and process mapping methods, e.g. Value Stream Mapping.

In Discrete Event Simulation (DES), the operation of a system is represented as a chronological sequence of events. Each event occurs at an instant in time and marks a change of state in the system. DES is well suited for modelling a specific well-defined system, such as a production system. It can provide statistically valid quantitative estimates of performance metrics as-sociated with the system. Integration of sustainability and environmental aspects to simulations is development topic in many research institutes. Currently most of the research efforts have been focused on energy efficiency, examples shown in [START_REF] Cannata | Energy Efficiency Optimization through Production Management Decisions in Manufacturing Environment: a Proposal[END_REF][START_REF] Duflou | Towards energy and resource efficient manufacturing: A processes and systems approach[END_REF][START_REF] Herrmann | Energy oriented simulation of manufacturing systems -Concept and application[END_REF]. Wider scope, sustainability and environmental aspect analysis are shown in [START_REF] Heilala | Simulation-Based Sustainable Manufacturing System Design[END_REF][START_REF] Lindskog | A Method for Determining the Environmental Footprint of Industrial Products Using Simulation[END_REF].

Value Stream Mapping (VSM) relies on Lean principles and identifying and eliminating wasteful activities. It is a process mapping method, and it can be also employed to environmental assessment. The potential of VSM has also been noted by the US Environmental protection agency EPA [START_REF]Lean Manufacturing and the Environment[END_REF]. EPA has gathered case studies, fact sheets and tools containing techniques for integrating environmental considerations into Lean initiatives and methods [START_REF]Lean Manufacturing and the Environment[END_REF]. A lot of research has been carried out in various research institutes to use VSM for sustainable production system development.

Typically LCA is conducted for a pre-specified use purpose. It can be decision making, e.g. when comparing two alternative materials, communication purpose, in a form of an environmental product declarations (EPD), or something else. Typically LCA is done for a product system. Use of LCA methods for assessmrent of production system footprint requires specific development in life cycle modeling. In practice light, streamlined or screening LCAs are common since full LCA may be too extensive.

Each analysis method has their limitations and assets which shall be taken into consideration. The essential difference between the three methods is that DES and VSM have generally been used for manufacturing processes and supply chains whereas LCA covers the whole product life cycle including manufacturing, transportation, use, maintenance and end-of-life. LCA method with ISO standardisation (ISO 14040/14044), is solely meant for environmental impact analysis. However DES and VSM have more flexibility in applications and can be used in light environmental analysis. DES is a tool more specifically aimed at production system life-cycle studies. Economic indicators, investment cost and total cost of ownership (TCO) or Activity Based Costing (ABC) analysis can be integrated to DES.

Both LCA and DES require high expertise from the user and computerised tools, while VSM in its simplest form can be done with paper and pencil.

Use of DES.

In the SIMTER project [START_REF] Heilala | Simulation-Based Sustainable Manufacturing System Design[END_REF] environmental analysis simulation tool was created (Fig. 1). Data management is in the simulation software interface. The user can control following simulation variables and their relationships: resourceenergy; partmaterial; and system input, system output and layout properties. Simulation run provides book keeping of events, resource utilisation as well state of the resource (down, idle, busy), material flow statistics, and number of products/parts manufactured (ready, rejected, repair) etc. data. Simulation model and run results can pin point in a detailed way, bottlecks of the system, where and how energy and materials are used, whether material is disposed / recycled, and what emissions and waste are produced. Life cycle inventory (LCI), e.g. energy type and material related data, were either selected from EU-LCA database (http://lca.jrc.ec.europa.eu/lcainfohub/datasetArea.vm) or user editable. Manufacturing process specific data is typically a challenge in the LCI databases.

MS-Excel is used for detailed analytical calculation and summary results can be shown in the simulation software interface. Product, resource or process based and piece count or time frame analysis can be reported using MS-Excel. Similar approach as SIMTER, can be used with other commercial factory simulation tools.

Use of VSM.

In a recent discrete manufacturing research project Ekoteho [START_REF] Paju | Framework and Indicators for Sustainable Manufacturing Mapping Methodology[END_REF], methods and tools for environmental assessment were studied. The methods and tools vere divided into those that are used primarily for the assessment of environmental aspects, such as LCA, and those that use environmental assessment as an add-on element. Add-on tools, such as VSM, require less effort to adapt to existing manufacturing modelling tools, but they compromise on comprehensiveness in the environmental assessment part.

Fig. 2. Use of VSM for production system energy efficiency analysis

In the project new methodology was created based on VSM (Fig. 2). Choosing the right indicators according to the goal, and setting the system boundaries are essential steps for the new methodology as shown in in Paju et al. ( 2010) [START_REF] Paju | Framework and Indicators for Sustainable Manufacturing Mapping Methodology[END_REF]. To test the methodology some simplified and connective process flow chart models were created with eVSM tool (http://www.evsm.com/). eVSM is a commercial tool that creates link between MS Excel and MS Visio. The modelling test platform utilizes preselected indicators and limited amount of visible parameters. The test platform had connections to web databases Lipasto (http://www.lipasto.vtt.fi/yksikkopaastot/indexe.htm) to import logistic emission data.

Genaral Model Development Steps

The general methodology for developing the process-oriented, environmental modules of the sustainability simulation toolkit involves the following steps according to Zhou and Kuhl [START_REF] Zhou | Design and Development of A Sustainability Toolkit for Simulation[END_REF]: 1. Identify sustainability factors and environmental performance measures for systems of interest. 2. Establish simulation state variables to represent the sustainability factors and performance measures. 3. Identify the events in the system that cause changes to the state variables, and translate these system events to simulation events and the associated event triggers. 4. Establish the mathematical, statistical, and logical relationships among the state variables to update and change the values of the state variables as events occur in the system over time. 5. Implement state variables, relationships, and events into a robust, flexible simulation toolkit modules. 6. Perform verification, validation, and testing of the simulation toolkit modules.

The authors have used similar approach in the past and the presented case studies [START_REF] Heilala | Simulation-Based Sustainable Manufacturing System Design[END_REF][START_REF] Paju | Framework and Indicators for Sustainable Manufacturing Mapping Methodology[END_REF] can be implemeted using also other commercial tools. Methodology and tool development for sustainability simulation toolkit continues in the EPES project [START_REF]EPES -Eco-process Engineering System for Composition of Services to Optimize Product Life-cycle[END_REF]. The aim of the EPES project is to bring sustainability intelligence to the decision making process for optimisation of the product service system (PSS) life cycle.

In sustainability aspect simulation or any simulation study, one of the first steps is to define the scope of study and select suitable indicators for assesstment. Both VSM and DES, are process oriented and study is focused on manufacturing material flow, process cycle times, resources utilisation, equipment and even human operators activities.

Workstation and manufacturing process level data can be quite similar in LCA, VSM or DES. Here deep understanding of processes and equipment is needed. For sustainability issues we are adding energy flow study, (energy consumption), more detailed consumables study; e.g. materials, (dimensions, type), components, semi products, lubricants, chemicals, waste generation, and also emission study (air emission, aerosol particle, water emission), depending on the scope of the study (see Fig. 3). Equipment simpliest model, include only three states; down (off), idle (stand-by) and busy (working). In more detailed model the busy state energy consumptioncan depend of equipment speed or process load. Fig. 3. From machine level to plant level analysis of complex process chains.

The system level combines the workstations and manufacturing processes together, (Fig. 3, see also case study Fig. 1 and2). The production system model can aggregate workstation and process level results to the system level. The analysis of material flow can be complex and here DES has advanges over LCA or VSM. DES studies support multi-product environment, detailed bottleneck and production efficiency analysis.

LCI factors, environmental sustainability aspects, do not always have to be incorporated in the simulation itself. Sometimes it is sufficient to combine the results of a simulation with an LCA knowledge base as a post processing phase. For example, a simulation can provide the distributions of different states that a set of production machinery are in during the production process. This can be later combined with the knowledge of the impacts that each state has on the overall LCA indicators.

Discussion and conclusion

LCA and its integration with modelling and simulation for the sustainability evaluation of manufacturing systems and processes have been discussed. There is need for comprehensive and structured approach that provides the necessary coherent process design with a strong emphasis on energy-and resource-efficiency. Industrial companies need integrated product-process-production system modelling and simulation approaches for enabling them to select the manufacturing processes and associated manufacturing systems that fulfil production requirements with minimal economic and environmental costs, especially in the field of energy consumption and related emissions. The methods described in chapter 2.2.can be utilised to integrate sustainability assessment. European research project EPES [START_REF]EPES -Eco-process Engineering System for Composition of Services to Optimize Product Life-cycle[END_REF] continues the development. In one of the demonstrators the early product concept will be analysed from both productivity and sustainability aspects using simulation as a service by nonsimulation expert. The essential questions answered through this assessment step are:  Productivity KPIs: What production rate can be achieved for a design using a given set of processes and resources?  Sustainability KPIs: What are the energy consumption, the emissions and the hazardous material waste resulting from the manufacturing for a design using a given set of processes and resources?

Environmental data management is essential in assessing the environmental aspects and the real bottleneck is in getting data for analysis. Site specific data (energy, emissions, waste) must be collected from the existing manufacturing processes or from design documents, engineering and other legacy systems. Life cycle inventory data can be connected to complement the site specific data and to enable sustainability assessment throughout the whole life cycle. Alternative approach could be to transfer the results from life cycle assessment software to the simulation models. The manufacturing system simulation gives opportunity to analyse also multiproduct manufacturing with view to resource, product or time based analysis.

With methdos presented in this paper industry can gain the knowledge to compare different production system alternatives with regards to their life-cycle performance already during the early design phase.

ACKNOWLEDGMENTS.

The research presented in the paper has been carried out within the frames of the EPES, "Eco-Process Engineering System for Composition of Services to Optimize Product Life-Cycle" collaboration project co-funded by the European Commission under FoF-ICT-2011.7.3-285093 contract. The authors wish to express the acknowledgement to EC for the support and to all project partners for their contributions during the development presented in this paper.

DISCLAIMER. This document does not represent the opinion of the European Community, and the European Community is not responsible for any use that might be made of its content. Mention of commercial products or services in this report does not imply approval or endorsement by authors, nor does it imply that such products or services are necessarily the best available for the purpose.

Fig. 1 .

 1 Fig. 1. VTT SIMTER Environmental analysis tool interface.


Teuvo Uusitalo
email: teuvo.uusitalo@vtt.fi

Markku Reunanen
email: markku.reunanen@vtt.fi

Katri Valkokari
email: katri.valkokari@vtt.fi

Pasi Valkokari
email: pasi.valkokari@vtt.fi

Katariina Palomäki
email: katariina.palomaki@vtt.fi

Toward Sustainability Governance in Manufacturing Networks

Keywords: sustainability, governance, manufacturing networks

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

This paper deals with results of an on-going FP7-funded research project entitled 'Sustainable Value Creation in Manufacturing Networks' (SustainValue). The overall goal of the SustainValue project is to develop industrial models, solutions, and performance standards for new sustainable and better-performing production and service networks. One objective of the project is to develop a sustainability governance model for manufacturing networks. This paper presents the first results from the development of this model.

Corporate governance provides the structure through which the objectives of the company are set, and thus it forms the system by which an organisation makes and implements decisions in pursuit of its objectives [START_REF]Guidance on social responsibility[END_REF]. The governance model defines 'what to do', 'how to do it', 'who should do it', and 'how it should be measured'. It addresses the rules, processes, metrics, and organisational structures needed for effective planning, decision-making, steering, and control [START_REF] Gewald | A governance model for managing outsourcing partnership: A view from practice[END_REF]. The main differences between the company and network governance models are related to legal factors, decision-making processes, and control mechanisms. Companies are legal entities with their own goals, and their decision-making is based on internal hierarchical structures (control governance) whereas networks consist of independent actors, who have their own targets and decision-making models.

The European Vision for 2020 report calls for understanding manufacturing as a network of complex and development-oriented relations. The new production paradigm is based on collaborative, value-adding networks, and globalisation has activated a different industrial revolution, leading to a new world distribution of production and markets [START_REF]European Commission: MANUFUTUREa vision for 2020: Assuring the future of manufacturing in Europe[END_REF]. Increasing demands for sustainability, however, have created new challenges and emerging opportunities for society and for business. A recent executive study illustrates that companies' perceptions of sustainability are changing. As in the past, company representatives see the potential for supporting corporate reputation. But recently they have also come to expect operational and growth-oriented benefits in cutting costs and pursuing opportunities provided by new markets and products. Additionally, in relation to the social and environmental aspects of sustainability, companies are now integrating sustainability principles into their business by retaining and motivating employees and by saving energy, alongside pursuit of other sustainability goals [START_REF] Bonini | The business of sustainability[END_REF].

Since manufacturing activities at present are organised through networked processes, new models for network governance are needed for ensuring sustainable development and performance of manufacturing operations. These models should enable clear identification of those network actors and stakeholders who influence and can be influenced by the sustainability of the product in the course of its life cycle.

Value

Sustainability is often perceived from a limited value creation view. The focus has been on an economic, compliance, regulation or legislation perspective, hence raising the need for a more holistic view of sustainable value that integrates economic, social and environmental goals. From a network perspective, the scope of value needs to go beyond customers, immediate partners and shareholders. The scope should consider relationships, exchanges and interactions. Value can be defined as the set of benefits derived by a stakeholder from an exchange. This implies the need for improved understanding of stakeholder value, and the need to seek opportunities for alignment and exchanges between stakeholders. [START_REF] Evans | D2.1 -State-of-practice in business modelling and valuenetworks, emphasising potential future models that could deliver sustainable value[END_REF] The development of a common value system in a network context is important in order to support the sustainability of collaborative behaviour [START_REF] Camarinha-Matos | A conceptual model of value systems in collaborative networks[END_REF]. Different value systems of network partners can lead to different perceptions of benefits and noncollaborative behaviours. In order to overcome this, mechanisms to promote transparency and alignment of value systems could be introduced at the level of the governance rules. Research is needed to identify suitable indicators of the collaboration level of each partner. [START_REF] Abreu | On the role of value systems to promote the sustainability of collaborative networks[END_REF] The key to new sustainable business models is in understanding the value from network perspective. A value network generates value through complex dynamic exchanges between enterprises, customers, suppliers, partners, stakeholders and the community. These networks engage in transactions around goods, services, and revenue. In addition the two other aspects are knowledge value and intangible value or benefits. All three are important in a value network. [START_REF] Allee | Reconfiguring the Value Network[END_REF] 3

Manufacturing networks

In traditional manufacturing network operations of suppliers, lead producers (such as OEMs) and customers are seen as independent sequential tasks, which form a value chain. Since the 1990s, however, this pattern has been changing and the theoretical discussion has emphasised the transfer from value chains to value networks [START_REF] Normann | Designing Interactive Strategy: From the Value Chain to theValue Constellation[END_REF][START_REF] Peppard | From Value Chain to Value Network: Insights for Mobile Operators[END_REF].

The trend among customers, lead producers (OEMs), and suppliers seems to be to engage in forward transfer in their value chains. This means that customers, lead producers or OEMs outsource manufacturing (give up earlier value chain phases), and their suppliers try to increase services (add later value chain phases and give up some of the earlier phases). Interdependency of operations and co-creation between the actors have been emphasized from several theoretical viewpoints [START_REF] Von Hippel | Democratizing Innovation[END_REF][START_REF] Dyer | Collaborative advantage: winning through extended enterprise supplier networks[END_REF][START_REF] Chesbrough | Open innovation[END_REF].

In the new network economy, the success of a firm depends on its strategic collaboration with other organizations that have an influence on the creation and delivery of its services or products. Manufacturing networks can, therefore, be defined as 'not only a new type of manufacturing system deriving new strategic capabilities and requiring design tools but also posing new theoretical questions about systems and decision processes' [START_REF] Shi | International Manufacturing Networks -to develop global competitive capabilities[END_REF].

Fjeldstad and Stabell presented a value configuration framework in which value network and value shop are the two alternatives to Michael Porter's traditional concept of value chains [START_REF] Fjeldstad | Configuring Value for Competitive Advantage: On Chains, Shops, and Networks[END_REF]. Later on, based on the notion of the value creation framework, Möller et al. have suggested a value continuum framework that includes three generic net types that are current business nets, business renewal nets, and emerging new business nets [START_REF] Möller | Strategic business nets -their type and management[END_REF]. Current business nets are value systems with a high level of determination and well-known and well-specified patterns of activities and resources. Emerging new business nets are characterized by radical changes and inherent uncertainty. In between these polar opposites are business renewal nets, which produce incremental local changes in existing value systems. Practical approaches in manufacturing networks can also be characterised by applying three network types. First, the traditional supply networks have the focus on efficiency of processes -the roles and connections between actors are quite well defined. Secondly, in business enhancing networks the focus changes from physical components to competences, while actors try to solve customer's problems together. Thirdly, emergence of radically new business opportunities requires new connections and network members -often over industry sectors. The business models of network actors differ within these network types. Furthermore, each business network evolves over time as network roles, business models, as well as strategies of actors change. Table 1 compares the key characteristics of these value creation frameworks and illustrates their appearance in manufacturing network practises.

Innovation networks

In manufacturing industries value network consist of organizations co-operating with each other to benefit all network members. Lead producer and its suppliers and customers form a typical value network. Value system consists of the suppliers' value networks (who provide input), core company's value network (that produces products), the distributers' and retailer's value networks (who distribute products to customers) and the customers' value networks (who use the products in their own activities) [START_REF] Miltenburg | Manufacturing Strategy -How to Formulate and Implement a Winning Plan[END_REF].

The focus should be broadened from supplier-lead producer-customer relationships to collaborative relationships [START_REF] Vallet-Bellmunt | Supply chain management: A multidisciplinary content analysis of vertical relations between companies, 1997-2006[END_REF]. Furthermore, based on system thinking the concept of business ecosystems has been introduced to highlight the importance of a value system, where all stakeholders co-produce value and thereby, value from co-operation is also captured by all stakeholders [START_REF] Moore | The Death of Competition: Leadership & Strategy in the Age of Business Ecosystems[END_REF]. In addition to the main actors of a value network (lead producers, their suppliers and customers) also interests of other involved actors (external stakeholders) should be considered. The need to consider sustainability requires tighter collaboration among a wide range of stakeholders. Collaborative networks is one concept that can bring a significant contribution to the better understanding of the stakes and paths towards potential solutions in sustainability. Studies on trust management, value systems, multicultural and multilegal contexts for collaborative networks can help in the development of better governance methods for sustainable development [START_REF] Camarinha-Matos | The role of collaborative networks in sustainability[END_REF].

Network governance models in manufacturing

From the standpoint of organisation theory, there are three main governance models: hierarchies (e.g., firms), markets, and networks. Networks are a hybrid model between hierarchies and markets, possessing characteristics from both extremes. Network organisation and management include governance structures that have to do with the degree of central or distributed co-ordination [START_REF] Valkokari | D1.2 Towards sustainability governance in manufacturing networks[END_REF].

On the basis of their structure, networks can be divided into hierarchical hub-spoke and multiplex models [START_REF] Svahn | The modes of supply net management: A capability view[END_REF]. In the hub-spoke model, the central actor (i.e., lead producer or OEM) is responsible for the network governance. In contrast, network governance in the multiplex model takes place within and between the network actors. Three distinct types of governance within networks can be identified: i) shared governance, ii) lead-organisation-governed, and iii) network-administrative-organisation-governed [START_REF] Doz | Clubs, Clans and Caravans: The Dynamics of Alliance Memberships and Governance[END_REF]. In NAO governance, all activities and decisions are co-ordinated through one organisation specifically created to oversee the network.

Governance structures are what bring actors into working togetherthe process, rules, and norms by which the network enables participating organisations to influence the network's operations and decision-making. Governance mechanisms can be divided into contractual-based and relational-based governance [START_REF] Provan | Interorganizational networks at the network level: A review of the empirical literature on whole networks[END_REF]. Contractual governance emphasises the use of a formalised, legally binding agreement to govern the inter-firm relationship. Relational governance, in contrast, highlights the role of norms of solidarity, flexibility, and information-sharing in the relationship process.

Since networks are mostly composed of autonomous organisations and are not legal entities, the network's participants typically have limited formal accountability for network-level goals, and conformance with rules and procedures is not governed by binding regulations but is voluntary. For goal-directed organisational networks with a distinct identity, governance is still necessary for ensuring that participants engage in collective and mutually supportive action, that conflict is addressed, and that network resources are acquired and utilised efficiently and effectively. Governance involves use of institutions and structures of authority and collaboration to allocate resources and to co-ordinate and control joint action across the network as a whole [START_REF] Poppo | Do formal contracts and relational governance function as substitutes or complements?[END_REF].

Model for sustainability governance in manufacturing networks

The presentand especially the future challengeis to govern sustainability within manufacturing networks and broader business ecosystems. The process towards developing a sustainable manufacturing value network requires reassessing value creation and capturing from the start of a business. Moreover, a more holistic sustainable business model of manufacturing networks should include economic, environmental and social impacts of the business. The governance model developed illustrates sustainability governance within a manufacturing network as a process for guiding the activities of all actors involved toward sustainable development and performance over a product's life cycle. There are three main tasks of sustainability governance: analysing, organising, and developing as illustrated in the Fig. 1. Through these, the governance model illustrates a process that integrates i) requirements and commitments of stakeholders within the manufacturing network as well as ii) business models and the self-interest of manufacturing-network companies. To guide the activities of all actors involved toward the sustainability objectives, companies must first determine the key players in the manufacturing network and the boundaries of the business model. Therefore, the network analysis requires visualisation of the connections (business relationships, ownership, etc.) between the actors. In this phase, an important aspect of the sustainability governance in manufacturing networks is the connection between sustainable development and business models. In order for the network-members to understand the network's value for each member, the objectives, interests, and expectations of each should be covered. Consequently, it is important to assess the requirements and expectations of the stakeholders within the business ecosystem. On the basis of these analyses, companies would be able to identify sustainability impacts over the product life cycle and the requirements imposed for the actors involved.

The analyses of said actors, their requirements, and the total impact direct the organising and management of the sustainability development at network level. Shared targets and collaboration models are formed both inside the manufacturing network and with respect to other stakeholders within the business ecosystem. Alignment of business models and integration of processes in accordance with the sustainability objectives should be carefully considered. Different collaboration models are required for different situations; e.g., the sustainability objectives should be considered when one is deciding with whom to collaborate and how.

In order to ensure continuous improvement as well as renewal, progress should be evaluated via shared indicators and new targets should be set transparently, based on the achievements. Actors will be able to renew actions, operations, and business models together in pursuit of sustainability goals.

Conclusions

The model developed addresses sustainability governance within a manufacturing network as a process to guide the activities of all actors involved toward sustainable development and performance throughout the product life cycle. According to the model, there are three main tasks of sustainability governance: analysing, organising, and developing. These three main tasks are in accordance with company-level approaches but highlight the need for multilevel network governance. One of the requirements identified in this study is that sustainability should be integrated into companies' as well as networks' core strategies. The governance model plays an important role for this aim and can be utilised for supporting the alignment of business models and processes with sustainability objectives.

A practical implication of the developed model is that it supports management in analysis and decision-making related to strategic collaboration for sustainability. The model contribution to scientific community is that it supports identification of governance mechanisms related to shared value system in downstreamupstream networking.

The model presented in this paper will be further refined as the SustainValue project progresses. The next version will take into account the advances made in the research carried out in the project. This includes, for example, how governance, corporate norms and values, and ownership structure drive sustainability within the business model and architecture. The model will be further developed and piloted together with companies in order to link it to new methods and tools that will be developed in the SustainValue project as well as to existing methods such as Global Reporting Initiative (GRI).

Fig. 1 .

 1 Fig. 1. Model for sustainability governance in manufacturing networks.

Table 1 .

 1 Value creation approaches in manufacturing networks.

	Approach	Value network types and their key characteristics
	Value configuration	Value chain	Value shop (value	Value network
	[13]	(components as	based on	(connections as
		value element)	competences)	value elements)
	Value continuum	Current business	Business renewal	Emerging new
	[14]	nets (efficiency	nets (incremental	business nets
		of operations)	changes)	(radical changes
				and uncertainty)
	Practical approaches	Traditional	Business enhancing
	in manufacturing	supply networks	networks, like
	networks		service networks

Acknowledgements. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7, 2007-2013) under grant agreement 262931. The authors wish to acknowledge the European Commission for their support.


Carlo Brondi
email: carlobrondi@itia.cnr.it

Rosanna Fornasiero

Manfredi Vale

Ludovico Vidali

Federico Brugnoli

Modular Framework for Reliable LCA-Based Indicators Supporting Supplier Selection within Complex Supply Chains

Keywords: Life Cycle Assessment, Independent information modules, Company Environmental Performance, Green Supply Chain Management, Green Purchasing

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Scientific Background : Optimizing sustainability of the supply chain

In the current business environment, purchasing process has become critical in adding value to products and a vital determinant to ensure the profitability and survival of a company. Literature reports many different approaches to the topic of purchasing strategies where [START_REF] Weber | Vendor selection criteria and methods[END_REF] and Ghodsypour and O'Brien (1998) did a comprehensive review on the past research. Some popular methods include the categorical method, the weighted-point method, the matrix method, the vendor profile analysis, and the Analytical Networking Process (ANP) approach [START_REF] Noci | Designing green vendor rating systems for the assessment of a supplier's environmental performance[END_REF]. While literature related to supplier evaluation is plentiful, the works on green supplier evaluation or supplier evaluation that consider environmental factors are rather limited (Handfield, Steven, Srouft, & Melnyk, 2002; Humphreys, McIvor, & Chan, 2003;[START_REF] Noci | Designing green vendor rating systems for the assessment of a supplier's environmental performance[END_REF].

The purchasing process becomes more complicated when environmental issues are considered. This is because green purchasing must consider the supplier's environmental responsibility, depending on product chain assets, in addition to the traditional factors such as the supplier's costs, quality, lead-time and flexibility. The management of suppliers based on strict environmental compliance seems to be not sufficient in view of a more proactive or strategic approach. [START_REF] Noci | Designing green vendor rating systems for the assessment of a supplier's environmental performance[END_REF] designed a green vendor rating system for the assessment of a supplier's environmental performance based on four environmental categories, namely, 'green' competencies, current environmental efficiency, suppliers' 'green' image and net life cycle cost, by applying ANP. Main limit in attributing a unique environmental performance index to a company seems to be linked to the management of reliable quantitative scientific set of values which can be considered constant in different comparison.

Life Cycle Assessment (LCA) methodology can represent a good basis to develop a comprehensive index by encouraging companies to look at their technological history placed in other Life Cycle stages as well as their operational efficiency (Lozano et al., 2008). Appropriate data can be gathered by transcending the boundaries of the company and by offering well-established assessment methodology. [START_REF] Lewandowska | Environmental life cycle assessment (LCA) as a tool for identification and assessment of environmental aspects in environmental management systems (EMS)[END_REF] accounts like LCA integration within internal environmental management systems may involve barriers both in terms of generation and verification of reproducible results and in terms of final assessment interpretation compliant with rapid business management. The lack of standard approaches for data aggregation from different manufacturers can in fact limit their liability to share data which can result essentials for evaluation in the end-of-pipe phases.

More in detail reliable and comparable results seem to imply pre-definition of system boundaries and allocation criteria (Suh et al., 2004). Studies have in fact shown that a significant portion of the environmental impacts may be neglected due to premature cutoff of impact assessment or by inadequate simplification (Lave et al., 1995;Lenzen, 2001;Norris, 2002). Another top concern in many LCA studies seems to be the linking of the firm on-site impact to the upstream and downstream processes (Lave et al. 1995[START_REF] Son | Integration of life cycle assessment in the environmental information system[END_REF]). Several authors (Suh et al., 2004, Peters andHertwich , 2005) proposed the "integrated hybrid LCA", which combine input/output analysis with traditional LCA, as an easy way to assess firm and business sector impact. Such methodology can in fact link the physical flows involved by processes together with economic evaluations and final environmental impacts. As a matter of fact classical LCA modeling requires detailed stages description, reasonably unknown by the same firm, while input-output assessment requires a wider flow assessment which is related to economical and traceable quantities. Gwan et al. (2003) and [START_REF] Buxmann | Independent information modules -a powerful approach for life cycle management[END_REF] proposed calculation methods which are applicable to complex systems with internally recurring unit processes. According to their studies the use of gate-to-gate independent modules and appropriate cut-off criteria can enable a dramatic simplification in Life Cycle Inventory (LCI) and Impact Assessment (LCIA).

Modular framework for company environmental performance assessment

This paper aims to provide a standard methodology to select best "green supplier" within a specific supply chain on the basis of their overall yearly performance. Such criterion is based on a two assessment stages both based on LCA methodology. They are reported in sequence hereafter.

Attribution of an environmental profile to firm activities

According to literature the assessment of the environmental impact referred to manufacturing activity requires to provide a general tracking of the physical flows involved by companies within a certain time-span. Such assessment provides the basis for a general comparison with other firms. General hypothesis of the proposed modular framework imply a limited adaptation of the integrated hybrid LCA. System boundaries are fixed coincident with factory physical limits in order to limit data collection within the area of accessible information and to make final data reusable by production managers for internal purposes.

Impact evaluation is provided in terms of cradle-to-gate environmental impact. Complex entering and outgoing flows are partitioned and analyzed as recurrent modules flows (i.e. common auxiliary materials) which are linked to gate-to-gate LCA studies provided by other suppliers or by Life Cycle Analysts. Each environmental impact has been expressed at the endpoint level by using the same common impact categories (p) in order to integrate different data. The same environmental firm performance is expressed in terms of resulting cradle-to-gate impact vector (p f ) that is parametrically dependent by input and output characteristic flows (figure 1).

=

(1)

= N f=1 (2)
In equation 1 Facility Environmental Profile (FEP) is P f , calculated as sum of vector by single contribution of characteristic mass and energy flows (m, e) entering and leaving the production facility boundaries within the same time period (i.e. fiscal year). Each flow quantity is multiplied for the Unitary Impact Profile (UIP) derived from a specific LCA study (p m , p e ). Scalar components (p 1 ,…,p n ) composing final impact vector (referred to single flows, item, facility or company) are standard endpoint categories in the LCA characterization phase expressed as quantities (kilograms of carbon dioxide equivalents for Global Warming potential, kilograms of PO 4 equivalents for Eutrophication Potential, etc.). Factors A and B are dimensional factors to make congruent the final dimensions with the same impact evaluation format (endpoint categories). Finally variable V f represent the economic value of the production by the same facility or the number of provided items.

The Company Environmental Profile (CEP) is expressed in equation 2 as vectoral summation P C of environmental profiles referred to N production facilities P f , composing the analyzed company.

Benchmarking of Environmental Performance at cluster or sector level

Scalar quantities reported in vectoral components of CEP are referred to physical impacts. Interpretation of results can provide useful outcomes to supply manager mainly thorough the comparison of final performance with benchmark values rather than the assessment in absolute terms. Such benchmark values can be referred both to an average performance value and to specific competitor performance value. In order to get a reliable assessment specific barriers are recognizable. Firstly comparisons confined to few competitors can limit the interpretation of the final values of CEP. In the absence of a reference value the CEP can be insignificant to understand whether a firm is producing a good or bad environmental performance within a supply network. Secondly the vectoral comparison can imply that some scalar components of CEP can be higher or lower than the respective scalar quantity of the competitor CEP (i.e. in a comparison kg of produced CO 2 equivalents can be higher while kg of PO 4 equivalents can be lower).

In order to overcome such barriers a LCA-based Company Environmental Performance Index (CEPI) is proposed. Initially benchmark values, PS or PCl, for cluster environmental performance are calculated according to two different inventory methods.

Benchmark values which are referred to statistical input-output approach (NAMEA tables) at sectoral level are calculated in equation 3 (vector P S ) . In equation 3 total impact referred to the cluster level is calculated as sum of vectors related to total flows involved at cluster/sector level. Single quantities of characteristic mass and energy flows (m, e) entering and leaving the sectoral cluster within the same time period (i.e. fiscal year) are multiplied for the corresponding Unitary Impact Profiles (UIP) derived from a specific LCA study (p m , p e ). Then each scalar component of the final vector is divided by the number of total companies (N S ) owning to the cluster (territorial cluster, national industrial sector etc.) and the total economic production (number of products, total turnover etc.). Alternatively the benchmark vector can be assumed coincident with P C in the presence of proper data inventory within a significant company cluster . In equation 4 total environmental impact is calculated as sum of the single company environmental profiles (CEP) and then divided for the number of total companies within the examined cluster (N Cl ).

= (3) = (4) =f (5) =f (6)
The resulting benchmark Company Environmental Performance Indexes (CEPI) can be calculated in equation 5 and 6 as vectors I S or I Cl . The scalar components of both index vectors depends on percentage difference between cluster benchmark values, P S or P Cl , and the Company Environmental Profile (CEP).

Application case : the use of energy in a territorial cluster

The methodology has been applied to a territorial district in order to evaluate best performers at environmental level in a manufacturing context. Cradle-to-grave approach has been limited to energy use assessment (Narrow I3 in figure 1).Different companies of different Italian manufacturing sectors owning to the same territorial cluster have been tracked in order to obtain their specific Environmental Profile referred to their energy use. Firstly the total Environmental Profile have been assesses for 188 companies owning to 12 different manufacturing sectors by evaluating the aggregate Energy consumption in terms of electricity mix , heating gas and district heating in two different years (2005 and 2010). Unitary Impact Profiles assessment included the electricity mix change and combustion technology change at industrial levels for the examined years. Category impact used in the final impact profiles are: Acidification Potential (kg of SO 2 equivalents), Eutrophication potential (kg of Phosphate equivalents), Global Warming potential (kg of CO 2 equivalents), Ozone Layer Creation Potential (kg of DCB Equivalents), Photochemical Ozone Creation Potential (kg of Ethene Equivalents).

Secondly a selection of 10 companies has been tracked in terms of economic performance for the same years. Yearly turnover has been used as economic performance indicator in order to make comparable the results among different sectors. Then the respective CEP has been calculated for each company.

Thirdly a benchmark vector P S has been evaluated within the territorial district by the use of equation 3. More in particular the average environmental profile has been divided for the sectoral turnover at cluster level.

4

Supplier selection within a green supply chain by using performance index based on modular LCA

The application of LCA based indicators can enable supplier selection in complex supply chains through the assessment of environmental impact weighted with the impact of other performance indicators. Environmental sustainability is just one dimension to be considered when evaluating the supply chain configuration. Other dimensions to be considered are cost, time, quality and flexibility as well as collaboration capability of a partner in the SC. The indicators to be considered are linked to the type of business opportunity to be faced by the network. For example in case of cus-tomized production it is necessary to focus on indicators of flexibility and service provision more than on cost reduction. The availability of indicators can be based on the following dimensions:

One-to-one indicators: these indicators allow measuring the performance of a company towards another one and are restricted to the performance of their buyer-seller relationship. This data are available only among the two companies and not accessible by others. Many-to-many indicators: in case of collaborative networks where the relationship of buyer-seller is overcome by a cooperative view of the business, it can be advantageous for all companies to share information about each other performance as they are aware of the benefits of making public these information in terms of marketing and return allowing them to give more visibility to their capabilities and stimulate them to perform better. The calculation of the environmental performance of a company based on the benchmarking proposed in the previous chapter allows to have an evaluation which is not only based on the experience of the company within a specific context but compared with companies in the same sector and other sectors and goes in the direction of sharing information useful to many companies. The approach based on benchmarking at cluster/sector level can overcome the initial problem of a supply chain configuration to retrieve specific data on specific products or components. Aggregating all these different indicators (environmental, time, quality, cost performance, etc.) a company can define different scenarios (SC configurations) where each SC can be characterized by different combination of partners. According to the specific product under development, each manufacturer can give a different level of importance to each indicator category. The decision support system under development is based on a multi-criteria evaluation of the possible performance of the different scenarios.

Conclusions and recommendations

A company Environmental Performance Index has been proposed to evaluate the total "green" performance referred to a specific company within a supply cluster. The proposed approach has been applied to SME in a territorial cluster. SMEs can benefit by a suitable application of such methodology. The index assessment allows in facts to emphasize the relative importance of company links with other product chain phases. Consumed and emitted quantities by facilities can be substituted with indexes which are based on their physical environmental impact at global level. Such indexes include the relative contribution of the different suppliers. Secondly CEPI can be applied to a specific company apart from his specific eco-efficiency focus in order to understand their effective environmental burden. Finally CEPI, being based on macro-flows assessments, can be calculated with a standard approach independently from factory technologies and from manufacturing sectors. Finally the assessment reliability can be focused separately on quantity inventory and on unitary impact assessment. Quantity inventory can be monitored yearly by stakeholders who are not necessarily expert in LCA while unitary impact assessment can be based on specific and detailed studies from scientific community. A further step can be represented by the relative weight attribution to the different impact categories during the final selection criteria.

Fig. 1 .

 1 Fig. 1. Input-Output flow assessment for Facility Environmental Performance Index calculationThe allocation of environmental impact can imply a subdivision of the whole impact by factory physical production (i.e. mass/number of single item produced yearly by the same facility) or by economic value (i.e. yearly turnover)

Fig. 2 .

 2 Fig. 2. Company Environmental Performance Indexes applied to sample companies

Fig. 3 .

 3 Fig. 3. Application of LCA based environmental performance index for supply chain configuration


Merve Kılıç

Seren Özmehmet Taşan

Performance Evaluation in Sustainability Conscious Manufacturing Companies by Using TOPSIS Method

Keywords: Sustainability, Indicator, Manufacturing, TOPSIS, Performance Evaluation

In a manufacturing environment, managing limited resources has always been a main issue for engineers. Recently, the idea of managing limited resources without harming ecological environment adopted by manufacturing sector and sustainable manufacturing has become a key issue. While the concept of sustainability has been recognized, companies need to measure how sustainable they perform. Therefore, sustainability indicators are developed and used in order to assess companies' production activities expediently to sustainable manufacturing. This paper presents a research indicating the application of TOPSIS method on sustainability indicators related to production for two different multi-criteria decision making problems in a sustainability conscious manufacturing company.

Introduction

In ecology, sustainability is defined as the providing the continuousness of biological systems' variety and productivity. Considering this definition, the term of sustainability is used for managing the resources via long term maintenance of responsibility for environment, economy and society. Sustainability can be evaluated as a problem statement that seeks ways for human and other forms of life will flourish on the planet forever. With the ever increasing interest in sustainability, the companies started to realize the importance and impact of manufacturing their products in a more sustainable way. Sustainable manufacturing refers to that decreasing the negative effects of a product and its production processes on environment, health and welfare of community to minimum level. From raw material to the finished good and even at the recycling phase, the product should cause no or minimum damage to environment and during its production process, environmental resources should be used efficiently. The objectives of sustainable manufacturing are defined by the European Union as creating more value for more (growth) and better jobs, increasing the competition of European industries and the communities in the knowledge century and sustainable development of economies [START_REF] Westkamper | Manufuture and Sustainable Manufacturing. Manufacturing Systems and Technologies for the New Frontier[END_REF]. Since the importance of the sustainable manufacturing has been increased rapidly, companies show tendency to adopt this concept. Similar to companies' approach which uses financial indicators to determining the business success, there has been needed to measure and evaluate sustainability. However, sustainability can be thought as an abstract concept which is hard to measure. Therefore sustainability indicators are developed and used in order to measure how a company succeeds in the concept of sustainability and sustainable production.

Several researchers have focus on determining indicators for sustainable manufacturing [START_REF]Organization for Economic Co-operation and Development[END_REF][START_REF] Neto | Indicators to Measure Sustainability of an Industrial Manufacturing[END_REF][START_REF] Krajnc | Indicators of Sustainable Production[END_REF]. These researchers gave utmost importance to create and define new sustainable manufacturing indicators. However, due to difficulties in determining suitable indicator baseline, there has been a lack of research concerning performance evaluations by using indicators. Practically, various indicators should be considered simultaneously while evaluating the sustainability performance of a manufacturing system. In order to fill this gap, the contribution of this study focuses on the application of TOPSIS method that makes us able to consider various sustainability indicators simultaneously. The remainder of this paper is organized as follows; Section 2 presents the necessary background information regarding to sustainability indicators while focusing on the product indicators. Following, section 3 consists of the brief explanation of the TOPSIS method. Later, section 4 includes the application of TOPSIS method on two different case studies. Finally, conclusions and directions for future researches are given in section 5.

Sustainability Indicators Related to Manufacturing

The indicator has significance that extends beyond the properties directly associated with the parameter values. Indicators possess a synthetic meaning and are developed for a specific purpose [START_REF]Organization for Economic Co-operation and Development[END_REF]. United Nations (UN) defined indicators for sustainable development considering sociological field of development problems as well as the physical problems [START_REF]Indicators of Sustainable Development: Guidance and Methodologies Third Edition United Nations Publication[END_REF]. UN grouped indicators according to fields such as poverty, governance, health, education, demographics, natural hazards, atmosphere, land, oceans, seas and coasts, freshwater, biodiversity, economic development, global economic partnership, consumption, and production. In literature, sustainability indicators related to manufacturing are evaluated in three differently named groups such as product, process and management [START_REF] Neto | Indicators to Measure Sustainability of an Industrial Manufacturing[END_REF]; social, environmental and economic [START_REF] Krajnc | Indicators of Sustainable Production[END_REF] or inputs, operations and products [START_REF]Organization for Economic Co-operation and Development[END_REF]. This paper presents only the indicators related to product. Indicators related with product generally state the impacts of materials used for producing the product, consumption and renewability of the resources used for production and recyclability of a product.

Neto et al. [START_REF] Neto | Indicators to Measure Sustainability of an Industrial Manufacturing[END_REF] defined nine indicator related to product considering the material usage and renewability, usage of resources such as energy and water and transportation of material and products. Similar to this study, OECD [START_REF]Organization for Economic Co-operation and Development[END_REF] defined product indicators related to materials with the aspects of renewable and non-renewable and also with the content of restricted substance. Energy consumption is also included in to indicators and as an addition; greenhouse gas emission intensity is mentioned. Krajnc and Glavic [START_REF] Krajnc | Indicators of Sustainable Production[END_REF] defined product indicators under the output indicators which is a branch of the main title of the environmental indicators. Additionally, they considered the recyclable materials.

TOPSIS Method

TOPSIS stands for technique for order preference by similarity to ideal solution developed by Hwang and Yoon [START_REF] Hwang | Multiple Attribute Decision Making: Methods and Applications[END_REF]. TOPSIS method has several advantages; one of which is the application convenience and simplicity when identifying the suitable alternative quickly. Additionally, it performs similar to various methods that use additive weights and performs better than other methods in most cases.

The TOPSIS method based on the selected alternative should to be found at the shortest distance from the positive ideal solution and farthest from the negative ideal solution. Positive ideal solution represents the best criteria values and conversely the negative ideal solution represents the worst criteria values attainable from all alternatives. TOPSIS can be summarized in six steps (Fig. 1). In first step, evaluation matrix is built by listing alternative horizontally and criterions vertically. Second step consists of dividing each center values by the norm of the total outcome vector in order to non-dimensionalize the center values in the evaluation matrix. Third step includes multiplying the matrix's values by normalized weights of each criterion and establishing the relative importance matrix. The fourth step consists of building positive and negative ideal solutions to compare the alternatives with each other. After determining the positive and negative ideal solutions, the separation of each matrix value from the ideals are measured as Euclidean distances in the fifth step. At the sixth step, these distances are transformed into a single metric called relative closeness to the ideal solution. Finally, alternatives ranked according to their closeness to the ideal solution.

Fig. 1. Summary of TOPSIS steps

Case Studies

In order to present the applications of multi-criteria decision making process for evaluating sustainability indicators in the concept of manufacturing, two different case studies are formed and examined according to company's perception of sustainability. The first case study includes the application of TOPSIS method on the decision making regarding six production period of the company concentrating on three sustainability indicators: product durability, revenues from eco-products and reusable packaging mass. After applying steps mentioned in section 3, the most appropriate period with the strategy that fits to the company's criterions are determined. The second case study includes determining that which product is matched with the firm's philosophy of sustainability. Six eco-products are examined based on the four criterions and the most preferable product with the maximum revenue, shortest production time, involves larger amount of recyclable material and with minimum amount of carbon emission is determined as a result of the study. After applying steps mentioned in section 3, the most appropriate eco-product that fits to the company's perception of sustainability is determined. Finally, results for both case studies are discussed in detail.

Case Study I

This case study concerns with the sustainability performance in Company X over time periods. While producing their ordinary goods the firm decided to enlarge its product range to the new segment: eco-products. During 6 time periods they have been trying to develop a production strategy related to their sustainability perception. Now Company X wants to eliminate the production of ordinary products and focus on the eco-products. The firm concentrates on 3 sustainability indicators: product durability (I 1 ), revenues from eco-products (I 2 ) and reusable packaging mass (I 3 ). They observed the information related these indicators and examined the 6 time periods (see Fig. 2, step 1). There were 6 different strategies in 6 time periods and now the firm wants to evaluate that which strategy is better. According to sustainability policy of Company X, it is better if a product has maximum durability, consists of more reusable package and with the maximum revenue.

Using the information gathered by Company X for 3 sustainability indicators over 6 time periods, TOPSIS method was applied as shown in Fig. 2 and summarized in Fig. 3. The results of TOPSIS showed that the strategy applied on the 6 th period fits best to the Company X's sustainability perception and the firm decided to continue its production activities with this strategy. Performance criterion of 5 th period is very close to period 6. From Fig. 3, it is seen that the durability is achieved in 5 th and 6 th period to 8 years and revenue obtained from eco-products shows small decrease. It is also seen that the reusable packaging mass is doubled from period 5 to 6. If the firm concentrates on only first 4 periods, it would be difficult to make a choice because the results provided from these periods are very close to each other while data belongs to these periods were varied.

Case Study II

This case study concerns with the sustainability performance in Company X for various products. Company X wants to determine that which product is matched with the firm's policy of sustainability. The relevant data regarding to six products A, B, C, D, E and F are shown in Table 1. Data related to production of the six ecoproducts: annual revenue calculated as multiplication of yearly demand and price per product. For example, from product A: 300*5000 = 1500000. Revenue from eco-product determined as 10500000 and total revenue of the firm recorded as 19500000. The firm produces 12 hour in a day and 5 days in a week. Recycled material costs 600 and normal material costs 1000. According to Company X, the product with the maximum revenue, shortest production time, involves larger amount of recyclable material and with minimum amount of carbon emission is preferable.

Step 1: Building the Evaluation Matrix

Step 4: Building Positive and Negative Ideal Solutions

The positive ideal solution corresponds to the set of best or maximum values of each column. Conversely, the negative ideal solution constitutes the set of worst or minimum values of each column of the evaluation matrix where A+ and A-are the set of maximum and minimum values of the criteria's. Using the information gathered by Company X for 6 products, TOPSIS method was applied as shown in Fig. 4 and summarized in Fig. 5. In the third step, weights are determined according to following calculations; Revenue from eco-products: revenue from eco-products / total revenue = 10.5 /19.5 =0.54; 12 hr production in a day and 5 days in a week, 50 hr production of eco-products : 50 / 60= 0.83; Recycled material costs 600, normal material costs 1000 : 1000/600= 1.66; It means that if the firm spends 1000 on normal material, they produce 1 product; if they spend same value on recycled material they produce 1.66 products; Mass fraction of greenhouse gases: total mass of CO2 equivalents/ total mass of products = 192 / 1900 =0.10. The results of TOPSIS revealed that product F is more suitable for Company X's policy of sustainability. If the data is reviewed, it is seen that the product F shows highest performance in production time and recyclability out of remaining products. Moreover production time and recyclability have the highest weights out of the other criterions. It is also seen from the graph that products A, B and C shows similar performance according to the firm's philosophy of sustainability.

Conclusion

Since importance of sustainability has been increased, companies have shown more tend to manufacture their products in sustainable way. As a result of this tendency to sustainable manufacturing, the creation of sustainability indicators became a hot topic among researchers. Hence the need to measure and evaluate become prominent, the application of indicators in performance evaluation has been ignored. Specifically, this study focused on usage of sustainable manufacturing indicators for performance evaluation and case studies concerning the application of the TOPSIS method which provides advantages of sufficiency and simplicity while identifying the most suitable alternative quickly in case of the conflicting criterion. Future studies will include complex case studies that contain multi-criteria decision making problem of a real company with the real data. Additionally, to reflect the vagueness concept of sustainability, fuzzy TOPSIS will be applied on sustainability indicators and to analyze the outputs of the fuzzy TOPSIS, sensitivity analysis will be used.

Step

I 1 (Step 2 :

 12 years) I 2 (million $) I 3 (tones) Non-Dimensionalizing the Center Values in the Evaluation Matrix Z ij = y ij / I 1 (years) I 2 (million $) I 3 (tones)

I 1 (Step 6 :Fig. 2 . 1 Fig. 3 .

 16213 Fig. 2. Applying TOPSIS steps to the case-1

AStep 6 :Fig. 4 . 2 Fig. 5 .

 6425 Fig. 4. Applying TOPSIS steps to the case-2

Table 1 .

 1 Product Data

		Demand	Price	Production Duration Recyclability CO 2 Emission
		(yearly)	(per product)	(of 1 product)	(%)	(yearly)
	A	300	5000	8 hr	75%	25
	B	400	3000	11 hr	85%	40
	C	200	5000	5 hr	70%	30
	D	300	10000	8 hr	50%	45
	E	100	20000	12 hr	68%	20
	F	600	3000	6 hr	90%	32

  1: Building the Evaluation Matrix Step 4: Building Positive and Negative Ideal SolutionsThe positive ideal solution corresponds to the set of best or maximum values of each column. Conversely, the negative ideal solution constitutes the set of worst or minimum values of each column of the evaluation matrix where A+ and A-are the set of best and worst values of the criteria's.

							Step 2: Non-Dimensionalizing the Center Values in the
							Evaluation Matrix
		Revenue	Time	Recycling	CO 2				Z ij = y ij /
		(I 1 )	(I 2 )	(I 3 )		Emission
						(I 4 )
	A	15	8	75		25		I 1	I 2	I 3	I 4
	B	12	11	85		40	A	0.33	0.37 0.41	0.31
	C	10	5	70		30	B	0.26	0.52 0.47	0.49
	D	30	8	50		45	C	0.22	0.23 0.38	0.37
	E	20	12	68		20	D	0.66	0.37 0.27	0.55
	F	18	6	90		32	E	0.44	0.56 0.37	0.25
							F	0.39	0.28 0.49	0.39
	Step 3: Establishing Relative Importance
	Establishing relative importance (w j ) of the criterion
	consists of multiplication the matrix values by the
	normalized weights for each criterion.
			I 1	I 2	I 3	I 4	Total
	Calculated Weights 0,54 0,83 1,66 0,1	3,13
	Normalized Values 0,17 0,27 0,53 0,03 1
								I 1	I 2	I 3	I 4
							A	0.056	0.099	0.217	0.009
		I 1	I 2	I 3		I 4	B	0.044	0.140	0.249	0.014
	A	0.056 0.099 0.217 0.009	C	0.037	0.062	0.201	0.011
	B	0.044 0.140 0.249 0.014	D	0.112	0.099	0.143	0.016
	C	0.037 0.062 0.201 0.011	E	0.074	0.151	0.196	0.007
	D	0.112 0.099 0.143 0.016	F	0.066	0.075	0.259	0.012
	E	0.074 0.151 0.196 0.007
	F	0.066 0.075 0.259 0.012